System and method using an open NMR device for non-invasive fat composition measurement in organs - Patents.com

Abstract

Systems and methods are provided for determining fat composition of an organ of interest using a non-invasive health measurement system. The non-invasive health measurement system may include an open magnet NMR device. The NMR device may measure NMR signals within a sensitive volume of a patient. The sensitive volume may coincide with an organ of interest, such as the liver. The systems and methods disclosed herein may provide separation of water and fat contributions to a measured NMR signal. Diffusion-based separation, T2-based separation, and T1-based separation may each serve as different methods for separating water and fat contributions to a signal. Separating water and fat contributions into a single may allow calculation of a proton density fat fraction that may reflect the fat composition of the organ of interest.

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of U.S. Provisional Application No. 63 / 159,346, filed March 10, 2021, which is incorporated by reference herein in its entirety.

[0002] The present disclosure relates generally to non-invasive diagnostic systems and methods, and in particular, some implementations may relate to non-invasive diagnostic systems and methods for determining fat and water concentrations and diffusion coefficients of fat and water in internal organs such as the liver. [Background technology]

[0003] Determining the amount of fat in an organ is important for the diagnosis and treatment of disease and other health conditions.In particular, the liver is an organ for which such information is beneficial, since detecting adverse changes in liver fat composition can allow for early diagnosis and treatment of disease leading to better health outcomes.Assessing liver fat content can help diagnose and determine certain health risks, including the progression of diseases such as fatty liver, cirrhosis, cancer, and other health conditions.In addition, even without detection of disease, liver fat composition can indicate overall health and is therefore an important measurement.

[0004] Conventional methods for assessing liver fat content, such as MRI, are expensive, require a lot of space, and can be very uncomfortable for patients. Other methods can provide low accuracy. For these reasons, monitoring liver fat composition is not part of routine preventive medicine, and diagnosis of health conditions related to liver fat content is often not performed until advanced disease progression. Early monitoring of changes in liver fat composition allows for early intervention and treatment, and better outcomes for patients. Accurate measurement of fat content allows for determination of treatment effectiveness over time. Summary of the Invention

[0005] A system and method for a non-invasive health measurement system is disclosed. The non-invasive health measurement system may include an open magnet nuclear magnetic resonance ("NMR") device. The NMR device may acquire an NMR response signal generated by atomic nuclei of a material comprising an organ. The NMR response signal may include a fat contribution signal and a water contribution signal. The system may include a processor and a memory communicatively coupled to the processor. The memory may store instructions that, when executed by the processor, cause the processor to transmit radio frequency ("RF") pulses to the organ by the open magnet NMR device in the presence of a magnetic field gradient. The instructions may further cause the processor to acquire the NMR response signal. The instructions may further cause the processor to separate water and fat contributions to the NMR response signal based on differences in the diffusion coefficients of water and fat to determine the water and fat composition of the organ.

[0006] In embodiments, separating the water and fat signal contributions based on the diffusion coefficients of water and fat may include measuring NMR signal amplitude dependence on diffusion time. Separating the water and fat signal contributions based on the diffusion coefficients of water and fat may also include determining the amplitudes and diffusion coefficients of the fat and water contributions using the measured NMR signal amplitude dependence on diffusion time. In embodiments, determining the water and fat composition of the organ may include calculating a proton density fat fraction ("PDFF") based on the determined amplitudes.

[0007] In an embodiment, the diffusion coefficient of fat may be known. Determining the water and fat composition of the organ may include calculating the PDFF by suppressing the water amplitude using a high b-value to calculate the fat amplitude based on the known diffusion coefficient of fat.

[0008] In an embodiment, the instructions for the non-invasive health measurement system further include causing the processor to calculate fat proton relaxation time (T 2f ) can be measured. 2f) can be measured by performing diffusion-encoded NMR measurements at high b values ​​to suppress the water contribution and by estimating the fat relaxation time (T) based on a monoexponential fit of the diffusion-encoded NMR measurements. 2f )

[0009] In an embodiment, measuring the NMR signal amplitude dependence on diffusion time may include performing diffusion-encoded NMR measurements at various b values, performing a double exponential fit to the NMR signal at each b value, and calculating the amplitude of the NMR signal at each b value based on the double exponential fit.

[0010] In an embodiment, determining the amplitude and diffusion coefficients of fat and water may include performing a double exponential fit to the total measurement signal amplitude dependence over time, calculating the amplitudes of the water and fat contributions based on the double exponential fit, and calculating the diffusion coefficients of the water and fat contributions based on the double exponential fit.

[0011] In an embodiment of the non-invasive health measurement system, the organ may be a liver. The organ may be a liver of a human patient. In an embodiment of the system, the NMR device may be applied to the human patient while the human patient is lying down. In an embodiment of the system, the NMR device may include a band to guide positioning of the device relative to the patient. The band may be an elastomeric band.

[0012] In an embodiment of the system, the accuracy of NMR signal measurements performed by the NMR device may be evaluated by applying the NMR device to a patient, moving the patient laterally relative to the placement of the NMR device, performing NMR signal measurements with the NMR device, and evaluating the amplitude of the signal measurements to determine the accuracy of the patient's position.

