Neuromelanin-sensitive MRI for assessing parkinson's disease

Abstract

To provide neuromelanin-sensitive MRI for assessing Parkinson's disease.SOLUTION: The invention provides a neuromelanin-sensitive magnetic resonance imaging ("MRI") technique, method and computer-accessible medium for measuring the extent of Parkinson's disease, providing a diagnosis thereof, monitoring the treatment thereof, assessing novel treatments thereof, or determining a prognosis related to Parkinson's disease. Provided herein are, inter alia, methods for determining the presence of Parkinson's disease in a subject, and methods for determining the change in the concentration of neuromelanin in the subject over time.SELECTED DRAWING: None

Description

[Technical field]

[0001] Related Applications This application claims priority to, and the benefit of, U.S. Provisional Application No. 62 / 889,300, filed Aug. 20, 2019, the contents of which are incorporated by reference herein in their entirety.

[0002] government support The work described herein was supported in whole or in part by grant numbers R01MH114965, R01MH117323, R01DA020855 and UL1TR001873 from the National Institutes of Health. Accordingly, the United States Government has certain rights in this invention.

[0003] Field of Disclosure The present disclosure relates generally to magnetic resonance imaging ("MRI"), and more particularly to exemplary embodiments of exemplary systems, methods, and computer-accessible media for neuromelanin-sensitive MRI techniques as a non-invasive measure of neurological conditions with a focus on Parkinson's disease. [Background technology]

[0004] background Parkinson's disease, one of the two major neurodegenerative diseases of aging, is a progressive nervous system disorder that affects as many as 1.5 million Americans. Parkinson's disease occurs when certain nerve cells (neurons) in a part of the brain called the substantia nigra die or become damaged. Normally, these cells produce a vital chemical known as dopamine. Dopamine allows the body's muscles and movements to function smoothly and in coordination. When about 80% of the dopamine-producing cells are damaged, the symptoms of Parkinson's disease appear. Parkinson's disease affects both men and women in almost equal numbers. It shows no social, racial, economic or geographical boundaries. It is estimated that 60,000 new cases are diagnosed each year in the United States. The condition usually begins after age 65, and 15% of those diagnosed are under the age of 50. Idiopathic Parkinson's disease is by far the most common and includes rare genetic forms caused by mutations in the alpha-synuclein and parkin genes. Known environmental causes include very rare cases of MPTP (1-methyl-4-phenyl-4-propionoxypiperidine), carbon monoxide, and manganese poisoning.

[0005] The incidence of Parkinson's disease increases with age. The median age of onset for all forms of Parkinsonism is 61.6 years, and for idiopathic Parkinson's disease, 62.4 years. Onset before age 30 is rare, but up to 10% of idiopathic Parkinson's disease cases begin by age 40. A recent study in the United States found that the incidence of Parkinson's disease is 10.9 cases per 100,000 per year in the general population and 49.7 cases per 100,000 per year in those over age 50. The incidence improves with population age. Prevalence is estimated to be approximately 300 per 100,000 in the United States and Canada, with an important caveat that perhaps 40% of cases may never be diagnosed.

[0006] Symptoms such as bradykinesia are slowness in voluntary movement. Once it progresses, it becomes difficult to initiate and complete movements. Bradykinesia occurs due to slowed propagation from the brain to the musculoskeletal system due to dopamine depletion. Tremors in the hands, fingers, forearms, or feet tend to occur when the limbs are at rest, but not when performing tasks. Tremors can also occur in the mouth and jaw. Stiffness or muscle stiffness can cause muscle pain and a blank, mask-like face. Stiffness tends to increase during movement. Poor balance is due to damage or loss of reflexes that regulate posture to maintain balance. Falls are common in people with Parkinson's disease. The gait of a person with Parkinson's disease is the characteristic unsteady gait associated with Parkinson's disease. There is a tendency to lean unnaturally back or forward, resulting in a hunched, head-down, shoulder-down posture. Arm swing is reduced or absent, and people with Parkinson's tend to take small shuffling steps (called decubitus steps). People with Parkinson's may have difficulty walking. They may have difficulty starting, appear to lean forward when walking, slow down mid-stride, and have difficulty changing direction.

[0007] Symptoms of Parkinson's disease also include micrographia (small handwriting), resting tremor, freezing episodes, painful leg cramps, akinesia - difficulty initiating movement, muscle stiffness, difficulty rising from a chair, slouched posture, facial masking - loss of facial expression, microphonia - low volume, monotonous speech, slurred, soft speech, staring, decreased blink rate, blepharopraxia, small shuffling steps, balance problems, rigidity - muscles, cogwheel rigidity - stopping / starting movements, drooling, seborrhea - abnormally oily skin, Symptoms may include tiring easily, reduced arm swing (including reduced ability to perform tasks such as hand flipping and finger tapping), constipation, difficulty swallowing (dysphagia) - where saliva or food accumulates in the back of the mouth and throat and choking is a risk, coughing or drooling, excessive salivation (hypersalivation), excessive sweating (hyperhidrosis), loss of bladder and / or bowel control (incontinence), loss of intellectual abilities (dementia) - in the later stages of the disease, slower responses to questions (bradyneuropathy), and psychosocial impairments (e.g. anxiety, depression and feelings of isolation).

[0008] Currently, there is no definitive diagnosis for Parkinson's disease and there is a great clinical need to develop a sensitive non-invasive diagnostic.

[0009] Diagnosis and monitoring of patients with Parkinson's disease is important to assess the severity of progression in order to address appropriate preventive care. Timely intervention during the onset of Parkinson's disease can be life-saving. Comprehensive imaging modalities for the evaluation of Parkinson's disease remain a significant unmet clinical need.

[0010] In vivo measurements of dopamine activity have been used to understand how these important neuromodulators contribute to cognition, neurodevelopment, aging, and neuropathological diseases in humans. In medicine, such measurements could ideally provide objective biomarkers that are easy to obtain in a clinical setting while at the same time predicting clinical outcomes, including Parkinson's disease, using procedures that capture the underlying pathophysiology.

[0011] Neuromelanin ("NM") is a dark pigment synthesized through iron-dependent oxidation of cytosolic dopamine and its subsequent association with proteins and lipids in midbrain dopamine neurons. NM pigment accumulates, along with lipids and various proteins, in specific autophagic organelles that contain NM-iron complexes. NM-containing organelles gradually accumulate throughout life in the cell bodies of dopamine neurons in the substantia nigra ("SN"), a nucleus that derives its name from its dark appearance due to its high concentration of NM, and are cleared from the tissue only after cell death by the action of microglia, such as in Parkinson's disease. Given that NM-iron complexes are paramagnetic, they can be imaged using MRI. A family of MRI sequences known as NM-MRI captures groups of neurons with high NM content, such as those in the SN, as high-signal regions. NM-MRI signal is robustly reduced in the SN of patients with Parkinson's disease, consistent with degeneration of NM-positive SN dopamine cells and reduced NM concentration in postmortem SN tissue of Parkinson's disease patients compared to age-matched controls. Although this evidence supports the use of NM-MRI for in vivo detection of SN neuronal loss in neurodegenerative disease, there is a lack of direct demonstration that this MRI procedure is sensitive to regional variations in NM concentration even in the absence of neurodegenerative SN pathology. Furthermore, induction of dopamine synthesis by L-dopa administration is known to induce NM accumulation in rodent SN cells, and previous studies have postulated that NM-MRI signal in the SN is an indicator of dopamine neuron function in humans, but direct evidence is lacking to support the premise that interindividual variations in NM accumulation result in MRI-detectable differences. Summary of the Invention [Problem to be solved by the invention]

[0012] Therefore, it would be beneficial to provide a system, process, method and computer-accessible medium for neuromelanin-sensitive MRI that can overcome the above-mentioned deficiencies. [Means for solving the problem]

[0013] overview Methods for determining the presence of Parkinson's disease in a subject and for determining the change in concentration of neuromelanin over time in a subject are provided herein, among others. The concentration of neuromelanin may change as a result of the normal course of Parkinson's disease or as a result of therapeutic intervention. In a first aspect, a method for determining whether a change in concentration of neuromelanin occurs over time in the brain of a subject is provided. In a preferred embodiment, the subject is a patient with Parkinson's disease. The method includes obtaining a first neuromelanin magnetic resonance image of the subject at a first time point. A second neuromelanin magnetic resonance image is then obtained at a second time point. The first magnetic resonance image is compared with the second magnetic resonance image, thereby determining whether a change in concentration of neuromelanin occurs between the first time point and the second time point.

[0014] In one embodiment, the present invention provides a method of diagnosing Parkinson's disease in a subject, comprising: (i) performing a neuromelanin-magnetic resonance imaging (NM-MRI) scan to measure levels of neuromelanin; (ii) comparing this level of neuromelanin with previous scans and / or reference values; and (iii) presenting a diagnosis of Parkinson's disease The present invention is directed to a method, comprising:

[0015] In one embodiment, the present invention provides a method of monitoring the progression of Parkinson's disease in a subject, comprising: (i) performing a neuromelanin-magnetic resonance imaging (NM-MRI) scan to measure levels of neuromelanin; (ii) comparing the level of neuromelanin to a previous scan and / or a reference value; and (iii) determining the progression of Parkinson's disease The present invention relates to a method comprising:

[0016] In one embodiment, the present invention provides a method for providing a prognosis of Parkinson's disease in a subject, comprising: (i) performing a neuromelanin-magnetic resonance imaging (NM-MRI) scan to measure levels of neuromelanin; (ii) comparing the level of neuromelanin to a previous scan and / or a reference value; and (iii) optionally providing a prognosis of Parkinson's disease. The present invention relates to a method comprising:

[0017] In one embodiment, the present invention provides a method of monitoring treatment of Parkinson's disease in a subject, comprising: (i) performing a neuromelanin-magnetic resonance imaging (NM-MRI) scan to measure levels of neuromelanin; (ii) comparing the level of neuromelanin to a previous scan and / or a reference value; and (iii) assessing the efficacy of the treatment for Parkinson's disease. The present invention relates to a method comprising:

[0018] In one embodiment, the present invention is directed to determining a first signal intensity from a first neuromelanin magnetic resonance image and determining a second signal intensity from a second neuromelanin magnetic resonance image, wherein comparing the first magnetic resonance image to the second magnetic resonance image comprises comparing the first signal intensity to the second signal intensity.

[0019] In one embodiment, the control refers to a level of neuromelanin present in a population of subjects at approximately the same level, or the standard control refers to approximately the average level of neuromelanin present in a population of subjects.

[0020] In one embodiment, a neuromelanin gradient phantom is used to measure neuromelanin levels, signals and / or concentrations.

[0021] In one embodiment, the neuromelanin phantom concentration gradient is scanned about once per patient, about once per hour, about once per day, about once per week, or about once per month.

[0022] In one embodiment, the neuromelanin phantom gradient is scanned daily.

[0023] In one embodiment, a neuromelanin phantom gradient is scanned for each patient.

[0024] In one embodiment, the present invention provides a method for assessing neuromelanin in a subject, comprising: performing a neuromelanin-magnetic resonance imaging (NM-MRI) scan on the subject; obtaining a neuromelanin dataset from the NM-MRI scan; optionally encrypting the neuromelanin dataset; uploading the neuromelanin dataset to a remote server; Decrypting the dataset as necessary; conducting an analysis of the neuromelanin dataset, the analysis comprising: (i) comparing the neuromelanin dataset to one or more neuromelanin datasets previously obtained from said subject; (ii) comparing the neuromelanin dataset with a control dataset; (iii) comparing the neuromelanin dataset to one or more previously obtained neuromelanin datasets from different subjects;

[0036] generating a report including the neuromelanin analysis; Optionally, encrypting the report; uploading the report to a remote server; Steps to interpret this report, if necessary The present invention relates to a method comprising:

[0025] In one embodiment, the present invention provides an in vivo method of determining the progression of Parkinson's disease in a subject over time, comprising: (i) obtaining a first neuromelanin magnetic resonance image at a first time point; (ii) after step (i), comparing the first neuromelanin magnetic resonance image with an age-matched control; (iii) determining the level, signal and / or concentration of neuromelanin that occurs between said first time point and said second time point; The present invention relates to a method comprising:

[0026] In one embodiment, there is provided an in vivo method for diagnosing Parkinson's disease, comprising: (i) obtaining a first neuromelanin magnetic resonance image at a first time point; (ii) after step (i), obtaining a second neuromelanin magnetic resonance image at a second time point; (iii) comparing the first neuromelanin magnetic resonance image to the second neuromelanin magnetic resonance image, thereby determining whether a change in one or more of neuromelanin level, signal, or concentration has occurred between the first and second time points. The present invention relates to a method comprising:

[0027] In one embodiment, the present invention is directed to a method of providing a treatment regimen to a patient, comprising the steps of performing an NM-MRI scan, acquiring an NM signal from the NM-MRI scan in a region of interest, comparing the NM signal from the NM-MRI scan in the region of interest data with age-matched database numbers, and administering a corresponding treatment regimen if the NM signal is below a predetermined value.

[0028] In one embodiment, the subject exhibits symptoms of Alzheimer's disease.

[0029] In one embodiment, the patient suffers from a disorder commonly misdiagnosed as Parkinson's disease. In one embodiment, the disorder is essential tremor. In one embodiment, the disorder is familial tremor.

[0030] In one embodiment, NM-MRI scans and analysis distinguish between Alzheimer's disease and Parkinson's disease. In one embodiment, NM-MRI scans and analysis can distinguish and individually identify related disorders (e.g., MSA, PSP, Parkinsonism, dyskinesia, dystonia). In one embodiment, NM-MRI scans and analysis can monitor the progression, treatment, and prognosis of Parkinson's disease-related disorders (e.g., MSA, PSP, Parkinsonism, dyskinesia, dystonia).

[0031] In one embodiment, the invention provides a method of determining whether a subject has or is at risk for developing Parkinson's disease comprising analyzing one or more Neuromelanin-Magnetic Resonance Imaging (NM-MRI) scans of a region of interest in the subject's brain, the analyzing step comprising: receiving imaging information of a brain region of interest; and Based on the imaging information, determine the NM concentration in the brain region of interest using voxel-wise analysis. Including, Determining whether a subject has or is at risk for developing Parkinson's disease includes: (1) that the subject has or is at risk of developing Parkinson's disease if the NM signal in one or more NM-MRI scans is reduced compared to one or more control scans without Parkinson's disease; or (2) The method includes determining that the subject does not have or is not at risk for developing Parkinson's disease if one or more NM-MRI scans have an NM signal equivalent to the signal of one or more control scans without Parkinson's disease.

[0032] In one embodiment, the present invention provides a method of treating a subject having Parkinson's disease comprising analyzing a Neuromelanin-Magnetic Resonance Imaging (NM-MRI) scan of a region of interest in the brain of the subject, the analyzing step comprising: Receiving imaging information of a region of interest of the brain at a first point in time; receiving imaging information of the brain region of interest at a second time point; determining NM concentrations at the first and second time points in the brain region of interest using voxel-wise analysis based on the imaging information; and Comparing NM concentrations at the first and second time points Including, The treatment method is as follows: (1) administering one or more of levodopa and carbidopa if the NM signal of the NM-MRI scan at the second time point is decreased compared to the NM signal at the first time point; or (2) withholding the step of administering one or more of levodopa and carbidopa if the NM signal of the NM-MRI scan at the second time point is increased compared to the NM signal at the first time point. The present invention is directed to a method, further comprising:

[0033] In one embodiment, the subject exhibits one or more symptoms of Parkinson's disease.

[0034] In one embodiment, the method provides a diagnosis of Parkinson's disease before symptoms are clinically manifest.

[0035] In one embodiment, the NM-MRI method distinguishes between Alzheimer's disease and Parkinson's disease.

[0036] In one embodiment, the NM-MRI method diagnoses the patient as having Parkinson's disease or not having Parkinson's disease and displays the diagnosis to the user via the user interface.

[0037] In one embodiment, the analysis is a voxel-wise analysis.

[0038] In one embodiment, the voxel-wise analysis includes determining at least one topographical pattern within the brain region of interest.

[0039] In one embodiment, the method further comprises a calculation using a value representing the volume of a neuromelanin voxel.

[0040] In one embodiment, the region of interest for the voxel-wise analysis is the substantia nigra.

[0041] In one embodiment, the region of interest for the voxel-wise analysis is a subregion of the ventral substantia nigra.

[0042] In one embodiment, the present invention provides a diagnostic system for providing diagnostic information relating to Parkinson's disease, the system being configured to generate and acquire neuromelanin sensitive MRI scans together with a set of neuromelanin data for voxels located within a region of interest in the brain of a subject; a signal processor configured to process the set of neuromelanin data to generate a processed neuromelanin MRI spectrum; and a diagnostic processor configured to process the processed neuromelanin MRI spectra, extracting measurements from the region of interest corresponding to neuromelanin at a point in time; The measurements are compared to one or more control measurements taken prior to the time point. a diagnostic processor that provides a diagnosis of Parkinson's disease if the measurement is more than about 25% less than the control measurement. The present invention relates to diagnostic systems, including

[0043] In another aspect, a method is provided for determining whether brain tissue in a subject contains an abnormal level of neuromelanin. The method includes detecting the level of neuromelanin in the tissue. The level of neuromelanin is compared to a standard control. If a lower level of neuromelanin is detected compared to the standard control, this indicates Parkinson's disease.

[0044] In one embodiment, a method is provided for determining whether a Parkinson's disease treatment administered to a subject is effective. The method includes detecting a level of endogenous neuromelanin in a tissue at a first time point. In a subsequent step, the treatment is administered to the subject. The level of neuromelanin in the tissue is then determined at a second time point. Thereafter, the level of neuromelanin at the first time point is compared to the level of neuromelanin at the second time point. A higher level of neuromelanin at the second time point compared to the first time point indicates that the treatment was effective. Alternatively, a lower level of neuromelanin at the second time point compared to the first time point indicates that the treatment administered to the subject was ineffective.

[0045] In one embodiment, a method of treating a patient with Parkinson's disease is provided. In one embodiment, the method includes administering an initial dose of L-dopa to the patient. In one embodiment, the method includes monitoring neuromelanin concentrations in a region of interest in the patient's brain and assessing treatment-related adverse events over the initial treatment period. In one embodiment, during the initial treatment period, the patient: i) a reduction in neuromelanin concentration in a region of interest in the patient's brain, and ii) Absence of L-dopa-related adverse or side effects. increasing the dose of L-dopa in subsequent treatment periods if the patient exhibits one or more of the following: L-dopa treatment results in improvement of Parkinson's disease symptoms in patients.

[0046] In one embodiment, the method of treatment comprises the following steps: Repeating steps a) to c) until the patient no longer exhibits one or more of i) to ii) in step c). Includes.

[0047] This patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the U.S. Patent and Trademark Office upon request and payment of the necessary fee. [Brief description of the drawings]

[0048] [Figure 1A-B] Figure 1A-B show MRI images. (A) A template of the midbrain in MNI space generated by averaging spatially normalized NM-MRI images from all participants. The substantia nigra (SN) is clearly visible as a high signal region. (B) A mask of the SN (yellow, an over-inclusive mask to ensure full SN coverage for all participants) and cerebral peduncle reference region (cyan) in MNI space was traced onto the NM-MRI template and applied to all participants for calculation of contrast-to-noise ratio (Methods).

[0049] [Figure 2A-D] Figure 2A-D shows a comparison between cocaine users and controls. (A) Diagnostic group differences in NM-MRI signal between cocaine users and controls. Scatter plots showing extracted NM-MRI signal (CNR) averaged within cocaine voxels (top panel, defined in C), cocaine voxels defined by the leave-one-out (LOO) procedure (middle panel), and total SN (bottom panel) in participants split based on diagnosis. To complement the results showing the effect of diagnostic group on NM-MRI signal after adjusting for covariates (B and statistics reported in the text), these scatter plots show diagnostic group differences in raw unadjusted NM-MRI signal. (B) Receiver operating characteristic curves showing the sensitivity and specificity of NM-MRI signal in separating diagnostic groups based on signal extracted from cocaine voxels (top panel), cocaine voxels defined by the leave-one-out procedure (middle panel), and total SN (bottom panel). The black line represents the NM-MRI signal adjusted for the covariates age, head coil, and tobacco use; the grey line represents the unadjusted NM-MRI signal. (B) Map of voxels where cocaine users showed higher NM-MRI signal than controls (shown in red, robust linear regression, p<0.05 one-tailed). This set of voxels was above chance level (p corrected=0.025, permutation test). (C) Unthresholded results of the same analysis showing the t-statistic for the effect of diagnostic group for all SN voxels. Voxels where the NM-MRI signal was higher in cocaine users are shown in red, and voxels where the signal was smaller in cocaine users are shown in blue.

[0050] [Diagram 3]Figure 3 shows a schematic diagram illustrating the transport of dopamine between cytosolic, vesicular and synaptic pools in the striatum and the subsequent accumulation of NM in the SN (curved arrows) in healthy subjects and in cocaine use disorder. The dashed box shows a schematic detail of the striatal synapse between presynaptic dopamine neurons in grey and postsynaptic striatal neurons in green. Left: Cytosolic dopamine pools are normally converted to NM and gradually accumulate over a lifetime in the cell bodies of presynaptic dopamine neurons in the SN in the midbrain. Right: A theoretical scenario is presented to explain the changes observed in cocaine use disorder, including the reduced dopamine release observed with PET in previous literature and the increased NM-MRI signal reported here. A reduction in VMAT2, also consistent with PET and postmortem studies, could explain both of these: lower VMAT2 expression reduces vesicular dopamine and increases the cytosolic dopamine pool from which NM is synthesized. See main text for alternative interpretations of the data.

[0051] [Figure 4] FIG. 4 shows clinical and demographic measurements.

[0052] [Diagram 5] FIG. 5 shows the demographic and clinical characteristics of the study presented in Example 4.

[0053] [Figure 6A-B]Figure 6A-B shows that baseline NM-MRI CNR correlates with walking speed at baseline. (a) Map of SN-VTA voxels where NM-MRI CNR correlated positively (thresholded at voxel level of P<0.05) with a single task measure of walking speed (green voxels) overlaid on the average NM-MRI CNR image from all subjects. (b) Scatter plot showing the average NM-MRI CNR extracted from significant voxels plotted against walking speed for visualization purposes. These plotted data show a Pearson correlation coefficient of 0.49, although this effect size estimate is likely significantly inflated given the selection of voxels significant for this effect.

[0054] [Figure 7A-B] Figures 7A-B show that secondary analysis of baseline NM-MRI CNR does not predict change in walking speed after 3 weeks of L-dopa treatment in region of interest or voxel-wise analysis. (a) Scatter plot showing mean NM-MRI CNR extracted from significant (green) voxels in Figure 1a plotted against walking speed. These plotted data have a Pearson correlation coefficient of 0.10. (b) Scatter plot showing mean NM-MRI CNR extracted from voxels where NM-MRI CNR positively correlates with change in walking speed after 3 weeks of L-dopa treatment (N=64, thresholded at voxel level of P<0.05). These plotted data have a Pearson correlation coefficient of 0.17.

[0055] [Figure 8A-C]Figure 8A-C shows that NM-MRI CNR increases significantly after 3 weeks of L-dopa treatment. (a) Map of SN-VTA voxels with significantly increased NM-MRI CNR after 3 weeks of L-dopa (thresholded at voxel level of P<0.05, red voxels) overlaid on the average NM-MRI CNR image from all subjects. (b) Histogram showing the mean change across subjects in NM-MRI CNR after treatment including all SN-VTA voxels, which generally shifts to the right of zero (signifying increased NM-MRI CNR). For visualization purposes, height is proportional to either the number of L-dopa voxels (N=200; red bars corresponding to voxels) or the number of other SN-VTA voxels (i.e., non-significant voxels; N=1607). For example, the bar with a voxel ratio of 0.2 for L-dopa voxels corresponds to 40 voxels, while the bar with a voxel ratio of 0.2 for other SN-VTA voxels corresponds to 321 voxels. (c) Ladder plot showing the mean NM-MRI CNR extracted from significant (red) voxels at baseline (pre-L-dopa) and 3 weeks after L-dopa treatment (post-L-dopa) for six subjects (each displayed in a different color to highlight the consistent increase across subjects). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0056] Detailed Description Before describing the present disclosure in more detail, it is to be understood that this disclosure is not limited to particular embodiments described, as such may, of course, vary. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be limited only by the appended claims. definition

[0057] The details shown in this specification are merely for the purpose of example and illustrative discussion of embodiments of the present invention, and are shown to provide what is believed to be the most useful and easily understood explanation of the principles and conceptual aspects of the present invention. In this regard, no attempt has been made to show in more detail the structural details of the present invention necessary for a fundamental understanding of the present invention, and the description is made in conjunction with figures that will make clear to those skilled in the art how forms of the present invention can be embodied in practice.

[0058] As used herein, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise.

[0059] Unless otherwise indicated, all numbers expressing quantities of ingredients, reaction conditions, and the like used in the specification and claims should be understood to be modified in all instances by the term "about." Accordingly, unless specifically indicated to the contrary, the numerical parameters set forth in the following specification and appended claims are approximations that may vary depending upon the desired properties sought to be obtained by the present invention. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should be construed in light of the number of significant digits and ordinary rounding conventions.

[0060] Furthermore, disclosure of a numerical range within this specification is considered to be a disclosure of all numerical values ​​and ranges within that range. For example, if a range is from about 1 to about 50, it is considered to include, for example, 1, 7, 34, 46.1, 23.7, or any other value or range within that range. Furthermore, the terminology includes at least the specified number, for example, "at least 50" includes 50.

[0061] The term "MR" refers to magnetic resonance, which is the physical principle underlying various experimental procedures known in the art and / or described herein, including MRI ("magnetic resonance imaging"), MRS ("magnetic resonance spectroscopy"), and the like. The term neuromelanin-sensitive MRI or neuromelanin-MRI refers to the use of MRI in the study of neuromelanin in the brain. As used herein, the general terms magnetic resonance imaging, magnetic resonance imaging, or MRI encompass neuromelanin-sensitive variants.

[0062] As used herein, the term "NM-MRI" and similar nomenclature refer, independently, both individually and together, to an MRI scan and corresponding voxel-wise analysis, respectively.

[0063] As used herein, the terms "T1" and "T2" refer to their conventional meanings well known in the art (i.e., "spin-lattice relaxation time" and "spin-spin relaxation time," respectively).

