Methods and systems for point estimation of ultrasound dose calculation

Abstract

A method for creating a media property map of a target region of an object, wherein the media property map provides multiple different media property values ​​in different segments of the target region, the media property values ​​depending on the medium in each of the segments, the method comprising: obtaining an image of the target region, wherein the target region includes a target treatment area and a surrounding area of ​​the target treatment area; processing the image to identify different components of the target region; segmenting the different components and classifying them into predetermined media categories; querying a media property value associated with each media category; and assigning the media property value to the respective corresponding component of the segmented target region.

Description

[0001] background

[0002] Ultrasound has long been used in diagnostic imaging applications. Recently, there has been growing interest and development in the use of ultrasound combined with microbubbles for drug delivery, immunotherapy, blood-brain barrier opening, and other applications.

[0003] When ultrasound waves propagate through tissue, the energy of the waves attenuates through several mechanisms, including scattering and absorption. Absorption transfers energy from the ultrasound waves to the tissue, where the energy dissipates as heat. Overheating of tissue can lead to tissue damage or other undesirable biological effects. Such effects should be avoided when ultrasound is used for diagnostic purposes. The thermal index (TI) is a dimensionless parameter designed to indicate the level of tissue heating during an ultrasound scan. This index is displayed on diagnostic ultrasound equipment and has a defined upper limit that should not be exceeded in diagnostic settings.

[0004] The combination of high rarefaction pressure and low frequency in ultrasound can lead to a mechanical effect known as cavitation. In cavitation, bubbles can form, oscillate, and disintegrate to varying degrees of intensity, producing undesirable biological effects. The mechanical index (MI) is a dimensionless parameter that indicates the likelihood of cavitation occurring and is typically displayed on diagnostic ultrasound instruments. Regulatory requirements during medical ultrasound imaging dictate the use of an MI less than 1.9. During ultrasound imaging with microbubble contrast agents, an MI below 0.7 is recommended to avoid harmful biological effects such as microbleeds and irreversible vascular damage. Using an MI below 0.4 during ultrasound imaging with microbubble contrast agents is considered "best practice."

[0005] MI is defined by the following formula: the peak negative (rarity) pressure (PNP) in the ultrasound field, which has been derated by an attenuation factor to account for acoustic attenuation within the tissue, divided by the square root of the center frequency (Fc) of the ultrasound field in MHz.

[0006]

[0007] in And it is included to provide MI as a dimensionless parameter;

[0008] f awf It is the operating frequency of the sound;

[0009] P r，α The attenuated peak rarefaction pressure; and

[0010] α is the attenuation factor for derating.

[0011] The ultrasonic pressure amplitude of the ultrasonic field generated by a medical ultrasound scanner with a connected ultrasound probe is characterized by immersing the probe face in water and measuring the pressure wave emitted from the probe using a hydrophone. Based on these measurements, the amplitude of the pressure wave that the probe can generate in tissue is estimated. A conservative value for the ultrasonic attenuation in tissue is used in this estimate to calculate the safe operating limit for MI or TI. 0.3 dB cm⁻¹ -1 MHz -1 The conservative value helps avoid undesirable biological effects during diagnostic ultrasound of the subject. However, this is a highly simplified calculation of MI, which assumes a homogeneous tissue path from the ultrasound source to the target area and is insufficient for ultrasound administration requiring high precision in ultrasound energy delivery.

[0012] These current recommendations are not tailored or optimized for ultrasound-mediated therapy. To effectively utilize the mechanical and thermal mechanisms involved in the application of ultrasound irradiation during therapy, it is crucial to optimally estimate the ultrasound dose delivered to the tissue volume being treated. This invention provides a method for real-time ultrasound dose measurement in ultrasound-mediated therapy.

[0013] EP2468191 A1 discloses an ultrasound diagnostic apparatus that provides a target index diagram. This ultrasound diagnostic apparatus includes: a calculation unit for calculating a mechanical index (MI) corresponding to a depth value in the direction in which ultrasound travels from the ultrasound output portion of the transmitting transducer; a visualization unit for generating an MI diagram in which the relationship between the calculated MI and the depth value is visualized graphically; and a display unit for displaying the MI diagram.

[0014] EP 2 521 593B1 discloses a system for applying focused ultrasound energy to nerves around a patient's blood vessels, the system comprising: a platform for supporting the patient; one or more piezoelectric arrays coupled to the platform, the one or more piezoelectric arrays comprising a plurality of piezoelectric elements; a controller configured to control the piezoelectric elements; a programmable generator configured to generate output power from one or more of the piezoelectric elements; and a programmable processor configured to process signals sensed by at least one of the piezoelectric elements; the platform comprising a stage having recesses for the one or more piezoelectric arrays; and one or more of the piezoelectric elements configured to deliver energy to treat the area around the blood vessels.

[0015] WO 2021 / 118783 A1 discloses a technique for the neuromodulation of tissues, which involves simultaneously or sequentially applying energy (e.g., ultrasound energy) to tissues at multiple target regions. Neuromodulation can lead to tissue displacement, which can be observed through changes in one or more target molecules.

[0016] Acoustic Cluster Therapy (ACT) – A novel concept in ultrasound-mediated targeted drug delivery, Sontum et al. [September 25, 2015] AL disclosed a novel approach for ultrasound (US)-mediated drug delivery—Acoustic Cluster Therapy (ACT)—and elucidated the fundamental characteristics of ACT formulations. The concept involves the application of free-flowing clusters of negatively charged microbubbles and positively charged microdroplets. The clusters are activated within the target pathology via diagnostic US, undergo a subsequent liquid-gas phase transition, and temporarily deposit as large 20–30 μm bubbles in the microtubule system, obstructing blood flow for approximately 5–10 minutes. Further application of US induces the following biomechanical effects: increased vascular permeability, leading to enhanced extravasation of components (e.g., released or co-administered drugs) from the vascular compartment. Methods for determining important in vitro characteristics of ACT compounds; cluster concentration and size distribution are described in detail. How these properties can be modified through multiple formulation parameters is shown, and their importance as predictors of biological behavior (e.g., deposit characteristics) is demonstrated by US imaging in a canine model. Furthermore, the in vivo properties of activated ACT bubbles were investigated in a rat model by in vivo microscopy, identifying the hypothetical behavior of the concept. Summary of the Invention

[0017] According to a first aspect of the invention, a method for point estimation of ultrasound dose in a target treatment region is provided, the method comprising: calculating a unique ultrasound propagation correction factor for a specific ultrasound propagation path through a specific target region by: obtaining a media properties map of the target region, wherein the media properties map provides multiple different media properties values ​​in different segments of the target region, the media properties values ​​depending on the medium in each of the segments, the obtaining of the media properties map of the target region comprising: obtaining an image of the target region, wherein the target region includes the target treatment region and a surrounding region of the target treatment region; processing the image to identify different components of the target region; segmenting and classifying the different components. The process involves: classifying media into predetermined media categories; querying media characteristic values ​​associated with each media category, including: estimating category-specific ultrasound coupler element corrections for the media characteristic values ​​caused by the presence of at least one ultrasound coupler element in at least one component; adjusting the media characteristic values ​​of the at least one component to take into account the corresponding category-specific ultrasound coupler element corrections; assigning the media characteristic values ​​to the respective components of the segmented target region; depicting the propagation path from the ultrasound source to the target treatment area; summarizing the media characteristic values ​​of each segment along the propagation path to calculate a unique propagation correction factor; and using the unique propagation correction factor to indicate the ultrasound dose delivered to the target treatment area.

[0018] The media category may include at least one of the following: different tissue types; different tissue types affected by one or more specific diseases; fluids; and gases.

[0019] Different tissue types include one or more of the following: soft tissue, which includes fat, muscle, parenchyma, tendons and ligaments; and hard tissue, which includes bone.

[0020] Obtaining an image of the target region may include at least one of the following: querying a pre-scanned scan of the target region; performing a pre-scan scan of the target region; and using images from a real-time diagnostic imaging system.

[0021] The scan may include one or more of the following: computed tomography (CT) images; and magnetic resonance (MRI) images.

[0022] Category-specific media property values ​​can be queried from the database.

[0023] The at least one ultrasonic coupling bubble element may include one or more of the following: contrast agent microbubbles; cavitation seeds; large microbubbles; Bubble technology ultrasonic coupling bubble element, among which Bubble technology ultrasonic coupling bubble element includes: Microbubble clusters and activated Bubble.

[0024] The at least one ultrasound coupling bubble element may include contrast agent microbubbles, and wherein estimating contrast agent microbubble correction includes: querying or estimating one or more contrast agent microbubble parameters, wherein the one or more contrast agent microbubble parameters include: a value of the dose of the applied contrast agent microbubble; contrast agent characteristics per unit concentration; the subject's blood volume; the subject's cardiac output; a value of blood volume associated with each category; the time to arrival for each category after intravenous administration of contrast agent; and a time-concentration curve; and calculating contrast agent correction for each category using the contrast agent parameters.