[0013] In an embodiment, the non-invasive health measurement system may include an open magnet nuclear magnetic resonance ("NMR") device. The NMR device may acquire an NMR response signal generated by atomic nuclei of a material comprising the organ. The NMR response signal may include a fat contribution signal and a water contribution signal. The system may include a processor and a memory communicatively coupled to the processor. The memory may store instructions that, when executed by the processor, cause the processor to transmit radio frequency ("RF") pulses to the organ by the open magnet NMR device in the presence of a magnetic field gradient. The instructions may further cause the processor to acquire the NMR response signal. The instructions may further cause the processor to separate water and fat contributions to the NMR response signal based on their spin-spin ("T2") relaxation times to determine the water and fat composition of the organ.

[0014] An embodiment of a non-invasive health measurement system that separates water and fat signal contributions based on their T2 relaxation times may include acquiring a Carr-Purcell-Meiboom-Gill ("CPMG") time series, performing a double exponential least squares fit to the CPMG time series, and calculating the amplitudes of the fat signal contribution and the water signal contribution based on the fit. In an embodiment, a short echo time may be used to minimize diffusion effects.

[0015] In an embodiment of the non-invasive health measurement system, separating the water and fat signal contributions based on their T2 relaxation times may include measuring the T2 relaxation time for fat protons by suppressing the water signal based on T1. In another embodiment, separating the water and fat signal contributions based on their T2 relaxation times may include measuring the T2 relaxation time for fat protons by suppressing the diffusion coefficient.

[0016] In an embodiment, the non-invasive health measurement system may include an open magnet nuclear magnetic resonance ("NMR") device. The NMR device may acquire an NMR response signal generated by atomic nuclei of a material including an organ. The NMR response signal may include a fat contribution signal and a water contribution signal. The system may include a processor and a memory communicatively coupled to the processor. The memory may store instructions that, when executed by the processor, cause the processor to transmit radio frequency ("RF") pulses to the organ by the open magnet NMR device in the presence of a magnetic field gradient. The instructions may further cause the processor to acquire the NMR response signal. The instructions may further cause the processor to separate water and fat contributions to the NMR response signal based on their spin-lattice ("T1") relaxation times.

[0017] In an embodiment of a non-invasive health measurement system, separating the contributions of water and fat signals based on their T1 relaxation times may include collecting echo trains using various recycle delays ("rd"), where the echo trains are much shorter than the shortest T2 value, measuring the NMR signal amplitudes over a range of rd values, performing a double exponential fit of the measured signal amplitudes, determining signal amplitude values ​​for water and fat based on the double exponential fit, independent of the T2 value, and determining T1 relaxation times for water and fat based on the double exponential fit, independent of the T2 value.

[0018] In an embodiment of the non-invasive health measurement system, separating the water and fat signal contributions based on their T1 relaxation times is 1f Calculate T 1w This may include separately calculating T 1f Calculating T involves performing NMR signal measurements at various rd values, summing the echoes, applying an NMR diffusion encoding sequence to suppress the water contribution, performing a monoexponential fit to the measurements, and calculating T based on the monoexponential fit. 1f and calculating T 1wSeparate calculation of T 1w T 1f so that the fat contribution becomes effectively constant as T becomes much larger than 1f setting an rd value much larger than T, performing a single exponential fit on the measurements, and finding T based on the single exponential fit. 1w and calculating:

[0019] Other features and aspects of the present disclosure will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the features according to various embodiments. The Summary is not intended to limit the scope of the invention, which is defined solely by the appended claims. [Brief description of the drawings]

[0020] The technology disclosed herein will be described in detail with reference to the following figures, according to one or more various embodiments. The drawings are provided for illustrative purposes only and merely depict typical or exemplary embodiments of the disclosed technology. These drawings are provided to facilitate the reader's understanding of the disclosed technology and should not be considered as limiting its breadth, scope, or applicability. Please note that for clarity and ease of illustration, these drawings are not necessarily drawn to scale.

[0021] [Figure 1] 1 is an example of a nuclear magnetic resonance ("NMR") device as part of a non-invasive health measurement system in accordance with the systems and methods disclosed herein.

[0022] [Diagram 2] 1 is an example of a stand-alone NMR instrument in accordance with the systems and methods disclosed herein.

[0023] [Diagram 3]1 is an example flow diagram illustrating how the PDFF and diffusion coefficient may be calculated according to embodiments of the systems and methods disclosed herein.

[0024] [Figure 4] 1 is an example flow diagram illustrating how water and fat signals may be separated in accordance with embodiments of the systems and methods disclosed herein.

[0025] [Diagram 5] FIG. 1 is an example of a flow diagram showing how water and fat signals can be separated and how the T1 of water and fat can be measured in accordance with an embodiment of the systems and methods disclosed herein.

[0026] [Figure 6A] FIG. 1 is an example flow diagram illustrating an embodiment in which T1f can be calculated using an NMR diffusion encoding sequence to suppress water signals and measure only fat signals, according to an embodiment of the systems and methods disclosed herein.