[0064] The term "T1 weighted" in the context of MRI images refers to images made with pulsed spin echo or inversion recovery sequences with appropriately shortened TR and TE, which can show contrast between tissues with different T1 values, as known in the art. The term "TR" in this context refers to the repetition time between excitation pulses. The term "excitation pulse" is understood to refer to a 90 degree radio frequency (RF) excitation pulse. The term "TE" refers to the echo time between the excitation pulse and MR signal sampling.

[0065] The term "subject" can be a mammalian subject, such as a mouse, rattus, horse, cow, sheep, dog, cat, or human. In some embodiments of the methods described herein, the subject is a mouse, while in other embodiments, the subject is a human. The term "patient" in this context refers to a human subject.

[0066] As used herein, the term "alleviate" is intended to describe the process of decreasing the severity of a sign or symptom of a disorder. Importantly, a sign or symptom can be alleviated without being eliminated. In a preferred embodiment, the use of the treatment methods disclosed herein results in, but does not require, the disappearance of a sign or symptom. Effective dosages as guided by the present invention are expected to reduce the severity of a sign or symptom.

[0067] Dosage and administration are adjusted to provide sufficient level of active agent or maintain desired effect.Factors that can be considered include: severity of disease state, general health of subject, age, weight and sex of subject, diet, administration time and frequency, drug interactions, reaction sensitivity and tolerance / response to treatment.Effective amount of pharmaceutical agent is that which realizes objectively identifiable improvement.

[0068] As used herein, "stable" refers to a reproducible measurement. In one embodiment, "stable neuromelanin levels" refers to neuromelanin levels that are: It refers to continuous scans that remain relatively constant. In some contexts, "stable neuromelanin levels" are maintained for one or more hours, one or more days, one or more weeks, or one or more treatment cycles.

[0069] The terms "treat", "treatment" and the like in the context of a disease refer to improving, inhibiting, eradicating, and / or delaying the onset of the disease being treated. In some embodiments, the methods described herein are performed on a subject in need of treatment. The term "in need of treatment" and the like as used herein refers to a subject at risk of developing a disease, having a condition that is understood by a medical or veterinary technician to lead to and / or actually have the disease. Treatments for Parkinson's disease include currently approved treatments and exploratory treatments. The NM-MRI of the present invention can monitor the effectiveness of treatments for Parkinson's disease. The NM-MRI of the present invention can determine the effectiveness of exploratory treatments. A non-exhaustive list of treatments for Parkinson's disease that can be monitored by an embodiment of the present invention includes one or more of the following:

[0070] Treatment of Parkinson's disease includes disease-modifying therapies. These therapies aim to prevent, slow or stop the overall progression of Parkinson's disease (PD). They target different proteins and pathways that are believed to play a role in the disease.

[0071] Alpha-synuclein; this protein forms toxic clumps in the brain and body cells of some people with PD.

[0072] Anle138b;MODAG, a small molecule, aims to inhibit the aggregation of alpha-synuclein. MJFF funded part of the preclinical and Phase I trials in people with Parkinson's disease.

[0073] BIIB054; Biogen's antibody aims to prevent aggregated alpha-synuclein from spreading. MJFF is funding instrumentation development and data collection to help design the study.

[0074] NPT088; a drug candidate from Proclara (formerly Neurophage) aims to prevent alpha-synuclein from clumping together and forming clumps. MJFF funded preclinical trials.

[0075] PD01A;AFFiRiS' vaccine aims to mimic antibodies against alpha-synuclein. MJFF funded preclinical trials, part of the Phase I study, and the boost study.

[0076] RO7046015; Prothena / Roche's antibody aims to prevent aggregated alpha-synuclein from spreading. MJFF is funding instrumentation development and data collection to support study design.

[0077] GBA; Mutations in the GBA gene are associated with Parkinson's disease and are linked to certain cellular dysfunction.

[0078] GZ / SAR402671; a Sanofi Genzyme drug that reduces the production of lipids composed of GBA variants. MJFF is funding instrumentation development and data collection to help with study design.

[0079] LTI-291; an oral drug from Lysosomal Therapeutics, can offset dysfunction associated with GBA mutations. MJFF funded preclinical trials.

[0080] LRRK2; Mutations in the LRRK2 gene are associated with Parkinson's disease and are linked to greater activity of the LRRK2 protein.

[0081] DNL201; Denali's LRRK2 inhibitor, aims to reduce increased LRRK2 activity. MJFF funded a safety study supporting this trial.

[0082] Exenatide; a diabetes drug that protects brain cells in a preclinical model of Parkinson's disease. MJFF funded the Phase II trial led by University of College London.

[0083] Inosine; a dietary supplement increases urate (antioxidant) levels. Population studies have shown that inosine may have a preventive effect on PD or slow its progression. MJFF has funded preclinical and Phase II studies and is supporting biomarker collection in a Phase III study led by the Parkinson's Study Group.

[0084] Isradipine; a high blood pressure drug, may help protect brain cells.

[0085] Nilotinib; this treatment for cancer of the white blood cells (chronic myeloid leukemia) can address the dysfunction seen in PD.

[0086] Treatments for Parkinson's disease include neurotrophic factors. Trophic factors are like natural fertilizer for the brain. They help restore neurons and protect them. GDNF; a trophic factor from MedGenesis, can protect dopamine cells. MJFF funded preclinical trials. CDNF; a trophic factor from Herantis, can protect dopamine cells. MJFF funded preclinical trials.

[0087] Treatments for Parkinson's disease include those that improve motor symptoms. Tremor, stiffness and slowness of movement affect movement. Levodopa helps, but does not treat all symptoms, can feel less effective over time, and can cause side effects such as dyskinesia with long-term use.

[0088] Levodopa delivery; the gold standard for treating motor symptoms, can wear off over time with long-term use and cause side effects such as dyskinesia. Researchers believe some side effects may be due to fluctuating levels of levodopa. Accordion Pill; a layer of levodopa / carbidopa that releases slowly from the stomach for better absorption. NDO612; Neuroderm's levodopa / carbidopa pump or pump patch can maintain a stable level of levodopa.

[0089] Levodopa is a prodrug of dopamine that is administered to patients with Parkinson's disease because of its ability to cross the blood-brain barrier. Levodopa can be metabolized to dopamine on one side of the blood-brain barrier, and therefore is commonly administered with a dopa decarboxylase inhibitor, such as carbidopa, to prevent metabolism until after levodopa has crossed the blood-brain barrier. Once levodopa has crossed the blood-brain barrier, it is metabolized to dopamine to compensate for low endogenous levels of dopamine and treat the symptoms of Parkinson's disease. The first drug product in development approved by the FDA was a combination product of levodopa and carbidopa, called Sinemet.

[0090] Treatments for Parkinson's disease include non-dopamine approaches. Targeting other brain chemicals with add-on therapies may help control the motor fluctuations associated with levodopa use. PXT002331; an oral medication from Prexton Therapeutics (Foliglurax) works on glutamate and other brain chemical systems to reduce motor symptoms and dyskinesias.

[0091] Treatments for Parkinson's disease include "off" rescue therapies. When levodopa levels drop, a patient's symptoms can return. This is called an "off" episode. APL-130277, a thin film of the drug apomorphine placed under the tongue from Sunovion (formerly Cynapsus), can rescue patients from "off" episodes. CVT-301, an inhaled levodopa from Acorda (formerly Civitas), can quickly relieve symptoms.

[0092] Treatments for Parkinson's disease include gene therapy. Through surgery, selected genes are delivered to the brain to increase production of the missing protein. AAV2-hAADC; Voyager's approach aims to replace the AADC enzyme in brain cells to improve the conversion of levodopa to dopamine in advanced Parkinson's disease, for better control of motor symptoms and less "off" time.

[0093] Conventional MRI lacks the spatial and quantitative data necessary to predict the clinical outcome of neurotrauma. However, the method discussed herein detects the level of neuromelanin in the brain, which can predict the clinical progression, severity and response of Parkinson's disease, taking into account the distribution of neuromelanin in the brain or the loss of neuromelanin-containing neurons.

[0094] In some embodiments, NM-MRI provides a dose titration method for the treatment of Parkinson's disease while avoiding the adverse effects or side effects caused by currently approved or investigational therapies. Specifically, administering L-dopa while monitoring NM signals using the voxel-wise approach described herein to guide dosage regimens can increase efficacy compared to administering L-dopa alone.

[0095] Furthermore, administering therapeutic agents according to specific dosage regimens guided by NM-MRI can reduce potential side effects associated with administration. For example, administering L-dopa according to specific dosage regimens guided by the NM-MRI voxel analysis of the present invention can significantly reduce or even completely eliminate treatment-related side effects.

[0096] In certain embodiments, the dose of L-dopa is increased, decreased, administered more frequently, or administered less frequently depending on physiological factors including, but not limited to, an increase or decrease in neuromelanin in the subject's brain region of interest compared to a previous scan or compared to a baseline control. In one embodiment, the region of interest is a voxel associated with Parkinson's disease symptoms. Dose variation increases patient compliance, improves treatment, and reduces undesirable and / or adverse effects. In certain embodiments, the therapeutic method of the present invention provides an improved overall treatment compared to administration of a therapeutic agent by itself.

[0097] In certain embodiments, when using the guided intervention of the present invention, the dosage of existing drugs can be reduced or administered less frequently, thereby increasing patient compliance, improving treatment, and reducing undesirable or adverse effects. In one embodiment, monitoring treatment with NM-MRI of the present invention allows patients to receive benefits from treatment for a longer time frame.

[0098] Neuromelanin-sensitive MRI data can be used as a biomarker for Parkinson's disease, or the risk of developing Parkinson's disease, severity, disease progression, treatment response, and / or clinical outcome. Neuromelanin-sensitive MRI methods fulfill the need for objective biomarkers to track Parkinson's disease, severity, or the risk of its onset. Neuromelanin-sensitive MRI can be used as a safe alternative to invasive / radiologic imaging measurements (e.g., PET). Neuromelanin-sensitive MRI can also be used for monitoring progression, which cannot currently be performed given the risk of repeated exposure to radiation. Neuromelanin-sensitive MRI is noninvasive, inexpensive, safe, and easy to acquire in a clinical setting. This allows for a significant improvement in anatomical resolution (5-10x), which allows for the resolution of anatomical details within relevant brain structures.

[0099] In certain embodiments, the neuromelanin-sensitive magnetic resonance image is obtained periodically, for example, every 1, 2, 3, 4, 5, 6 or 7 days, every 1, 2, 3 or 4 weeks, every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 months, or every 1, 2, 3, 4 or 5 years. In certain embodiments, the first magnetic resonance image is obtained before symptoms appear. In certain embodiments, the first magnetic resonance image is obtained before symptoms associated with Parkinson's disease. The second magnetic resonance image may be obtained either before symptoms appear or after. In other embodiments, the second magnetic resonance image may be obtained one year after the first magnetic resonance image.

[0100] In some embodiments, neuromelanin-sensitive magnetic resonance imaging ("NM-MRI") techniques are useful for non-invasively diagnosing, measuring the effects and / or providing a prognosis for Parkinson's disease.

[0101] In some embodiments, the NM-MRI technique is used as a means to diagnose pre-symptomatic Parkinson's disease. In some embodiments, the NM-MRI technique is effective in distinguishing Parkinson's disease from other neurological conditions, including but not limited to Alzheimer's disease. In other embodiments, the NM-MRI technique is effective in selecting a course of treatment, and optionally, such treatment is effective in treating Parkinson's disease.

[0102] In some embodiments, the NM-MRI technique is used as a means to monitor the progression of Parkinson's disease, hi some embodiments, the NM-MRI technique is useful for longitudinal assessment of the progression of Parkinson's disease.

[0103] In some embodiments, the technique measures neuromelanin directly or indirectly. In other embodiments, the technique measures dopamine function directly or indirectly. In some embodiments, there is a relationship between neuromelanin-sensitive MRI (NM-MRI) signal and the severity of Parkinson's disease.

[0104] In some embodiments, the NM-MRI technique is capable of determining the concentration of neuromelanin across all areas of brain tissue. In other embodiments, the NM-MRI technique is capable of determining the local concentration of neuromelanin. In other embodiments, the NM-MRI technique is capable of determining the local level of neuromelanin. In other embodiments, the NM-MRI technique is capable of determining the local signal intensity of neuromelanin.

[0105] In other embodiments, the NM-MRI technique determines neuromelanin concentration in substantia nigra subregions. In further embodiments, the NM-MRI technique determines, either directly or indirectly, dopamine release in the dorsal striatum and resting blood flow within the substantia nigra.

[0106] In some embodiments, NM-MRI signal and severity of Parkinson's disease are directly correlated. In some embodiments, NM-MRI signal and severity of Parkinson's disease are inversely correlated. In other embodiments, NM-MRI shows lower signal in the nigrostriatal tract of individuals with Parkinson's disease. In some embodiments, NM-MRI captures dopamine dysfunction. In yet other embodiments, NM-MRI can be used as a biomarker for Parkinson's disease. In further embodiments, NM-MRI can be used to determine the severity of Parkinson's disease. In further embodiments, NM-MRI can be used to provide a diagnosis and / or prognosis for Parkinson's disease.

[0107] In some embodiments, the analysis is performed in comparison to a previous NM-MRI. In other embodiments, the analysis is performed in comparison to a reference value and / or range. In some embodiments, the reference value and / or range is generated using a compilation of neuromelanin data from healthy individuals. In some embodiments, the reference value and / or range is generated using a compilation of neuromelanin data from individuals with Parkinson's disease. In some embodiments, the reference value and / or range is generated using a compilation of neuromelanin data from individuals with Parkinson's disease and people without Parkinson's disease.

[0108] In some embodiments, the NM-MRI signal is received from the lateral substantia nigra. In other embodiments, the NM-MRI signal is received from the posterior substantia nigra. In further embodiments, the NM-MRI signal is received from a ventral region of the substantia nigra. In some embodiments, the NM-MRI signal is received from one or more of the lateral, posterior, and ventral regions of the substantia nigra.

[0109] In some embodiments, the NM-MRI signal is received from the substantia nigra or the locus coeruleus. In some embodiments, the NM-MRI signal is received from the ventral substantia nigra. In some embodiments, the NM-MRI signal is received from the substantia nigra lateralis. In some embodiments, the NM-MRI signal is received from the ventrolateral substantia nigra. In some embodiments, the NM-MRI signal is received from the substantia nigra pars compacta (SNpc). In some embodiments, the NM-MRI signal is received from the substantia nigra pars reticulata (SNpr). In some embodiments, the NM-MRI signal is received from the ventral tegmental area (VTA). In some embodiments, the NM-MRI signal is received from the locus coeruleus. In some embodiments, the NM-MRI signal is received from one or more of the substantia nigra ventralis, the substantia nigra lateralis, the ventrolateral substantia nigra, the substantia nigra pars compacta (SNpc), the substantia nigra pars reticulata (SNpr), the ventral tegmental area (VTA), and the locus coeruleus.

[0110] In some embodiments, the NM-MRI technique comprises the steps of assessing neuromelanin in a subject, comprising the steps of performing an MRI scan, acquiring neuromelanin data, optionally encrypting the neuromelanin data, optionally uploading the neuromelanin data to a remote server, optionally decrypting the data, and performing an analysis of the neuromelanin data, the analysis optionally comprising comparing the neuromelanin data to previously acquired data, a large population database, or both, generating a report including the neuromelanin analysis, optionally encrypting the report, optionally uploading the report to a remote server, and optionally decrypting the report.

[0111] In some embodiments, the report provides a diagnosis for Parkinson's disease. In some embodiments, a physician or imaging professional interprets the report. In further embodiments, the analysis is performed remotely. In other embodiments, the remote analysis is performed on a cloud platform. In other embodiments, the remote analysis is performed on a cloud server.

[0112] In one embodiment, the invention is directed to analyzing and classifying Parkinson's disease in a subject, e.g., a human subject of a study or investigation, or a patient. Subject data is acquired by NM-MRI measurements. A plurality of templates classified according to the degree of Parkinson's disease are stored in a data store, e.g., a database. Each template represents a subset of neuromelanin measurements selected from a population of at least one other subject known to have Parkinson's disease and measured. The set of data is processed to obtain a model that represents temporal measurements between neuromelanin concentrations in the subject. At least a portion of the neuromelanin data is compared to the plurality of templates to generate a classification of Parkinson's disease.

[0113] Embodiments of the invention include diagnostic tools for use in clinical settings or tools for evaluating subjects in research settings. More generally, aspects of the invention provide tools for utilizing NM-MRI to obtain an evaluation or diagnosis of Parkinson's disease. Systems and methods according to various aspects of the invention are useful for monitoring potentially changing conditions of a subject, such as, for example, the progression of Parkinson's disease. Additionally, aspects of the invention provide solutions for monitoring the effectiveness of treatment in patients.

[0114] A second aspect of the present invention is a method of screening for therapeutic agents that prevent, delay or halt the onset or progression of Parkinson's disease or a corresponding symptom in a patient, comprising the steps of: 1) exposing the patient to at least one candidate therapeutic agent; 2) measuring neuromelanin concentration; and 3) evaluating the effect of the at least one therapeutic agent on the onset or progression of Parkinson's disease or a corresponding symptom in the patient.

[0115] Certain embodiments of the present invention can provide an objective test to improve diagnostic accuracy, accelerate recognition of Parkinson's disease to a presymptomatic stage, and act as a monitor for treatment. In general, embodiments of the present invention can be used to diagnose neuromelanin using stored templates, differentiate between several different conditions or diseases, and monitor subjects over a period of time.

[0116] In one embodiment, the invention is used with a second imaging method, the second imaging method being Positron Emission Tomography (PET). In one embodiment, the invention is used with a second imaging method that is structural MRI. In one embodiment, the invention is used with a second imaging method that is functional MRI (fMRI). In one embodiment, the invention is used with a second imaging method that is blood oxygen level dependent (BOLD) fMRI. In one embodiment, the invention is used with a second imaging method that is iron sensitive MRI. In one embodiment, the invention is used with a second imaging method that is quantitative susceptibility mapping (QSM). In one embodiment, the invention is used with a second imaging method that is diffusion tensor imaging DTI. In one embodiment, the invention is used with a second imaging method that is single photon emission computed tomography (SPECT). In one embodiment, the invention is used with a second imaging method that is DaTscan. In one embodiment, the invention is used with a second imaging method that is DaTquant.

[0117] In some embodiments, neuromelanin concentration and / or level is measured against a control, and a diagnosis of Parkinson's disease is supported if the neuromelanin concentration and / or level is about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40%, about 50%, about 60%, about 70%, about 80%, about 90% lower than the control. In some embodiments, the change in neuromelanin is evaluated as the net concentration or level change per year. In some embodiments, the change in neuromelanin is evaluated as the percentage change per year. In some embodiments, the neuromelanin concentration and / or level is measured against a control, and the neuromelanin concentration and / or level is about 1%, about 2%, about 3%, about 4%, about 5%, about 6%, about 7%, about 8%, about 9%, about 10%, about 11%, about 12%, about 13%, about 14%, or about 15% lower than the control. In some embodiments, the neuromelanin concentration and / or level is measured against a control, and the neuromelanin concentration and / or level is reduced by about 1%, about 2%, about 3%, about 4%, about 5%, about 6%, about 7%, about 8%, about 9%, about 10%, about 11%, about 12%, about 13%, about 14%, or about 15% per year compared to the control. In one embodiment, the control is a previous NM-MRI scan and voxel-wise analysis of the patient. In one embodiment, the neuromelanin concentration and / or level is measured relative to a control, and the neuromelanin concentration and / or level is measured annually, every two years, every three years, every four years, every five years, every six years, every seven years, every eight years, every nine years, every ten years, every twenty years. In one embodiment, the second time point is about three months, about six months, about nine months, about twelve months, about two years, about three years, about four years, about five years, about six years, about seven years, about eight years, about nine years, about ten years, about fifteen years, about twenty years, about twenty five years, or about thirty years after the first time period. In certain embodiments, the patient is diagnosed with Parkinson's disease if the neuromelanin concentration and / or level is measured to be lower than the control. In certain embodiments, the patient is diagnosed with Parkinson's disease if the neuromelanin concentration and / or level is measured to be a predetermined amount less than the control, either annually or by net overall change.In further embodiments, the measured neuromelanin is greater than about 20% less than the control. In further embodiments, the measured neuromelanin is greater than about 25% less than the control. In further embodiments, the measured neuromelanin is greater than about 30% less than the control. In further embodiments, the measured neuromelanin is greater than about 35% less than the control. In further embodiments, the measured neuromelanin is greater than about 45% less than the control. In further embodiments, the measured neuromelanin is greater than about 40% less than the control. In further embodiments, the measured neuromelanin is greater than about 50% less than the control. In certain embodiments, the control is optionally a previous neuromelanin MRI scan of the same patient. In other embodiments, the control includes a reference number, optionally determined from a database of neuromelanin MRI scans from at least one other person with Parkinson's disease.

[0118] In one embodiment, a diagnosis of Parkinson's disease is indicated if the change in the level, signal and / or concentration of neuromelanin at the second time point is more than about 5% lower or more than about 10% lower than the level, signal and / or concentration of neuromelanin at the first time point, and the first and second time points are about 1 year, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years or about 10 years apart.

[0119] In one embodiment, a diagnosis of Parkinson's disease is indicated if the change in neuromelanin level, signal and / or concentration at the second time point is more than about 35% lower, more than about 40% lower, more than about 45% lower, or more than about 50% lower than the neuromelanin signal and / or concentration at the first time point, and the first and second time points are separated by about 1 year, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years, or about 10 years.

[0120] In one embodiment, the degree of reduction in neuromelanin volume, signal or concentration in a given patient compared to a control is proportional to the progression and / or severity of Parkinson's disease.

[0121] In one embodiment, the degree of increase in neuromelanin volume, signal or concentration in a given patient compared to a control is proportional to the progression of Parkinson's disease and / or improvement and / or effectiveness of the treatment.

[0122] In one embodiment, the standard control is a level of neuromelanin present at approximately the same level in a population of subjects, or the standard control is approximately the average level of neuromelanin present in a population of subjects.

[0123] To illustrate the broadening of the use of NM-MRI for such applications, a series of validation studies are presented. The first step is presented to show that NM-MRI may be sensitive enough to detect local variations in tissue concentrations of NM, which likely depend on inter-individual and inter-regional differences in dopamine function (including, for example, synthetic and storage capacity), and not simply loss of NM-containing neurons. To test this, MRI measurements were compared to neurochemical measurements of NM concentrations in postmortem tissue without Parkinson's disease. Since variations in dopamine function may not necessarily occur uniformly throughout all SN layers, the next step was to show that NM-MRI, with its high anatomical resolution compared to standard molecular imaging procedures, has sufficient anatomical specificity. NM-MRI is used to test the ability of a novel voxel-wise approach to capture known topographical patterns of cell loss within the SN in Parkinson's disease. Then, the next step is to use the voxel-wise approach to present direct evidence of a relationship between NM-MRI and Parkinson's disease.

[0124] As discussed in WO2020 / 077098, which is incorporated by reference in its entirety, NM-MRI signals correlate with well-validated positron emission tomography ("PTET") measurements of dopamine release into the striatum (the major projection site of SN neurons) and functional MRI measurements of regional blood flow in the SN, an indirect measure of SN neuronal activity, in a group of individuals without Parkinson's disease. Neuromelanin levels are increased (concentration in SNc, volume of NM in SNc) as measured by Terran NM-101, which improves UPDRS with L-dopa therapy.

[0125] The present invention correlates Parkinson's voxels with Parkinson's symptoms as measured by the UPDRS; demonstrates that applying voxel-based analysis methods with the Terran NM-101 finds specific voxels (called PD voxels) unique to each patient that correlate with their specific symptoms on the UPDRS; determines the correlation between changes in neuromelanin measurements after initiation of L-dopa therapy and improvement in UPDRS scores; determines the difference in neuromelanin measurements in patients with PD from the normal range of controls (e.g., total NM concentration (micrograms of neuromelanin per microgram of wet tissue) in the substantia nigra pars compacta (SNc), NM concentration in subregional SNc, volume of neuromelanin in total SNc, volume of subregional SNc); determines the difference in neuromelanin measurements in patients with PD from the normal range of controls (e.g., total NM concentration (micrograms of neuromelanin per microgram of wet tissue) in the substantia nigra pars compacta (SNc)), NM concentration in subregional SNc, volume of neuromelanin in total SNc, volume of subregional SNc); determines the difference in neuromelanin measurements in patients with PD from the normal range of controls that would justify a diagnosis of PD Determine the differences in neuromelanin levels from the groups; correlate changes in neuromelanin measurements after initiation of L-dopa therapy with improvement in UPDRS scores; determine increases in neuromelanin levels that result in improvement in UPDRS to validate that NM levels can be used to monitor response to treatment; correlate Parkinson's voxels with Parkinson's symptoms as measured by UPDRS scores; apply voxel-based analysis methods to find specific voxels unique to each patient (called PD voxels) that correlate with their specific symptoms on the UPDRS; correlate between both NM-MRI scans, and DaTscan and UPDRS scores.

[0126] In one embodiment, L-dopa is a representative treatment for any Parkinson's disease treatment. In one embodiment, L-dopa stands for carbidopa / levodopa. In one embodiment, the treatment is gene therapy. In one embodiment, if the neuromelanin concentration remains stable, unchanged or constant, the dosage of L-dopa remains constant. In one embodiment, if the neuromelanin concentration remains stable, the dosage of L-dopa is increased. In one embodiment, if the neuromelanin concentration decreases by more than about 1%, more than about 2%, more than about 3%, more than about 5%, more than about 10%, more than about 15%, more than about 20%, or more than about 25%, the dosage of L-dopa is increased. In one embodiment, neuromelanin is monitored by serial scans. In one embodiment, neuromelanin is measured according to symptom-specific voxels in a single patient. In one embodiment, the symptom-specific voxels are specific to Parkinson's disease. In one embodiment, Parkinson's disease specific voxels are determined in a patient by comparing the patient's NM-MRI data with a predetermined set of controls from other patients. In one embodiment, the set of controls from other patients is age-matched. In one embodiment, the set of controls from other patients is gender-matched.