[0025] The at least one ultrasonic coupling bubble element may include Bubble technology for ultrasonic coupling bubble elements, and in which additional calculations are performed. Bubble correction includes: correction of bubbles generated in the presence of high-frequency activated ultrasound. Estimate the additional correction caused by microbubble clusters; for the generation of high-frequency activated ultrasound in the presence of such ultrasound. Estimate the additional corrections caused by the bubble; and estimate the corrections for the effects of low-frequency enhanced ultrasound in the presence of the bubble. Estimate the additional corrections caused by bubbles.

[0026] Calculate additional Foam correction may also include: estimating the category associated with each component by means of the following methods. Number of bubbles: Query or estimate one or more. Bubble parameters, among which The bubble parameters include: the subject's blood volume; the subject's cardiac output; the perfusion volume of each category of the component; and the time-concentration profile; as well as the cardiac output fraction corresponding to the perfusion volume of each category of the component multiplied by... The activation yield of the bubble clusters is used to calculate the delivery rate to each component. The number of bubbles.

[0027] In the categories associated with each segment The estimation of the number of bubbles can incorporate time dependence by querying each category. The value of the bubble's lifespan, for each category. The number of bubbles is modeled as it decreases over time.

[0028] The correction caused by the presence of contrast agent in each category can be calculated based on contrast mode imaging ultrasound.

[0029] Calculations are made from each category The additional corrections caused by the presence of bubbles can be based on fundamental B-mode imaging ultrasound.

[0030] The method may also include using a unique propagation correction factor to calculate at least one of the following as an indication of the delivered ultrasonic dose: generated pressure, generated mechanical index, generated intensity, generated power, and generated thermal index.

[0031] According to a second aspect of the invention, a non-transitory computer-readable storage medium is provided, wherein instructions are stored on the computer-readable storage medium, which, when executed on a processor, perform the method of the first aspect of the invention.

[0032] According to a third aspect of the invention, a system is provided for providing point estimation of ultrasound dose in a target region of an object, the system comprising: an ultrasound source; an image processor module for processing an image to identify different components of the target region; a computer processor; a database module containing media property values ​​associated with multiple categories of components in the target region; and a data storage module containing computer-readable instructions that, when executed on the processor, perform the following tasks: querying an image of the target region, wherein the target region includes a target treatment area and a surrounding area of ​​the target treatment area; processing the image to identify different components of the target region; segmenting the different components and classifying them into predetermined media categories; and querying media property values ​​associated with each media category, which include... The process involves estimating the class-specific ultrasound coupler element correction for the media property values ​​caused by the presence of at least one ultrasound coupler element in at least one of the components; adjusting the media property values ​​of the at least one component to take into account the corresponding class-specific ultrasound coupler element correction; assigning the media property values ​​to the respective components of the segmented target region; depicting the ultrasound propagation path from the ultrasound source to the target treatment area; summarizing the media property values ​​of each component along the propagation path to calculate an ultrasound propagation correction factor unique to the ultrasound propagation path through the target region; calculating a point estimate of the ultrasound dose for the target region based on the unique propagation correction factor; and adjusting the ultrasound source based on the calculated point estimate of the ultrasound dose if the dose is outside a predetermined range.

[0033] According to a fourth aspect of the invention, a system is provided for providing a point estimate of an ultrasound dose for a target region in an object, the system comprising: an ultrasound source; an image processor module for processing an image to identify different components of the target region; a computer processor; a database module containing media property values ​​associated with multiple categories of components in the target region; and a data storage module containing computer-readable instructions that, when executed on the processor, perform the following tasks: depicting an ultrasound propagation path from the ultrasound source to a target treatment area; summarizing the media property values ​​of each component along the propagation path to calculate an ultrasound propagation correction factor unique to the ultrasound propagation path through the target region; calculating a point estimate of the ultrasound dose for the target region based on the unique propagation correction factor; and adjusting the ultrasound source according to the calculated point estimate of the ultrasound dose if the dose is outside a predetermined ultrasound dose range.

[0034] An image processor can be configured to segment and classify different components of a target region by: identifying boundaries between different patterns in an image; analyzing patterns within boundaries; and comparing each of the patterns with image patterns of known tissue types to find a match.

[0035] The system may be a machine learning system, wherein each processed image and associated image data are accumulated as training data to provide more accurate segmentation and classification by an image processor over time.

[0036] The system can also be configured to: track probe positions; re-evaluate one or more propagation correction factors as the probe positions move; and store one or more propagation correction factors for each probe position to reduce computational load.

[0037] The system may also be configured to: track the in-plane and out-of-plane rhythmic movement of a medium in a target area; re-evaluate one or more propagation correction factors for each in-plane and out-of-plane position of the moving medium; and store one or more propagation correction factors for each in-plane and out-of-plane position of the moving medium.

[0038] The system can be configured to track the in-plane and out-of-plane rhythmic movement of a medium using speckle tracking or machine learning algorithms.

[0039] The method of the first aspect, or the system of the second aspect, or the fourth aspect, wherein the medium properties may include at least one of the following: attenuation, sound velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient.

[0040] The media properties may also include one or more derived properties that may be derived from any or any combination of the listed media properties. Attached Figure Description

[0041] Figure 1 This is a flowchart of a point estimation method for calculating ultrasound dose;

[0042] Figure 2 This is a flowchart of a method for calculating the medium property map of a target region;

[0043] Figure 3a This is an example image of the target region of the object;

[0044] Figure 3b It has identified different components. Figure 3a Example image of the target region;

[0045] Figure 3c A representative of the target region, consisting of the identified components, is shown;

[0046] Figure 4a It is a graph of the normalized backscatter intensity curve of vesicles in the human liver;

[0047] Figure 4bIt is a graph of the actual concentration as a function of time, which uses... Figure 5 The backscattering intensity curve of a;

[0048] Figure 5 It is a point estimation system used to calculate ultrasound dose;

[0049] Figure 6a This is a schematic diagram of the method implemented according to the first embodiment of the present invention;

[0050] Figure 6b It is a diagram of the tissue layer relative to depth according to the method of the first embodiment;

[0051] Figure 6c It is a graph of MI relative to depth according to the first embodiment;

[0052] Figure 7a This is a schematic diagram of the method implemented according to the second embodiment of the present invention;

[0053] Figure 7b It is a diagram of the tissue layer relative to depth according to the second embodiment;

[0054] Figure 7c It is a result map of MI relative to depth according to the second embodiment; and

[0055] Figure 8 Provides the use of enhanced step acoustic wave action field The result of tumor-specific uptake of fluorescent dye after treatment. Detailed Implementation

[0056] Unless otherwise specified, all technical terms, symbols, and other scientific terms used herein are intended to have the meaning commonly understood by one of ordinary skill in the art to which this invention pertains. In some instances, for clarity and / or ease of reference, terms are defined herein with the meaning commonly understood, and the inclusion of such definitions herein should not necessarily be construed as representing significant differences beyond the common understanding in the art.

[0057] As used in this article, the term "ultrasound dosimetry" in the field of medical ultrasound technology describes the determination (e.g., measurement, calculation, and evaluation) of the ultrasound radiation dose to be delivered to target tissue to achieve the desired biological effect.

[0058] As used in this article, the terms “ultrasound irradiation” or “sound wave action” describe exposure to ultrasound or treatment with ultrasound.

[0059] As used in this article, the term "velocity of sound" refers to the group velocity and / or phase velocity and / or signal velocity of a longitudinal pressure wave.

[0060] As used herein, the term “ultrasound dose” or “ultrasound dosage” refers to the instantaneous, time-averaged, spatially averaged, time-integrated, and spatially integrated ultrasound parameters at a point or region, such as those defined in international standards for medical diagnostic ultrasound, IEC 62127-1, IEC 62359, and IEC 60601-2-37.

[0061] As used in this article, the term 'ACT bubble' or ' The word 'bubble' is used interchangeably and refers to a large activated bubble originating from ACT microbubble clusters after acoustic action via activated ultrasound.

[0062] In diagnostic imaging applications, there are many acoustic parameters used to quantify the applied ultrasound dose, such as mechanical index (MI), thermal index (TI), and intensity spatial peak temporal average (Ispta). Generally, therapeutic and diagnostic ultrasound therapy involves irradiating a target area of ​​a subject with ultrasound using a predetermined ultrasound dose delivered by a transducer located at or toward the target area.

[0063] The use of ultrasound, alone or in combination with contrast agents (e.g., microbubble compositions), for diagnostic applications is well established. There is now growing interest and development regarding the use of ultrasound for therapeutic applications. There is a need for ultrasound dosimetry for ultrasound- and microbubble-mediated drug delivery, ultrasound- and microbubble-mediated therapy, and ultrasound-mediated therapy. To effectively deploy the mechanical and thermal mechanisms involved in the application of ultrasound irradiation in therapy, it is important to optimally estimate the ultrasound dose delivered to the volume of tissue being treated.