[0027] [Figure 6B] 1 shows an example of a flow diagram illustrating an embodiment in which T1w may be calculated.

[0028] [Figure 7] 1 is an exemplary computing component that can be used to implement various features of the embodiments described in this disclosure.

[0029] The drawings are not intended to be exhaustive or to limit the invention to the precise form disclosed, it being understood that the invention may be practiced with modification and alternatives, and the disclosed technology is limited only by the claims and their equivalents. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0030] The systems and methods described herein relate to non-invasive diagnostic techniques for measuring the concentration of fat in an organ. The organ of interest may be the liver. The systems and methods are non-invasive, portable, relatively inexpensive, and accurate, providing advantages over existing diagnostic techniques.

[0031] The non-invasive health measurement system may include an NMR device. The NMR device may be an open magnet NMR device. In an embodiment, the NMR device may be a standalone medical device. The NMR device may be positioned relative to a patient. The NMR device may measure the fat composition of an organ of interest by collecting NMR signals from a sensitivity volume within the patient. The sensitivity volume may correspond to a desired depth into the patient's organ of interest, such as the liver. The standalone NMR device may be communicatively coupled to other devices to enable processing and transmission of medical results. For example, the NMR device may be communicatively coupled to a user interface, such as a keyboard, mouse, touch screen, remote control device, or other interface.

[0032] An open magnet NMR device may mean that the probe is unilateral or open. The probe does not have to completely surround the patient, as is the case for MRI measurements. Rather, the open magnet NMR probe may be placed adjacent to and / or abutting the patient's region of interest. The open magnet NMR probe may create a sensitivity volume within the patient within the region of interest either outside or inside the boundary of the probe.

[0033] The NMR device may perform measurements as follows: Protons and / or other nuclei, such as hydrogen protons, spin axes, etc., within the sensitive volume may be aligned with the magnetic field. The spin alignment of the nuclei may be altered by exciting the nuclei with a radio frequency ("RF") pulse or series of RF pulses. RF pulses may be delivered within the sensitive volume to excite hydrogen protons present in tissue within the sensitive volume. The spinning nuclei may be knocked out of their preferred alignment with respect to the magnetic field when the RF pulse is delivered. The excited nuclei may then realign with the magnetic field. As the excited nuclei realign, they may emit an RF signal. This emitted RF signal is the NMR response signal. The NMR response signal may be detected by an RF receiver within the NMR device. The NMR response signal may provide information regarding the properties and / or composition of the tissue and material within the sensitive volume.

[0034] Specifically, when the sensitive volume is an organ composed of adipose tissue, such as the liver, the fat content of the liver can be determined based on the NMR response signal.The signal from the protons in fat in the liver can be separated from the signal from water in the liver based on the proton NMR spectrum, diffusion coefficient, T1 or T2.Therefore, the total NMR signal can be measured, which can include the contribution from the signal from the protons in fat and the protons in water in the liver.Protons are abundant in water and fat.

[0035] FIG. 1 illustrates an example of an NMR device 100 as part of a non-invasive health measurement system. As shown in FIG. 1, the NMR device 100 is placed on a gurney 106. A human patient 104 lies on the gurney 106 on their right side. The NMR device 100 is positioned below the patient's abdominal region. The NMR device 100 may be aligned with the patient's sternum. The NMR device 100 may include a band or strap that may be attached to the patient 104 to guide the positioning of the patient on the NMR device. The NMR device 100 may be communicatively coupled to other medical instruments 102 and / or a user interface. The NMR device 100 may be configured to measure the fat composition of an organ of interest in the patient 104 by collecting NMR signals from a sensitive volume 108 within the patient 104. The sensitive volume 108 may correspond to a desired depth into the organ of interest of the patient 104, such as the patient's liver. FIG. 2 illustrates an example of a standalone NMR device 100. In an embodiment, the NMR device may be incorporated into a hospital bed.

[0036] In an embodiment, the accuracy of the signal of the NMR device can be evaluated by changing the patient positioning. The patient can be asked to move laterally relative to the NMR device. For example, the patient can be asked to move and / or be moved approximately 2 inches toward the top of the gurney where the patient's head is located. The NMR device can then perform a test measurement of the NMR signal in the sensitive volume. If the patient is not positioned correctly, the signal amplitude may follow a diffusion-driven response consistent with fat protons, but the signal amplitude may be higher than the liver fat model predicts. Thus, a higher than expected signal amplitude may indicate that the patient is not positioned correctly relative to the NMR device.

[0037] Proton density fat fraction ("PDFF") may be a parameter for measuring the fat content of an organ. In an embodiment, the organ may be the liver. The PDFF may be the ratio of the fat proton NMR signal amplitude to the total NMR signal amplitude. The fat proton NMR signal amplitude may be proportional to the number of fat protons per unit volume. The total NMR signal amplitude may be proportional to the water and fat protons per unit volume. The PDFF may be expressed as:

number

[0038] Discrimination of water and fat signals can be achieved by separating the signal responses based on different parameters, which can include, for example, proton relaxation times, spectroscopic responses, relaxation times, and diffusion.