[0127] In some embodiments, neuromelanin is measured at least every other day, every week, every two weeks, every month, every other month, every three months, every six months, every year, every two years, every three years, every four years, every five years, every six years, every seven years, every eight years, every nine years, every ten years, every fifteen years, every twenty years, every twenty-five years, every thirty years. In certain embodiments, the dose of the second therapeutic agent is administered every week or every two weeks. In certain embodiments, the therapeutic agent is administered every hour, every two hours, every three hours, every four hours, every five hours, every six hours, every eight hours, every ten hours, every twelve hours, every fourteen hours, every sixteen hours, every eighteen hours, every twenty hours, every twenty-four hours, every day, every two days, every three days, every four days, every five days, every six days, every seven days, or every thirteen days.

[0128] In one embodiment, the treatment period (either initial or thereafter) or monitoring period discussed herein is daily, every other day, every 28 days, weekly, every 2 weeks, every 3 weeks, every 4 weeks, every 5 weeks, every 6 weeks, every 7 weeks, every 8 weeks, every 9 weeks, every 10 weeks, every 11 weeks, every 12 weeks, every 13 weeks, every 14 weeks, every 15 weeks, every 16 weeks, every 17 weeks, every 18 weeks, every 19 weeks, or every 20 weeks, about monthly, about every other month, about every 3 months, about every 6 months, or about yearly.

[0129] In one embodiment, a region of interest is determined and voxels within the region are measured to determine the volume of neuromelanin within the region.

[0130] In one embodiment, the region of interest is subdivided and the voxels encompassing that subregion are measured to determine the volume of neuromelanin within that region.

[0131] In one embodiment, these voxels are compared to a reference data set and used to calculate the concentration of neuromelanin in the region of interest or a subregion within the region of interest.

[0132] In one embodiment, these voxels are compared to a reference data set and used to calculate the total amount of neuromelanin in the region of interest or a subregion within the region of interest.

[0133] In one embodiment, multiple comparisons are performed between all voxels identified in the region of interest and a particular symptom or symptom severity scale, or disease state, or demographic information, or other patient or disease specific information to find relationships between subgroups of individual voxels and levels of symptom severity on a particular symptom or disease monitoring scale. These are referred to as symptom-specific voxels.

[0134] In one embodiment, multiple comparisons are performed between all voxels identified in the region of interest and specific disease diagnostic or demographic information, or other patient or disease-specific information, to find associations between subgroups of individual voxels and specific disease diagnostic conditions. These are called disease-specific voxels, and in one example may include Parkinson's disease specific voxels.

[0135] In one embodiment, these symptom-specific or disease-specific voxels have similarities between multiple patients with the same symptoms in the same disease context and can be used to make comparisons between multiple patients with the same disease (e.g., two patients with Parkinson's disease, both of whom have the symptom of psychomotor retardation). In this case, the similarities between the patients can be compared and the symptom-specific voxels can serve as diagnostic biomarkers.

[0136] In one embodiment, these symptom-specific or disease-specific voxels have differences between patients with the same symptom occurring in different disease contexts, in which case the differences between the symptom-specific voxels can be used to distinguish between two different disorders that share the same symptom.

[0137] In one embodiment, either symptom- or disease-specific voxels, or neuromelanin concentration or neuromelanin volume of a particular region or subregion can be used as non-invasive biomarkers to determine diagnostic information to diagnose the presence of a particular disease (in this case Parkinson's disease or related disorders such as MSA, PSP, parkinsonian symptoms, dyskinesia, dystonia or essential tremor).

[0138] In one embodiment, this can be accomplished by comparing baseline measurements of either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume, in a particular patient, with future measurements of these values ​​in the same patient.

[0139] In one embodiment, this can be accomplished by comparing measurements of either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume, in a particular patient, in a particular region or subregion, to a standard control.

[0140] In one embodiment, either symptom-specific or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a specific region or subregion can be used as a non-invasive biomarker to determine diagnostic information and to rule out or differentiate between related disorders (Parkinson's disease, and MSA, PSP, parkinsonian symptoms, dyskinesia, dystonia, or essential tremor).

[0141] In one embodiment, this can be accomplished by comparing baseline measurements of either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume, in a particular patient, with future measurements of these values ​​in the same patient.

[0142] In one embodiment, this can be accomplished by comparing measurements of either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume, in a particular patient, in a particular region or subregion, to a standard control.

[0143] In one embodiment, either the condition-specific voxels or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a particular region or subregion can be used as a non-invasive biomarker to stage or grade a particular disease or condition in a patient, and this information can be differentiated or classified. For example, this can be used to determine the stage of PD or related movement disorders in a particular patient.

[0144] In one embodiment, either symptom-specific or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a particular region or subregion can be used as a non-invasive biomarker to determine the severity of the current condition in the patient.

[0145] In one embodiment, either symptom-specific or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume in a particular region or subregion can be used as a non-invasive biomarker to predict the onset of new symptoms that the patient has not yet developed.

[0146] In one embodiment, either symptom-specific or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a specific region or subregion can be used as a non-invasive biomarker to predict the severity of a current condition, to predict the future progression of the disease course, or to predict either the response of a specific symptom of the disease or the response of the disease as a whole to a treatment, and can serve as a non-invasive prognostic biomarker.

[0147] In one embodiment, either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a particular region or subregion can be used as non-invasive biomarkers to monitor response to treatment for either a particular symptom or disease state as a whole.

[0148] In one embodiment, either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a particular region or subregion can be used as non-invasive biomarkers to guide the selection of the correct treatment for either a particular symptom or disease state as a whole.

[0149] In one embodiment, either symptom-specific or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a particular region or subregion can be used as a non-invasive biomarker to determine the status of treatment as a whole and whether there has been an adequate response to treatment for either a particular symptom or disease state.

[0150] In one embodiment, either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume of a particular region or subregion can be used as non-invasive biomarkers to predict future response to treatment for either a particular symptom or disease state as a whole.

[0151] In any embodiment, a comparison may be made between:

[0152] Baseline measurements of either symptom- or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume, in a particular patient, in a particular region or subregion, versus future measurements of these values ​​in the same patient.

[0153] Measurement of either symptom-specific or disease-specific voxels, or neuromelanin concentration, or neuromelanin volume, in a particular region or subregion, in a particular patient, versus a standard control. EXAMPLES

[0154] Example 1 Validation experiment of NM-MRI voxel-wise analysis Exemplary relationships with Nm concentrations in postmortem midbrain tissue Tests were conducted to determine whether NM-MRI could be sensitive to variations in NM tissue concentrations at levels found in individuals without major neurodegeneration of the SN, a prerequisite for its use as a marker of inter-individual variation in healthy and Parkinson's disease affected populations. To this end, it is validated against the gold standard measurement of NM concentration by scanning midbrain sections containing the SN from individuals without histopathology compatible with Parkinson's disease or Parkinson's disease related syndromes using NM-MRI sequences. After scanning, each specimen is dissected into 13-20 grid sections along the grid line markings. In each grid section, the tissue concentration of NM is measured using biochemical separation and spectrophotometric determination, and the NM-MRI contrast-to-noise ratio ("CNR") averaged across voxels within the grid section is also calculated.

[0155] Across all midbrain specimens, grid areas with higher NM-MRI CNR had higher tissue concentrations of NM (β 1 = 0.56, t 114 = 3.36, p = 0.001, mixed effects model; 116 grid regions, 7 specimens). As expected, hypersignal areas were most evident in grid regions corresponding to NM-rich SNs. However, similar to in vivo NM-MRI images, posterior-internal regions of the midbrain surrounding periaqueductal gray ("PAG") regions tended to appear hyperintense despite relatively low concentrations of NM. Controlling for the presence of PAG in grid regions (e.g., PAG), we found no significant differences in non-PAG regions (131 = 1.03, t112 = 5.51, p = 10 -7 ), but could not explain the cause of this high signal. In this model, a 10% increase in NM-MRI CNR corresponds to an estimated increase of 0.10 μg NM per mg tissue.

[0156] The relationship between NM-MRI CNR and NM concentration was maintained in extended models controlling for the proportion of SN voxels within each grid area (e.g., again for PAG content) (β1 =0.45, t 111 = 2.15, p = 0.034). This latter result suggests that the NM-MRI CNR explains a higher variation in NM concentration in the SN and surrounding regions than would be explained simply by an increase in both measures in the SN compared to non-SN voxels (an increase that would be expected even if the NM-MRI were restricted to the SN without measuring regional NM concentration). Thus, these results indicate that the NM-MRI signal corresponds to regional tissue concentrations of NM, particularly in the focal region, the midbrain region surrounding the SN.

[0157] Exemplary validation of the voxelwise approach

[0158] Having shown that NM-MRI measures regional concentrations of NM in and around the SN, we determined whether regional differences in NM-MRI signal capture biologically meaningful variation across anatomical subregions within the SN. It was necessary to use this measure to examine dopamine function because the heterogeneity of cell populations in the SN suggests that dopamine function may vary substantially between neuronal layers projecting to the ventral striatum, dorsal striatum or cortical sites. We determined that voxel-wise analysis within the SN may be sensitive to processes affecting specific subregions or possibly discontinuous neuronal layers within the SN for information about the spatial normalization and anatomical masks used in the voxel-wise analysis. To support the feasibility of this technique, the majority of individual SN voxels showed good or excellent test-retest reliability, extending a similar demonstration at the regional level.

[0159] To test the anatomical specificity of the voxel-wise NM-MRI approach, we exploit the ability of NM-MRI to detect disease and the known topography of cell loss in disease.

[0160] Using NM-MRI data from 28 patients and 12 age-matched controls, we analyze whether voxel-wise analysis captures this topographical pattern. The exemplary approach is capable of capturing the known anatomical topography of dopamine neuron loss within the SN: the greater the CNR reduction, the more lateral (β |x| =-0.13, t 1803 =-14.2, p=10 -43 ), posterior (β y =-0.05, t 1803 =-6.6, p=10 -10 ), and ventral SN voxels (β z -0.17, t 1803 =16.3, p=10 -55 Multiple linear regression analyses predicting t-statistics of group differences across SN voxels as a function of their x [absolute distance from midline], y-direction, and z-direction coordinates: Omnibus F 3,1803 =111, p=10 -65 ) tended to predominate.

[0161] Exemplary relationships of NM-MRI signals to dopamine function

[0162] Having verified the anatomical sensitivity of the exemplary voxel-wise approach, we now analyze whether NM-MRI signal in the SN correlates with dopamine function in vivo. To that end, we used positron emission tomography ("PET") imaging to measure the D2 / D3 radiotracer [ 11 C]Dopamine release potential as a change in raclopride binding potential (ΔBP ND) is measured. This method measures the release of dopamine from presynaptic sites of dopamine axons, including its vesicular and cytosolic pools, to striatal synapses, and thus it may be relevant that interindividual differences, such as light, in the size of these dopamine pools may be an important determinant of MN accumulation. Data were collected in a group of 18 individuals without neurodegenerative disease, including 9 healthy controls and 9 unmedicated patients with neurodegeneration. We focused on dopamine release in the association striatum, a part of the dorsal striatum, to ensure sufficient variability, since patients with Parkinson's disease tend to show differences in dopamine release in this subregion. Similarly, the dorsal striatum receives projections from the SN (e.g., via the nigrostriatal pathway), while the ventral striatum receives projections mainly from the ventral tegmental area (e.g., via the mesolimbic pathway), which may be more difficult to visualize on NM-MRI scans due to its lower NM concentration and smaller size. For each subject, ΔBP ND was measured and correlated with the NM-MRI CNR of the SN mask in each voxel, and a voxel-wise analysis was performed. This revealed a set of SN voxels in which the NM-MRI CNR was positively correlated with dopamine release potential in the associative striatum (e.g., 225 out of 1341 SN voxels at p < 0.05, Spearman partial correlation adjusting for diagnosis, age, and head coil; p 補正後 = 0.042, permutation test; peak voxel MNI coordinates [x, y, z]: -1, -18, -16 mm). The effect showed a topographic distribution such that voxels associated with dopamine release tended to predominate in the anterior and lateral parts of the SN. This analysis was performed with a smaller SN mask (e.g., 1341 voxels) because a relatively small number of subjects had data available in the most dorsal SN. No interactions with diagnosis were found (e.g., p = 0.31). Voxel-wise results were mirrored by region of interest ("ROI") results, with mean NM-MRI CNR across the entire SN significantly correlated with mean ΔBP across the striatum. ND(e.g., p = 0.64, p = 0.013; partial correlations with the same covariates as in the voxel-wise analysis and additional covariates in the case of incomplete SN coverage).

[0163] Exemplary relationship of NM-MRI signals to neural activity in the SN

[0164] The latter results showed that individuals with higher dopamine release from nigrostriatal SN neurons had higher NM accumulation as measured by NM-MRI, so we determined that NM accumulation could also correlate with trends such as regional properties of enhanced activity in SN neurons. To test this, we used arterial spin-labeling functional magnetic resonance imaging ("ASL-fMRI") to measure regional cerebral blood flow ("CBF"), a well-established (e.g., indirect) functional measure of neuronal activity that captures inter-individual differences such as properties in resting activity. Individuals without neurodegenerative disease (e.g., 12 healthy individuals, 19 schizophrenia patients) were found to have higher CBF in the SN, which correlated with higher SN NM-MRI CNR. This was true for mean ROI analyses in SN voxels associated with dopamine release potential (e.g., "dopamine voxels," r=0.40, p=0.030; partial correlations controlling for age and diagnosis) and in the entire SN (e.g., r=0.48, p=0.008; partial correlations controlling for age, diagnosis and incomplete SN coverage). Again, no interactions with diagnosis were found (e.g., all p>0.7).

[0165] Relationship between NM-MRI and Parkinson's disease

[0166] NM-MRI, as a measure of NM concentration in the SN, can be used as a marker of neuronal loss in individuals with Parkinson's disease or suffering from symptoms indicative of Parkinson's disease.

[0167] Showing that NM-MRI can capture changes in neuromelanin concentration associated with Parkinson's disease supports the potential value of NM-MRI as a research tool and neuromelanin concentration as a candidate biomarker for Parkinson's disease. This phenomenon has been identified in patients with a history of Parkinson's disease. In some embodiments, this phenomenon is proportional to the severity of the experience. In certain embodiments, Parkinson's disease is characterized by one or more symptoms. Exemplary procedures suggest that this Parkinson's disease-related phenotype, consisting of nigrostriatal dopamine excess, leads to reduced NM accumulation in the SN, which can be captured by NM-MRI. Specifically, it was found that mostly ventral SN subregions may have reduced NM-MRI CNR in proportion to the severity of Parkinson's disease. Exemplary findings further highlight the promise of NM-MRI as a clinically useful biomarker of conditions related to neuromelanin concentration. It has the clear advantage of being practical (e.g., cheap and non-invasive) especially for longitudinal imaging and achieving high anatomical resolution compared to standard imaging methods, which facilitates the resolution of functionally distinct SN layers with different pathophysiological roles. Given the slow accumulation of NM in the SN over the lifespan and the high reproducibility of this procedure, the putative ability of NM-MRI to index NM longitudinally suggests that it could be a stable marker that is insensitive to acute conditions (e.g., recent sleep loss or substance consumption). This is a particularly attractive property for a candidate biomarker, one that could complement other markers. Dimensional markers of NM alterations associated with Parkinson's disease would be highly useful as longitudinal biomarkers for Parkinson's disease. Such biomarkers could further aid in selecting a subset of at-risk individuals who could benefit from medication overall more than individuals with CHR, thus enhancing current risk prediction procedures based solely on non-biological measurements.

[0168] There may be some limitations to the potential applications of NM-MRI. As with other neuroimaging measurements, the exemplary data show that NM-MRI signal can be sensitive but not entirely specific to NM concentration. Other tissue properties, including proton density, may affect the signal. Thus, caution may be warranted in interpreting all changes in NM-MRI signal as changes in NM concentration, especially in areas with low NM concentration.

[0169] Exemplary longitudinal monitoring of Parkinson's disease

[0170] MR images are obtained about every year, about every two years, about every three years, about every four years, about every five years, and measure neuromelanin levels, signals and / or concentrations. Neuromelanin levels, signals and / or concentrations are compared to previous scans. After comparing neuromelanin levels, signals and / or concentrations, a decrease over time indicates the progression of the condition. In some embodiments, this decrease is proportional to the progression or severity of Parkinson's disease. In some embodiments, the medicament is administered after the first MRI scan and after an MRI scan at a second time point after administration of the medicament. Comparing the two scans can indicate the success of the treatment regimen.

[0171] Exemplary NM-MRI Acquisition MR images were acquired using a 32-channel phased array Nova head coil from a GE All study participants were acquired on a Healthcare 3T MR750 scanner. For logistic reasons, a few scans (e.g., 17% of all scans, 24 out of 139 in total) were acquired using an 8-channel in vivo head coil instead. During the pilot, various NM-MRI sequences were compared, with the following parameters: repetition time (TR) = 260 ms, echo time (TE) = 2.68 ms, flip angle = 40°, in-plane resolution = 0.39 × 0.39 mm 2Optimal CNR was achieved in the SN using a 2D gradient response echo sequence with magnetization transfer contrast (e.g., 2D GRE-MT) with partial brain coverage including field of view (FoV) = 162 × 200, matrix = 416 × 512, number of slices = 10, slice thickness = 3 mm, slice gap = 0 mm, magnetization transfer frequency offset = 1200 Hz, number of excitations [NEX] = 8, and acquisition time = 8.04 min. The slice prescription protocol consisted of orienting the image stack along the anterior commissure-posterior commissure ("ACPC") line, viewed in the sagittal plane in the midbrain, with the top slice positioned 3 mm below the floor of the third ventricle. This protocol covered the SN-containing parts of the midbrain (e.g., cortical and subcortical structures surrounding the brainstem) with high in-plane spatial resolution using short scans that are well tolerated by clinical populations. For preprocessing of 2D GRE-MT (e.g., NM-MRI) data, a high-resolution structural MRI scan of the whole brain was also acquired: a T1-weighted 3D BRAVO sequence (e.g., inversion time = 450 ms, TR ~ 7.85 ms, TE ~ 3.10 ms, flip angle = 12°, FoV = 240 × 240, matrix = 300 × 300, number of slices = 220, isotropic voxel size = 0.8 mm). 3 ) and a T2-weighted CUBE sequence (e.g., TR = 2.50 ms, TE approx. ms, echo train length = 120, FoV = 256 × 256, number of slices = 1, isotropic voxel size = 8 mm 3 ). NM-MRI image quality was visually inspected for artifacts immediately after acquisition and, if necessary, scans were repeated as time permitted. Ten participants were excluded due to clearly visible smearing or banding artifacts affecting the midbrain (e.g., participant movement, n=4), or incorrect imaging stack placement (e.g., n=6).

[0172] Reprocessing of an exemplary NM-MRI

[0173] NM-MRI scans were preprocessed using SPM12 to facilitate voxel-wise analysis in standardized MNI space. For example, NM-MRI and T2-weighted scans were co-registered to the T1-weighted scan. Tissue segmentation was performed using the T1- and T2-weighted scans as separate channels. Scans from all study participants were normalized to MNI space using DARTEL routines using grey and white matter templates generated from the individual's initial sample. The resampled voxel size of the unsmoothed normalized NM-MRI scans was isotropic at 1 mm. All images were visually inspected following each preprocessing step. Intensity normalization and spatial smoothing were then performed using custom Matlab® scripts. The CNR for each subject and voxel v was calculated using the CNR V =(I V -Mode(I RR )) / Mode(I RR ) was calculated as the relative change in NM-MRI signal intensity I from a reference region RR of white matter tracts known to have minimal NM inclusion, the cerebral peduncle. A template mask of the reference region in MNI space was created by manually tracing a template NM-MRI image (e.g., the average of normalized NM-MRI scans from the first sample individual). Mode (I RR ) was calculated for each participant from a kernel smoothing function fit of the histograms of all voxels in the mask. The mode was utilized rather than the mean or median, as this was found to be more robust to outlier voxels (e.g., due to edge artifacts) and thus avoided the need to further modify the reference region mask. Images were then spatially smoothed with a Gaussian kernel of 1 mm full width at half maximum.

[0174] Additionally, an over-inclusive mask of SN voxels was created by manually tracing the template NM-MRI image. The mask was then reduced by removing edge voxels with extreme values: voxels showing extreme relative values ​​for a given participant (e.g., above the 1st or 99th percentile of the CNR distribution across SN voxels in more than two subjects) or voxels with consistently low signal across participants (e.g., CNR less than 5% in more than 90% of subjects). These procedures removed 9% of the voxels in the manually traced mask, leaving a final template SN mask containing 1,807 resampled voxels.

[0175] Exemplary NM-MRI Analysis

[0176] All analyses were performed in Matlab® (Mathworks, Natick, MA) using custom scripts. In general, robust linear regression analyses were performed across subjects for all voxels v in the SN mask as follows:

number

[0177] Hypothesis testing was based on permutation tests in which measures of interest were randomly shuffled with respect to CNR. This test corrected for multiple comparisons by determining whether the spatial extent of the effect, k, was larger than expected by chance (e.g., p 補正後<0.05, 10,000 permutations, equivalent to a cluster-level family-wise error-corrected p-value, but in this case we did not require voxels to form clusters of neighboring voxels, given that the size of the SN was small and that SN layers defined by specific projection sites do not necessarily contain anatomically clustered neurons). At each iteration, the order of values ​​of the variable of interest (e.g., dopamine release potential) was randomly permuted across subjects (and maintained for analysis of all voxels within the SN mask for a given iteration of the permutation test, e.g., to account for spatial dependence). This resulted in a measure of spatial extent for each of the 10,000 permuted datasets, which allowed us to estimate the probability (p 補正後 For hypothesis tests related to conjunctive effects, permutation analysis was used to calculate the mean mean of both effects based on a null distribution that counts the overlap of significant voxels after the locations of the true significant voxels of each effect are randomly shuffled within the SN mask.

number

[0178] Exemplary Topographic Analysis. Multiple linear regression analysis across SN voxels was used to predict the strength of the effect (or, for example, the presence of a significant conjunctural effect) as a function of MNI voxel coordinates in the x (e.g., absolute distance from the midline), y, and z directions.

[0179] Exemplary ROI Analysis. Post-hoc ROI analyses examining the average NM-MRI signal across voxels across the entire SN mask included the same covariates used in the respective voxel-wise analyses in these subjects, plus an additional dummy covariate that indexed subjects with incomplete coverage of the dorsal SN as the dorsal-ventral gradient of signal intensity at the biased mean CNR value. This "incomplete SN coverage" covariate was not used in analyses involving NM-MRI signal extracted from "dopamine" or "Parkinson's-overlap" voxels, as these limited sets of voxels have a relatively small contribution from the dorsal SN.

[0180] Exemplary postmortem experiments

[0181] Postmortem specimens of human midbrain tissue were obtained from The New York Brain Bank at Columbia University. Seven specimens were obtained from each individual with Parkinson's disease. The specimens were approximately 3 mm thick slices of freshly frozen tissue from the rostral hemi-midbrain containing the pigmented SN. These specimens were scanned using a NM-MRI protocol similar to that used in vivo, and then cut for analysis of NM tissue concentrations. The dish containing the specimens contained a grid insert that was used to keep the cuts in line with the MR images.

[0182] Exemplary neurochemical measurement of NM concentration in postmortem tissue. The samples derived from each grid section were homogenized using titanium instruments. Then, with minor modifications to improve the removal of interfering tissue components from midbrain regions that have higher fiber content and few NM-containing neurons compared to the section of SN that was properly dissected along anatomical boundaries, the NM concentration of each grid section was then measured according to the exemplary spectrophotometric method described above. Additional testing confirmed that the exemplary method of washing with Fomblin® was effective, and that neither this substance nor methylene blue dye likely affected the spectrophotometric measurement of NM.

[0183] Exemplary MRI measurements of NM signal in postmortem tissue. NM-MRI signals were measured in the corresponding grid regions using custom Matlab® scripts. Processing of NM-MRI images included automatic removal of voxels showing edge artifacts and signal dropouts, averaging slices to create 2D images, and alignment with a grid of dimensions matching the grid insert. Grid alignment was manually adjusted based on the well markers present in the top slice where the grid insert was placed and edge artifacts of the grid shape. Signals of the remaining voxels were averaged within each grid region. To normalize signal intensity across specimens, the CNR of each grid region was calculated voxel-wise in vivo. The reference region of each specimen was defined by three grid regions that best matched the location of the cerebral peduncle reference region used for the in vivo scan.

[0184] Exemplary Statistical Analysis of Postmortem Data. A generalized linear mixed-effects ("GLME") model including data across all grid sections g and specimens s was used to predict NM tissue concentration for each grid section based on the mean NM-MRI CNR in the same grid section. GLME analyses were fitted by maximum likelihood estimation using an isotropic covariance matrix, as implemented by the Matlab® function fitglme. A likelihood ratio test at p<0.05 favored the reduced model with no random slope. Thus, all models included the following:

number

number

[0185] Exemplary PET Imaging Studies

[0186] Subjects (e.g., healthy controls, Parkinson's disease patients) were administered a radioactive tracer [ 11 C]raclopride and amphetamine challenge were used to quantify dopamine release capacity in rats. A baseline PET scan was performed on one day, and the following day, dextroamphetamine (e.g., 0.5 mg / kg, po) was administered and post-amphetamine PET scans were acquired 5–7 hours later. For each PET scan, list-mode data were analyzed on a Biograph mCT PET-CT scanner (Siemens / CTI, Knoxville TN) to obtain the dopamine release capacity. 11C] PET data were acquired over 60 min after a single bolus injection of raclopride, binned into a series of frames of the enhancement period, and reconstructed by filtered backprojection using software provided by the supplier. PET data were motion corrected and registered to the individual's T1-weighted MRI scans using SPM2. ROIs were drawn on each subject's T1-weighted MRI scan and transferred to the co-registered PET data. Time-activity curves were created as the average activity of each ROI in each frame. Exemplary a priori ROIs were the entire caudate nucleus and the association striatum, defined as the precommissural putamen, a part of the dorsal striatum that receives nigrostriatal axonal projections from SN neurons and is consistently implicated in conditions related to Parkinson's disease. Data were analyzed using a simplified reference tissue model ("SRTM") using the cerebellum as the reference tissue, with non-permuted compartments (e.g., BP ND The primary outcome measure was BP, reflecting amphetamine-induced dopamine release, a measure of dopamine-releasing potential. ND Relative decrease in (ΔBP ND ) Amphetamine induces synaptic release of dopamine derived from both cytosolic and vesicular stores. This leads to excessive competition with the radiotracer at D2 receptors and, concomitantly, agonist-induced internalization of D2 receptors, both of which result in displacement of the radiotracer and a decrease in BPND. Thus, ΔBP ND combines both effects and reflects the size of dopamine stores. Because these stores are dependent on dopamine synthesis, PET measurements of dopamine release capacity may be relevant to dopamine function. It may also be relevant to NM, given that NM accumulation may be driven by cytosolic dopamine (e.g., or by vesicular dopamine once transported to the cytosol).