[0064] The actual ultrasound dose delivered from the ultrasound source to the target region (a point estimate of the ultrasound dose) depends on the configuration of the source, the ultrasound transmission parameters, and the characteristics of the medium through which the ultrasound propagates from the source to the target region. Therefore, propagation through various tissue types and the presence of an ultrasound coupling bubble element can alter ultrasound parameters such as frequency, wavefront phase, and amplitude, and thus affect the true ultrasound dose to the target region.

[0065] This invention includes identifying and segmenting multiple tissue types in a target region, and estimating at least one ultrasound-coupled bubble element (e.g., microbubbles and / or...) in each of the multiple tissue types. The presence of bubbles is considered, and at least one propagation correction factor is calculated for calculating a more accurate ultrasound dose, and optionally, the ultrasound source providing the ultrasound dose is reconfigured.

[0066] Ultrasonic coupling bubble elements can be contrast agent microbubbles, Microbubble clusters, cavitation seed reagents, large bubbles and / or activated Bubble. In other words, ultrasound-coupled bubble elements are a form of microbubble technology. Large bubbles in microbubble technology have a diameter greater than 8 μm and can remain in the capillary bed of the target.

[0067] Sound cluster therapy It is a technology used for ultrasound-mediated local drug delivery. The process involves combining negatively charged microbubbles containing perfluorobutane (PFB) stabilized by a monomolecular phospholipid membrane with positively charged microdroplets containing perfluoromethylcyclopentane (PFMCP), also stabilized by a monomolecular phospholipid membrane. These microbubbles and microdroplets are then mixed to form small clusters held together by electrostatic forces. Microclusters can be co-administered with therapeutic agents. When subjected to acoustic stimulation with pulsed ultrasound (typically in clinical diagnostic protocols and at frequencies of 2 to 5 MHz), these clusters undergo an activation step, causing microbubble oscillation to transfer energy to droplets, resulting in the droplets' instantaneous vaporization and formation of larger bubbles, hereinafter referred to as... Bubble.

[0068] The spatial variation characteristics of the medium in the region through which ultrasound propagates include: attenuation, sound velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient. At least one propagation correction factor can be calculated based on one or more of these characteristics or their derivatives.

[0069] Ultrasonic dose is determined based on one or more established ultrasonic parameters as defined in IEC 62127-1, IEC 62359, and IEC 60601-2-37, such as: negative peak pressure, positive peak pressure, mechanical index (MI), thermal index (TI), spatial peak temporal average intensity (Ispta), spatial peak pulse average intensity (Ipa), spatial average temporal average intensity (Isata), and total acoustic power.

[0070] Figure 1 This is a flowchart of a point estimation method 100 for calculating ultrasound dose.

[0071] The method begins at 102, where a media property (MP) map of the target region of the object is obtained, where the MP map provides specific and distinct MP values ​​within the target region. The MP map is based on the specific composition and anatomy of the target region and / or the presence of other components. See below for reference. Figure 2 A more detailed description of MP graphs and example methods for obtaining MP graphs.

[0072] One example MP plot is an attenuation plot, which provides specific and distinct attenuation values ​​in the target region based on the specific composition and anatomy of the target region, as well as the presence of other components, particularly one or more ultrasound coupling bubble elements. Another example MP plot is a velocity plot, where changes in the mass density and bulk modulus of the varying medium through which the ultrasound travels affect the velocity of the ultrasound waves. The velocity plot provides specific and distinct velocity values ​​in the target region, based on the specific composition and anatomy of the target region, as well as the presence of other components. Another example is a phase plot, which can be a combination of a velocity plot and an attenuation plot. In a preferred embodiment, two or more individual MP plots of attenuation, velocity, nonlinearity coefficient, and phase are combined to provide a combined media property (CMP) plot of the target region.

[0073] At 104, a dose-defined propagation path (PP) is approximated (projected). In a first instance, this is achieved by depicting a line-of-sight from the source to the target tissue. Alternatively, this is achieved by tracing multiple lines of sight, each originating from each of the elements in the transducer array. In a preferred instance, the PP is an acoustic model of the emitted ultrasonic field. Ultrasound is typically applied to the outer or inner surface of the body, or generated inside the body by inserting a transducer (e.g., via a laparoscopy). As the wave travels along the path through each component, the ultrasound will experience different absorption, scattering, refraction, and aberration.

[0074] At 106, the MP value on the PP can be calculated (i.e., integrated) to calculate 108 the unique propagation correction factor (PCF) of the PP through the specific target area. In some instances, the PCF is complex-valued.

[0075] In 110, the MI or TI generated by the ultrasound field along the PP is estimated based on the pre-selected set of ultrasound parameters and PCF.

[0076] The pre-selected ultrasound parameter set can be modified based on the initial MI or TI estimate and used with PCF to give a modified / enhanced MI / TI estimate.

[0077] The further optimized parameter set can be used with PCF to iteratively converge to the optimal estimate of MI / TI. Therefore, the decayed temporal peak rarefaction pressure P... r，α The ultrasonic field emitted by the source can be defined at any point by the following:

[0078] P r,a =P r ·10 -α / 20 Equation 2

[0079] The optimal MI can be calculated using a modified version of Equation 1, where α is replaced by the attenuation correction factor (α). CF )

[0080] α→α CF

[0081] and

[0082]

[0083] Where N t It is the number of different tissue types between the transducer and the target depth, Δd i It is the tissue layer thickness per unit depth for the corresponding tissue type i, and α i It is the tissue layer attenuation coefficient per unit depth, expressed in dB per unit depth.

[0084] Alternatively, the attenuation coefficient can be modeled as a spatial variation function. in It is spatial location, so that

[0085]

[0086] Therefore, in the instance where PCF is an attenuation correction factor, the attenuation correction factor can be used in the adjusted equation involving said attenuation factor, ultrasonic operating frequency, and mechanical index:

[0087]

[0088] in And it is included to provide MI, f as a dimensionless parameter. awf It is the operating frequency of the sound; and It is the rarefaction pressure of the decay time peak at the target region, which depends on the decay correction factor.

[0089] In step 112, the calculated MI can be transmitted to an ultrasound source to automatically adjust the output settings of the ultrasound source in order to deliver a specific ultrasound dose to the tissue volume to be treated. Alternatively, the MI can be displayed and the user can manually adjust the settings of the ultrasound source, wherein the displayed MI value is calculated and updated in real time via method 100.

[0090] Steps 104 to 110 can be performed in real time during ultrasound imaging and / or treatment in continuous loop 103. For example, if the ultrasound source / transducer is moved, the PP changes and the PCF is recalculated. Movement of the ultrasound source can be detected using hardware and software for spatial tracking of one or more of the movement, orientation, and posture of the ultrasound source. Such tracking can also be combined with co-registered images from other imaging modalities, including CT and MRI. In another instance, the PCF is recalculated when the target area moves due to other external factors, such as object movement or respiratory motion.

[0091] In one instance, the PCF is determined by an attenuation correction factor and a phase change correction factor. In this case, steps 104 to 110 can be performed in real time in consecutive loops during ultrasound imaging and / or treatment. For each loop iteration, one of the factors is recalculated based on an image-specific metric, such as the point spread function of a single point scatterer in the target region. One instance of such a point scatterer is activated. cluster.

[0092] Figure 2 This is a flowchart of method 200 for creating a unique (C)MP map for a specific target region. Method 200 provides step 102 of method 100. The (C)MP map consists of segments with known volumes / areas having associated MP values ​​for each segment. The MP map can be an attenuation map, sound velocity map, shear wave velocity map, acoustic impedance map, dispersion coefficient map, nonlinearity coefficient map, or a map of parameters derived from these characteristics. The MP map can be a combination of two or more of the above-mentioned CMP maps.

[0093] At step 202, an image of the target region in the subject is obtained. The target region is the target area and the surrounding area. The target region is the area in which an ultrasound dose is to be delivered. For example, the target region could be a metastasis in the subject's liver, and the surrounding area could be healthy liver, muscle, fat, and other adjacent organs. Images of the target region can be obtained in a variety of different ways. For example, many images of the target region may have been taken during a health survey of the subject. Preferably, the images of the target region are obtained using 3D imaging data; however, the use of 2D imaging data is also possible.

[0094] A scan of the target area may already exist, particularly a volume scan, such as magnetic resonance imaging (MRI), computed tomography (CT), or an earlier ultrasound scan that can provide an image of the target area in method 100. Alternatively, a new scan (e.g., MRI or CT scan) can be performed on the target area to provide an image of it. Another method for obtaining an image of the target area is by utilizing an ultrasound source. The ultrasound source used in method 100 may initially be used to obtain an ultrasound scan of the target area by applying sound waves to it. Until a method for accurately estimating the calculated radiation dose is found, the pressure amplitude of the ultrasound waves used for the purpose of obtaining an image of the target area can be via 0.3 dB cm⁻¹. -1 MHz -1 The conservative reduction factor is determined to avoid overexposure. In some instances, ultrasound scans are acquired in real time. In yet another instance, real-time ultrasound scans are overlaid on pre-scanned images to enhance information about the target region. If not already known, imaging may include steps to identify the target volume. Imaging may also include additional steps to identify tumors or metastases within the target region.