[0039] In embodiments, the diffusion coefficient and relaxation time can be measured in addition to the PDFF. The diffusion and relaxation time information can be correlated with droplet size and fibrosis. The fitting of the collected data according to the systems and methods described herein can provide new values ​​of diffusion constant and relaxation time, which can then be used for other liver diagnostic applications, since there can be a correlation between diffusion constant and T1 with stiffness and / or swelling, which can be correlated with fibrosis. Therefore, obtaining the diffusion constant using the methods and devices disclosed herein can provide additional clinical value.

[0040] Diffusion-Based Separation Embodiments Water and fat signals can be separated based on their diffusion coefficients. The diffusion coefficients of water and fat can be significantly different, and this method can be effective in separating water and fat signals. It may be possible to suppress the water signal while observing the fat signal. The diffusion coefficient of water can be as much as 10 times higher than the diffusion coefficient of fat. Thus, a clear separation of the NMR signal from water protons and fat protons can be achieved. The signals can be differentiated by performing the measurement in the presence of a magnetic field gradient. For example, a Carr-Purcell-Meiboom-Gill ("CPMG") pulse sequence with different interpulse intervals can be used. A CPMG sequence with a diffusion encoding preparation phase can also be used. Phase cycling of the RF pulses and signal channels can be performed to remove unwanted spurious signals.

[0041] The signal amplitude for various diffusion encoding times can be modeled taking into account the diffusion coefficients for water and fat protons. The signal decay in Hahn echo or CPMG sequences in the presence of a magnetic field gradient may depend on the inter-echo interval. A higher diffusion coefficient may be positively correlated with a faster decay. Varying the inter-echo interval may allow the calculation of the respective contributions of water and fat to the total signal. Diffusion encoding may also be achieved by applying a preparation pulse followed by a multi-echo sequence. The multi-echo sequence may be a CPMG sequence. If a CPMG sequence is used after the preparation pulse, the sensitivity may be enhanced.

[0042] The NMR signal amplitude may decrease as a function of encoding time. The b-value may be used to scale the time series by the static magnetic field gradient G. The b-value may be expressed as: b=γ 2 G 2 τ3 / 12 where γ is the gyromagnetic ratio of proton spin, which has a value of 267,520,000 rad / (sT), and in an embodiment of a device according to the systems and methods disclosed herein, G=1.875 T / m.

[0043] In the case of a pulse sequence, the signal amplitude of the first echo may be a function of the initial pulse separation. Then, each echo in the CPMG section may decay exponentially. In the case of signals generated by fat and water proton signals, the decay may be represented by a double exponential decay.

[0044] To increase the signal-to-noise ratio ("SNR"), the diffusion encoding sequence may be repeated and signals may be added. For white Gaussian noise, if the repetitions are performed after the spins are fully polarized, the SNR increases as the square root of the number of repetitions.

[0045] For a recycle delay, or time between sequences, rd, the NMR signal amplitude at time t along the CPMG time series can be expressed versus the diffusion encoding time τ. 2 G 2 τ3 / 12) depends on the diffusion encoding time τ. The NMR signal amplitude can be expressed as:

number

number

[0046] For full polarization before the pulse sequence is repeated, the amplitude is rd = T 1f and T 1w , can be given by the following formula:

number

[0047] Since the amplitude does not depend on the T1 value for water or fat protons in this embodiment, T1 correction may not be necessary if a long repeat delay is used. The amplitude at t=0 may be determined by identifying the zero crossing point in the amplitude time series of the echo train. Determining the amplitude at t=0 is the same as determining the T 2f and T 2w Calculating the amplitude at t=0 depends on T 2f and T 2w This can be simplified by using an echo train duration much shorter than T and then adding or averaging all the echoes to increase the sensitivity. In this way, the amplitude at t=0 is 2f and T 2w Furthermore, as described above, rd can be determined independently of T 1f and T 1w If the spreading coding signal is assumed to be much larger than T 1f and T 1w Therefore, if appropriate time parameters are used during signal acquisition, the diffusion coded signal can be obtained independently of T 2f and T 2w And T 1f and T 1w can be determined independently of both

[0048] If the diffusion encoding time is long, only the fat signal can be observed. The amplitude that depends only on the fat signal given the high b-value due to the long diffusion encoding time can be given by the following formula:

number

number

[0049] The diffusion-encoded NMR signal can be collected at various encoding times τ, which results in a change in the b-value. This can allow the calculation of the PDFF mentioned above, as well as the diffusion coefficients of water and fat. The CPMG time series is then calculated for each b-value, T 2f and T 2w The T1 values ​​for water and fat protons may not be known. However, as described above, assuming and / or setting a long rd may avoid the need to perform a T1 correction.