[0187] Exemplary Arterial Spin Labeling ("ASL") Perfusion Imaging Study

[0188] Subjects (e.g., healthy controls, patients with Parkinson's disease) underwent ASL functional MRI scans at rest to quantify regional CBF. All of these subjects also participated in the studies mentioned above and described below. Pseudo-continuous ASL (e.g., 3D-pCASL) perfusion imaging was performed using a 3D background-suppressed fast spin-echo stack-of-spiral readout module with eight in-plane spiral interleaves (e.g., TR=4463ms, TE=10.2ms, labeling period=1500ms, post-labeling delay=2500ms, no flow-crash gradients, FoV=240×240, NEX=3, slice thickness=4mm), and an echo train length of 23, resulting in 23 consecutive axial slices. A 10mm-thick labeling plane was placed 20mm below the inferior edge of the cerebellum. The total scan time was 259s. ASL perfusion data was analyzed to generate CBF images using Functool software (version 9.4, GE Medical Systems). CBF was calculated as in previous work.

[0189] For preprocessing, CBF images were co-registered to ASL localizer images and then to T1 images, and the co-registration parameters were applied to the CBF images. CBF images were then normalized to MNI space using the same procedure described above for NM-MRI scans. Mean CBF was calculated within the entire SN mask and within a mask of SN voxels significantly associated with connectivity layer dopamine release potential. ROI-based partial correlation analysis tested the relationship between mean CBF and mean NM-MRI CNR in the same masks, controlling for age and diagnosis.

[0190] Further post-mortem experiments

[0191] Postmortem specimens of human midbrain tissue were obtained from The New York Brain Bank at Columbia University. Seven specimens each were obtained from individuals who suffered from Alzheimer's disease or other non-PD dementia at the time of death (e.g., ages 44-90 years; see Table 1 below for further clinical and demographic information). None suffered from Parkinson's disease, Parkinson's symptoms, or any other movement disorder or neurodegenerative disease affecting the SN based on neuropathological examination for accumulation of abnormal proteins such as alpha-synuclein, beta-amyloid, or tau. One case showed a marked reduction in neuronal density in the SN despite clearly identifiable NM. Analysis excluding this one case did not change the observed relationship between NM-MRI CNR and NM concentration. Therefore, the data presented included this case to increase statistical power. Specimens were approximately 3 mm thick slices of freshly frozen tissue from the rostral hemi-midbrain of the right hemisphere containing the pigmented SN. They were stored at -80 °C. These specimens were scanned using the NM-MRI protocol and then cut for analysis of NM tissue concentrations. For the MRI scan session, the specimens were gradually thawed to 20°C, as confirmed by a laser thermometer. The specimens were placed in a custom-made dish 3D printed from an MRI-compatible nylon polymer (NW Rapid Mfg., McMinnville, OR), and a matching grid-insert lid was placed over the specimen and attached to hold the specimen in place. While secured in the dish, the specimen was fully immersed in MRI-invisible lubricant (Fomblin® perfluoropolyether Y25; Solvay, Thorofare, NJ) and placed in a desiccator for 30 minutes to remove air from the tissue. Wells at the four cardinal points on the edge of the dish were filled with water to mark its location and orientation in the MRI images. The dish was then placed on a custom stand within a 32-channel phased array Nova head coil and scanned for in vivo imaging using the 2D GRE-MT NM-MRI sequence described above. The only change in the postmortem scanning protocol was an increase in resolution (e.g., in-plane resolution = 0.3125 × 0.3125 mm). 2, slice thickness -0.60 mm) and a reduced FoV (e.g., 160 × 80).

[0192] After the scanning session, the specimens were refrozen in place and marked with grid lines by applying methylene blue dye (e.g., 0.05% aqueous solution [5 mg / 10 ml]; Sigma-Aldrich, St. Louis, MO) to the tissue using the grid insert as a stamp. Guides built into the wall of the dish ensured that the orientation of the grid relative to the specimen was always fixed. Within 4 days after scanning, the partially thawed specimens were cut along the grid lines after extensive removal of Fomblin® by dropping the tissue slices and then gently rolling the surface of the sections on ultraclean filter paper. Cutting and manipulation of the tissue sections was performed with a ceramic blade and titanium and plastic forceps to avoid contamination with iron. Each grid section (e.g., 3.5 mm × 3.5 mm × approximately 3 mm depending on the thickness of the slice) was weighed together with adjacent partial grid sections, stored separately in Eppendorf tubes, and frozen. Thus, the specimens were divided into 13–20 grid sections. The grid column and row number of each excised grid section was coded.

[0193] Exemplary NM-MRI analysis: Exclusion of voxels with few observations

[0194] To reduce the risk of type II error, the regression coefficients β for a given analysis were calculated after truncation of data points of interest with missing or extreme values. 1If the degrees of freedom of the t-test are less than 10, then the voxel is excluded from this analysis (note that the degrees of freedom take into account the sample size with data available at a given voxel as well as the number of model predictors). This voxel exclusion only applied to the analysis relating NM-MRI signal to dopamine release potential given the smaller sample size of the PET dataset, and therefore this analysis was performed on the 1,341 resampled SN voxels (rather than on the full mask of 1,807 resampled voxels, for example). Choosing an exclusion threshold anywhere between 8 and 11 degrees of freedom gave very similar results. See inset for the distribution of the degrees of freedom for all voxels in this analysis.

[0195] Exemplary NM-MRI analysis: Noncircular voxel selection for unbiased effect size estimation

[0196] For voxel-wise analyses, unbiased measures of effect size were generated by using a leave-one-out procedure. For a given subject, voxels in which the variable of interest was associated with NM-MRI signal were first identified in an analysis including all subjects excluding this (e.g., donated) subject. The mean signal for the donated subjects was then calculated from this set of voxels. This procedure was repeated for all subjects, so that each subject had an extracted mean NM-MRI signal value obtained from the analysis that excluded them. Thus, this unbiased voxel selection and data extraction avoided statistical circularity. Unbiased estimates of effect size (e.g., Cohen's d or correlation coefficient) were then determined by relating these extracted NM-MRI signal values ​​to the variable of interest across donated subjects, including the same covariates as in the voxel-wise analyses, as well as an additional covariate that indexed subjects who lacked complete dorsal SN subject coverage (e.g., for a dorsal-ventral gradient in NM-MRI signal intensity).

[0197] Exemplary neurochemical measurements of NM concentrations in postmortem tissue: Testing of chemical agents applied to postmortem tissue

[0198] To test whether Fomblin® affects NM measurements, small cubes of SN pars compacta with similar levels of pigmentation were excised from one healthy subject. Some cubes (e.g., n=3) were immersed in Fomblin® and then the Fomblin® was washed (e.g., drained and rolled in filter paper). The remaining cubes (e.g., n=5) were not immersed in Fomblin® as control samples. NM concentrations were comparable in these two sets of cubes (e.g., mean + standard deviation: 0.82 + 0.08 vs. 0.86 ± 0.09 μg NM / mg wet tissue, respectively; t 6 =-0.62, p=0.56). The water-soluble methylene blue dye was efficiently removed during the washing procedure in the exemplary standard protocol for measuring NM concentration. Furthermore, it was determined that the absorption wavelength of this compound (e.g., having a peak around 680 nm) can be far away from the wavelength (e.g., 350 nm) used to determine NM concentration.

[0199] Exemplary MRI measurements of NM signal in postmortem tissue: Automatic removal of voxels exhibiting edge artifacts and signal dropout

[0200] Processing of NM-MRI images included automated removal of low-signal voxels, including all voxels outside the specimen or voxels within the specimen that exhibited signal dropout. A threshold for excluding low-signal voxels was determined for each specimen based on a histogram of all voxels in the image that was fitted using a kernel smoothing function. The threshold was defined as the signal corresponding to the minimum value lying between the left-most peak of the match histogram, which corresponds to a low-signal voxel outside the specimen, and the right-most peak, which corresponds to a higher-signal voxel within the specimen (e.g., consistent with a bimodal distribution).

[0201] To eliminate edge artifacts, the first step was to define the boundaries between the specimen and the space surrounding the specimen outside, and between the specimen and the area of ​​signal dropout. These boundaries were defined in 3D and 2D. To do so, the specimen's boundary voxels (defined above) immediately adjacent to low signal voxels were labeled using the bwperim function in Matlab®. These boundary voxels were defined for the entire volume and also for the 2D flattened image created by averaging across slices. These boundary voxels were removed from the specimen (e.g., first the 3D boundary voxels were removed from the 3D image, then the 2D boundary voxels extended by 2 voxels were removed from the resulting flattened image). Finally, the extreme signal values ​​compared to other voxels in the same 2D grid area (e.g., Cook's distance >4 / n in a linear regression model with only constants) were removed. The resulting 2D image, with edge artifacts, signal dropouts, and other outlier voxels removed, was carried forward to the final analysis step.

[0202] Exemplary PET Imaging Study: Timing of Post-Amphetamine PET Scan

[0203] Each subject underwent two post-amphetamine PET scans for the purposes of a separate study published previously. This previous study used the D2 radiotracer [ 11 We aimed to assess the time course of receptor internalization following agonist challenge, measured via the long-term displacement of [C]raclopride. PET scans were acquired in four sessions: baseline, 3 h after amphetamine, 5–7 h after amphetamine and 10 h after amphetamine. However, not all post-amphetamine time points were necessarily available for all subjects. However, displacement was highly stable and did not differ between the 3 and 5–7 h time points (ΔBP NDwas indeed strongly correlated between subjects between these two time points; r = 0.75). Only one of these post-amphetamine scans was used: those administered 5-7 hours after amphetamine. The 5-7 hour time point was chosen because this was the time point with the most available data (e.g., missing only 3 / 18 participants replaced by data from the 3 hour time point). The displacement from 5-7 hours post-amphetamine (like the displacement from 3 hours post-amphetamine) reflects a greater amount of dopamine release by amphetamine, which may be a combination of competition between dopamine and the radiotracer for binding to the receptor and agonist-induced receptor internalization, both of which depend on the magnitude of agonist availability. Thus, due to the larger number of subjects with available data and considering the observed stability of the displacement between the 3 hour and 5-7 hour time points, the 5-7 hour time point may be the optimal time point for this study. At the 10 hour time point, this is due to the possibility of decreased receptor internalization following receptor recycling, which may lead to a higher BP ND) When 11 subjects were examined using PET data at 3 hours, the NM-MRI CNR and ΔBP at this 3 hour time point tended to be higher. ND The effect size of the correlation between was found to be similar to that at the 5- to 7-hour time point.

[0204] An illustrative study related to Parkinson's disease using neuromelanin (NM) MRI

[0205] background

[0206] Parkinson's disease (PD) is a progressive motor neurodegenerative disorder that is the second most common neurodegenerative disorder after Alzheimer's disease among older adults. With typical symptoms of resting tremor, bradykinesia, rigidity and unstable posture, PD is defined primarily as a movement disorder and is pathologically characterized by the degeneration of nigrostriatal dopaminergic neurons and the presence of Lewy bodies (misfolded α-synuclein) in surviving neurons. Non-motor signs may include depression, autonomic dysfunction, cataracts, and cognitive impairment such as mild cognitive impairment and Parkinson's dementia.

[0207] Neuromelanin (NM) MRI signal is robustly reduced in the SN of patients with PD, consistent with degeneration of NM-positive SN dopamine cells and reduced NM concentrations in postmortem SN tissue of PD patients compared to age-matched controls. Since NM-MRI was first utilized in 2002, there have been at least 35 clinical trials of NM changes in the substantia nigra, showing it to be a biomarker of degeneration in Parkinson's disease with high sensitivity and specificity. A recent meta-analysis of 16 clinical trials including 364 PD cases and 231 healthy controls found that NM-MRI had a sensitivity of 97.7% and a specificity of 94.4% for detecting SN changes.

[0208] We believe that our technique improves the diagnostic accuracy of NM-MRI. NM-MRI without comparison with a control database may have low diagnostic accuracy as a biomarker in the very early stages of PD due to the fluctuating NM levels in the SN in these patients and in relation to normal controls. The accuracy of NM-MRI would be significantly improved by longitudinal evaluation over time, showing the decrease of NM in the SN over time. This outcome does not occur in non-PD patients.

[0209] the purpose To demonstrate that NM levels in the SN decline over time in potential and early PD subjects using NM-MRI.

[0210] To improve the accuracy of the sensitivity / specificity of NM-MRI as a diagnostic biomarker and predictor of PD progression.

[0211] Rationale

[0212] The rationale is that NM-MRI can be used as a surrogate measure of dopamine function in the SN, and that lower values ​​of NM in the SN are observed in PD patients, and that their values ​​continue to decline over time.

[0213] Study design

[0214] A multicenter NM-MRI study was conducted to assess SN and LC NM levels over time in approximately 200 early PD subjects, including 100 control subjects. NM-MRI assessments will be performed every 6 months for up to 2 years. Subjects will also be evaluated every 6 months, including the Unified Parkinson's Disease Rating Scale (UPDRS) and concomitant medications.

[0215] Total sample size: Approximately 300 subjects

[0216] Review period: 2 years

[0217] Registration period: 1.5 years

[0218] Number of facilities: Approximately 40

[0219] Primary endpoint:

[0220] Changes in absolute NM levels between subjects with possible Parkinson's disease and control subjects at baseline and endpoint (total of 2 years).

[0221] Percentage of NM decline between subjects with probable Parkinson's disease and control subjects at baseline and endpoint (total 2 years)

[0222] Embodiments Related to NM-MRI and Parkinson's Disease

[0223] Not all patients have reduced neuromelanin levels to the same extent in PD. Indeed, as shown in Cassidy et al. 2019, some patients with PD have higher neuromelanin than healthy controls, and conversely, some healthy patients have lower neuromelanin levels than patients with PD. The software discussed herein is a medical device capable of assisting in the diagnosis of Parkinson's disease without the patient having a known baseline and in the absence of symptoms by comparing the patient's neuromelanin levels to levels in a large population database. If the patient's neuromelanin levels are lower (more than about 30-50% less) than a level determined to be the cutoff, the diagnosis of PD is supported.

[0224] In a second embodiment, a patient undergoes serial neuromelanin scans every 5 years. If the patient's rate of neuromelanin loss exceeds a certain percentage (%) of neuromelanin loss per year (greater than about 10-15%), a diagnosis of PD is supported.

[0225] In a third method, a patient is determined to have Parkinson's disease if the total amount of neuromelanin on successive scans decreases to less than about 30% of the patient's baseline neuromelanin.

[0226] Example 2A Diagnostic and longitudinal assessment of Parkinson's disease Longitudinal neuromelanin-MRI assessment of NM-MRI aids in the diagnosis of early Parkinson's disease primary purpose

[0227] To determine the absolute and percentage change from baseline in NM concentrations that would be required to diagnose Parkinson's disease (PD) using longitudinal evaluation of Terran Neuromelanin MRI voxel-based analysis.

[0228] To demonstrate a reduction in NM concentrations from baseline to endpoint using Terran Neuromelanin MRI voxel-based analysis in subjects with early Parkinson's disease (stage 1 or 2) or LRRK2 haplotypes compared to control subjects

[0229] To determine the differences (absolute values ​​and percentage changes) in neuromelanin levels (SNc and SNc subregion concentrations, volume of NM in SNc and SNc subregions) from the control group that would allow for the diagnosis of PD

[0230] To demonstrate that total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in SNc subregions, volume of NM in the entire SNc, and volume of subregions of the SNc are smaller in subjects with PD compared to the normal range in controls.

[0231] Secondary purpose:

[0232] To demonstrate correlations between NM-MRI assessments (SNc and SNc subregional density, NM volume in SNc and SNc subregions) and MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores.

[0233] To demonstrate correlation between NM-MRI assessments (SNc and SNc subregion concentration, NM volume in SNc and SNc subregions) and DaTscan imaging over a 5-year period

[0234] To demonstrate the correlation between NM-MRI assessment (SNc and SNc subregion concentration, NM volume in SNc and SNc subregions) and the Hohen-Yahr severity classification

[0235] To demonstrate that application of TerranNeuroMelanin MRI voxel-based analysis finds specific voxels (called PD voxels) unique to each patient that correlate with their specific symptoms for MDS-UPDRS.

[0236] To demonstrate correlation between Parkinson's disease voxels and Parkinson's disease symptoms as measured by the MDS-UPDRS

[0237] Endpoints

[0238] NM-MRI Imaging Using Terran Neuromelanin MRI Voxel-Based Analysis

[0239] Percent change from baseline to endpoint for TerranNeuroMelanin MRI voxel-based analysis in subjects with early PD (stage 1 or 2) or LRRK2 haplotype compared with control subjects.

[0240] Total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in the SNc, volume of NM in the whole SNc, and volume of subregions of the SNc

[0241] Change from baseline to endpoint for TerranNeuroMelanin MRI voxel-based analysis in subjects with early PD (stage 1 or 2) or LRRK2 haplotype compared with control subjects.

[0242] Total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in the SNc, volume of NM in the whole SNc, and volume of subregions of the SNc.

[0243] Differences (absolute values ​​and percentage changes) in neuromelanin levels (SNc and SNc subregion concentrations, volume of NM in SNc and SNc subregions) from the control group (as neuromelanin levels are relevant to the diagnosis of PD).

[0244] Total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in the SNc, volume of NM in the entire SNc, and volume of subregions of the SNc in subjects with PD compared to controls.

[0245] Correlation between NM-MRI assessment (SNc and SNc subregion concentration, volume of NM in SNc and SNc subregions) and Hohen-Yahr severity classification.

[0246] PD voxels in subjects with PD versus control subjects, as PD voxels correlate with specific symptoms on the MDS-UPDRS and MDS-UPDRS.

[0247] DaTscan imaging: 1) diagnosis of PD; 2) correlation with Terran Neuromelanin MRI voxel-based analysis at baseline and over 5 years.

[0248] MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS): 1) correlation with TerranNeuromelanin MRI voxel-based analysis at baseline and over 5 years; 2) correlation with PD voxels.

[0249] Study design

[0250] This is a 6-year study (1 year of recruitment and 5 years of follow-up) to demonstrate the diagnostic value of Terran Neuromelanin MRI voxel-based analysis in subjects with early PD (stage 1 or 2) not treated with L-dopa or subjects >55 years of age with the LRRK2 haplotype who are asymptomatic. The study will enroll approximately 300 subjects with early PD (stage 1 or 2) not treated with L-dopa or asymptomatic subjects (age >55 years) with the LRRK2 haplotype, and 200 age- and sex-matched controls. Subjects will be enrolled in the study after signing an informed consent form (ICF) and meeting all inclusion / exclusion criteria. During the screening period, subjects will have NM-MRI scans, DaTscans and MDS-UPDRS. Each subject will be evaluated using the Yahr severity classification. Subjects will complete the same series of tests 12, 24, 36, 48 and 60 months after enrollment in the study.

[0251] Target population

[0252] Upon completion of the screening procedures, patients must meet the following inclusion criteria and must not meet the exclusion criteria to be enrolled in the study.

[0253] Selection Criteria

[0254] Women and men over 40 years of age with early stage PD (stage 1 or 2) not treated with L-dopa. Clinical diagnosis of PD will be confirmed by DaTscan.

[0255] Women and men aged >55 years who carry the LRRK2 haplotype and are asymptomatic and have not been diagnosed with PD.

[0256] Agree to participate in this study and are capable of providing informed consent.

[0257] Exclusion criteria

[0258] History of treatment with L-dopa

[0259] A history of substance use disorder (excluding tobacco) as defined by DSM-V for at least 6 months prior to screening or positive urine drug test (for amphetamines, cocaine, opioids, and phencyclidine). Subjects with mild cannabis or alcohol substance use disorder may be enrolled with permission of the medical monitor.

[0260] Any metallic implants or paramagnetic objects placed inside the body that may cause claustrophobia or interfere with the MRI scan, as determined by the guidelines outlined in the following reference book: "Guide to MR procedures and metallic objects" Shellock, PhD, Lippincott-Raven press, NY 1998.

[0261] Moderate or severe kidney disease

[0262] Allergy or hypersensitivity to iodine or DaTscan. History of DSM-V defined substance use disorder (excluding tobacco) for at least 6 months prior to screening or positive urine drug test (for amphetamines, cocaine, opioids and phencyclidine). Subjects with mild cannabis or alcohol substance use disorder may be enrolled with permission of the medical monitor.

[0263] Any metallic implants or paramagnetic objects placed inside the body that may cause claustrophobia or interfere with the MRI scan, as determined by the guidelines outlined in the following reference book: "Guide to MR procedures and metallic objects" Shellock, PhD, Lippincott-Raven press, NY 1998.

[0264] Moderate or severe kidney disease

[0265] Allergy or hypersensitivity to iodine or DaTscan

[0266] Evaluation - Screening: Signing the ICF Miniature Mental Illness Interview (MINI) Neurological and medical history · Demographics Physical examination, including height and weight without shoes Urine Drug Testing Concomitant medications Eligibility Criteria NM-MRI Imaging DaTscan Hohen-Jahr classification MDS-UPDRS

[0267] Study period (visits at 12, 24, 36, 48 and 60 months)

[0268] Plan to evaluate: NM-MRI Imaging DaTscan MDS-UPDRS

[0269] Statistical analysis:

[0270] The study will enroll approximately 300 subjects with early stage PD (stage 1) who have not previously been treated with L-dopa, or asymptomatic subjects (age >55 years) with the LRRK2 haplotype, and 200 age- and sex-matched controls. Sample size is based on a 20% reduction in SNc neuromelanin concentration levels at endpoint (after 5 years) in subjects with stage 1 PD or the LRRK2 haplotype compared to control subjects. Analysis of primary and secondary endpoints will be performed by analysis of covariance (ANCOVA), linear regression, or Pearson correlation.

[0271] Primary endpoint:

[0272] Percent change from baseline to endpoint on NM-MRI in subjects with early PD (stage 1 or 2) not treated with L-dopa or subjects with LRRK2 haplotypes compared to control subjects

[0273] Total NM concentration (micrograms of neuromelanin per microgram of wet tissue) in the substantia nigra pars compacta (SNc), NM concentration in the SNc, volume of NM in the entire SNc, and volume of subregions of the SNc

[0274] Change from baseline to endpoint on NM-MRI in subjects with early PD (stage 1 or 2) not treated with L-dopa or subjects with the LRRK2 haplotype compared to control subjects

[0275] Total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in the SNc, volume of NM in the whole SNc, and volume of subregions of the SNc

[0276] Total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in the SNc, NM volume in the entire SNc, and the volume of subregions of the SNc were smaller in subjects with early PD compared to the normal range in controls.

[0277] To determine the difference (absolute value and percent change) in neuromelanin levels (concentration in SNc, volume of NM in SNc) in LRRK2 subjects from a control group allowing for the diagnosis of PD, as confirmed by DaTscan

[0278] Secondary endpoints

[0279] Correlation between NM-MRI assessments and MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores and DaTscan imaging over a 5-year period

[0280] Correlation between NM-MRI assessment (SNc and SNc subregion concentration, NM volume in SNc and SNc subregion) and Hohen-Yahr severity classification

[0281] Correlation between Parkinson's disease voxels (identified by TerranNeuroMelanin MRI voxel-based analysis) and Parkinson's disease symptoms measured by UPDRS

[0282] Identification of Parkinsonian voxels (identified by TerranNeuroMelanin MRI voxel-based analysis) that correlate with specific Parkinsonian symptoms as measured by the UPDRS

[0283] Exemplary voxel-based analysis procedures based on the dopamine biomarker neuromelanin can be used to detect Parkinson's disease in patients. There are currently no approved imaging tests that can diagnose Parkinson's disease, differentiate between different stages of Parkinson's disease, predict the course and / or progression of symptoms of Parkinson's disease, predict future responses to treatment, or predict future symptoms in high-risk individuals. The exemplary systems, methods, and computer-accessible media can be performed on standard hospital MRI equipment. When the methods are applied to NM-MRI, the exemplary voxel-based procedures can be used as biomarkers in patients with Parkinson's disease in clinical settings. The exemplary systems, methods, and computer-accessible media can also be used to predict symptom reversal in people at high risk. Furthermore, the exemplary systems, methods, and computer-accessible media can be used to diagnose or predict the onset of Parkinson's disease.

[0284] Neuromelanin-sensitive MRI (NM-MRI) can detect the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age, in dopamine neurons of the substantia nigra (SN). Because NM-MRI can measure the degeneration of dopamine cells in the SN, this technique can be a useful marker for the diagnosis of Parkinson's disease (PD) and can be utilized for other neuropathological conditions.

[0285] Parkinson's disease is a debilitating neurodegenerative disease that impairs motor control and cannot be adequately treated by current methods. The biological changes underlying the disease are known to involve the degeneration of catecholaminergic neurons (dopamine and norepinephrine neurons), but this degeneration cannot be accurately measured using current clinical tools. NM-MRI sequences are said to be able to detect the neurochemical neuromelanin present in certain structures in the midbrain, namely the substantia nigra pars compacta (SNc; containing dopamine neurons) and the locus coeruleus (LC; containing norepinephrine neurons).

[0286] Recent evidence in PD suggests that dysfunction in the metabolism of dopamine and its by-product neuromelanin may contribute to the degeneration of dopamine cells in the SN, specifically neuromelanin-positive cells. Damaged neuromelanin-containing dopamine cells consequently regress and are removed by microglia along with their neuromelanin granules (the only known biological process that removes NM from tissues). Therefore, an MRI scan sensitive to neuromelanin should be able to detect the degeneration of catecholaminergic neurons in PD. The NM-MRI procedure is a short (8 min) and non-invasive structural MRI scan. Unlike most structural MRI scans, this type of scan is sensitive to a specific neurochemical, neuromelanin, due to the tendency of such neurochemicals to bind to metals.