[0095] refer to Figure 3a This shows an example image 300 of the target region 301 of the object, which is an instance of an image to be processed by an image processor. Figure 3a The images in the example were obtained via ultrasound scanning.

[0096] At 204, image processing is performed on the image of the target region to identify different components and the image is segmented into different categories based on the identified components 206. The components to be identified and classified can be different tissue types in both healthy and diseased states. To give only a few non-limiting examples, different tissue types can include soft tissues (e.g., fat, muscle, tendons, and ligaments) and hard tissues (e.g., bone). Metastasis can also be identified and classified differently from other components. The target region is segmented in this way because each component can affect ultrasound differently.

[0097] Figure 3b It is segmented into different components by the image processor. Figure 3a Example image 300 for target region 301. Figure 3b In the examples, the identified components were muscle 304, metastasis 306, healthy liver 302, and aorta 308.

[0098] In step 208, for each component in the target region, at least one of the relevant category-specific MP values ​​for the component, such as attenuation and / or sound velocity, is retrieved from the database and assigned to that component. An example database is shown in Table 1 below.

[0099] Table 1

[0100]

[0101] Figure 3c An example MP map in the form of an example attenuation map 500 of the target region 301, consisting only of its component parts, is shown. The attenuation map 500 is a graphical representation of a set of data points containing the 3D / 2D coordinates of each segment and the corresponding attenuation values ​​within those segment coordinates. The attenuation map 500 is divided into segments representing the region of healthy liver 502, segments representing the region of muscle 504, several segments representing the region of metastasis 506, and segments representing the region of aorta 508. The attenuation map 500 can be stored in a database for access via ultrasound scanner software. The attenuation map can be stored in long-term or short-term data storage for later retrieval.

[0102] The method incorporates a correction to the unique PCF based on the presence of one or more ultrasound-coupled bubble elements in at least some tissue layers 210.

[0103] exist Figure 2 In a specific instance, in step 210a, the correction for PCF is calculated based on the presence of microbubbles (e.g., contrast agent microbubbles) in at least one component in the target region.

[0104] When ultrasound is used to treat metastases, contrast agent microbubbles are typically present in the tissue of the target region because the contrast agent is usually added during the preceding ultrasound image capture phase. Adding contrast agent to this region alters its acoustic properties. Depending on the frequency of ultrasound scattering, the absorption, reflection, and refraction characteristics of the region can be altered. For example, a decrease in density at the interface between the contrast agent and surrounding tissue causes ultrasound to be strongly scattered and reflected back to the ultrasound probe. This acoustic characteristic is known as backscattering and results in higher contrast between different regions on the captured ultrasound image. Because the contrast agent alters the acoustic properties of the region, it can significantly affect the derating factor of the ultrasound pulses applied to the target region. Therefore, additional corrections are needed for the contrast agent and its amount to improve the estimation of the ultrasound dose delivered to the target region. At least four commercially available diagnostic ultrasound imaging (contrast) agents are available; Sonazoid... TM Definity TM Optison TM and SonoVue TMThese agents are also used in clinical studies for therapeutic applications. These agents are 'free-flowing' tracers because they are small enough to circulate in the bloodstream without stagnating in capillaries. The term 'microbubble' or 'conventional angiography microbubble' is used in this article to describe microbubbles with a diameter of 0.2 to 10 μm, typically with an average diameter of 2 to 3 μm. Other microbubble technologies are also moving towards clinical application, such as Acoustic Cluster. (Exact ) and SonoTrans TM (Oxsonics TM ).

[0105] In a specific instance where the correction factor is an attenuation correction factor to calculate the additional attenuation due to the presence of the contrast agent, the contrast agent characteristics, in terms of attenuation per unit concentration, can be looked up or calculated from in vivo experiments. For example, the in vivo environment could be whole blood or 5% human serum albumin at 37°C and 85% gas saturation. Ultrasound at a predetermined frequency is then applied to the contrast agent-containing environment. The median intensity (MI) acting on this environment can be measured. The measured MI and the applied ultrasound frequency can be used to calculate the attenuation per unit concentration of the contrast agent microbubbles.

[0106] Next, the blood volume of the subject is approximated, for example, a 70 kg subject has approximately 5 liters of blood. The cardiac output of the subject is then estimated, for example, 5 liters of blood per minute for the 70 kg subject. For each segmented tissue type, typical values ​​for blood volume not in large compliant vessels also need to be estimated. For example, the liver has approximately 15% blood volume, and resting skeletal muscle, skin, and adipose tissue have only a fraction of that percentage of blood volume compared to the liver. A table of typical arrival times after intravenous administration of the contrast agent for each component category is then required. For each component category, a table of concentration-time curves for intravenously administered free-flowing contrast agents is also required. Tables providing values ​​for concentration-time curves of intravenously administered free-flowing contrast agents are available in the art.

[0107] For freely flowing microbubbles, the dynamics of bubble inflow and wash-out from various organs are well known and have also been studied in activated microbubbles. Bubbles were studied. For example, in a dog model, backscatter intensity was measured via ultrasound imaging. The half-life of the bubble is 70 seconds. Figure 4a This shows the free-flowing microbubbles of Sonazoid and... A typical normalized backscattering intensity curve of a bubble. Vortices accumulate in the liver over time due to their activation. Sonazoid influx is faster and decreases rapidly as vesicles are partially washed out of the liver. Some vesicles are taken up by Kuppfer cells in the liver, resulting in a residual concentration after washing is complete. Similar curves can be created for other organs, where the absence of Kuppfer cells leads to… The injected free-flowing component follows the dashed line 402. Figure 4b It shows the use of Figure 4a The backscattered intensity curve represents the actual concentration as a function of time. The attenuation in each tissue type will depend on the time-varying curves, such as these. These curves can be predetermined or calculated for each patient, for example, by parameterizing a tissue-type-specific function using the injection duration τ and tissue-specific washout time θ, as shown in the following equation.

[0108]

[0109] Similarly, by approximating the above integrals...

[0110]

[0111] These models can also be used as parameterized models in model-based estimation schemes, where parameters are estimated based on backscatter information collected from each segment during treatment and a concentration-based prior model. The calculated concentration is used to calculate the attenuation experienced by the ultrasound pulse as it passes through the tissue structure between the probe and the target tissue at each time point. For each time point, the configuration of the ultrasound source is updated to achieve the desired in-situ mechanical index in the target lesion, for example, by adjusting the amplitude or frequency of the source's excitation.

[0112] Therefore, based on the attenuation per unit concentration in each component category, blood volume, time to arrival after administration, and concentration over time, the additional attenuation caused by the presence of the contrast agent can be calculated and added to at least one category attenuation value, preferably each category attenuation value associated with the component contrast agent concentration.

[0113] The peak attenuation of ultrasound pulses caused by contrast agent microbubbles was calculated based on data provided in the database. The peak attenuation caused by free-flowing contrast agent microbubbles can be approximated using a formula that calculates the concentration of free-flowing microbubbles for each tissue type. The patient's weight M, contrast agent injection dose per body weight D, cardiac output Q, and organ blood volume fraction R are used. B The injection duration τ and activation efficiency η, and the peak dose can be calculated as follows:

[0114]

[0115] After calculating the correction caused by the presence of the contrast agent, the method may then proceed to step 214, where an MP map of the target region is generated.

[0116] As an alternative or supplement, the method may proceed to step 210b, such that treatment is performed by at least one type of acoustic cluster. The presence of bubbles necessitates additional corrections.

[0117] exist In this process, clusters of charged microbubbles attached to oil droplets with opposite charges are injected into the bloodstream. Ultrasound is applied to induce vibration of the microbubbles and transfer energy to the clusters, causing the particles within the clusters to fuse into single particles. The oil then vaporizes into the gas contributed by the microbubbles, creating expanded microbubbles. (Bubble). Apply to The ultrasonic pulse of the bubble caused a large gas Bubble vibration.

[0118] More specifically, the formulation is a cluster dispersion of droplets and microbubbles, wherein the median diameter of the droplets is 2 to 3 μm, stabilized by a lipid membrane with a net positive surface charge; and the median diameter of the microbubbles is 2 to 3 μm, stabilized by a lipid shell with a negative surface charge. It is the opposite charges on the surfaces of the oil droplets and microbubbles that enable the formation of small clusters through electrostatic interactions. These clusters are approximately 5 μm in diameter and flow freely within the vascular system. Upon exposure to medical diagnostic ultrasound frequencies, the microbubbles within the clusters oscillate, and the particles fuse into a single entity, while the oil vaporizes to produce enlarged microbubbles. Bubble).