[0050] The PDFF and diffusion coefficients may be calculated using the following method, consistent with the embodiments described above. Figure 3 shows an example of a flow diagram illustrating how the PDFF and diffusion coefficients may be calculated based on the diffusion contrast. As a first operation 300, T 2f As a first sub-operation 302 to the first operation 300, T 2f Diffusion-encoded NMR measurements may be performed at high b values ​​to measure the fat proton relaxation times (T). As a second suboperation 304 to the first operation 300, this configuration may allow for observation of only the fat signal, as described above. As a third suboperation 306 to the first operation 300, a mono-exponential fit to the data may be performed. As a fourth suboperation 308 to the first operation 300, fat proton relaxation times (T 2f ) may be calculated based on a single exponential fit. In an embodiment, the SNR may be high and the signals from fat and water may already be effectively picked out for the CPMG time series per encoding time. Therefore, when the SNR is high, this operation may not be necessary.

[0051] As a second operation 310, the signal amplitude dependence on diffusion time may be measured. As a first suboperation 312 to the second operation 310, NMR measurements may be performed at various b values. As a second suboperation 314 to the second operation 310, a bi-exponential fit of the signal may be performed at each b value. As a third suboperation 316 to the second operation 310, the T calculated from the fourth suboperation 308 to the first operation 300 may be fitted to the 2f may be used to make the fit statistically reliable. As a fourth sub-operation 318 to the second operation 310, the amplitude of the signal at each b value (t=0) may be calculated.

[0052] As a third operation 320, the amplitude coefficients and diffusion coefficients of fat protons and water protons may be determined. As a first suboperation 322 to the third operation 320, a double exponential fit to the total signal amplitude may be performed. As a second suboperation 324 to the third operation 320, the amplitudes and diffusion coefficients of water and fat protons may be calculated based on the double exponential fit. As a third suboperation 326 to the third operation 320, the amplitudes and coefficients may be used to calculate the PDFF.

[0053] In an embodiment, during operation of the NMR device, an operator may instruct the patient to inhale, exhale, and hold their breath while the NMR device measures the NMR signal within the patient's sensitivity volume. The patient may hold their breath for 5 to 15 seconds for each b-value for which an NMR measurement is desired.

[0054] In an embodiment, if the diffusion coefficient of fat is known, the PDFF can be estimated by suppressing water signals with high b values ​​in the diffusion encoded signal to obtain Afat(b,t=0) using:

number

[0055] Echo is T 2f If applied over a period of time much shorter than

number

[0056] This simplifies the measurement of fat signal response, and thus a fast PDFF reading can be performed. If the total signal is assumed to be constant from patient to patient, the PDFF can be measured using a single measurement at a high b-value to determine the fat signal and a known total signal response.

[0057] Embodiments of T2-Based Separation The water and fat signals are also measured by their spin-spin relaxation times (T2), or time constants in a multi-echo pulse sequence, T 2eff 4 shows an example of a flow diagram illustrating how water and fat signals can be separated based on their T2. As a first operation 400, a CPMG time series can be acquired. As described above for the diffusion-based separation embodiment, phase cycling of the RF pulses and signal channels can be performed to remove unwanted spurious signals.

[0058] As a sub-operation 402 to the first operation 400, a short echo time may be used to minimize diffusion effects during the echo train. A longer echo interval may reduce the water signal more than the signal from fat, resulting in an inaccurate PDFF calculation. As a third operation 404, the NMR signal may be measured at a repeat delay rd. The NMR signal using the repeat delay rd may be given by the following equation:

number

[0059] As a fourth operation 406, a double exponential least squares fit may be performed to single out the signal contributions from fat and water. As a fifth operation 412, the amplitudes of the signals from fat and water may be calculated using a double exponential fit to the echo amplitudes in the CPMG time series. The A water and A fat obtained by the double exponential fit may be used to calculate the PDFF. If rd is T 1w and T 1f, the formula can be simplified to:

number

[0060] This method can quantify the contribution of water and fat protons to the NMR signal. To help achieve separation of the two signals, as a first sub-operation 408 to the fourth operation 406, T 2f can be measured by suppressing the water signal based on T using fast repetition, or based on the diffusion coefficient using a diffusion encoding sequence or large echo spacing. Then, as a second sub-operation 410 to the fourth operation 406, T 2f can be used as a fixed parameter when water and fat signals are observed.

[0061] An embodiment of T1-based separation The water and fat signals can also be separated based on differences in spin-lattice relaxation times (T1). 1w ) length T1 is the fat (T 1f ) may be about four times the length T1, which may make separation on this basis feasible. However, T1 testing may be time consuming. FIG. 5 is an example of a flow diagram showing how water and fat signals may be separated based on T1. As a first operation 500, differentiation of fat and water proton signals may be achieved by signal saturation. In the first operation 500, NMR signals may be collected using various recycle delays. In an alternative first operation 502, differentiation of fat and water proton signals may also be achieved using an inverse recovery method. In an alternative first operation 502, NMR signals may be collected by inverting the phase of the initial RF pulse and applying a variable delay after the pulse.