[0287] Thus, neuromelanin can be observed without any exposure of the subject to exogenous contrast agents, affecting T1 and T2 relaxation times. NM-MRI scans show the SNc and LC as high signal areas in the midbrain. A significant reduction in the intensity and area of ​​this signal is observed in PD for both the SNc and LC, clearly indicating that this signal can detect the neurodegeneration that occurs in PD. NM-MRI has already been shown to be superior to existing PD biomarkers. These measurements have also been shown to significantly correlate with disease severity in PD and to provide high sensitivity and specificity (80-95%) in detecting early PD. A recent meta-analysis of 16 clinical trials including 364 PD cases and 231 healthy controls found that NM-MRI had a sensitivity of 97.7% and a specificity of 94.4%.

[0288] Neuromelanin imaging is FDA approved for use in patients with Parkinson's disease using the DaTscan (Iofulpan) 123 The study was compared with DaTscan (SPECT imaging using a I radioactive tracer) and showed a statistically significant correlation with DaTscan. Specifically, the volume of neuromelanin-positive substantia nigra pars compacta (SNc) area and the asymmetry index of neuromelanin-positive SNc volume showed a significant correlation with the specific binding ratio (SBR) of DaTscan.

[0289] Most cases of Parkinson's disease are likely due to a complex interplay of environmental and genetic factors. These cases are classified as sporadic and occur in individuals with no obvious history of the disorder in their families. The cause of these sporadic cases remains unclear. Nearly 15 percent of people with Parkinson's disease have a family history of the disorder. One of the mutations associated with PD is LRRK2, which is inherited in an autosomal dominant pattern. Mutations in LRRK2 are the most common genetic cause of late-onset Parkinson's disease (PD) currently identified. The penetrance of LRRK2 mutations is clearly age-dependent, increasing from 17% at age 50 to 85% at age 70.

[0290] TerranNeuroMelanin MRI voxel-based analysis has been validated as a surrogate measure of dopamine function in an investigation relating NM-MRI scans to NM concentrations in postmortem midbrain tissue. Seven postmortem individuals without histopathology consistent with PD or PD-related syndromes (including the absence of Lewy bodies consisting of abnormal protein aggregates) underwent NM-MRI scans of SN-containing midbrain sections. After scanning, each specimen was dissected along the grid line markings and NM concentrations were measured using biochemical separation and spectrophotometric determination. The average NM-MRI contrast-to-noise ratio (CNR) across voxels within the grid regions was also calculated. Across all midbrain specimens, grid regions with higher NM-MRI CNR had higher tissue concentrations of NM (β 1 = 0.56, t 114 = 3.36, P = 0.001, mixed effects model). As expected, high signal was most evident in non-periaqueductal gray (PAG) regions in grid areas corresponding to NM-rich SNs in the NM-MRI CNR versus NM concentration (β 1 = 1.03, t 112 = 5.51, P = 10 -7 In this model, a 10% increase in NM-MRI CNR corresponds to an estimated increase of 0.10 μg NM per mg of tissue.

[0291] Terran Neuromelanin MRI Voxel-Based Analysis has been developed as a standalone software for a medical device (SaMD) that measures neuromelanin levels obtained using NM-MRI. Terran Neuromelanin MRI Voxel-Based Analysis can be used to obtain accurate measurements of neuromelanin concentration and volume in the substantia nigra. Neuromelanin is a surrogate measure of dopaminergic neuronal activity that can be used as an aid to physicians evaluating subjects with medical conditions that affect midbrain dopamine levels. The study longitudinally evaluates subjects with early PD (stage 1 or 2) who have not previously been treated with L-dopa, or asymptomatic subjects with LRRK2 haplotypes, over a 5-year period.

[0292] To use longitudinal evaluation of TerranNeuroMelanin MRI voxel-based analysis to determine the absolute and percentage change from baseline in NM concentrations that would be required to diagnose Parkinson's disease (PD).

[0293] To demonstrate a reduction in NM concentrations from baseline to endpoint using Terran Neuromelanin MRI voxel-based analysis in subjects with early Parkinson's disease (stage 1 or 2) or LRRK2 haplotypes compared to control subjects

[0294] To determine the differences (absolute values ​​and percentage changes) in neuromelanin levels (SNc and SNc subregion concentrations, and volume of NM in SNc and SNc subregions) from the control group that would allow for the diagnosis of PD.

[0295] To demonstrate that total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in SNc subregions, volume of NM in the entire SNc, and volume of subregions of the SNc are smaller in subjects with PD compared to the normal range in controls.

[0296] Secondary purpose:

[0297] To demonstrate correlation between NM-MRI assessments (SNc and SNc subregional density, NM volume in SNc and SNc subregions) and MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores using DaTscan imaging over a 5-year period

[0298] To demonstrate the correlation between NM-MRI assessment (SNc and SNc subregion concentration, NM volume in SNc and SNc subregions) and the Hohen-Yahr severity classification

[0299] To demonstrate that application of TerranNeuroMelanin MRI voxel-based analysis finds specific voxels (called PD voxels) unique to each patient that correlate with their specific symptoms for MDS-UPDRS.

[0300] To demonstrate correlation of voxels of Parkinson's disease with Parkinson's disease symptoms as measured by the MDS-UPDRS

[0301] TerranNeuroMelanin MRI voxel-based analysis is a valid method to diagnose PD, distinguish PD subjects from controls, and track PD progression over time

[0302] TerranNeuroMelanin MRI Voxel-Based Analysis Identifies Parkinsonian Voxels Corresponding to Parkinsonian Symptoms as Measured by MDS-UPDRS

[0303] Study design

[0304] This is a 6-year study (1 year of recruitment and 5 years of follow-up) to evaluate the diagnostic value of NM-MRI in subjects with early stage PD (stage 1 or 2) who have not been treated with L-dopa or who are asymptomatic and are ≥55 years old with the LRRK2 haplotype. The study will enroll approximately 300 subjects with stage 1 PD or asymptomatic subjects (age ≥55 years) with the LRRK2 haplotype, and 200 age- and sex-matched controls. Subjects will be enrolled in the study after signing an informed consent form (ICF) and meeting all inclusion / exclusion criteria. During the screening period, subjects will have NM-MRI scans, DaTscan SPECT imaging, and MDS-UPDRS over three visits. Each subject will be assessed using the Yahr severity classification. Subjects will complete the same series of tests at 12, 24, 36, 48, and 60 months after enrollment in the study. At each visit, the MDS-UPDRS and Hohen-Jahr severity classification will be performed.

[0305] Subjects with a current history of substance abuse will be excluded from this study. Finally, subjects with unstable medical conditions or contraindications to MRI studies will also be excluded.

[0306] Evaluation timeline

[0307] The evaluation will be carried out according to the following flowchart.

[0308] Table 1.

[0309] [Table 1]

[0310] Screening – Visit 1

[0311] The screening phase lasts for a maximum of 30 days, during which demographic information, medical history, and informed consent are obtained. Subjects who meet the inclusion and exclusion criteria may be admitted to enrollment. The nature and purpose of the study should be explained to subjects prior to the start of the screening process.

[0312] After signing the Informed Consent Form (ICF), the following demographic data should be collected and recorded: patient's date of birth, age at time of informed consent, sex, ethnicity, and race. Study site personnel will obtain a full medical history from the patient during screening, updated as necessary at Visit 1. A medical history will be obtained, as well as vital signs (blood pressure and pulse). A urine sample will be collected for drug screening. A history of current and recent use of medications will also be obtained. The investigator or designer will determine if the subject meets all of the eligibility criteria for this study.

[0313] The following evaluations will be performed: · Signing the ICF MINI ·Demographics Medical History Hohen-Jahr severity classification · UPDRS ·MRI Metal Survey Questionnaire Vital signs (blood pressure and heart rate) Urine Drug Testing Concomitant medications Adverse Events Eligibility Criteria

[0314] Screening Visits 2 and 3

[0315] During Screening Visits 2 and 3, the following tests will be performed: NM-MRI Imaging DaTscan Imaging Vital signs (blood pressure and heart rate) Urine Drug Testing Concomitant medications Adverse Events

[0316] Study period (Visits 4-8 at 12, 24, 36, 48 and 60 months) NM-MRI Imaging ·DaTscan Hohen-Jahr severity classification MDS-UPDRS ·MRI Metal Survey Questionnaire Vital signs (blood pressure and heart rate) Urine Drug Testing Concomitant medications Adverse Events

[0317] Review evaluation - MRI screening Prior to inclusion in the MRI study, all subjects are screened to confirm eligibility for MRI scanning. The screening questionnaire includes questions regarding inclusion / exclusion criteria, including the presence of strong paramagnetic implants. If subjects have any metallic implants that are inappropriate for the scanner (i.e., metallic heart valves, aortic clips, etc.), they will not be included in our study. Inclusion and exclusion in our study will be determined by the PI and co-PI of this study.

[0318] Review Evaluation - MRI Procedure

[0319] Subjects undergo a structural 3 Tesla MRI scan and a neuromelanin-sensitive (structural) scan. Both scans do not involve the use of exogenous contrast agents. Total scan time is usually around 30 minutes and not to exceed 1 hour. If initial data is not available, subjects may be asked to return for additional scans. During the MRI scan, subjects are placed in a supine position on the camera table. The head is placed in position and a plastic head holder is used to reduce head movement during the scan. Participants are given a squeeze ball and instructed to squeeze it if they feel unwell or have any problems during the scan, so that the MRI staff can stop the scan. Participants are given over-ear headphones to reduce MRI noise. All subjects undergo a structural MRI scan at the beginning of the session to allow for anatomical co-registration. All participants receive a metal survey questionnaire before each scanning session.

[0320] DaTscan Procedure

[0321] DatScan (Iofulpane I 123 injection) is an FDA-approved radiopharmaceutical indicated for visualization of striatal dopamine transporters using single photon emission computed tomography (SPECT) brain imaging to aid in the evaluation of adults with suspected Parkinsonism (PS). Parkinsonism is associated with dopamine transporter (DAT) loss in the striatum. Iofulpane I 123 is a radiopharmaceutical indicated for visualization of striatal DAT using SPECT brain imaging to aid in the evaluation of adult patients with suspected PS. Iofulpane I 123 binds to the DaT protein located in dopaminergic nigrostriatal neurons, a bundle of nerve fibers in the brain. In a normal scan, Iofulpane I 123 is distributed in the striatum and appears similar to a "comma" or crescent shape. Decreased isoflupane I 123 activity results in circular "periods" or oval shapes with reduced image intensity on one or both sides.

[0322] procedure Before the scan, each subject is asked whether they are allergic to iodine, whether they have a history of kidney or liver disease, and whether they are current or past cocaine users. Staff should administer a thyroid blocking agent (e.g., potassium iodide oral solution equivalent to 100 mg of iodine or potassium perchlorate 400 mg) at least 1 hour before administration. · The imaging facility will measure the patient's dose with a suitable radioactivity calibration system immediately prior to administration. The recommended dose is 111 to 185 MBq (3 to 5 mCi) given via an intravenous (IV) line into the arm. · After injection, begin SPECT imaging using a gamma camera between 3 and 6 hours. Once started, DaTscan takes approximately 30-45 minutes.

[0323] During a SPECT scan, the subject lies on a table and the imaging technician places the subject's head in a headrest. A piece of tape or flexible restraint may be placed around the subject's head to help keep the head from moving during the scan. A camera is placed above the subject's head, and the subject must remain absolutely still for approximately 30 minutes while images are taken.

[0324] DaTscan is excreted by the kidneys and severe renal impairment can increase radiation exposure to the patient and alter images.

[0325] Safety of DaTscan

[0326] contraindication

[0327] Hypersensitivity to the active substance, excipients or iodine

[0328] MDS-Universal Parkinson's Disease Rating Scale

[0329] The MDS-UPDRS has four parts:

[0330] Part I (Non-exercise experiences of daily life)

[0331] Part II (Exercise Experiences in Daily Life)

[0332] Part III (Motor Examination)

[0333] Part IV (motor complications)

[0334] Part I has two components and 13 questions: IA, which concerns several behaviors assessed by the investigator with all of the relevant information from the patient and caregiver, and IB, which is completed by the patient independently of the investigator, with or without the help of the caregiver. However, these sections can be reviewed by the assessor to ensure that all questions have been answered clearly and that the assessor can help explain any points that they feel are unclear. Part II, which has 13 questions, is designed to be a self-administered questionnaire like Part IB, but can be reviewed by the investigator for completeness and clarity. Part III is a motor examination, with 18 assessments. Part I addresses motor complications, with 6 questions.

[0335] Hoehn and Yahr Severity

[0336] The Hoehn and Yahr scale is used to measure how Parkinson's disease symptoms progress and the level of disability. The original scale has stages 1 to 5. This study uses a modified scale, which adds stage 0.

[0337] Stage 0 – No signs of disease

[0338] Stage 1 - Symptoms on only one side (unilateral)

[0339] Stage 2 - Bilateral symptoms, but balance is not impaired

[0340] Stage 3 – Balance impairment, mild to moderate disease, physical independence

[0341] Stage 4 - Severely disabled, but still able to walk or stand without assistance

[0342] Stage 5 - Wheelchair required or bedridden without assistance

[0343] statistical analysis

[0344] Number of subjects and sample size calculations

[0345] The study will enroll approximately 300 subjects with stage 1 PD or asymptomatic subjects (age ≧55 years) with the LRRK2 haplotype, and 200 age- and sex-matched controls. Sample size is based on a 20% reduction in substantia nigra neuromelanin levels at endpoint (after 5 years) in subjects with stage 1 PD or the LRRK2 haplotype compared to control subjects.

[0346] Secondary endpoints are correlations between NM-MRI scans and both DaTscan scans and UPDRS scores.

[0347] Analysis population

[0348] The following patient populations will be used for statistical analysis:

[0349] Subjects who underwent one post-screening NM-MRI scan

[0350] statistical methods

[0351] The study will enroll approximately 300 subjects with early stage PD (stage 1 or 2) who have not previously been treated with L-dopa, or asymptomatic subjects (age >55 years) who have the LRRK2 haplotype, and 200 age- and sex-matched controls. Sample size is based on a 20% reduction in substantia nigra neuromelanin levels at endpoint (after 5 years) in subjects with early stage PD (stage 1 or 2) or the LRRK2 haplotype compared to control subjects.

[0352] Target predisposition

[0353] The numbers of subjects who enrolled and completed or discontinued from the study, and reasons for discontinuation, will be tabulated by treatment group, as appropriate.

[0354] Primary endpoint

[0355] The study will enroll approximately 300 subjects with early PD (stage 1 or 2) not treated with L-dopa, or asymptomatic subjects (age ≥ 55 years) with the LRRK2 haplotype, and 200 age- and sex-matched controls. Sample size is based on a 20% reduction in SNc neuromelanin concentration levels at endpoint (after 5 years) in subjects with stage 1 PD or the LRRK2 haplotype compared to control subjects. Analyses for primary and secondary endpoints will be performed by analysis of covariance (ANCOVA), linear regression, or Pearson correlation.

[0356] Percent change from baseline to endpoint on NM-MRI in subjects with early PD (stage 1 or 2) not treated with L-dopa or subjects with LRRK2 haplotypes compared to control subjects

[0357] Total NM concentration (micrograms of neuromelanin per microgram of wet tissue) in the substantia nigra pars compacta (SNc), NM concentration in the SNc, volume of NM in the entire SNc, and volume of subregions of the SNc

[0358] Change from baseline to endpoint on NM-MRI in subjects with early PD (stage 1 or 2) not treated with L-dopa or subjects with the LRRK2 haplotype compared to control subjects

[0359] Total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in the SNc, volume of NM in the whole SNc, and volume of subregions of the SNc

[0360] Total NM concentration in the substantia nigra pars compacta (SNc), NM concentration in the SNc, NM volume in the entire SNc, and the volume of subregions of the SNc were smaller in subjects with early PD compared to the normal range in controls.

[0361] To determine the difference (absolute value and percentage change) in neuromelanin levels (SNc concentration, volume of NM in SNc) in LRRK2 subjects from controls, allowing for the diagnosis of PD, as confirmed by DaTscan

[0362] Secondary endpoints

[0363] Correlation between NM-MRI assessments and MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores and DaTscan imaging over a 5-year period

[0364] Correlation of Parkinsonian voxels (identified by TerranNeuroMelanin MRI voxel-based analysis) with Parkinsonian symptoms as measured by MDS-UPDRS

[0365] Correlation between NM-MRI assessment (SNc and SNc subregion concentration, NM volume in SNc and SNc subregion) and Hohen-Yahr severity classification

[0366] Identification of Parkinsonian voxels (identified by TerranNeuroMelanin MRI voxel-based analysis) that correlate with specific Parkinsonian symptoms as measured by the MDS-UPDRS

[0367] To demonstrate a correlation between changes in neuromelanin measurements and improvement in MDS-UPDRS scores after initiation of L-dopa therapy

[0368] Neuromelanin levels increase (SNc concentration, volume of NM in SNc) as measured by Terran Neuromelanin MRI voxel-based analysis, which improves MDS-UPDRS with L-dopa therapy.

[0369] Example 2B Assessment of carbidopa / levodopa treatment in Parkinson's disease by voxel-based analysis of TerranNeuromelanin MRI Terran Neuromelanin MRI Voxel-Based Analysis has been developed as a standalone software as a medical device (SaMD) to measure neuromelanin levels obtained using NM-MRI. Terran Neuromelanin MRI Voxel-Based Analysis can be used to obtain accurate measurements of neuromelanin concentration and volume in the substantia nigra. Neuromelanin is a surrogate measure of dopaminergic neuronal activity that can be used as an aid to physicians evaluating subjects with medical conditions that affect midbrain dopamine levels. This study uses Terran Neuromelanin MRI Voxel-Based Analysis to evaluate the efficacy of carbidopa / levodopa treatment in the treatment of PD.

[0370] primary purpose

[0371] To demonstrate correlations between neuromelanin measurements (NM concentration in the substantia nigra pars compacta (SNc), SNc subregions, NM volume in the entire SNc, and SNc subregion volume) and improvement in MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores after initiation of carbidopa / levodopa treatment.

[0372] To determine an increase in levels of neuromelanin (SNc and SNc subregion concentration, volume of NM in SNc and SNc subregions) as measured by Terran Neuromelanin MRI voxel-based analysis, which results in an improvement in MDS-UPDRS, validating that NM levels can be used to monitor response to treatment.

[0373] Terran Neuromelanin MRI Voxel-Based Analysis is an Effective Method to Determine Whether Patients Have an Optimal Response to Carbidopa / Levodopa Treatment

[0374] Study design

[0375] This study is a 12-week study in carbidopa / levodopa-naive symptomatic PD subjects. This study demonstrates the value of Terran Neuromelanin MRI voxel-based analysis for monitoring subjects with PD who are starting carbidopa / levodopa treatment. This study will enroll approximately 100 subjects with symptomatic PD who are not being treated with carbidopa / levodopa. Subjects will be enrolled in this study after signing an informed consent form (ICF) and meeting all inclusion / exclusion criteria. During the screening period, subjects will undergo NM-MRI scans using Terran Neuromelanin MRI voxel-based analysis and MDS-UPDRS. Each subject will be assessed using the Yahr severity classification. Subjects will undergo repeat assessments of NM-MRI scans and MDS-UPDRS at weeks 4, 8, and 12. After completing screening, subjects will enter the treatment period and begin carbidopa / levodopa treatment. The dose of carbidopa / levodopa will be individualized by the clinician in this study based on clinical response and adverse events. Dosing is best initiated with one 25 mg to 100 mg carbidopa / levodopa tablet three times daily. This dosing schedule provides 75 mg of carbidopa per day. Dosing may be increased by one tablet daily or every other day, as needed, until a dose of eight 25 mg to 100 mg tablets per day is reached. Extended release formulations of carbidopa / levodopa are permitted with similar dosing. Dose escalation and reduction will be guided by NM-MRI signal comparison.

[0376] Subjects with a current history of substance abuse will be excluded from this study. Finally, subjects with unstable medical conditions or contraindications to MRI studies will also be excluded.

[0377] Evaluation timeline The evaluation will be carried out according to the examination flowchart in Table 1. [Table 2]

[0378] Screening – Visit 1

[0379] The screening phase lasts up to 30 days, during which demographic information, medical history, and informed consent are obtained. Subjects who meet the inclusion and exclusion criteria may be admitted to the study. The nature and purpose of the study should be explained to the subjects before the screening process begins.

[0380] After signing the Informed Consent Form (ICF), the following demographic data should be collected and recorded: patient's date of birth, age at time of informed consent, sex, ethnicity, and race. Study site personnel will obtain a full medical history from the patient during screening and update as necessary at Visit 1. A medical history will be obtained, as well as vital signs (blood pressure and pulse). A urine sample will be collected for drug testing. A history of current and recent medications will also be obtained. The investigator or designer will determine if the subject meets all of the eligibility criteria for this study.

[0381] The following evaluations will be performed: · Signing the ICF MINI ·Demographics Medical History Hohen-Jahr severity classification · UPDRS ·MRI Metal Survey Questionnaire Vital signs (blood pressure and heart rate) Urine Drug Testing Concomitant medications Adverse Events Eligibility Criteria

[0382] Screening Visit 2

[0383] During Screening Visit 2, the following tests will be performed: NM-MRI Imaging

[0384] Review and evaluation

[0385] MRI procedure

[0386] MRI screening

[0387] Prior to enrollment in the MRI study, all subjects are screened to confirm eligibility for MRI scanning. The screening questionnaire includes questions regarding inclusion / exclusion criteria, including the presence of strong paramagnetic implants. If a subject has any metallic implants that are inappropriate for the scanner (i.e., metallic heart valves, aortic clips, etc.), the subject will not be included in our study. Inclusion and exclusion in our study will be determined by the PI and co-PI in this study.

[0388] MRI procedure

[0389] Subjects undergo a structural 3 Tesla MRI scan and a neuromelanin-sensitive (structural) scan. Both scans do not involve the use of exogenous contrast agents. Total scan time is typically around 30 minutes and not to exceed 1 hour. If initial data is not usable, subjects may be asked to return for additional scans. During the MRI scan, subjects are placed in a supine position on the camera table. The head is placed in position and a plastic head holder is used to reduce head movement during the scan. Participants are given a squeeze ball and instructed to squeeze it if they feel unwell or have any problems during the scan, so that the MRI staff can stop the scan. Participants are given over-ear headphones to reduce MRI noise. All subjects undergo a structural MRI scan at the beginning of the session to allow for anatomical co-registration. All participants receive a metal survey questionnaire before each scanning session.

[0390] MDS-Universal Parkinson's Disease Rating Scale

[0391] The MDS-UPDRS has four parts: Part I (non-exercise experiences of daily life) Part II (Exercise experience in daily life) Part III (Motor Examination) ·Part IV (motor complications)

[0392] Part I has two components and 13 questions: IA, which concerns several behaviors assessed by the investigator with all of the relevant information from the subject and the caregiver, and IB, which is completed by the patient independently of the investigator, with or without the caregiver's help. However, these sections can be reviewed by the assessor to ensure that all questions have been answered clearly and that the assessor can help explain any points that they feel are unclear. Part II has 13 questions and is designed to be a self-administered questionnaire like Part IB, but can be reviewed by the investigator for completeness and clarity. Part III is a motor examination, with 18 assessments. Part I addresses motor complications, with 6 questions.

[0393] Hoehn and Yahr Severity

[0394] The Hoehn and Yahr scale is used to measure how Parkinson's disease symptoms progress and the level of disability. The original scale has stages 1 to 5. This study uses a modified scale, which adds stage 0. Stage 0 – no signs of disease Stage 1 - Symptoms on only one side (unilateral) Stage 2 - Bilateral symptoms, but balance is not impaired Stage 3 – Balance impairment, mild to moderate disease, physical independence Stage 4 - Severely disabled, but still able to walk or stand without assistance Stage 5 - Requires a wheelchair or is bedridden without assistance.

[0395] Target Enrollment and Exit

[0396] Selection Criteria

[0397] To be eligible to participate in this study, subjects must meet all of the following inclusion criteria:

[0398] Women and men aged 40 years or older with carbidopa / levodopa or levodopa-naive symptomatic PD.

[0399] Agree to participate in this study and are capable of providing informed consent.

[0400] Exclusion criteria

[0401] Subjects will be excluded from this study if they meet any of the following exclusion criteria:

[0402] Previous treatment with carbidopa / levodopa or levodopa

[0403] A history of substance use disorder (excluding tobacco) as defined by DSM-V for at least 6 months prior to screening or positive urine drug test (for amphetamines, cocaine, opioids, and phencyclidine). Subjects with mild cannabis or alcohol substance use disorder may be enrolled with permission of the medical monitor.

[0404] Any metallic implants or paramagnetic objects placed inside the body that may cause claustrophobia or interfere with the MRI scan, as determined by the guidelines outlined in the following reference book: "Guide to MR procedures and metallic objects" Shellock, PhD, Lippincott-Raven press, NY 1998.

[0405] Previous and concomitant treatments

[0406] All medications, including over-the-counter preparations and home remedies, used by patients within one month of enrollment in this study must be recorded on the case report form.

[0407] safety

[0408] This is a non-interventional study that longitudinally evaluates NM-MRI. The evaluation involves a standard 3-T MRI and software that measures the amount of neuromelanin in specific structures of the brain. Vital signs (blood pressure and pulse) will be measured at each study visit.

[0409] At the beginning of each study visit, study staff will ask a series of questions from a "quick screening" form that inquires about hospitalizations, medical conditions, physician visits, medication use, substance use, and whether they are involved in incidents involving metals. If information regarding adverse experiences arises during this interview, this information must be recorded on the Case Report Form (CRF).

[0410] Please note that given that this is a non-interventional study, no physical exam, laboratory evaluation, or electrocardiogram will be performed.

[0411] Measurement of vital signs

[0412] Blood pressure (systolic and diastolic) will be measured with the subject in a sitting position at each visit in accordance with AHA recommendations. Pulse rate can be determined by palpation of the radial pulse in a sitting position. Blood pressure and pulse can be measured by a blood pressure monitoring device.