[0119] The frequency of medical diagnostic ultrasound is 1 to 15 MHz, preferably 2 to 10 MHz, and more preferably 5 MHz. Even with the short imaging pulses, low MI (e.g., less than 0.1 MI), and low duty cycle commonly used in medical imaging systems, the oil droplet-microbubble fusion process can be achieved. Once fused, the oil droplet vaporizes into the gas that forms the bubble nucleus, resulting in a bubble with a median diameter of 20 to 30 μm. The oil has low water solubility and a low diffusion length, which allows the bubble to remain for several minutes before dissolving. After intravenous administration, the cluster flows in the bloodstream and, upon application of an ultrasound field (activated ultrasound), forms a large cluster (activated ultrasound). Bubbles, spatially, are only generated within tissues irradiated with ultrasound. The bubbles are large enough to remain in the first capillary bed they flow into and persist for several minutes. During this time, a lower frequency ultrasound field (enhanced ultrasound) is applied at low MI to drive mechanical oscillations that drive biomechanical mechanisms that can produce therapeutic effects and / or enhance drug extravasation and delivery. The lower frequency of the applied ultrasound field is 0.1 to 1 MHz, preferably 0.3 to 0.6 MHz, more preferably 0.5 MHz.

[0120] The preferred MI is 0.1 to 0.4. Therefore, for the use of Treatment using this technology requires careful control of the clusters generated under high-frequency (activation ultrasound) conditions. The ultrasonic field of the bubble and the ultrasonic field at a low frequency (enhanced ultrasound) driving the mechanical action for treatment are combined to achieve the best therapeutic effect.

[0121] Due to use The ultrasound dose applied during treatment requires a certain energy lower limit, and undesirable biological effects and tissue damage must still be controlled; therefore, accurate estimation of the ultrasound dose is crucial. Treatment is especially important. For example, the conservative lower limit of the head reduction factor in current ultrasound control standards may not provide sufficient [treatment / treatment]. Treatment outcomes, and the need for target region-specific PCF, are important. It is particularly useful for treatment.

[0122] Because activation ultrasound is high-frequency and enhancement ultrasound is low-frequency, therefore The treatment process involves three components, each affecting media properties (i.e., attenuation, sound velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient of the target region). Therefore, MP correction is preferably calculated for each component. The first component is microbubbles generated in the presence of high-frequency activated ultrasound. The second component is generated in the presence of high-frequency activated ultrasound. Bubble. The third element is present in the presence of low-frequency enhanced ultrasound. Bubble. Preferably, MP correction is calculated for each component category for each of the three elements mentioned above. Therefore, for Treatment targets tissue type, the number of free-flowing microbubbles, and Both bubble generation and lifespan can potentially be corrected for therapeutically, by altering ultrasound dosimetry parameters during both the high-frequency ultrasound activation step and the low-frequency ultrasound therapy enhancement step.

[0123] In calculating due to During the additional MP correction caused by bubbles, an optional intermediate step is to disrupt the free-flowing microbubbles with high-amplitude and high-power diagnostic imaging pulses. These high-amplitude and high-power diagnostic imaging pulses can be incorporated into the diagnostic scanner as part of a 'flash' sequence or a 'decorrelated' imaging mode. The MI of such pulses is typically 0.7 or higher. Such pulses can be used to more effectively image free-flowing microbubble components or to remove free-flowing microbubbles from the scan plane or tissue volume. However, such high-intensity pulses do not disrupt the free-flowing microbubbles. Therefore, these imaging pulses can be used to remove free-flowing microbubble components while simultaneously... The bubble components are unaffected. Therefore, the need for MP correction due to the presence of contrast agents can be reduced or even eliminated. For example, by destroying almost all free-flowing microbubbles before applying a therapeutic dose of ultrasound to the treatment area, attenuated components from free-flowing microbubbles can be removed, up to and including completely.

[0124] In order to calculate Bubble-related MP correction first estimates the amount of fluid retained in the capillaries. The number of bubbles. Estimate or query the total blood volume and cardiac output values ​​of the object. Then, calculate the estimated perfusion rate for each component category. The delivery to the tissue can then be calculated by multiplying the cardiac output fraction corresponding to the perfusion volume of the tissue type by the activation yield of the cluster. The number of bubbles. The activation yield was quantitatively calculated to be 24% in a large animal dog model. Furthermore, the presence of [a certain number of bubbles] as a function of time in each category of components. The reduction in the number of vesicles can be estimated or queried from a database. This can be achieved by measuring the number of vesicles in different tissue types. Estimate by the lifespan of the bubble The reduction in time relative to the soaking time.

[0125] Table 2 shows an example database that provides component-specific information, where only two frequencies are shown for simplicity.

[0126] Table 2

[0127]

[0128] Where MP is attenuation, contrast-modal imaging ultrasound is suitable for estimating the attenuation of free-flowing contrast agents, and basic B-mode imaging is suitable for estimating the attenuation due to... Bubble-induced attenuation. This is due to the following reasons.

[0129] Contrast imaging modalities will be more specific for backscattered signals generated by free-flowing microbubble components (e.g., commercially available microbubble contrast agents). These imaging modalities utilize the nonlinear behavior of bubbles and extract nonlinear oscillation features to form images more dominated by microbubble components and selectively suppress backscattered signals from tissue components. These microbubbles are strongly coupled to diagnostic imaging pulses because these pulses have frequencies of approximately 2 to 10 MHz, close to the mechanical resonance of the bubble system. Therefore, bubble oscillations are significantly increased compared to acoustic effects with non-resonant pulses. In contrast, The resonant frequency of the bubble is approximately 300 kHz. This resonant frequency is significantly lower than the diagnostic imaging frequency range. At diagnostic imaging frequencies, The bubble is subjected to above-resonance acoustic waves, and in this state, the bubble's scattering efficiency is much higher than that of the contrast agent, where scattering efficiency is defined as the ratio of scattering to absorption cross-section. Because... The increased bubble size also results in significantly more backscattering (increased scattering cross-section compared to free-flowing reagents), making them easier to visualize in basic B-mode. In this imaging modality, the tissue contrast enhancement during basic B-mode imaging compared to contrast agents is due to… The bubble component is dominant. Therefore, contrast-modal imaging ultrasound is preferred for estimating the attenuation of free-flowing contrast agents, and basic B-mode imaging is preferred for estimating the attenuation due to... Bubble-induced attenuation.

[0130] Or, another one. Specific imaging modalities can be used to estimate the effects of... Bubble-induced attenuation.

[0131] Query activated The attenuation values ​​of clusters and their microbubble components over the frequency range. Table 3 provides an example of such a database, where only two frequencies are shown for simplicity. The attenuation values ​​are proportional to the concentration.

[0132] Table 3

[0133]

[0134] Calculated based on the data provided in the database The injection of clusters causes additional attenuation of the ultrasound pulse peak. For example, by free-flowing... The peak attenuation caused by microbubble clusters can be approximated using a formula that calculates the concentration of free-flowing vesicles for each tissue type. This is achieved using the patient's weight M and the concentration of free-flowing vesicles per unit body weight. Injection dose D, cardiac output Q, organ blood volume fraction R BThe peak dose can be calculated based on the injection duration τ, the proportion of free-flowing bubbles r in the injected formulation, and the activation efficiency η.

[0135]

[0136] Similarly, each tissue type can be calculated using the following formula. Peak concentration of the bubble, where V is the total blood volume.

[0137]

[0138] Using additional information and assigning values ​​to different segments of the identified tissue type, the expected maximum attenuation for a given dose can be calculated, as shown in Table 4, where a dose of 40 μL / kg is used to calculate the attenuation from microbubbles and... The decay of foam components.

[0139] Table 4

[0140]

[0141] Once the MP value for each category specificity is adjusted to... If the treatment process is corrected to take into account up to three additional elements specific to the corresponding category and is assigned to each corresponding component, the method may then proceed to step 214, where a (C)MP diagram is generated.

[0142] Microbubbles and The presence of bubbles can affect sound velocity and phase changes. Similar to adding additional attenuation to each component in a segmented target region, components in an MP map (e.g., a sound velocity map or a phase change map) can also be affected by microbubbles and... The presence of bubbles and adjustments made in a manner similar to additional attenuation.

[0143] Precise target control is of particular importance. Bubble and aim to make The ultrasonic dose for bubble oscillation is crucial because if the ultrasonic dose is far below the effective dose range, the bubble will not oscillate sufficiently. Insufficient bubble oscillation will prevent the desired effect from being achieved. Therapeutic effects. However, ultrasound doses that are too high above the effective dose range... If the oscillations are too strong, it can potentially lead to undesirable biological effects. These undesirable biological effects can include damage to blood vessels and disruption of capillary walls. This can lead to blood flow obstruction and result in conditions worse than without oscillations. Therapeutic chemotherapy delivers smaller doses of chemotherapy to the tissue site. Therefore, there are methods suitable for driving drug delivery and achieving the desired results. The therapeutic ultrasound energy window. Using the method of the invention described herein, this ultrasound energy (ultrasound dose) window can be controlled more easily and reliably, regardless of the anatomy and composition of the object and the imaging and / or... The presence of other components in the treatment.

[0144] Once (C)MP is generated, method 200 is completed, and according to method 100, the process can proceed to step 104, where the attenuation value on PP is calculated to calculate the PCF, including additional contrast agent correction for the bubble, such as including additional contrast agent attenuation and / or The attenuation correction factor includes bubble attenuation.