[0062] Because the polarization times of the fat and water signals are different, a double exponential analysis of the response may be used to separate the water and fat contributions to the signal. In an embodiment, a single echo sequence may be repeated. The NMR signal with repetition time rd, if the first echo is discarded, may be expressed as:

number

[0063] To increase sensitivity, as a sub-operation 504 to the first operation 500 or alternatively the first operation 502, an echo train may be collected instead of a single echo. The signal processing in this case may consider the time series in the echo train to be driven by the T2 of water and fat protons. If the echo train is much shorter than the shortest T2 value, the echoes may be summed to increase sensitivity with minimal T2 bias. In this way, sensitivity may be increased over a single echo examination without the need to perform fitting to a multi-echo time series.

[0064] In other embodiments, the T values ​​for water and fat may also be measured separately. 1fFIG. 6 shows an example of a flow diagram illustrating an embodiment in which T may be calculated to suppress the water signal and measure only the fat signal. This may simplify the analysis since only a single exponential time series is present. An effective way to perform this reading and process the data may be, as a first operation 600, an NMR diffusion encoding sequence is applied to suppress the water signal. As a second operation 602, all echoes are added together and measurements are performed with various rd values. As a third operation 604, a single exponential fitting to the obtained data may be performed. As a fourth operation 606, T 1f can be calculated based on a single exponential fit. This T value can be used as a fixed parameter for the double exponential decay in the absence of diffusion encoding to aid in the separation of water and fat signals.

[0065] FIG. 6B shows the T 1w 6 shows an example of a flow diagram illustrating an embodiment in which T may be calculated. As a first operation 608, a single echo or multi-echo train pulse sequence with diffusion encoding, e.g., CPMG, with various rd values ​​may be acquired. As a second operation 610, T 1w T 1f It becomes much larger than T 1f With rd much larger than T, the fat signal may become effectively constant and the signal recovery may become dominated by the water signal. Thus, as a third operation 612, rd is adjusted to be greater than T 1f If T is much larger than T, a single exponential function may be applied to approximate the signal recovery. 1w can be calculated based on a single exponential fit.

[0066] Embodiments of J-coupling-based separation J-coupling can also be used to separate the signals. Pulse separation can be applied to dephase the water signal while the fat signal is refocused.

[0067] Example of integration with computing components When components are implemented in whole or in part using software, these software elements can be implemented to operate in conjunction with computing or processing components capable of performing the functions described with respect thereto. One such exemplary computing component is shown in FIG. 7. Various embodiments are described with respect to this exemplary computing component 700. After reading this description, it will become apparent to one of ordinary skill in the art how to implement applications using other computing components or architectures.

[0068] Referring now to FIG. 7, computing components 700 may represent computing or processing capabilities found, for example, in self-adjusting displays, desktops, laptops, notebooks, and tablet computers. They may be found in handheld computing devices (tablets, PDAs, smart phones, cell phones, palmtops, etc.). They may be found in workstations or other devices with displays, servers, or any other type of dedicated or general-purpose computing device that may be desirable or appropriate for a given application or environment. They may be found in smart medical equipment. Computing components 700 may also represent computing capabilities built into or otherwise available to a given device. For example, computing components may be found in other electronic devices, such as portable computing devices, smart medical equipment, and other electronic devices that may include some form of processing capabilities.

[0069] The computing component 700 may include, for example, one or more processors, controllers, control components, or other processing devices. This may include any one or more of the processors and / or components that make up a user device, a user system, and / or a non-decrypting cloud service. The processor 704 may be implemented using a general-purpose or special-purpose processing engine, such as, for example, a microprocessor, controller, or other control logic. The processor 704 may be connected to a bus 702. However, any communication medium may be used to facilitate interaction with other components of the computing component 700 or to communicate with the outside world.

[0070] The computing component 700 may also include one or more memory components, referred to herein simply as main memory 708. For example, a random access memory (RAM) or other dynamic memory may be used to store information and instructions to be executed by the processor 704. The main memory 708 may also be used to store temporary variables or other intermediate information during execution of instructions to be executed by the processor 704. Similarly, the computing component 700 may include a read only memory ("ROM") or other static storage device coupled to the bus 702 for storing static information and instructions for the processor 704.

[0071] The computing component 700 may also include one or more various forms of information storage mechanisms 710, which may include, for example, a media drive 712 and a storage unit interface 720. The media drive 712 may include a drive or other mechanism for supporting a fixed or removable storage medium 714. For example, a hard disk drive, a solid state drive, a magnetic tape drive, an optical drive, a compact disk (CD) or digital video disk (DVD) drive (R or RW), or other removable or fixed media drive may be provided. The storage medium 714 may include, for example, a hard disk, an integrated circuit assembly, a magnetic tape, a cartridge, an optical disk, a CD or a DVD. The storage medium 714 may be any other fixed or removable medium that is read, written, or accessed by the media drive 712. As these examples show, the storage medium 714 may include a computer usable storage medium having computer software or data stored thereon.

[0072] In alternative embodiments, information storage mechanism 710 may include other similar means for allowing computer programs or other instructions or data to be loaded into computing component 700. Such means may include, for example, fixed or removable storage units 722 and interfaces 720. Examples of such storage units 722 and interfaces 720 may include program cartridges and cartridge interfaces, removable memory (e.g., flash memory or other removable memory components), and memory slots. Other examples may include PCMCIA slots and cards, and other fixed or removable storage units 722 and interfaces 720 that allow software and data to be transferred from storage unit 722 to computing component 700.