[0413] Risk to subject

[0414] Risks that may be encountered during the review period

[0415] All procedures are substantially free of any risk or potential danger to participants. Most procedures carry a small risk of discomfort due to nuisance. Some of the questions in the evaluation touch on sensitive subjects.

[0416] Magnetic resonance imaging

[0417] Both the FDA and NYSPI IRB consider MRI scans to be classified as non-serious risks. For this cross-scanner validation study, the only applicable risks are those associated with MRI scans (i.e., discomfort, fatigue, anxiety). MRI scans include 3 Tesla scanners, which are considered to pose a non-serious risk by the FDA.

[0418] To minimize risk and discomfort to participants, facilities will:

[0419] Screening for metallic devices, implants and other contraindications to scanning by using the MRI Metal Survey Questionnaire

[0420] Pregnant subjects are excluded prior to scanning and a urine pregnancy test is performed.

[0421] Subjects with claustrophobia are excluded. We reduce this potential adverse reaction by discussing the procedure with the subject before entering the magnetic chamber, providing the subject with a mirror through which they can see into the chamber, and communicating with the subject via an intercom. If the subject continues to feel uncomfortable, we terminate the imaging procedure and remove the subject from the magnet.

[0422] Staff will provide appropriate medical monitoring, safety monitoring, and observation during the scan.

[0423] Study staff can provide assistance, reduce anxiety, optimize subject comfort, and remove subjects from the MRI machine if requested.

[0424] Carbidopa / levodopa

[0425] All patients should be closely observed for the development of depression with accompanying suicidal tendencies.

[0426] Carbidopa / levodopa should be administered with caution to patients with severe cardiovascular or pulmonary disease, bronchial asthma, renal, hepatic or endocrine disease.

[0427] As with levodopa, caution should be exercised when administering carbidopa / levodopa to patients with a history of myocardial infarction who have residual atrial, nodal, or ventricular arrhythmias.

[0428] As with levodopa, treatment with carbidopa / levodopa may increase the potential for upper gastrointestinal bleeding in patients with a history of peptic ulcer disease.

[0429] Falling Asleep During Activities of Daily Living and Somnolence: Patients taking carbidopa / levodopa alone or with other dopaminergic medications have reported falling asleep suddenly, without prior warning of drowsiness, while engaged in activities of daily living (including driving a car). Patients should be advised to use caution while driving or operating machinery during treatment with carbidopa / levodopa. Patients who have already experienced episodes of somnolence or sudden onset of sleep should not participate in these activities during treatment with carbidopa / levodopa.

[0430] Before initiating treatment with carbidopa / levodopa, advise patients about the potential for developing drowsiness and ask specifically about factors that may increase the risk of carbidopa / levodopa-induced somnolence, such as use of concomitant sedative medications and the presence of sleep disorders.

[0431] Hyperpyrexia and confusion: sporadic cases of complications resembling neuroleptic malignant syndrome.

[0432] Adverse reactions / events

[0433] The most common adverse reactions reported with carbidopa / levodopa include dyskinesias, including chorea, dystonic and other involuntary movements, and nausea.

[0434] The following other adverse reactions have been reported with carbidopa / levodopa:

[0435] Physically, as a whole: Chest pain, weakness.

[0436] Cardiovascular: Orthostatic effects including cardiac irregularities, hypotension, orthostatic hypotension, hypertension, fainting, phlebitis, palpitations.

[0437] Gastrointestinal: dark saliva, gastrointestinal bleeding, development of duodenal ulcers, loss of appetite, vomiting, diarrhea, constipation, indigestion, dry mouth, altered taste.

[0438] Hematologic system: Agranulocytosis, hemolytic and nonhemolytic anemia, thrombocytopenia, leukopenia.

[0439] Hypersensitivity: Angioedema, urticaria, pruritus, Henoch-Schönlein purpura, bullous lesions (including pemphigoid reactions).

[0440] Musculoskeletal: Back pain, shoulder pain, muscle spasms.

[0441] Nervous system / Neurological: Psychotic episodes including delusions, hallucinations and paranoid ideation, bradykinesia episodes ("on-off" phenomenon), confusion, agitation, dizziness, somnolence, dream abnormalities including nightmares, insomnia, paresthesias, headache, depression with or without development of suicidal tendencies, dementia, pathological gambling, increased sexual drive including hyperlibido, impulse control symptoms.

[0442] Breathing: Difficulty breathing, upper respiratory infection.

[0443] Skin: Rash, increased sweating, hair loss, dark sweat.

[0444] Urogenital: Urinary tract infections, frequent urination, dark urine.

[0445] Laboratory tests: Decreased hemoglobin and hematocrit; abnormal alkaline phosphatase, SGOT (AST), SGPT (ALT), LDH, bilirubin, BUN, Coombs test; improved serum glucose; urinary leukocytes, bacteria and blood.

[0446] Adverse events

[0447] Adverse events (AEs) will be collected during the study. Please see section 0457 for detailed information regarding the collection, definition, classification, and reporting of AEs / SAEs during the study.

[0448] AEs will be monitored throughout the study and the following information will be recorded:

[0449] Verbatim medical condition

[0450] Whether the event was a treatment-emergent adverse reaction

[0451] Whether the event was a serious adverse event

[0452] Date and time of onset

[0453] Severity of the event

[0454] Relationship of the event to the drug under study

[0455] Actions taken regarding the study drug by event

[0456] The clinical outcome of the event (resolved or ongoing). If resolved, provide the date and time of resolution.

[0457] Adverse events

[0458] Definition of AEs, observation period and recording of AEs

[0459] An AE is any untoward or unintended sign, symptom, or illness, whether or not considered relevant to the study. Recording of adverse events begins when the informed consent form is signed. From then on, AEs are ascertained by asking the patient how they have been since their last visit. Evaluations should continue as necessary to follow up the AE for its resolution or acceptable stabilization consistent with the investigator's medical judgment.

[0460] Every attempt should be made to describe the AE in terms of a diagnosis. Once a definite diagnosis is made, individual signs and symptoms should not be recorded unless they are atypical or extreme signs of the diagnosis, in which case they should be reported as separate events. The events leading up to the diagnosis should be retained. If a definite diagnosis cannot be established, each sign and symptom must be recorded separately.

[0461] The Investigator is responsible for ensuring that all adverse clinical experiences, whether observed by the Investigator or reported by the patient, are reported in the CRF and in the patient's medical record. The Investigator must assign the following AE attributes:

[0462] Diagnosis of the adverse event, or, if known, syndrome (if unknown, signs or symptoms)

[0463] Dates of onset and resolution

[0464] Severity (and / or protocol-specific toxicities)

[0465] Assessment of relevance to the product under consideration; and

[0466] Measures adopted

[0467] Strength Classification

[0468] For both AEs and SAEs, the investigator must assess the severity / intensity of the event. The severity / intensity of AEs will be graded based on the patient's symptoms as follows:

[0469] Mild - Transient or mild discomfort; no limitation of activity; no medical intervention / treatment required.

[0470] Moderate - Mild to moderate limitation of activity; some assistance may be required; no or minimal medical intervention / treatment required.

[0471] Severe - Significant limitation of activity. Usually requires some assistance; medical intervention / treatment required. Possible hospitalization.

[0472] Life-threatening - severe limitation of activity; requires significant assistance; requires major medical intervention / treatment, likely requiring hospitalization or hospice care.

[0473] The term "severe" is often used to describe the intensity of a particular event (e.g., mild, moderate, or severe myocardial infarction). However, the event itself may be of relatively minor medical significance (e.g., severe headache). This criterion is not the same as "severe," which is based on patient / event outcomes or behavioral diagnostic criteria relating the event to a threat to the patient's life or function.

[0474] Severity, rather than severity, serves as a guide to clarify regulatory obligations.

[0475] statistical analysis

[0476] Number of subjects and sample size calculations

[0477] The study will enroll approximately 100 carbidopa / levodopa-naive subjects with symptomatic PD. Sample size is based on a 20% improvement in SNc neuromelanin concentration levels at endpoint after carbidopa / levodopa treatment.

[0478] Analysis population

[0479] The following patient populations will be used for statistical analysis:

[0480] Subjects who underwent one post-screening NM-MRI scan

[0481] statistical methods

[0482] Target predisposition

[0483] The numbers of subjects who enrolled and completed or discontinued from the study, and reasons for discontinuation, will be tabulated by treatment group, as appropriate.

[0484] Primary endpoint

[0485] Correlation of neuromelanin measures (NM concentration in the substantia nigra pars compacta (SNc), SNc subregions, NM volume in the whole SNc, and SNc subregions volume) with improvement in MDS-UPDRS scores after initiation of carbidopa / levodopa treatment

[0486] Neuromelanin levels (SNc and SNc subregion concentrations, volume of NM in SNc and SNc subregions) resulting in improvement of MDS-UPDRS after initiation of carbidopa / levodopa

[0487] Details of the statistical analysis are contained in the Statistical Analysis Plan (SAP).

[0488] NM-MRI analysis

[0489] Details of the analysis will be presented in the statistical analysis plan.

[0490] Protocol deviations

[0491] All deviations will be listed. Protocol deviations will be classified as major or minor. Major protocol deviations will be adjudicated by the sponsor. Subjects with major protocol deviations or data points judged to be major protocol deviations will be excluded from the PP population.

[0492] Demographic and baseline characteristics

[0493] Demographic and baseline characteristics will be listed and summarized by treatment and overall.

[0494] safety

[0495] Adverse events

[0496] The types and incidence of adverse events will be tabulated.

[0497] AEs will be coded using the most recent version of the Medical Dictionary for Regulatory Activities (MedDRA®).

[0498] The numbers and percentages of subjects experiencing TEAEs, treatment-emergent SAEs, and TEAEs leading to study discontinuation will be summarized by treatment group and overall by MedDRA system organ class (SOC) and / or preferred term (PT).

[0499] Vital signs Descriptive statistics will be calculated for all vital sign measurements (blood pressure and pulse rate) change from baseline.

[0500] List of abbreviations used: [Table 3-1] [Table 3-2]

[0501] Reference to Example 2

[0502] The following references are incorporated herein by reference in their entirety:

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[0508] Kitao S, Matsusue E, Fujii S, et al. Correlation between pathology and neuromelanin MR imaging in Parkinson’s disease and dementia with Lewy bodies. Neuroradiology. 2013;55(8):947-953.

[0509] Matsuura K, Maeda M, Yata K, et al. Neuromelanin magnetic resonance imaging in Parkinson's disease and multiple system atrophy. European neurology. 2013;70(1-2):70-77.

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[0538] Example 3 Evidence for dopamine abnormalities in the substantia nigra in cocaine dependence revealed by neuromelanin-sensitive MRI summary

[0539] Objective: Recent evidence supports the use of neuromelanin-sensitive MRI (NM-MRI) as a novel tool to investigate dopamine function in the human brain. The aim of this study was to investigate NM-MRI signal in cocaine use disorder compared to age- and sex-matched controls, building on previous imaging studies showing that this disorder involves blunt presynaptic striatal dopamine.

[0540] Methods: NM-MRI and T1-weighted images were acquired from 20 participants with cocaine use disorder and 35 controls. The effect of diagnostic group on NM-MRI signal was determined using voxel-wise analysis within the substantia nigra (SN). To examine whether NM-MRI was associated with alterations in reward processing, a subset of 20 cocaine users and 17 controls also underwent functional MRI imaging using a monetary reward delay task.

[0541] Results: Compared to controls, cocaine users showed significantly increased NM-MRI signal in the ventrolateral region of the SN (linear regression; corrected p = 0.025, permutation test; area under the receiver operating characteristic curve = 0.83). Exploratory analyses found no significant correlation of NM-MRI signal to ventral striatal activation during monetary reward anticipation.

[0542] Conclusions: Given that previous imaging studies have shown reduced dopamine signaling in the striatum, the finding of increased NM-MRI signal in the SN provides further insight into the pathophysiology of cocaine use disorder. One interpretation is that cocaine use disorder is associated with a redistribution of dopamine between cytosolic and vesicular pools, resulting in increased accumulation of neuromelanin. Thus, this study suggests that NM-MRI can serve as a practical imaging tool to investigate the dopamine system in addiction.

[0543] Introduction

[0544] Altered dopamine function has been previously demonstrated in cocaine use disorder using positron emission tomography (PET), including measurements of dopamine uptake, receptor density, and dopamine release (1). Reductions in stimulant-induced presynaptic dopamine release in cocaine users, measured with PET, have been well replicated (1-4) and are associated with the more refractory symptoms of cocaine use disorder, including relapse (1, 2). However, although PET can provide important insights into dopamine signaling in addiction, it is expensive and requires a fairly specialized infrastructure. Furthermore, its use in longitudinal studies and studies in at-risk youth populations is limited by radioactive exposure.

[0545] Recent reviews suggest that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) can provide a complementary noninvasive surrogate measure of dopamine function and integrity (5, 6). Neuromelanin (NM) is a pigment produced from the conversion of cytosolic dopamine that gradually accumulates over a lifetime in dopamine neurons of the substantia nigra (SN) (7). Neuromelanin binds to iron, which forms a paramagnetic complex that can be imaged using MRI (6, 8, 9). NM-MRI can reliably capture neuromelanin depletion following SN neurodegeneration in Parkinson's disease (6, 10). Importantly, this technique can also capture changes in dopamine function in the absence of neurodegeneration (5, 11), consistent with in vitro evidence that stimulating dopamine synthesis enhances NM synthesis (12, 13).

[0546] In particular, NM-MRI signal within subregions of the substantia nigra is increased in association with psychosis (5), consistent with PET findings of increased dopamine signaling in psychosis (14). Moreover, NM-MRI signal directly correlates with both PET measurements of presynaptic dopamine release and resting blood flow in the midbrain (5). Thus, in one embodiment, the subject matter disclosed herein demonstrates that NM-MRI provides a surrogate measure of functional changes in dopaminergic pathways that has utility for studying psychiatric disorders without overt neurodegeneration.

[0547] Here, we used NM-MRI for the first time to test whether similar changes could be detected in cocaine use disorder, a disorder that involves dopamine dysfunction. To this end, the primary analysis herein tested for the effect of diagnostic group on NM-MRI signal in the substantia nigra. Without being bound by theory, based on previous PET studies (1, 3), we believe that cocaine use disorder is accompanied by a reduction in NM-MRI signal. In an exploratory analysis, we assessed associations between changes in NM-MRI signal intensity in cocaine use disorder and hemodynamic brain responses during a monetary reward delay task. Activation of the ventral striatum during reward anticipation in this task has been shown to provide a robust functional readout of reward processing (15) associated with dopamine (16, 17), which is consistently reduced in drug dependence and behavioral addictions (18, 19). As the ventral striatum receives projections from the ventral tegmental area and dorsomedial SN (20, 21), we explored the relationship between NM-MRI signal in the SN and reward-related activation in the ventral striatum.

[0548] method

[0549] participants

[0550] The study was approved by the New York State Psychiatric Institute Institutional Review Board. All participants provided written informed consent. Cocaine-using participants met DSM-V criteria for moderate to severe cocaine use disorder with no other current Axis I diagnoses or current medical illnesses. Any other substance use disorder (except tobacco and cocaine) was an exclusion criterion. At the time of inclusion, these participants were actively using smoked cocaine, which was confirmed by urine toxicology. They were required to abstain for a minimum of 5 days before scanning, which was confirmed by urine drug testing (performed every other day). Participants abstained from tobacco use for a minimum of 1 hour before scanning. Tobacco-using and non-tobacco-using control groups were also included. Screening procedures included physical examination, electrocardiogram, and laboratory tests. All participants were recruited by advertisement and by word of mouth. Controls were excluded for current or past axis I disorders (except tobacco use disorder), history of neurological disorders, or current major medical illness. In total, 58 men participated in the study. Three participants (one cocaine user and two controls) were excluded due to unusable NM-MRI images (because the participant moved [displaying clearly visible stains or band-like artifacts affecting the midbrain, n = 2], or because of incorrect alignment of the image stack [n = 1]). Thus, a total of 55 participants were reserved for the analysis: 20 cocaine users and 35 age- and sex-matched controls, as shown in Figure 4. All participants completed self-report questionnaires, including the Multidimensional Scale of Perceived Social Support (22) and the Beck Depression Inventory (23).

[0551] NM-MRI acquisition

[0552] Magnetic resonance (MR) images were acquired for all study participants on a GE Healthcare 3T MR750 scanner using a 32-channel phased-array Nova head coil, following the methodology in a previous study (5). For logistical reasons, a few scans (7% of all scans, 4 out of a total of 55 participants) were acquired using an 8-channel in vivo head coil instead. NM-MRI images were acquired using a 2D gradient response echo sequence with magnetization transfer contrast (2D GRE-MT) with the following parameters: repetition time (TR) = 260 ms; echo time (TE) = 2.68 ms; flip angle = 40°; in-plane resolution = 0.39 × 0.39 mm2; partial brain coverage including field of view (FoV) = 162 × 200; matrix = 416 × 512; number of slices = 10; slice thickness = 3 mm; slice gap = 0 mm; magnetization transfer frequency offset = 1,200 Hz; number of excitations (NEX) = 8; acquisition time = 8.04 min. The slice prescription protocol consisted of orienting the image stack along the anterior commissure-posterior commissure line and placing the top slice 3 mm below the floor of the third ventricle (for further details, see (5)). This protocol provides coverage of the SN-containing portion of the midbrain and surrounding structures. To support preprocessing of NM-MRI images (see below), high-resolution T1-weighted structural MRI scans of the whole brain were also acquired using a fast spoiled gradient echo sequence (inversion time = 500 ms, TR = 6.37 ms, TE = 2.59 ms, flip angle = 11°, FoV = 256 × 256, number of slices = 244, isotropic voxel size = 1.0 mm3) or, in some cases, a 3D BRAVO sequence (inversion time = 450 ms, TR ~ 7.85 ms, TE ~ 3.10 ms, flip angle = 12°, FoV = 240 × 240, number of slices = 220, isotropic voxel size = 0.8 mm3). NM-MRI image quality was visually inspected for artifacts immediately after acquisition and, if necessary, scans were repeated as time permitted.

[0553] Preprocessing of NM-MRI

[0554] Similar to previous studies (5), NM-MRI scans were preprocessed using SPM12 to facilitate voxel-wise analysis in standardized MNI space. NM-MRI scans were first coregistered to the participants' T1-weighted scans. Tissue segmentation was then performed using the T1-weighted images. NM-MRI scans were normalized to MNI space using DARTEL routines using gray and white matter templates generated from all studied participants. Resampled voxel size of unsmoothed normalized NM-MRI scans was isotropic at 1 mm. All images were visually inspected after each preprocessing step. Intensity normalization and spatial smoothing were then performed using custom Matlab® (Mathworks) scripts. Contrast-to-noise ratios (CNRs) for each participant and voxel v were calculated using CNR v =(I v -Mode(I RR )) / Mode(I RR The mode (I) was calculated as the relative difference in NM-MRI signal intensity I from a reference region RR in the cerebral peduncle, a white matter tract known to have the lowest NM content. A template mask of the reference region and a template mask of the SN were created by manually tracing onto a template NM-MRI image in MNI space (average of normalized NM-MRI scans from all participants studied, see Figure 1 and previous report for further details (5)). RR ) was calculated for each participant from a kernel smoothing function fitted to a histogram of the distribution of all voxels in the mask. The resulting NM-MRI contrast-to-noise ratio maps were then spatially smoothed using a 1 mm full-width-at-half-maximum Gaussian kernel.

[0555] NM-MRI analysis

[0556] All analyses were performed in Matlab®. In accordance with previous studies (5), the primary analysis consisted of a voxel-wise analysis of contrast-to-noise ratio values ​​in the SN mask. This approach captured topographical changes that likely correspond to functionally distinct SN neuronal subpopulations (20), and this approach has previously been shown to be highly sensitive to dopaminergic pathophysiology (5). Notably, the primary voxel-wise analysis was based on the CNR v =β 0 +β 1 ·Diagnosis+Σ n i=2 Specific differences between cocaine users and controls were examined by robust linear regression analysis (robustfit function in Matlab®) predicting contrast-to-noise ratio (NM signal) at each voxel v in the SN mask as βi·nuisance covariates + ε, with tobacco use (number of cigarettes per day), head coil, and age being nuisance covariates. Note that correction for age is important given the known relationship between age and neuromelanin accumulation (7). As in previous studies (5), we used group-derived template SN masks after truncating participant data points with missing values ​​due to incomplete SN coverage or extreme values ​​(contrast-to-noise ratio <-8% or contrast-to-noise ratio >40%; per subject, we truncated an average of 71 ± 195 voxels or 4% of all SN voxels). Correcting for multiple comparisons, and again following previous considerations ( 5 ), we defined the spatial extent of the effect as the number of voxels k (adjacent or nonadjacent) that showed a diagnostic difference (between cocaine users and controls) in the NM signal in either the positive or negative direction (regression coefficient β at p < 0.05). 1(Note that the results are still significant at the more stringent height threshold of p<0.01 for a t-test of p<0.01, voxel-level height threshold). Next, significance tests were determined based on a permutation test, in which diagnostic labels were randomly shuffled for individual maps of NM signal. This results in spatial extent measurements for each of the 10,000 permuted datasets, forming a null distribution for calculating the probability of observing the spatial extent k of an effect in the true data by chance. This test thus corrects for multiple comparisons by determining whether the spatial extent k of an effect is larger than expected by chance (p 補正後 <0.05, 10,000 permutations).

[0557] For a more detailed topographical description of the voxel-wise effects in the SN, a post hoc multiple linear regression analysis across SN voxels was used to predict the strength of the effect as a function of MNI voxel coordinates in the x (absolute distance from midline), y and z directions within the SN mask. For completeness, a region of interest analysis was also performed on the average NM signal across the SN mask. The region of interest analysis consisted of a robust linear regression analysis including head coil, age and incomplete SN coverage (yes / no) as nuisance covariates.

[0558] The ability of NM-MRI to separate participants based on diagnostic group was determined by calculating effect size estimates and areas under the receiver operating characteristic curve based on the mean NM-MRI signal in voxels identified as associated with cocaine use disorder in the primary voxel-wise analysis (hereafter referred to as "cocaine use voxels": voxels showing a diagnostic effect by the primary voxel-wise analysis or by a voxel-wise analysis following a leave-one-out procedure. A leave-one-out procedure was used to obtain effect size measures that were unbiased by voxel selection: for a given participant, voxels in which the variable of interest was associated with NM-MRI signal were first identified in an analysis including all participants except this (provided) participant. The mean signal in the provided participant was then calculated from this set of voxels. This procedure was repeated for all participants so that each participant had an extracted mean NM-MRI signal value obtained from the analysis that excluded them. Cohen's d and f 2 Confidence intervals for effect size measures were determined by boost trapping.

[0559] Partial correlations related clinical measures to NM-MRI signal extracted from cocaine-using voxels, with age and tobacco use as covariates. Because clinical measures were not normally distributed according to Lilliefors' test at p<0.05, Spearman partial (non-parametric) correlations were used.

[0560] fMRI method

[0561] Thirty-seven study participants (20 cocaine users, 17 controls) were included in the study and fMRI data were collected. Blood oxygen level-dependent (BOLD) fMRI was acquired while participants completed a monetary reward delay task. Echo-planar images were captured with the following parameters: repetition time (TR) = 1500 ms; echo time (TE) = 27 ms; flip angle = 60°; in-plane resolution = 3.5 × 3.5 mm. 2Acquisition was performed in two runs, each lasting 12.1 min. fMRI images were preprocessed using standard methods in SPM12, including slice time correction, realignment, co-registration to the T1-weighted scan, spatial normalization to standardized MNI space, and smoothing (6 mm full-width at half-maximum kernel). The monetary reward delay task used was similar to the standard version (24), which included the presentation of a visual cue (a geometric shape) linked to the subsequent receipt of feedback regarding a monetary reward ($1 or $5), a monetary loss ($1 or $5), or no outcome ($0). The task consisted of 110 trials divided equally into five conditions. Gaining money or avoiding a loss was probabilistically realized by having participants make a quick key press following a visual cue. The time available for key pressing was individualized based on the participants' movement speed during the practice trials. The first-level model included boxcar regressors for all five conditions during the anticipation period (defined as the period after the button press and before the feedback), the prospective period (after the cue presentation and before the button press), and the outcome period (when the feedback was delivered). Nuisance regressors included 24 motion parameters (six motion parameters and their squares, derivatives, and squared derivatives), and session-specific intercepts corresponding to the two runs. As in previous studies (15), activation during reward anticipation was defined by the contrast between the $5 and $0 earn conditions. For each participant, we extracted the signal from this contrast within a mask of the ventral striatum (from a published functional mask of the striatum, http: / / osf.io / jkzwp / ). The ventral striatum is the most commonly investigated brain structure using this task (19) and has been shown to yield robust and reliable readouts of reward-related activity during this task (25). To determine relationships to NM-MRI, linear regression was used to examine the effects of diagnosis, NM-MRI signal in cocaine use voxels, and the interaction of diagnosis by NM-MRI signal on predictive BOLD activity in the ventral striatum, controlling for age and tobacco use.

[0562] result

[0563] Impact of diagnosis on NM-MRI signal in the substantia nigra

[0564] A priori voxel-wise analysis of differences between cocaine users and controls

[0565] A subset of voxels located primarily ventrolaterally within the SN showed significantly increased NM-MRI signal (contrast-to-noise ratio) in cocaine users compared with controls (344 of 1775 voxels at p < 0.05, robust linear regression controlling for age, head coil, and number of cigarettes smoked per day; p 補正後 = 0.025, permutation test; peak voxel MNI coordinates [x, y, z]: 6, -26, -17 mm; see Figure 2B). In this sample of relatively light smokers, tobacco use was not significantly associated with NM-MRI signal differences (267 SN voxels were included in the first linear regression model, p 補正後 = 0.054) that correlated positively with the number of cigarettes smoked per day.