[0145] Figure 5 This is a schematic diagram of a system 500 for both generating a (C)MP map of the target region of an object (method 200) and a point estimate for calculating ultrasound dose (method 100). System 500 includes a computer processor 205, an ultrasound source 504, an image processor 506, a database module 508, and a data storage module 510. As indicated by dashed lines 502a to h, each module of system 500 communicates data with each of the other modules directly or via one of the other modules. The data storage module 510 contains computer-readable instructions 502, which, when executed on the computer processor 205, perform the tasks described later. For simplicity, the computer-readable instructions, when executed on the computer processor, are referred to as a 'program'.

[0146] First, the program instructs the image processor module 506 to process the image of the target region of the object to segment the target region into its different components and classify the components. The image processor 506 can segment and classify the different components of the target region by identifying the boundaries between different patterns in the image and analyzing the patterns within these boundaries to find the closest match by comparing them with patterns of known tissue types. Over time, each processed image and associated attenuation map data can be used as historical data in the system 500, accumulating more accurate segmentation and classification capabilities of the image processor in the form of machine learning.

[0147] The program then instructs access to the MP value database 508, queries the MP value for each of the identified categories, and assigns the appropriate value to the corresponding identified component. Table 1 shows an example of a database containing ultrasound parameter (MP) values ​​for each of the identified categories (e.g., tissue types). In this example table, attenuation values ​​for skin, muscle, fat, parenchyma, and pancreas are provided at a first frequency of 0.5 MHz and a second frequency of 2 MHz. Preferably, the MP value database contains ultrasound parameter values ​​across a frequency range. Such data is publicly available in the art.

[0148] Preferably, database module 508 further includes a contrast agent microbubble (or other ultrasound coupling bubble element) database 516 containing additional correction (e.g., attenuation) values ​​per unit concentration for different contrast agents. Database 516 may also contain the following queryable values:

[0149] - Blood volume of different body weights;

[0150] - Estimation of cardiac output for individuals with different body weights;

[0151] - Typical values ​​for blood volume in each component category;

[0152] - Typical arrival times for each component category after intravenous administration of different contrast agents; and - Concentration-time curves for free-flowing contrast agents administered intravenously for each component category.

[0153] The program can query the required values ​​from another database 516 to estimate additional corrections, such as additional attenuation, based on the presence of contrast agent in each category. Then, before the program performs the step of calculating the PCF on the PP, the additional corrections can be added to the MP value of each corresponding component, such as the attenuation value.

[0154] As mentioned above, the additional peak attenuation of the ultrasound pulse caused by contrast agent microbubbles can be calculated based on data provided in the database. The peak attenuation from free-flowing contrast agent microbubbles can be approximated using Equation 8, which calculates the free-flowing bubble concentration for each tissue type.

[0155] In existence In the case of treatment, database module 508 may include database 518, which contains information for estimating the effects of treatment. The additional correction value caused by the three components of the treatment process.

[0156] Database 518 may also contain the following queryable values:

[0157] -Total blood volume in individuals of different weights;

[0158] - Cardiac output of individuals with different body weights;

[0159] - Perfusion rate for each component category (Table 2, row 4);

[0160] - Activation yield of microbubble clusters (Table 2, row 8);

[0161] -The existence of each category component as a function of time The decrease in the number of bubbles (Table 2, row 7); and

[0162] -Different organizational types Bubble lifespan (Table 2, row 6).

[0163] As an alternative to querying a database, a patient's total blood volume and cardiac output can be determined through patient examination or by using approximations. For example, blood volume and cardiac output can be estimated based on the patient's weight.

[0164] The program can calculate based on the data provided in the database. The injection of clusters causes additional attenuation of the ultrasound pulse peak. For example, from free flow... The peak attenuation of microbubble clusters can be approximated using Equation 9, which calculates the free-flowing bubble concentration for each tissue type. (From activated...) The peak decay of the bubble can be approximated using Equation 10.

[0165] The program can query the required values ​​from another database, 518, to determine the values ​​based on each category. The presence of treatment is used to estimate additional corrections. Then, before the procedure performs the step of calculating the PCF on the PP, the estimated additional corrections are added to the MP value of each corresponding component.

[0166] Therefore, a result depends on the geometry and tissue type, the presence of the contrast agent, and / or The existence of bubbles is represented by a C(MP) graph and stored in the data storage module 510.

[0167] Values ​​in database module 516 can also be queried and used to estimate corrections to the following media properties due to the presence of microbubbles: sound velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient, or derived properties depending on the desired MP plot. Additional values ​​in database module 518 can also be queried and used to estimate corrections due to the presence of microbubbles. The presence of bubbles causes additional corrections to the aforementioned media properties. Therefore, this can produce results depending on geometry and tissue type, the presence of the contrast agent, and / or... The corresponding sound velocity diagram, shear wave velocity diagram, acoustic impedance diagram, nonlinear compressibility coefficient diagram, and dispersion coefficient diagram (as well as any derived characteristic diagrams) of the bubble are stored in the data storage module 510.

[0168] Database 508 and data storage module 510 may be contained in the same or separate hardware device. Alternatively, database 508 and / or data storage module 510 may be contained in a cloud-based platform.

[0169] Once the MP (e.g., attenuation) map has been generated, the program then plots the PP from the ultrasound source 504 to the target treatment area. The locations of the ultrasound source 504 and the target treatment area are identified by the program or entered manually by the user. The program then aggregates the MP (e.g., attenuation) values ​​for each component on the PP to generate the PCF, such as the PCF for attenuation.

[0170] The program uses PCF (e.g., attenuation) to calculate the associated MI caused by a specific PP, indicating the ultrasound dose delivered to the target area. The program generates a CMP map, using several media properties to calculate one or more PCFs to determine the associated MI and ultrasound dose.

[0171] The calculated path-specific MI / ultrasound dose is transmitted to the ultrasound source 504 (i.e., the ultrasound scanner). The ultrasound source can be adjusted based on the calculated MI / ultrasound dose for the target region and the desired US dose.

[0172] In some embodiments of the invention, system 500 is configured to perform the calculation of a unique path-specific PCF and thus the calculation of MI / ultrasound dose values ​​on a continuous basis. In this way, the ultrasound dose can be tracked as the ultrasound source 504 moves relative to the target region and / or adjusts the ultrasound frequency. If the ultrasound source remains within the target region, system 500 does not need to generate a new (C)MP (e.g., attenuation) map, thus saving time and processing power.

[0173] As mentioned above, the large difference (reduction) between the actual tissue peak negative pressure and the tissue peak negative pressure given in the standard definition of MI makes this definition of MI unsuitable for some ultrasound applications. In particular, it is suboptimal when point estimation of peak sparseness is required for therapeutic applications. This is due to the simplified definition of MI, which includes a simple power-law dependence of attenuation and a single conservative value for the tissue (for a safety upper limit). Therefore, the recommended MI output for diagnostic imaging may not be the optimal output for treatment. Therefore, the method of the present invention instead takes into account the propagation medium composition to estimate the ultrasound dose that should be delivered for treatment. Thus, the more accurate method according to the invention involves the following steps: classifying the tissue type present between the ultrasound transducer and the volume of tissue to be treated, identifying bubbles (contrast agents, etc.) Microbubble clusters and / or The role of ultrasound in the corresponding tissue type, and in order to identify and limit the ultrasound dose to be used in treatment.

[0174] PCF (Positive Frame Flow) is required to adapt to the specific environment in which the ultrasound field travels from the ultrasound source to the target region. As mentioned above, this specific environment depends on the anatomy and composition of the object and the conditions used for imaging and / or... The presence of other components in the treatment.

[0175] In this context, MP is a specific instance of attenuation, where the currently conservative, lower attenuation factor is used to effectively treat obese subjects. Treatment presents particular challenges. This is because the extra fat in the ultrasound pathway leads to above-average attenuation of the ultrasound field delivering the sound waves, and thus can result in insufficient ultrasound dose delivered to the target treatment area. Because the methods described herein can be tailored to specific compositions in terms of tissue type and geometry, they are particularly suitable for ultrasound treatment of obese individuals.

[0176] Example

[0177] The first example of the method of the present invention described above is performed in Figures 6a to 6c As shown in the image.

[0178] Figure 6a A cross-section of the abdomen 610 of a human subject is shown. The cross-section includes muscles 603, liver 604, blood vessels 605, kidneys 606, bones 607, spleen 608, intestines 609, stomach 610, and pancreas 611. An ultrasound transducer 600 is positioned to contact the external skin surface of the abdomen 610 of the human subject. The ultrasound transducer 600 emits an ultrasound field along an acoustic path 601 toward a target depth indicated by a crosshair 602. As shown, the acoustic path 601 passes through several different types of organs between the ultrasound transducer 600 and the target 602, namely skin, muscles 603, fat, liver 604, intestines 609, and pancreas 611.

[0179] exist Figure 6a In the example, acoustic path 601 is shown as a single linear path from a discrete point of transducer 600 to target 602. However, as mentioned above, acoustic path can consist of multiple ultrasonic rays having their respective paths.