[0073] The computing component 700 may also include a communications interface 724. The communications interface 724 may be used to allow software and data to be transferred between the computing component 700 and external devices. Examples of the communications interface 724 may include a modem or soft modem, a network interface (such as Ethernet, a network interface card, IEEE802.XX, or other interface). Other examples include a communications port (e.g., a USB port, an IR port, an RS232 port, a Bluetooth interface, or other port) or other communications interface. The software / data transferred through the communications interface 724 may be carried on signals that may be electronic, electromagnetic (including optical), or other signals capable of being exchanged by a given communications interface 724. These signals may be provided to the communications interface 724 via a channel 728. The channel 728 may carry signals and may be implemented using a wired or wireless communications medium. Some examples of channels may include a telephone line, a cellular link, an RF link, an optical link, a network interface, a local or wide area network, and other wired or wireless communications channels.

[0074] As used herein, the terms "computer program medium" and "computer usable medium" are generally used to refer to transitory or non-transitory media. Such media may be, for example, memory 708, storage unit 720, medium 714, and channel 728. These and other various forms of computer program medium or computer usable medium may be involved in carrying one or more sequences of one or more instructions to a processing device for execution. Such instructions embodied on the medium are generally referred to as "computer program code" or a "computer program product" (which may be grouped in the form of a computer program or other groupings). When executed, such instructions may enable the computing component 700 to perform the features or functions of the present application as described herein.

[0075] In an embodiment, the computing component may be integrated with, communicatively coupled to, or otherwise form part of a laboratory system. For example, the computing component may be communicatively coupled to medical and / or laboratory equipment. In another example, the computing component may be part of a medical workstation. The medical workstation may be configured as a mobile cart. The medical workstation may also be stationary. A stand-alone NMR device may be communicatively coupled to a medical workstation. An NMR device integrated into a patient bed may also be communicatively coupled to a medical workstation.

[0076] While various embodiments of the present invention have been described above, it should be understood that they are presented by way of example and not limitation. Similarly, various figures may depict exemplary architectures or other configurations for the present invention, which are made to aid in the understanding of features and functionality that may be included in the present invention. The present invention is not limited to the exemplary architectures or configurations depicted, and the desired features may be implemented using various alternative architectures and configurations. Indeed, it will be apparent to one of ordinary skill in the art how alternative functional, logical or physical divisions and configurations may be implemented to implement the desired features of the present invention. Also, many different component module names other than those depicted herein may be applied to the various divisions. Furthermore, with respect to flow diagrams, operational descriptions, and method claims, the order in which steps are presented herein does not require that the various embodiments be implemented to perform the recited functions in the same order, unless the context dictates otherwise.

[0077] While the present invention has been described above with reference to various exemplary embodiments and implementations, it should be understood that various features, aspects and functions described in one or more of the individual embodiments are not limited in their applicability to the particular embodiment in which they are described, but may be applied alone or in various combinations to one or more of the other embodiments of the present invention, regardless of whether such an embodiment is described and whether such features are presented as part of the embodiment in which they are described. Thus, the breadth and scope of the present invention should not be limited by any of the exemplary embodiments described above.

[0078] Terms and phrases used herein, and variations thereof, unless expressly stated otherwise, should be construed as open ended rather than limiting. As an example of the foregoing, the term "including" should be read to mean "including, without limitation" and the like. The term "example" is used to provide illustrative examples of the items under discussion, rather than an exhaustive or limiting list thereof. The terms "a" or "an" should be read to mean "at least one," "one or more," and the like. Adjectives such as "conventional," "traditional," "normal," "standard," "known," and words of similar meaning should not be construed as limiting the described items to items available during a given period or at a given time, but instead should be read to embrace conventional, traditional, ordinary, or standard technology that may be available or known now or at any time in the future. Similarly, when this specification refers to technology that would be apparent or known to a person of ordinary skill in the art, such technology encompasses technology that would be apparent or known to a person of ordinary skill in the art now or at any time in the future.

[0079] In some cases, the presence of broadening words and phrases such as "one or more," "at least," "but not limited to," or other similar phrases should not be construed to imply that a narrower case is intended or required in the case where such broadening phrase may not be present. Use of the term "module" does not imply that components or functionality described or claimed as part of a module are all configured within a common package. Indeed, any or all of the various components of a module, whether control logic or other components, may be combined into a single package or maintained separately, and may even be distributed into multiple groups or packages or at multiple locations.

[0080] Moreover, various embodiments described herein are described with reference to exemplary block diagrams, flow charts, and other diagrams. As will become apparent to one of ordinary skill in the art after reading this specification, the illustrated embodiments and their various alternatives can be implemented without being limited to the illustrated examples. For example, block diagrams and their accompanying description should not be construed as mandating a particular architecture or configuration.