[0566] Based on the mean NM-MRI signal values ​​extracted from voxels in which cocaine users exhibited increased NM-MRI signal relative to controls in the voxel-wise analysis (cocaine-use voxels shown in red in Figure 2B, with extracted values ​​from these voxels shown in the top panel of Figure 2A), a diagnosis of cocaine use disorder had a moderate to large effect on NM-MRI signal (Cohen's d = 1.34, 95% confidence interval [CI] = 0.91 to 1.90; Cohen's f2 = 0.46, 95% CI = 0.19 to 0.95; unbiased leave-one-out Cohen's d = 0.77, 95% CI = 0.35 to 1.27; Cohen's f2 = 0.15, 95% CI = 0.02 to 0.43; all estimates were based on NM-MRI signal adjusted for age, head coil, and tobacco use). The diagnostic variance of NM-MRI signal after adjustment extracted from cocaine use voxels remained moderate to large when analyzing subsets of the study sample for possible confounds (controlling for years of education: Cohen's d = 0.76, 95% CI = 0.22 to 1.39, n = 38; controlling for depressive symptoms: Cohen's d = 0.84, 95% CI = 0.31 to 1.52, n = 37; controlling for perceived social support: Cohen's d = 1.06, 95% CI = 0.52 to 1.72, n = 37; excluding non-smokers: Cohen's d = 1.05, 95% CI = 0.50 to 1.74, n = 28; excluding participants scanned with an 8-channel coil: Cohen's d = 1.38, CI = 0.93 to 1.97, n = 51). Furthermore, most cocaine users could be successfully classified relative to all 35 controls based on adjusted NM-MRI signal extracted from cocaine-using voxels (area under the receiver operating characteristic curve [AUC] = 0.83, unbiased leave-one-out AUC = 0.71; Figure 2 ).

[0567] For completeness, we examined NM-MRI signal averaged within all SNs using region-of-interest analysis. Again, cocaine users showed significantly increased NM-MRI signal compared to controls (t49=2.07, p=0.044, Cohen's d=0.62, 95% CI=0.19 to 1.12; robust linear regression controlling for age, head coil, tobacco use and incomplete SN coverage; AUC=0.69).

[0568] Exploratory analysis of the relationship between NM-MRI signal in the substantia nigra and measures of severity of cocaine use

[0569] We tested whether NM-MRI signal extracted from cocaine use voxels correlated with severity of cocaine use and found no significant correlation with duration of use (ρ = -0.33, p = 0.18) or amount of money spent on cocaine per week (ρ = -0.08, p = 0.74; Spearman partial correlation controlling for age and tobacco use).

[0570] Exploratory analysis of the relationship between NM-MRI signals in the substantia nigra and the ventral striatum in response to reward expectancy

[0571] To explore the relationship of NM-MRI findings to dopamine-related circuit dysfunction in cocaine use disorder, we measured fMRI BOLD activation in the ventral striatum during anticipation of monetary reward. As expected, across participants, BOLD signal was higher in the ventral striatum when reward was anticipated compared to when reward was not. 36 = 2.56, p = 0.015, one-sample t test of the [$5 to $0] contrast during expectation). However, this reward-related activation in the ventral striatum did not differ between groups (β = 0.038, t 32 = 0.72, p = 0.48) or did not correlate with NM-MRI signal in cocaine-using voxels across all participants (β = -0.015, t 32=-1.52, p=0.14). There was also no group by NM-MRI signal interaction for reward-related activation in the ventral striatum (p=0.24; linear regression controlling for age and tobacco use).

[0572] Discussion

[0573] Data are presented herein showing increased NM-MRI signal in the SN of individuals with cocaine use disorder. This increase was not seen throughout the entire SN, but rather predominated in more ventral and lateral SN subregions. Given that NM-MRI signal reflects the concentration of synthetic melanin in experimental preparations (8) and NM in postmortem midbrain tissue (5), and that NM accumulation in the SN is dependent on dopamine function (5, 12, 13), these findings suggest that cocaine users exhibit enhanced NM concentrations in these SN subregions, which may be indicative of dopaminergic dysfunction.

[0574] The finding that NM signal is elevated in cocaine users was surprising given previous PET studies that showed presynaptic dopamine is blunted in cocaine use disorder (1-4). However, this difference provides further insight into the pathophysiology of dopamine signaling in this disorder. The combination of blunted dopamine release in the striatum and elevated NM in the SN suggests that dopamine is distributed differently in cocaine users compared to controls. Less dopamine concentrated in synaptic vesicles and more dopamine in the cytosolic pool explains the discrepancy between PET studies that estimate dopamine release from vesicles and imaging of NM accumulation based on dopamine concentration in the cytosol (12, 26). On the other hand, if cocaine use disorder is associated with a global and sustained decrease in dopamine synthesis, we would expect a decrease in both PET and NM-MRI signal.

[0575] There are several previous studies supporting the hypothesis that cocaine use disorder involves a redistribution of dopamine between vesicular and cytosolic stores (see Figure 3 for an illustration of this hypothesis). Chronic cocaine exposure is associated with reduced expression of vesicular monoamine transporter 2 (VMAT2), resulting in less dopamine in the vesicular pool and more dopamine in the cytosolic pool. Reductions in VMAT2 have been shown in non-human primates who chronically self-administer cocaine (27) and in human cocaine users (28). Postmortem human studies have also shown reduced striatal VMAT2 in cocaine users (29-31).

[0576] Blunted VMAT2 expression in cocaine use disorder could explain the reduced presynaptic dopamine release by PET (1-4) and the reduced [18F]DOPA accumulation seen in this population (32), which is likely dependent on the radioactive tracer concentrating in synaptic vesicles (33). Reduced VMAT2 expression has also been shown to correlate with increased NM formation in the midbrain (12, 34). Cocaine use has been shown to be associated with changes in the expression of D2 autoreceptors and several other proteins (1, 35), but these changes generally seem to shift both NM accumulation and dopamine release in the same direction. On the other hand, changes in VMAT2 stand out as the most parsimonious explanation for the observed changes that occur in opposite directions. Taken together, these imaging studies suggest that cocaine use is associated with a reduction in dopamine in the vesicular pool and a higher concentration in the cytosolic compartment. However, imaging of VMAT2 and dopamine release in cocaine users combined with NM-MRI in the midbrain is needed to confirm the hypothesis. If cocaine use indeed increases cytosolic dopamine, this could pose a risk to neurons, as oxidation of dopamine in this compartment forms reactive quinone species (36). However, there is no clear evidence of enhanced dopamine cell death (37) or risk of Parkinson's disease (38) in cocaine users.

[0577] An alternative interpretation of the main findings is that NM elevation in cocaine users may result from repeated episodic spikes of dopamine that occurred throughout the participants' lifetime, which may not be captured by PET. NM granules are only cleared following cell death (26) and therefore may serve as a long-term reporter of dopamine function and may manifest as persistent increases in NM-MRI signal even well before a history of cocaine use (which may lead acutely to dopamine excess during cocaine consumption). Future longitudinal studies will be required to address this possibility.

[0578] As an initial test of the functional significance of the findings, we examined whether NM-MRI signal in cocaine-using voxels within the SN correlated with fMRI responses to reward expectancy in the ventral striatum during a monetary reward delay task, a robust probe of reward system function (15, 19, 25). No significant correlation was found. This is perhaps not surprising, as abnormalities in cocaine users do not cluster in the vicinity of the “limbic” SN or ventral tegmental area [dorsomedial region of the overinclusive SN mask (21)], which send major projections to the ventral striatum. Rather, topographical analysis showed that group differences were predominant in the ventral (or “cognitive”) SN (21), a subregion with prominent projections to the dorsal striatum thought to be involved in cognitive flexibility and other higher-order functions. Although PET imaging studies of dopamine function in cocaine users have found consistent evidence of dopaminergic changes in the dorsal striatum, the studies described above also found prominent changes in the ventral striatum. Interestingly, in this population, the observation that cocaine users show increased NM-MRI signal in dorsal but not ventral striatal-projecting regions of the SN is consistent with previous observations of significant VMAT2 reduction in the ventral but not dorsal striatum (28, 31). Whatever underlies this anatomical pattern, it highlights that nigrostriatal circuits subserving cognitive function may be important in cocaine use disorder, and future studies may be well positioned to determine the functional significance of NM-MRI signal changes in this disorder by exploring higher-order cognitive processes in addition to reward tasks.

[0579] The main limitation of this study is the relatively small, all-male sample. However, this first report of NM-MRI in substance use disorder supports the promise of such methods for measuring dopamine function in this population. The only previous NM-MRI study investigating substance use was a preliminary assessment of SN area size in a small group of psychiatric patients. Psychiatric patients with substance use showed larger SN area than non-users (39). There are no previous studies investigating NM concentrations in postmortem tissues in substance use disorder, and this would be an important future direction to provide convergent support for the findings. Further studies are needed to address the issue of generalization, especially in light of the findings showing a trend-level relationship between NM-MRI and tobacco use (which may well reach significance in larger samples or more frequent smokers). Assuming that the increased NM signal is due to downregulation of VMAT2 (27, 28), the reported NM-MRI phenotype may be specific to cocaine or other drugs that affect VMAT2 [possibly including methamphetamine, although the relationship to VMAT2 is less clear (1)]. The lack of significant correlation between NM-MRI signal and duration of cocaine use in the data herein is surprising. Given that NM accumulates over time, longer duration of use would be expected to exaggerate any abnormalities seen in cocaine users. However, the lack of significant association may be due to the limited range of duration of use in the samples disclosed herein, as all participants had been using cocaine for many years. NM-MRI signal does not reflect a single biological process, but may be altered by changes in dopamine synthesis (12), dopamine trafficking to vesicles (34) or dopamine cell death (6). Such nonspecificity is common to imaging measurements (40, 41), and the findings herein can be interpreted in light of previous PET imaging reports, providing evidence for the utility of multimodal studies in triangulating neurobiological mechanisms.Although interpretation of NM-MRI results is simplified by the lack of enhanced dopamine cell death in cocaine users ( 37 ), interpretation of NM-MRI results that result in lesions showing substantial cell death combined with altered NM accumulation can be more challenging.

[0580] Here, NM-MRI evidence of abnormal NM accumulation in cocaine users is presented, which is an indirect indicator of dopamine dysfunction consistent with previous studies.The subject matter disclosed herein therefore positions NM-MRI as a promising research tool for addiction and supports its development as a candidate biomarker for stimulant use disorder.Given the central role of dopamine in addiction and the ease of acquiring NM-MRI data, this method has the potential to advance understanding of dopamine changes in addiction, providing an opportunity to particularly young and at-risk populations that are challenging to study using PET, and to describe the longitudinal trajectory of dopamine changes.

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[0582] Example 4 Association of neuromelanin-sensitive MRI signals with psychomotor retardation in geriatric depression summary

[0583] Geriatric depression (LLD) is a common disabling condition in older adults that is often associated with slowed processing and gait speed. These symptoms are associated with impaired dopamine function and are occasionally treated with levodopa (L-dopa). In this study, we recruited 33 older adults with LLD to determine the association between neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a surrogate measure of dopamine function, and baseline slowing measured by the digit symbol test and gait speed paradigm. In a secondary analysis, we also evaluated the ability of NM-MRI to predict L-dopa treatment response in a subset of these patients (N=15) who received 3 weeks of L-dopa. A further subset of these patients (N=6) was scanned with NM-MRI at baseline and after treatment to evaluate the effect of L-dopa treatment on NM-MRI signal. Specifically, lower baseline NM-MRI was found to correlate with slower baseline walking speed in the medial, anterior, and dorsal SN-VTA (346 of 1,807 substantia nigra ventral tegmental area (SN-VTA) voxels, P 補正後 = 0.038). Secondary analyses failed to demonstrate associations between baseline NM-MRI and treatment-related changes in gait speed, processing speed, or depression severity (all P 補正後 >0.361). Evidence of increased NM-MRI signal was found after 3 weeks of treatment with L-dopa compared to baseline (200 of 1,807 SN-VTA voxels, P-corrected = 0.046). Overall, these findings indicate that NM-MRI is sensitive to gait speed variations in patients with LDD, suggesting that this noninvasive MRI measure may provide a promising marker of dopamine-related psychomotor retardation in geriatric neuropsychiatry.

[0584] Introduction

[0585] Geriatric depression (LLD) is a common disabling condition in older adults that is often relapsing, can become chronic, and is often non-responsive to antidepressant medication (1-4). Motivation deficits, slowed processing speed, and gait disturbances are prominent aspects of the LLD phenotype, suggesting that dopaminergic dysfunction may play an important pathophysiological role (5-7). These features are negative prognostic factors for antidepressant treatment (8) and predict a broader range of adverse health outcomes, including death (9, 10). Recent studies suggest that carbidopa / levodopa (L-dopa) monotherapy significantly improves processing speed, gait speed, and depressive symptoms in depressed older adults by increasing dopamine availability in selected striatal subregions (11). However, LLD is a heterogeneous and etiologically complex disorder, suggesting the need for noninvasive, scalable methods to identify individuals with dopamine deficiency and individualize their treatment. As a first step in this direction, here we tested the ability of neuromelanin-sensitive magnetic resonance imaging (NM-MRI) to capture dopamine-related phenotypes of LDD, specifically psychomotor retardation.

[0586] Psychomotor retardation is of great clinical importance for LDD and has been linked to dopamine function. In LDD, reduced processing speed predicts poor acute response to antidepressants (8) and higher risk for dementia (12), while gait slowing is associated with increased risk of falls (13), disability (14), and death (6). Psychomotor retardation in older individuals is thought to be due, at least in part, to age-related declines in dopamine transmission (15-17), consistent with human and preclinical studies linking mesostriatal dopaminergic transmission to gait speed (18, 19). Given this link, the presence of psychomotor retardation may be indicative of an underlying dopaminergic deficit that may be central to the pathophysiology of LDD (7), a deficit that may be ameliorated by prodopaminergic treatments such as L-dopa. Indeed, previous studies have shown that in LLD individuals with slow gait speed, L-dopa monotherapy can improve psychomotor retardation and depressive symptoms by normalizing mesostriatal dopamine transmission. (11) Although these results are promising, we suggest that slow gait speed is an indirect and nonspecific marker of dopamine deficiency and that more direct measures such as NM-MRI may optimize the selection of LDD patients who may benefit most from L-dopa treatment.

[0587] NM-MRI is a non-invasive imaging technique that allows visualization of neuromelanin (NM) concentrations in NM-rich regions (20, 21). NM is a product of dopamine metabolism that accumulates in dopaminergic neurons of the substantia nigra (SN) (22–25). NM-MRI imaging of the SN has recently been validated as a marker of dopamine function, with NM-MRI signal correlating with positron emission tomography (PET) measurements of dopamine release potential in the striatum, capturing dopamine dysfunction associated with psychiatric illness (20). Thus, NM-MRI is uniquely suited as a potential biomarker for treatment selection in patients with dopamine dysfunction, including at least some LDD patients, and could be widely adopted given its non-invasive nature, cost-effectiveness, and lack of ionizing radiation.

[0588] The aim of this study was to determine the suitability of NM-MRI as a potential biomarker for psychomotor retardation and to begin to test and monitor its ability to predict L-dopa treatment response in LLD. Without being bound by theory, it is believed that individuals with slower processing and slower gait exhibit lower dopamine function as measured by NM-MRI. Additionally, secondary analyses in smaller samples examined the ability of NM-MRI to predict improvement in psychomotor retardation following L-dopa treatment. Analyses in a further subset of patients also examined the sensitivity of NM-MRI to capture longitudinal changes in dopamine function associated with L-dopa treatment.

[0589] Methods and Materials

[0590] subject

[0591] The described study was conducted at the Adult and Late Life Depression Research Clinic at the New York State Psychiatric Institute (NYSPI) and was approved by the NYSPI Institutional Review Board. The research program on LLD encompasses numerous therapeutic and pathophysiological studies. To increase sample size, data were pooled from two studies with similar inclusion criteria and utilizing the same NM-MRI sequences. The first study (N=18; Study 1) was an antidepressant treatment study, from which only baseline data were used. The second study (N=15; Study 2) was an open-label L-dopa study, from which baseline and post-treatment data were used (pre- and post-treatment L-dopa dataset). Of these 15 individuals, follow-up NM-MRI data after taking L-dopa were collected for 6 individuals. For further illustration of the samples included in this analysis, see Figure 5. All subjects (N=33; Study 1+Study 2) were adult outpatients aged ≥60 years with a diagnosis of Diagnostic and Statistical Manual 5 major depressive disorder, dysthymia, or depression not otherwise specified and with a minimal depressive symptom score on a standardized scale (Hamilton Depression Rating Scale [HRSD] ≥16 or Center for Epidemiological Studies Depression Rating Scale ≥10). All subjects who exhibited substance abuse or dependence, were diagnosed with psychotic disorder, bipolar disorder, or possible dementia, and had a Mini-Mental State Examination score ≤24, HRSD suicide item >2, or Clinical Subject Global Impression-Severity score of 7 at baseline were excluded. Subjects with acute or severe medical illness, osteoarthritis or joint disease limiting movement, contraindications to MRI, or who had been treated within the past 4 weeks with psychotropic medications or other medications known to affect dopamine were also excluded.

[0592] evaluation

[0593] Processing speed was assessed using the Digit Symbol Test from the Wechsler Adult Intelligence Scale-III (26). Walking speed was measured in m / s as a single task in which study participants walked a 15-foot walking course at their usual or normal speed. Two trials were completed, and the final walking speed measurement was recorded as the average of these two trials. Depression severity was assessed using the 24-item HRSD.

[0594] Study 1 Design

[0595] Assessments and MRI data were obtained at baseline prior to initiating antidepressant treatment (N=18). Further details can be found at clinicaltrials.gov / ct2 / show / NCT01931202.

[0596] Study 2 Design

[0597] Inclusion in this study also required a decrease in gait speed (defined as average walking speed <1 m / sec over a 15-foot course). Assessment and MRI data were obtained at baseline before beginning L-dopa treatment (N=15). After their MRI scans, subjects began taking 37.5 mg carbidopa / 150 mg levodopa once daily (9 am). After one week on this dosage, subjects were instructed to take 37.5 mg carbidopa / 150 mg levodopa twice daily (9 am and 5 pm). For the third week of treatment, subjects took 37.5 mg carbidopa / 150 mg levodopa three times daily (9 am, noon, and 5 pm). Participants were instructed to maintain the same dose timing throughout the study. A subset of these participants (N=6) underwent post-treatment MRI scans at the 3-week visit where post-treatment assessments were performed. Please refer to the previously published primary outcomes manuscript for a full description of study procedures (11). Further details can be found at clinicaltrials.gov / ct2 / show / NCT02744391. Processing and walking speed were assessed at baseline and then weekly during L-dopa treatment (i.e., weeks 0–3). Assessments were performed at approximately 1:00 PM to control for time-of-day effects and time since the last morning L-dopa dose (expected to be 4 h). HRSD was also performed at weeks 0 and 3. Changes in processing speed, walking speed, and HRSD were taken as the difference between weeks 3 and 0.

[0598] Magnetic resonance imaging

[0599] Brain magnetic resonance images were acquired for all participants on a GE MR750 3.0T scanner using a 32-channel phased array Nova head coil. NM-MRI data were acquired using a 2D gradient-reduced-echo sequence with magnetization transfer contrast (2D GRE-MT) with the following parameters (20): repetition time (TR) = 260 ms; echo time (TE) = 2.68 ms; flip angle = 40°; in-plane resolution = 0.39 × 0.39 mm2; partial brain area of ​​interest including field of view (FoV) = 162 × 200; matrix = 416 × 512; number of slices = 10; slice thickness = 3 mm; slice gap = 0 mm; magnetization transfer frequency offset = 1,200 Hz; number of excitations (NEX) = 8; acquisition time = 8.04 min. The slice prescription protocol consisted of orienting the image stack along the anterior-posterior commissure line, with the top slice positioned 3 mm below the floor of the third ventricle, viewed in the sagittal plane at the mid-brain. This protocol covered the SN-containing portion of the midbrain (as well as cortical and subcortical structures surrounding the brainstem) with high in-plane spatial resolution using short scans that are more likely to be tolerated by clinical populations. For preprocessing of NM-MRI data, high-resolution T1-weighted 3D BRAVO structural MRI scans of the whole brain were acquired with the following parameters: inversion time = 450 ms, TR = 7.85 ms, TE = 3.10 ms, flip angle = 12°, FoV = 240 × 240, matrix = 300 × 300, number of slices = 220, isotropic voxel size = 0.8 mm3.

[0600] NM-MRI data were preprocessed using a pipeline combining SPM and ANT, which was previously shown to achieve high test-retest reliability (27). The pipeline consisted of the following steps: (1) brain extraction of T1w images using “antsBrainExtraction.sh”; (2) spatial normalization of brain-extracted T1w images to MNI space using “antsRegistrationSyN.sh” (rigid+affine+deformable syn); (3) co-registration of NM-MRI images to T1w images using “antsRegistrationSyN.sh” (rigid); (4) spatial normalization of NM-MRI images to MNI space by a single-step transformation combining the transformations estimated in steps (2) and (3) using “antsApplyTransforms”; (5) resampling of spatially normalized NM-MRI images to an isotropic resolution of 1 mm using “ResampleImage”; (6) spatial smoothing of spatially normalized NM-MRI images with a Gaussian kernel of 1 mm full width at half maximum using “SPM-Smooth”. The preprocessed NM-MRI images were then used to estimate NM-MRI contrast ratio (CNR) maps. The NM-MRI CNR at each voxel was calculated as CNR V ={[I v -Mode(I cc )] / mode(I CC )} × 100, was calculated as the percentage signal difference of the NM-MRI signal intensity at a given voxel (IV) from the signal intensity of the cerebral peduncle (ICC), a region of white matter tracts known to have the lowest NM content. The mode (ICC) was calculated for each participant from a kernel smoothing function fit of the histogram of all voxels in the CC mask (20).

[0601] statistical analysis

[0602] In an a priori analysis, we tested the hypothesis that a lower baseline NM-MRI CNR would correlate with slower psychomotor variables (digit symbols and walking speed; N = 33; Study 1 + Study 2). In a secondary analysis, we examined whether baseline NM-MRI CNR would predict L-dopa-induced improvements in these psychomotor variables (speed) (N = 15; Study 2). These effects were tested within the substantia nigra-ventral tegmental area (SN-VTA) complex using a voxel-wise analysis approach validated in Cassidy et al. (20). Briefly, the method uses robust linear regression analysis with permutation tests and tests of significance of regression coefficients. The linear model used to test the a priori hypothesis (Model 1) was the CNR V =β 0 +β 1 Walking speed +β 2 ·Number symbol score +β 3 ·HRSD+β 4 Age + β 5 ·Gender+β 6 Education and β 1~3 is the variable of interest, and β 4~6 is an unintended covariate. The linear model for the secondary analysis (Model 2) was V =β 0 +β 1 ΔWalking speed +β 2 ·Δ Number symbol score + β 3 ΔHRSD+β 4 Walking speed +β 5 ·Number symbol score +β 6 ·HRSD+β 7 Age + β 8 ·Gender+β 9 Education and β 1~3 is the variable of interest, and β 4~9are uninteresting covariates. Including all variables of interest in one model provides greater specificity of effects while also providing a more conservative test that protects against false positives by adjusting the degrees of freedom of the t-tests of regression coefficients (28). The number of voxels showing significant effects was determined to be significant by a permutation test in which 10,000 iterations of random permutations of the variables of interest were performed while holding uninteresting covariates constant. For further details, see Cassidy et al. (20). This voxel-wise permutation test corrects for multiple comparisons between voxels and provides adequate protection against false positives, similar to the method used in functional MRI studies (29).

[0603] In an exploratory analysis, we also investigated whether we could detect changes in NM-MRI CNR after 3 weeks of L-dopa treatment (N=6, subset of study 2). A similar voxel-wise analysis approach was used, except that a nonparametric signed-rank test was used to compare NM-MRI CNR values ​​before and after L-dopa treatment. The number of voxels showing significant effects was determined to be significant by a permutation test in which a null distribution was induced by repeating the random assignment of labels before and after L-dopa treatment for each subject 10,000 times (i.e., a 50% chance of a subject's pre-L-dopa NM-MRI CNR value was assigned as their post-L-dopa value, and their post-L-dopa value was assigned as their pre-L-dopa value).

[0604] An a priori power analysis (19) using effect sizes comparing baseline gait speed with PET measures of dopamine function demonstrated 85% power to detect an effect in the baseline sample of 33 subjects (two-sided, □ = 0.05), but only 50% power in the L-dopa sample of 15 subjects. Thus, the analysis in the former sample (Model 1) was adequately powered as an a priori study. Given the exploratory nature of the latter, which is presented for completeness and illustration purposes, no additional corrections were made across the a priori and second-order studies.

[0605] To exclude potential selection bias in the follow-up NM-MRI subset from Study 2, demographic and clinical characteristics were compared between participants in Study 2 who underwent a follow-up NM-MRI scan 3 weeks after L-dopa treatment (N = 6) and those who did not undergo a follow-up NM-MRI scan after treatment (N = 9) using Pearson's chi-square test or Mann-Whitney U test.

[0606] result

[0607] Sample characteristics

[0608] Clinical and demographic characteristics of the sample are shown in Figure 5. For all 33 subjects, the mean age was 71.8±6.5 years, 63.6% were female, the mean education was 16.8±2.5 years, the mean walking speed was 0.97±0.32 m / sec, the mean digit symbol score was 36.8±10.7, and the mean HRSD was 20.7±6.6. No significant differences were observed between subjects in Study 2 who had a follow-up NM-MRI scan and those who did not have a follow-up NM-MRI scan.

[0609] Baseline walking speed is related to baseline NM-MRI

[0610] Without being bound by theory, we investigated the a priori hypothesis that slower processing and slower walking individuals would show lower dopamine function as measured by NM-MRI in 33 patients with LLD (Study 1 + Study 2). A voxel-wise linear regression model (Model 1) predicted NM-MRI CNR within the SN-VTA mask as a function of walking speed, digit symbol score and HRSD, with age, sex and education as covariates. This revealed a set of SN-VTA voxels whose NM-MRI CNR was positively correlated with walking speed (at P < 0.05, 346 of 1,807 SN-VTA voxels; robust linear regression, P 補正後= 0.038, permutation test; Figure 7 ). In contrast, digit symbol scores (194 of 1,807 SN-VTA voxels with P < 0.05, P 補正後 = 0.121, permutation test) or HRSD ( P < 0.05 in 19 of 1,807 SN-VTA voxels; P 補正後 = 0.731, permutation test). Topographic analysis of the relationship between walking speed and NM-MRI CNR revealed no significant effect for the more medial (β |x| = 0.02, t 1803 =2.40, P=0.016), anterior (β y = 0.14, t 1803 =25.8, P=10 -124 ) and dorsal (β = −0.05, t 1803 =-6.62, P=10 -10 ) Multiple regression analysis predicting the t-statistics of walking speed effects across SN-VTA voxels [SN-VTA voxels as a function of their coordinates in the x (absolute distance from the midline), y, and z directions: Omnibus F 3,1803 =297, P=10 -155 ] showed that stronger relationships tended to occur.