[0180] Figure 6b The attenuation coefficient is shown relative to along Figure 6a A graph showing the depth of acoustic path 601, where the attenuation coefficient depends on the type of tissue traversed at that depth. Figure 6b In the examples, the attenuation coefficient is 0.4 at a depth of 0 cm to approximately 0.5 cm, which is the attenuation coefficient for skin. The attenuation coefficient is 0.3 at depths of approximately 0.5 cm to 1.0 cm and 2.0 cm to 2.5 cm, which is the attenuation coefficient for fat. The attenuation coefficient is 0.5 at a depth of approximately 1.0 cm to 2.0 cm, which is the attenuation coefficient for muscle. The attenuation coefficient for liver is approximately 0.35 at a depth of approximately 2.5 cm to 5.5 cm. At a depth of 5.5 to 6.5 cm, the sound path passes through the intestine, where the attenuation coefficient is approximately 1.5. The final tissue type that the ultrasound field passes through before reaching the target is pancreatic tissue with an attenuation coefficient of approximately 0.25 dB / cm.

[0181] Figure 6cA graph showing the obtained mechanical index (Equation 5) relative to the depth along the acoustic path 602 is presented. Figure 6c In the examples (for) Figure 6b (The medium), the solid line represents the mechanical index adjusted for a standard derating of 0.3 dB / cm / MHz, and the thick solid line with dots represents the mechanical index adjusted for medium-specific attenuation. Therefore, when α→α CF At that time, the thick solid line with dots represents the pressure according to Equation 5. At the target, the mechanical index is approximately 0.15.

[0182] The second example of the method of the present invention described above is performed in Figures 7a to 7c As shown in the image.

[0183] Figure 7a A cross-section of the abdomen 710 of a human subject is shown. The cross-section shows tissues from muscle 703, liver 704, fat 705, and skin 706. An ultrasound transducer 700 is positioned to contact the external skin surface of the abdomen 710 of the human subject. The ultrasound transducer 700 emits an ultrasound field along an acoustic path 701 toward a target depth indicated by a crosshair 702. As shown, the acoustic path 701 passes through several different types of organs between the ultrasound transducer 700 and the target 702, namely skin 706, fat 705, muscle 703, and liver, all of which contain microbubbles and Bubble.

[0184] Similar to Example 6a, in Figure 7a In the example, acoustic path 701 is shown as a single linear path from a discrete point of transducer 700 to target 702. However, as mentioned above, acoustic path can consist of multiple ultrasonic rays having their respective paths.

[0185] Figure 7b The attenuation coefficient is shown relative to along Figure 7a A graph showing the depth of acoustic path 701, where the attenuation coefficient depends on the type of tissue traversed at that depth. Figure 7b In the example, the attenuation coefficient was 0.96 dB / cm at a depth of approximately 0 cm to 0.5 cm, indicating the presence of microbubbles and The attenuation coefficient of the vesicles on the skin. The attenuation coefficient is 0.37 dB / cm at depths of approximately 0.5 cm to 1.0 cm and 2.0 cm to 2.5 cm, indicating the presence of microbubbles and... The attenuation coefficient of the fat in the vesicles. The attenuation coefficient is 0.41 dB / cm at a depth of approximately 1.0 cm to 2.0 cm, indicating the presence of microbubbles and... The attenuation coefficient of the muscle in the microbubbles. The attenuation coefficient is 0.71 dB at a depth of approximately 2.5 cm between the target depth (approximately 5.0 cm) and the depth of the target (502), and this is observed in the presence of microbubbles and... The attenuation coefficient of liver tissue in the blister.

[0186] Figure 7c A graph showing the obtained mechanical index relative to the depth along the acoustic path 702 is presented. Figure 7c In the examples (for) Figure 7b The thick solid line with dots represents the mechanical index adjusted for medium-specific attenuation, while the solid line represents the mechanical index adjusted for standard attenuation (0.3 dB / cm / MHz). At target depth, the mechanical index is approximately 0.15.

[0187] According to Figures 6a to 6c Example 1 and according to Figures 7a to 7c Example 2 illustrates the correlation between pressure and tissue type, as well as the presence or absence of bubbles in the tissue.

[0188] As an example, the target area is metastatic lesions located in the patient's liver. The patient receives treatment consisting of chemotherapy drugs administered as an infusion, and through a single injection... Clusters of ultrasound are activated and enhanced at the target lesion site to enhance treatment. For example... Figure 6a and Figure 7a As shown, therapeutic ultrasound is provided from an ultrasound scanner with a connected ultrasound probe positioned to contact the skin on the patient's abdomen. Prior to treatment, a preferred probe placement is determined based on the patient's ultrasound imaging. Once the preferred placement is determined, the tissue type present between the probe and the target lesion is identified. This process can be accomplished using a segmentation algorithm of trained artificial intelligence with access to ultrasound scanner data. One or more lines of sight are drawn from the probe surface to the target lesion, and the thickness of each segment along these lines is calculated. Typically, in this case, the ultrasound field emitted by the probe passes through layers of skin, fat, muscle, and liver parenchyma before reaching the target lesion. For each tissue type, the ultrasound scanner determines the tissue perfusion by querying a database... Bubble lifespan half-life of the bubble The bubble activation yield and ultrasonic attenuation values ​​within the frequency range are used to create a medium property map. Table 2 provides an example of such a database.

[0189] In addition, query activation The attenuation values ​​of clusters and their microbubble components over the frequency range. Table 3 provides an example of such a database, where only two frequencies are shown for simplicity. The attenuation values ​​are proportional to the concentration.

[0190] A patient's total blood volume and cardiac output can be determined through patient examination or by using approximations. For example, blood volume and cardiac output can be estimated based on the patient's weight. In this example, the patient's weight is 70 kg and is provided as input to the ultrasound scanner. The algorithm uses this figure to calculate a blood volume of 4.6 L and a cardiac output of 5 L / min. The clusters are injected over a 30-second timeframe, so for the first time through the circulatory system, the dose is mixed in a limited pool of blood.

[0191] Calculated based on the data provided in the database Additional peak attenuation of the ultrasound pulse caused by cluster injection. For example, peak attenuation from free-flowing microbubbles can be approximated using Equation 9.

[0192] Similarly, calculations can be performed for each tissue type using the following equation 10. Peak concentration of the bubble.

[0193] Using additional information and assigning values ​​to different segments of the identified tissue type, the algorithm calculates the expected maximum attenuation for a given dose, as shown in Table 4, where a dose of 40 μL / kg has been used to calculate the attenuation from microbubbles and The decay of foam components.

[0194] In the described examples, compared to the standard derating of 1.4 and 5.5 dB obtained by using standard derating, a total attenuation of 5.0 and 15.2 dB is given at 0.5 and 2 MHz respectively, using discrete integration along a specified line of sight, for a given value.

[0195] As mentioned above, precise control of the target is of particular importance. Bubble and aim to make The ultrasonic dose for bubble oscillation is crucial because if the ultrasonic dose is far below the effective dose range, the bubble will not oscillate sufficiently. This is in... Figure 8 This has been proven in the text. Figure 8 Provided for enhancing the step acoustic field with 500kHz and mechanical exponents (MI) of 0, 0.1, 0.2, 0.3, and 0.4. Following treatment, the results of tumor-specific uptake of the fluorescent dye (Evans blue) are shown in the figures below. The Y-axis represents tumor-specific uptake in mg Evans blue / mg tumor tissue. The X-axis represents the mechanical index. The four figures above show the modeling results of the activated bubble's response to the incident US field under the different MIs studied. The Y-axis represents the radius of the activated bubble in μm. The X-axis represents the time in microseconds.

[0196] To investigate the effect of changes in medial intensity (MI) in a US-enhanced field, tumor-specific uptake of Evans Blue (EB, a fluorescent dye) was studied in a mouse subcutaneous prostate cancer model (PC3). Five groups (N = 3 animals / group) with enhanced acoustic field MIs of 0, 0.1, 0.2, 0.3, and 0.4 were investigated. A single dose of the cluster composition (2 mL / kg, (iv)) was administered immediately after intravenous injection of EB, followed by 45 seconds of activating US (2.25 MHz, MI 0.4) and 5 minutes of enhancing US (0.5 MHz, variable MI), which focused on the tumor volume. Thirty minutes after treatment, the tumor was excised, and the amount of EB was measured spectrophotometrically at 620 nm.

[0197] Tissue uptake and bubble oscillations of Evans blue as a function of MI.

[0198] The result is Figure 8 Visualization was performed. It can be observed that tissue uptake increased from no ultrasound (MI=0) to MI=0.1, and further increased at MI=0.2, but then decreased again at MI=0.3, and further decreased at MI=0.4. At MI=0.2, tumor-specific uptake was observed to be nearly 60% higher than at MI=0 (no ultrasound). Simultaneously, from the embedded bubble oscillation plot, the maximum radial oscillation increased from approximately 3 μm at MI=0.1 to approximately 6 μm at MI=0.2, to approximately 10 μm at MI=0.3, and further to over 20 μm at MI=0.4. Importantly, the subsequent onset of decreased tissue uptake (from MI=0.2 to MI=0.3) coincided with the onset of significant nonlinear behavior, in which inertial cavitation began.