Claims

1. 1. A non-invasive health measurement system, comprising: an open magnet nuclear magnetic resonance ("NMR") apparatus for acquiring NMR response signals produced by atomic nuclei of a material including an organ, the NMR response signals including a fat contribution signal and a water contribution signal; A processor; A method for implementing a method for a computer-implemented ... program that is communicatively coupled to the processor and that, when executed by the processor, causes the processor to: transmitting radio frequency ("RF") pulses to the organ in the presence of a magnetic field gradient using the open magnet NMR device; acquiring said NMR response signal; and a memory storing instructions for determining the water and fat composition of the organ by separating the water and fat contributions to the NMR response signal based on differences in the diffusion coefficients of water and fat, measuring the amplitude dependence of the NMR response signal on diffusion time, and using the measured NMR signal amplitude dependence on diffusion time to determine the amplitudes and diffusion coefficients of the fat and water contributions.

2. The system of claim 1 , wherein separating the contributions of the water and fat signals based on the diffusion coefficients of water and fat further comprises calculating a proton density fat fraction ("PDFF") based on the determined amplitudes.

3. 2. The system of claim 1, wherein the diffusion coefficient of fat is known, and separating the contributions of the water and fat signals based on the diffusion coefficients of water and fat further comprises calculating a PDFF by suppressing the water amplitude using a high b-value to calculate the fat amplitude based on the known diffusion coefficient of fat.

4. The system described in claim 1, further comprising the processor measuring fat proton relaxation time (T2f).

5. Measuring fat proton relaxation time (T2f) performing a diffusion-encoded NMR measurement at a high b-value to suppress the water contribution; and calculating a fat relaxation time (T2f) based on a mono-exponential fit of the diffusion-encoded NMR measurements.

6. Measuring the NMR signal amplitude dependence on diffusion time; performing diffusion encoded NMR measurements at different b-values; performing a double exponential fit to the NMR signal at each b value; and calculating an amplitude of the NMR signal at each b-value based on the double exponential fit.

7. determining the amplitude and diffusion coefficients of the fat and water performing a double exponential fit to the total measured signal amplitude dependence on diffusion time; calculating the amplitudes of the water and fat contributions based on the double exponential fit; and calculating the water and fat diffusion coefficients based on the double exponential fit.

8. The method of claim 1 , wherein the organ is the liver.

9. 9. The method of claim 8, wherein the organ is the liver of a human patient.

10. The system of claim 8 , wherein the NMR device is applied to the human patient while the human patient is lying down.

11. The system of claim 1 , wherein the NMR device is applied to a patient, the NMR device comprising a band for guiding positioning of the patient.

12. The system of claim 11 , wherein the band comprises an elastomeric band.

13. The accuracy of the NMR signal measurements performed by the NMR device is applying the NMR device to a patient; moving the patient laterally relative to the location of the NMR device; performing an NMR signal measurement with the NMR device; and evaluating an amplitude of the signal measurement to determine the accuracy of the patient position.

14. A method for using an open magnet nuclear magnetic resonance ("NMR") apparatus to acquire NMR response signals produced by atomic nuclei of a material including an organ, the NMR response signals including a fat contribution signal and a water contribution signal; The method further comprising: transmitting radio frequency ("RF") pulses to the organ in the presence of a magnetic field gradient using the open magnet NMR device; acquiring the NMR response signal; measuring the NMR response signal amplitude dependence on diffusion time; determining the amplitudes and diffusion coefficients of fat and water contributions using said amplitude dependence on measured diffusion time; Calculating a proton density fat fraction ("PDFF") based on the determined amplitudes; and determining the water and fat composition of the organ based on the PDFF; A method comprising:

15. The method of claim 14, wherein the fat diffusion coefficient is known, and separating the contributions of the water and fat signals based on the water and fat diffusion coefficients further comprises calculating a PDFF by suppressing the water amplitude using a high b-value to calculate the fat amplitude based on the known fat diffusion coefficient.

16. The method of claim 14, further comprising measuring fat proton relaxation time (T2f).

17. Measuring fat proton relaxation time (T2f) performing a diffusion-encoded NMR measurement at a high b-value to suppress the water contribution; 17. The method of claim 16, comprising: calculating fat relaxation times (T2f) based on a mono-exponential fit of the diffusion-encoded NMR measurements.

18. Measuring the NMR signal amplitude dependence on diffusion time, performing diffusion encoded NMR measurements at different b-values; performing a double exponential fit to the NMR signal at each b value; and calculating an amplitude of the NMR signal at each b-value based on the double exponential fit.

19. The method of claim 18, wherein determining the amplitude and diffusion coefficients of fat and water comprises: performing a double exponential fit to the total measured signal amplitude dependence on diffusion time; calculating the amplitudes of the water and fat contributions based on the double exponential fit; and calculating the water and fat diffusion coefficients based on the double exponential fit.

20. The accuracy of the measurement of the NMR signal is applying the NMR device to a patient; moving the patient laterally relative to the location of the NMR device; performing an NMR signal measurement with the NMR device; and evaluating an amplitude of the signal measurement to determine the accuracy of the patient position.

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