[0611] Secondary analyses fail to demonstrate an association between baseline NM-MRI and changes in psychomotor speed with L-dopa treatment

[0612] In a secondary analysis, we examined the relationship between baseline NM-MRI signal and change in psychomotor speed after 3 weeks of L-DOPA treatment in 15 patients with both baseline and post-treatment psychomotor assessments (Study 2). As a more rigorous, spatially constrained test of this relationship, we first determined whether there was a relationship between change in gait speed after 3 weeks of L-DOPA treatment and the mean NM-MRI CNR of 346 SN-VTA voxels (green voxels in Figure 1) that positively correlated with baseline gait speed. Here, no relationship was found between baseline NM-MRI CNR and change in gait speed (t 1,9= 0.71, P = 0.49; robust linear regression testing for the effect of change in walking speed controlling for baseline walking speed, age, sex, and education; Figure 7). As a more permissive test of the hypothesis, a voxel-wise analysis was performed, in this case examining the relationship between change in walking speed and digit symbol score after L-dopa treatment with baseline NM-MRI CNR within the SN-VTA at each voxel for each subject (Model 2). Again, no relationship was found between baseline NM-MRI CNR and change in gait speed (64 of 1,807 SN-VTA voxels with P<0.05; robust linear regression testing for the effects of change in gait speed, change in digit symbol score, and change in HRSD adjusted for baseline gait speed, baseline digit symbol score, baseline HRSD, age, sex, and education, P-adjusted=0.377, permutation test), change in digit symbol score (69 of 1,807 SN-VTA voxels with P<0.05, P-adjusted=0.361, permutation test), or change in HRSD (67 of 1,807 SN-VTA voxels with P<0.05, P-adjusted=0.371, permutation test).

[0613] Increase in NM-MRI CNR of the SN-VTA by L-dopa treatment

[0614] In an exploratory analysis, we also investigated whether the NM-MRI signal changed after 3 weeks of L-dopa treatment in six patients with available baseline and post-treatment MRI data (Study 2 subset). To this end, we performed a nonparametric voxel-wise analysis, in which we examined for each subject the difference between the NM-MRI CNR at baseline and post-treatment within the SN-VTA mask at each voxel. This revealed a set of SN-VTA voxels in which the NM-MRI CNR was significantly higher in the post-treatment scan (200 of 1,807 SN-VTA voxels at P < 0.05, signed-rank test testing for differences between baseline and post-treatment NM-MRI CNR; P 補正後 = 0.046, permutation test; Figure 8).

[0615] Discussion

[0616] As diagnostic biomarkers for PD symptoms: determining movement disorder symptoms and predicting the severity of current symptoms

[0617] Voxel-based analysis of NM-MRI includes voxels used to determine neuromelanin concentration, voxels used to determine neuromelanin volume, and certain voxels associated with specific symptoms (called symptom-specific voxels, in this case voxels of movement disorder symptoms, e.g., voxels of psychomotor retardation). Psychomotor retardation symptoms have been shown to occur in Parkinson's disease, and voxel-based analysis methods can also serve as diagnostic biomarkers and determine the severity of certain symptoms.

[0618] In Parkinson's disease (PD), gait speed is notably slower (Peterson et al., 2020). We first examined the relationship between NM-MRI data and psychomotor speed in older adults with geriatric depression (LLD) and found that lower NM-MRI signal in the medial, anterior and dorsal parts of the SN-VTA complex was associated with slower gait speed, as determined by voxel-based analysis methods. This provides evidence that both the presence and severity of key motor symptoms of PD (in this example, psychomotor retardation) can be predicted by voxel-based analysis of neuromelanin MRI data, presenting a non-invasive method to determine important information that can guide care for these conditions.

[0619] The finding of lower dopamine function associated with slower gait speed, indexed by lower NM-MRI signal, is consistent with a priori hypotheses based on previous literature. For example, recent studies have identified a relationship between genetic polymorphisms in catechol-O-methyltransferase (COMT, rs4680; regulating tonic dopamine) and gait speed (30, 31). Furthermore, in elderly patients with cerebral small vessel disease, gait decline is due to reduced nigrostriatal dopamine. More generally, a strong rationale has been proposed to implicate dopamine function in the dorsal basal ganglia in age-related motor dysfunction, supporting the need for dopaminergic biomarkers in this region.

[0620] The data show that baseline NM-MRI data can predict psychomotor speed symptoms. Because neuromelanin is reduced in PD and gait slowing is a prominent feature, this analysis method can predict specific symptoms of PD in specific voxels. Prediction of different symptoms on NM-MRI can provide a non-invasive method to determine the diagnosis of Parkinson's disease and distinguish it from related disorders with different motor symptoms.

[0621] The finding that dopamine function indexed by NM-MRI signal is associated with a trend toward non-significance with digit symbol scores is limited by the small sample size (N=33), which limits the ability to determine a significant association between digit symbol scores and dopamine function, and requires studies with larger samples to address this. Although dopamine is theoretically linked to processing speed, empirical evidence correlating neuroimaging-based measures of dopamine signaling with performance on processing speed tasks is mixed. The largest study to date (N=181 healthy adults) showed no significant correlation between striatal raclopride PET D2 receptor binding and processing speed, while smaller studies observed small but significant associations between processing speed and dopamine function. Applicants are not aware of any studies that have demonstrated a significant correlation between dopamine signaling and digit symbol scores. Thus, the motor requirements and speed dependence of the digit symbol test theoretically suggest a link to dopamine function, but may be more complexly involved. Furthermore, although motor speed and attention are impaired in both aging and depressed populations, these deficits are often subtle and not detected by digit symbol testing, and the mechanism of their impairment in these clinical populations may not be dopaminergic.

[0622] As a diagnostic biomarker for the diagnosis of PD and for the exclusion of related disorders

[0623] This data supports the ability of voxel-based analysis methods to distinguish between LLD and Parkinson's disease based on NM-MRI. For example, the results of topographic analysis of the relationship between gait speed and NM-MRI signal showed that stronger relationships occurred in the medial, anterior, and dorsal regions of the SN-VTA. In contrast, NM-MRI data show that the greater signal reduction in PD tends to predominate in more lateral, posterior, and ventral voxels. Furthermore, histopathological studies have also found that PD-related neuronal loss occurs primarily in the ventrolateral layer of the SN, and recent free water imaging studies have identified a similar spatial pattern. A recent study used NM-MRI to analyze the signal intensity of the SN in two motor subtypes of PD, with patients classified as either unstable posture, predominantly gait-prone, or predominantly tremor-prone, along with controls. Significant signal attenuation was detected in the lateral parts of the SN in both PD subtypes when compared to controls, and severe signal attenuation was also observed in the medial parts of the SN in unstable posture gait-prone patients compared to the tremor-predominant group (52). Taken together, the topological findings, coupled with the fact that slow-moving, depressed subjects do not typically exhibit clinical features of PD (e.g., cogwheel movement, rigidity, tremor, etc.), support the fact that samples of LLD patients are unlikely to represent samples of asymptomatic PD patients, and support the ability of the voxel-based analysis methods described here to distinguish movement disorders with similar symptoms.

[0624] Voxel-based analysis methods can distinguish between PD and related motor disorders. In our study, voxel-based analysis methods were able to determine important differences between subregions of the SNc affected by geriatric depression (LLD) and regions known to be affected in PD. Although both LLD and PD show psychomotor retardation, voxel-based analysis methods were able to determine that the subregions of the SNc affected by LLD are different from those known to be affected by PD pathology. Voxel-based analysis methods can determine that patients with LLD do not exhibit PD. This provides strong evidence that voxel-based analysis methods can distinguish between different motor disorders that have been shown to have overlapping symptoms. This can be applied to guide the diagnosis of PD and help exclude related disorders with similar symptoms.

[0625] Voxel-based analysis of voxels associated with baseline NM-MRI symptoms may predict future response to treatment and provide important prognostic biomarkers for PD.

[0626] In a secondary analysis of a smaller sample of L-dopa-treated subjects, a non-significant trend toward a positive association between baseline NM-MRI and change in psychomotor speed after treatment was observed. Our data did not reach significance, but it was severely underpowered and we expect that in a larger study it would reach significance.

[0627] This analysis suggests that individual baseline NM-MRI voxels, as determined by voxel-based analysis, may be associated with a movement disorder symptom and predict future response to treatment of that symptom before treatment is initiated. This provides important prognostic information that can predict the course of the disease and guide the selection of appropriate treatments. Because psychomotor retardation is a hallmark symptom of Parkinson's disease and L-dopa treatment is one of the most effective and widely used PD therapies, this finding directly supports the application of voxel-based analysis methods to predict response to treatment of motor symptoms of Parkinson's disease, including psychomotor retardation.

[0628] To monitor response to treatment

[0629] Furthermore, we observed that 3 weeks of L-dopa treatment, one of the most widely used PD treatments, was associated with a significant increase in NM-MRI signal. This is the first evidence to date that administration of L-dopa therapy induces changes in the substantia nigra that can be measured via voxel-based analysis of NM-MRI. This was supported by previous studies showing that NM-MRI captures NM concentrations in ex vivo tissue samples and correlates with increased dopamine transmission, consistent with the finding that enhanced dopamine synthesis leads to increased NM accumulation.

[0630] This supports the ability of the voxel-based analysis method to track changes in NM-MRI data over the course of treatment. This provides a non-invasive method to track response to treatment and determine if the patient has had an adequate or inadequate response to treatment. This information can be used to guide treatment and determine whether to increase or decrease the dosage of treatment. In this case, in a patient with Parkinson's disease, the Parkinson's voxels should respond to treatment with L-dopa. For example, administering L-dopa to a patient with established Parkinson's voxels will: Patient's baseline Parkinson's voxel readings Readings from untreated patients with similar Parkinson's voxels · and should induce changes in Parkinson's voxels relative to normal controls.

[0631] Changes in Parkinson's voxels can indicate whether a patient is being treated appropriately. The method can also be applied to therapeutic agents other than L-dopa.

[0632] Voxel-based analysis methods are used to detect differences between patients that can be used to predict different responses to treatment specific to each patient.

[0633] In exploratory analyses, we observed a significant increase in NM-MRI signal after L-dopa treatment, supporting the view that L-dopa treatment likely increases available striatal dopamine, but that participants respond differently to that increase. This is important because it shows that voxel-based analysis methods are capable of detecting differences in response to treatment specific to each patient. This age-related process occurs very slowly and should only be detected over timescales significantly longer than the 3-week period evaluated here, making it unlikely that the observed changes are due to natural NM accumulation over time. Furthermore, although the sample size is limited (N=6), the excellent reproducibility of NM-MRI suggests that any observed increases in NM-MRI signal are indeed due to increases in NM concentration. This result presents further evidence in support of NM-MRI measuring dopamine function, including synthesis induced by L-dopa. This result also suggests that NM-MRI can be surprisingly sensitive to changes in NM over shorter timescales than previously thought. This finding suggests that NM-MRI may be well suited for monitoring dopaminergic treatment responses in patients with PD or related disorders.

[0634] In conclusion, in patients with LLD, we found an association between NM-MRI signal in the SN-VTA and baseline walking speed, as well as a trend-level effect with changes in walking speed or processing speed after 3 weeks of L-dopa treatment.

[0635] Reference to Example 4

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[0695] Computer-based analysis

[0696] Exemplary procedures according to the disclosure described herein may be performed by a cloud-based processing device and / or computing device (e.g., computer hardware device). Such processing / computing device may be, for example, all or part of, or may include, a computer / processor, which may include, for example, but is not limited to, one or more microprocessors, and may use instructions stored on a computer-accessible medium (e.g., RAM, ROM, hard drive or other storage device).

[0697] For example, a computer-accessible medium (e.g., a storage device such as an encrypted cloud file, a hard disk, a floppy disk, a memory stick, a CD-ROM, RAM, ROM, or a collection thereof, as described herein above) may be provided (e.g., in communication with a processing device). The computer-accessible medium may include instructions executable thereon. Additionally or alternatively, a storage device may be provided separate from the computer-accessible medium, which may provide instructions to the processing device to configure the processing device to perform certain exemplary procedures, processes, and methods, as described herein above.

[0698] Additionally, the exemplary processing device may provide or include input / output ports that may include, for example, wired networks, wireless networks, the Internet, an intranet, data collection probes, sensors, etc. The exemplary processing device may communicate with an exemplary display device, which may be, for example, a touch screen configured to input information into the processing device in addition to outputting information from the processing device, according to certain exemplary embodiments of the present disclosure. Additionally, the exemplary display device and / or storage device may be used to display and / or store data in a user accessible and / or user readable format.

[0699] Equivalent The above merely illustrates the principles of the disclosure. Various modifications and alterations to the described embodiments will be apparent to those skilled in the art in light of the teachings herein. Thus, it will be appreciated that those skilled in the art can devise various systems, devices and procedures not expressly shown or described herein, but which embody the principles of the disclosure and thus fall within the spirit and scope of the disclosure. Various different exemplary embodiments can be used together with each other and interchangeably therewith, as should be understood by those skilled in the art. Furthermore, certain terms used in this disclosure, including this specification, its drawings and claims, can be used synonymously in certain instances, including, but not limited to, for example, data and information. These terms and / or other terms that can be synonymous with each other can be used synonymously herein, although it should be understood that there may be cases where such terms are not intended to be used synonymously. Furthermore, to the extent that prior art knowledge has not been expressly incorporated by reference above in this specification, it is expressly incorporated herein in its entirety. All publications referenced are incorporated herein by reference in their entirety.

[0700] Where a range of values ​​is presented, it is understood that each intervening value, to the tenth of the unit of the lower limit (unless the context clearly dictates otherwise), between the upper and lower limits of that range, and any other stated or intervening value in that stated range, is encompassed within the scope of the disclosure. The upper and lower limits of these smaller ranges may be independently included in the smaller ranges and are also encompassed within the scope of the disclosure, subject to any specifically excluded limit in the stated range. Where a stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure. In certain embodiments, for example, the following are provided: (Item 1) 1. An in vivo method for determining the progression of Parkinson's disease in a subject over time, comprising: (i) obtaining a first neuromelanin-magnetic resonance imaging (NM-MRI) scan at a first time point; (ii) after step (i), obtaining a second NM-MRI scan at a second time point; (iii) comparing the first neuromelanin magnetic resonance image with the second neuromelanin magnetic resonance image, thereby determining whether a change in neuromelanin level, signal and / or concentration has occurred between the first and second time points. The method includes: (Item 2) 2. The method of claim 1, wherein Parkinson's disease is progressing if the change in neuromelanin level, signal and / or concentration at the second time point is more than about 1%, more than about 2%, more than about 3%, more than about 4%, more than about 5%, more than about 6%, more than about 7%, more than about 8%, more than about 9%, more than about 10%, more than about 11%, more than about 12%, more than about 13%, more than about 14%, more than about 15%, more than about 20% or more than about 25% lower than the neuromelanin level, signal and / or concentration at the first time point. (Item 3) 1. An in vivo method for diagnosing Parkinson's disease comprising: (i) obtaining a first neuromelanin magnetic resonance image at a first time point; (ii) after step (i), obtaining a second neuromelanin magnetic resonance image at a second time point; (iii) comparing the first neuromelanin magnetic resonance image to the second neuromelanin magnetic resonance image, thereby determining whether a change in neuromelanin level, signal and / or concentration has occurred between the first and second time points. (Item 4) The method of any of the preceding items, wherein a diagnosis of Parkinson's disease is presented if the change in neuromelanin level, signal and / or concentration at the second time point is more than about 1%, more than about 2%, more than about 3%, more than about 4%, more than about 5%, more than about 6%, more than about 7%, more than about 8%, more than about 9%, more than about 10%, more than about 11%, more than about 12%, more than about 13%, more than about 14%, more than about 15%, more than about 20% or more than about 25% lower than the neuromelanin level, signal and / or concentration at the first time point. (Item 5) 1. A method for diagnosing a patient with Parkinson's disease, comprising: (i) measuring the level of neuromelanin; (ii) comparing said level of neuromelanin with a standard control; (iii) optionally proposing a diagnosis of Parkinson's disease if the measured level of neuromelanin is lower compared to the standard control. The method includes: (Item 6) The method of any of the preceding items, further comprising determining a first signal intensity from the first neuromelanin magnetic resonance image and determining a second signal intensity from the second neuromelanin magnetic resonance image, wherein the comparing the first magnetic resonance image and the second magnetic resonance image comprises comparing the first signal intensity and the second signal intensity. (Item 7) The method of any of the preceding items, wherein the standard control is a level of neuromelanin present at approximately the same level in a population of subjects, or wherein the standard control is approximately the average level of neuromelanin present in a population of subjects. (Item 8) The method of any of the preceding items, wherein a neuromelanin gradient phantom is used to measure neuromelanin levels, signals and / or concentrations. (Item 9) The method of any of the preceding items, wherein the neuromelanin phantom concentration gradient is scanned about once per patient, about once per hour, about once per day, about once per week, or about once per month. (Item 10) The method of any of the preceding items, wherein the neuromelanin phantom gradient is scanned daily. (Item 11) The method of any of the preceding items, wherein a neuromelanin phantom gradient is scanned for each patient. (Item 12) A diagnosis of Parkinson's disease is presented if the change in neuromelanin level, signal and / or concentration at the second time point is more than about 5% lower or more than about 10% lower than the neuromelanin level, signal and / or concentration at the first time point, and the first time point and the second time point are separated by about 1 year, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years or about 10 years. 11. The method according to claim 11. (Item 13) The method of any of the preceding items, wherein a diagnosis of Parkinson's disease is presented if the change in neuromelanin level, signal and / or concentration at the second time point is more than about 35% lower, more than about 40% lower, more than about 45% lower, or more than about 50% lower than neuromelanin signal and / or concentration at the first time point, and the first and second time points are about 1 year, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years, or about 10 years apart. (Item 14) The method of any of the preceding items, wherein the second time point is about 3 months, about 6 months, about 9 months, about 12 months, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years, about 10 years, about 15 years, about 20 years, about 25 years or about 30 years after the first time point. (Item 15) 1. A method for assessing neuromelanin concentration in a brain region of interest in a subject, comprising: performing a neuromelanin-magnetic resonance imaging (NM-MRI) scan on the subject; obtaining a neuromelanin data set from the NM-MRI scan; Optionally encrypting said neuromelanin data set; uploading the neuromelanin dataset to a remote server; optionally decrypting said data set; conducting an analysis of the neuromelanin dataset, the analysis comprising: (i) comparing said neuromelanin dataset to one or more neuromelanin datasets previously obtained from said subject; (ii) comparing said neuromelanin dataset with a control dataset; (iii) comparing said neuromelanin dataset to one or more previously obtained neuromelanin datasets from different subjects;

[0036] generating a report including said neuromelanin analysis; Optionally, encrypting said report; uploading the report to a remote server; and Optionally, decrypting said report. The method includes: (Item 16) 1. A method of determining whether a subject has or is at risk for developing Parkinson's disease, comprising analyzing one or more Neuromelanin-Magnetic Resonance Imaging (NM-MRI) scans of a region of interest in the subject's brain, said analyzing comprising: receiving imaging information of the brain region of interest; and determining NM concentration in the brain region of interest using voxel-wise analysis based on the imaging information; Including, Determining whether a subject has or is at risk for developing Parkinson's disease includes: (1) that the subject is at risk for or at risk of developing Parkinson's disease if the NM signal of one or more NM-MRI scans is reduced compared to one or more control scans without Parkinson's disease; or (2) if one or more NM-MRI scans have an NM signal equivalent to the signal of one or more control scans without Parkinson's disease, the subject is not at risk for or is not at risk for developing Parkinson's disease; A method comprising: (Item 17) 1. A method of treating a subject having Parkinson's disease comprising analyzing a neuromelanin-magnetic resonance imaging (NM-MRI) scan of a region of interest in the subject's brain, said analyzing comprising: (i) receiving imaging information of the brain region of interest at a first point in time; (ii) receiving imaging information of the brain region of interest at a second time point; (iii) determining NM concentrations at the first and second time points in the brain region of interest using voxel-wise analysis based on the imaging information; and (iv) comparing the NM concentrations at the first and second time points. Including, The method of treating comprises: (1) if the NM-MRI scan at the second time point indicates a decrease in NM signal compared to the NM signal at the first time point, the method includes administering one or more of levodopa and carbidopa; or (2) if the NM-MRI scan at the second time point shows an increase in NM signal compared to the NM signal at the first time point, the method further comprises: (a) withholding administration of one or more of levodopa and carbidopa; and (b) Repeating steps (i) to (iv) The method further comprising: (Item 18) The method of any of the preceding items, wherein the MRI scan is sensitive to neuromelanin. (Item 19) 1. A method for providing a treatment regimen to a patient, comprising the steps of performing an NM-MRI scan, acquiring an NM signal from the NM-MRI scan in a region of interest, comparing the NM signal from the NM-MRI scan in the region of interest data with age-matched database numbers, and administering a corresponding treatment regimen if the NM signal is below a predetermined value. (Item 20) The method of any of the preceding items, wherein the patient exhibits symptoms of Alzheimer's disease. (Item 21) The method of any of the preceding items, wherein the NM-MRI scan distinguishes between Alzheimer's disease and Parkinson's disease. (Item 22) The method of any of the preceding items, wherein the subject or patient exhibits one or more symptoms of Parkinson's disease. (Item 23) The method of any of the preceding items, wherein the patient is diagnosed with Parkinson's disease without exhibiting symptoms. (Item 24) The method of any of the preceding items, wherein the NM-MRI distinguishes between Alzheimer's disease and Parkinson's disease. (Item 25) The method of any of the preceding items, further comprising diagnosing the patient as having Parkinson's disease or not having Parkinson's disease, and displaying the diagnosis to a user via a user interface. (Item 26) 13. The method of any of the preceding items, wherein the analysis is a voxel-wise analysis. (Item 27) 11. The method of any of the preceding items, wherein the voxel-wise analysis includes determining at least one topographical pattern within the brain region of interest. (Item 28) 11. The method of any of the preceding items, further comprising calculation using a value representing the volume of neuromelanin voxels. (Item 29) 13. The method of any of the preceding items, wherein the region of interest for the voxel-wise analysis is the substantia nigra. (Item 30) 13. The method of any of the preceding items, wherein the region of interest for the voxel-wise analysis is a subregion of the ventral substantia nigra. (Item 31) 1. A diagnostic system for providing diagnostic information regarding Parkinson's disease, comprising: an MRI system configured to generate and acquire a neuromelanin sensitive MRI scan with a set of neuromelanin data for voxels located within a region of interest in the subject's brain; a signal processor configured to process the set of neuromelanin data to generate a processed neuromelanin MRI spectrum; and The processed neuromelanin MRI spectrum is processed to obtain extracting measurements from said region of interest corresponding to neuromelanin at a point in time; comparing said measurements to one or more control measurements taken prior to said time points; a diagnostic processor configured to provide a diagnosis of Parkinson's disease if the measurement is more than about 25% less than the control measurement. 2. A diagnostic system comprising: (Item 32) a) administering to the patient an initial dose of L-dopa; b) performing serial NM-MRI scans of said patient to monitor neuromelanin concentration in regions of interest in said patient's brain and to assess treatment-related adverse events over the initial treatment period; c) during said initial treatment period, said patient: i) reducing the neuromelanin concentration in said region of interest in said patient's brain; ii) Absence of L-dopa-related adverse or side effects. When indicating increasing the dose of L-dopa during subsequent treatment periods 1. A method of treating a patient with Parkinson's disease comprising: The method, wherein said L-dopa treatment results in an improvement in the symptoms of Parkinson's disease in said patient. (Item 33) d) repeating steps a) to c) until the patient no longer exhibits one or more of i) to ii) in step c); Item 33. The method according to item 32. (Item 34) The method of any of the preceding items, used in conjunction with a second imaging method selected from the group consisting of positron emission tomography (PET), structural MRI, functional MRI (fMRI), blood oxygen level dependent (BOLD) fMRI, iron sensitive MRI, quantitative susceptibility mapping (QSM), diffusion tensor imaging DTI, and single photon emission computed tomography (SPECT), DaTscan, and DaTquant. (Item 35) The method of any of the preceding items, wherein the second imaging method comprises Positron Emission Tomography (PET). (Item 36) 11. The method of any of the preceding items, wherein the second imaging method comprises structural MRI. (Item 37) The method of any of the preceding items, wherein the second imaging method comprises functional MRI (fMRI). (Item 38) The method of any of the preceding items, wherein the second imaging method comprises blood oxygen level dependent (BOLD) fMRI. (Item 39) 2. The method of any of the preceding items, wherein the voxel-wise analysis comprises determining at least one topographical pattern within the brain region of interest, the brain region of interest being voxels associated with one or more Parkinson's disease symptoms. (Item 40) 2. The method of any of the preceding items, wherein the voxel-wise analysis comprises determining at least one topographical pattern within the brain region of interest, the brain region of interest being voxels associated with one or more patient-specific Parkinson's disease symptoms. (Item 41) 13. The method of any of the preceding items, wherein the brain region of interest is the substantia nigra or the locus coeruleus. (Item 42) 42. The method according to items 1 to 41, wherein the brain region of interest is the ventral substantia nigra. (Item 43) 42. The method according to items 1 to 41, wherein the brain region of interest is the substantia nigra lateralis. (Item 44) 42. The method according to items 1 to 41, wherein the brain region of interest is the ventrolateral substantia nigra. (Item 45) 42. The method according to items 1 to 41, wherein the brain region of interest is the substantia nigra pars compacta (SNpc). (Item 46) 42. The method according to items 1 to 41, wherein the brain region of interest is the substantia nigra pars reticulata (SNpr). (Item 47) 42. The method according to any one of the preceding claims, wherein the brain region of interest is the ventral tegmental area (VTA). (Item 48) 42. The method according to items 1 to 41, wherein the brain region of interest is the locus coeruleus.

Claims

[Claim 1] The invention described in the specification.

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