[0199] This invention should not be limited to the embodiments and examples shown. While multiple embodiments of this disclosure have been described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications and alterations, variations and substitutions to the embodiments described herein will be apparent to those skilled in the art without departing from this disclosure. It should be understood that various alternatives to the embodiments described herein may be employed in practicing this disclosure.

[0200] It should be understood that each embodiment of this disclosure may optionally be combined with any one or more of the other embodiments described herein.

[0201] It should be understood that each component, compound, particle, or parameter disclosed herein should be interpreted as being disclosed for use alone or in combination with one or more of the various and each other component, compound, or parameter disclosed herein. It should also be understood that each amount / value or range of each amount / value disclosed herein should be interpreted as being disclosed in combination with each amount / value or range of any other amount / value disclosed herein, and therefore, for the purposes of this specification, any combination of amounts / values ​​or ranges of two or more components, compounds, or parameters disclosed herein is also disclosed in combination with each other. Any and all features described herein, as well as combinations of such features, are included within the scope of this invention, provided that the features are not inconsistent with each other.

[0202] It should be understood that, for the same component, compound, or parameter, the lower limit of each range disclosed herein should be interpreted as disclosed in combination with the upper limit of each range disclosed herein. Thus, the disclosure of two ranges will be interpreted as the disclosure of four ranges obtained by combining the lower limit of each range with the upper limit of each range. The disclosure of three ranges will be interpreted as the disclosure of nine ranges obtained by combining the lower limit of each range with the upper limit of each range, and so on. Furthermore, the specific amount / value of a component, compound, or parameter disclosed in the specification or examples will be interpreted as the disclosure of the lower or upper limit of a range, and can therefore be combined with any other lower or upper limit or range or specific amount / value of the same component, compound, or parameter disclosed elsewhere in this application to form a range of that component, compound, or parameter.

[0203] Preferred embodiments of the invention have been described, and it will be apparent to those skilled in the art that other embodiments incorporated herein may be used. These and other embodiments exemplified above are intended merely as examples, and the true scope of the invention will be determined by the appended claims.

Claims

1. A method for point estimation of ultrasound dose in a target treatment area, the method comprising: The unique ultrasound propagation correction factor is calculated for a specific ultrasound propagation path through a specific target area using the following method: Obtaining a dielectric property map of the target region, wherein the dielectric property map provides multiple different dielectric property values ​​in different segments of the target region, the dielectric property values ​​depending on the dielectric in each segment, the process of obtaining the dielectric property map of the target region includes: Obtain an image of the target region, wherein the target region includes the target treatment area and the surrounding area of ​​the target treatment area; The image is processed to identify different components of the target region; The different components are segmented and classified into predetermined media categories; Query the media characteristic values ​​associated with each media category, including; Estimate the category-specific ultrasonic coupling bubble element correction for the medium property values ​​caused by the presence of at least one ultrasonic coupling bubble element in at least one component; and Adjusting the dielectric properties of at least one component to take into account the corresponding category-specific ultrasonic coupling bubble element correction; and The medium property values ​​are assigned to the respective components of the segmented target regions; Describe the propagation path from the ultrasound source to the target treatment area; The medium property values ​​of each segment along the propagation path are summarized to calculate a unique propagation correction factor; and The unique propagation correction factor is used to indicate the ultrasound dose delivered to the target treatment area.

2. The method of claim 1, wherein the medium category comprises at least one of the following: Different organizational types; Different tissue types affected by one or more specific diseases; Fluids; and gas.

3. The method of claim 2, wherein the different tissue types comprise one or more of the following: Soft tissue, which includes fat, muscle, parenchyma, tendons, and ligaments; and Hard tissue, which includes bone.

4. The method of any one of claims 1 to 3, wherein obtaining an image of the target region comprises at least one of the following: Query the pre-scanned scan image of the target area; Perform a pre-scanning scan on the target area; and Images from a real-time diagnostic imaging system.

5. The method of claim 4, wherein the scan image comprises one or more of the following: Computed tomography images; and Magnetic resonance imaging.

6. The method of any one of claims 1 to 3, wherein the category-specific media characteristic values ​​are retrieved from a database.

7. The method of any one of claims 1 to 3, wherein the at least one ultrasonic coupling bubble element comprises one or more of the following: Contrast agent microbubbles; Cavitation seeds; Large microbubbles; ACT bubble technology ultrasonic coupling bubble element, wherein the ACT bubble technology ultrasonic coupling bubble element comprises: ACT microbubble clusters; and Activated ACT bubble.

8. The method of claim 7, wherein the at least one ultrasound coupling bubble element comprises contrast agent microbubbles, and wherein estimating contrast agent microbubble correction comprises: Query or estimate contrast agent microbubble parameters, wherein the contrast agent microbubble parameters include: The dose value of the contrast agent microbubbles applied; Contrast agent decay per unit concentration; The object's blood volume; The object's output value; The blood volume value associated with each category; Time to arrival for each category after intravenous administration of contrast agent; and Time-concentration curve; as well as The contrast agent microbubble parameters were used to calculate the contrast agent correction for each category.

9. The method of claim 8, wherein the at least one ultrasonic coupling bubble element comprises an ACT bubble technology ultrasonic coupling bubble element, and wherein calculating the additional ACT bubble correction comprises: Estimate the additional correction caused by ACT microbubble clusters in the presence of high-frequency activated ultrasound; Estimate the additional correction caused by the generated ACT bubble in the presence of high-frequency activated ultrasound; and The additional correction caused by the ACT bubble in the presence of low-frequency enhanced ultrasound is estimated.

10. The method of claim 9, wherein calculating the additional ACT bubble correction further comprises: The number of ACT bubbles in the category associated with each component is estimated using the following method: Query or estimate one or more ACT bubble parameters, wherein the ACT bubble parameters include: The object's blood volume; The object's output value; The perfusion volume for each category of the component; and Time-concentration curve; and The number of ACT bubbles delivered to each component is calculated by multiplying the cardiac output fraction corresponding to the perfusion volume of each category of the component by the activation yield of the ACT bubble cluster.

11. The method of claim 10, wherein the estimation of the number of ACT bubbles in the category associated with each segment incorporates time dependence by means of: Query the lifetime value of ACT bubbles in each category to model the decrease in the number of ACT bubbles in each category over time.

12. The method of any one of claims 8 to 11, wherein the calculation of the correction caused by the presence of contrast agent in each category is based on contrast-modal imaging ultrasound.

13. The method of any one of claims 10 to 11, wherein the calculation of the additional correction caused by the presence of ACT bubbles in each category is based on basic B-mode imaging ultrasound.

14. The method of any one of claims 1 to 3, further comprising using the unique propagation correction factor to calculate at least one of the following as an indication of the delivered ultrasound dose: generated pressure, generated mechanical index, generated intensity, generated power, and generated thermal index.

15. The method of any one of claims 1 to 3, wherein the medium property comprises at least one of the following: attenuation, sound velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient.

16. The method of claim 15, wherein the medium characteristic further comprises one or more derived characteristics derived from any or any combination of the listed medium characteristics.

17. A non-transitory computer-readable storage medium having instructions stored thereon that, when executed on a processor, perform the method of any one of claims 1 to 16.

18. A system for providing point estimation of ultrasound dose in a target region of an object, the system comprising: Ultrasonic source; An image processor module for processing an image to identify different components of the target region; Computer processor; A database module containing media property values ​​associated with multiple categories of components in the target region; A data storage module containing computer-readable instructions that, when executed on the processor, perform the following tasks: Query an image of the target region, wherein the target region includes the target treatment area and the surrounding area of ​​the target treatment area; The image is processed to identify different components of the target region; The different components are segmented and classified into predetermined media categories; Query the media characteristic values ​​associated with each media category, which include: Estimate the category-specific ultrasonic coupling bubble element correction for the medium property values ​​caused by the presence of at least one ultrasonic coupling bubble element in at least one component; and Adjusting the dielectric properties of at least one component to take into account the corresponding category-specific ultrasonic coupling bubble element correction; and Assigning the medium property values ​​to the respective components of the segmented target regions; and Describe the ultrasound propagation path from the ultrasound source to the target treatment area; The media property values ​​of each component along the propagation path are summarized to calculate the unique ultrasonic propagation correction factor for the ultrasonic propagation path through the target region. A point estimate of the ultrasound dose in the target area is calculated based on the ultrasound propagation correction factor; and If the ultrasound dose is outside the predetermined range, the ultrasound source is adjusted based on the calculated point estimate of the ultrasound dose.

19. The system of claim 18, wherein the image processor is configured to segment and classify the different components of the target region by: Identify the boundaries between different patterns in the image; Analyze the pattern within the boundary; and Each of the patterns is compared with an image pattern of a known tissue type to find a match.

20. The system of claim 19, wherein the system is a machine learning system and wherein each processed image and associated image data are accumulated as training data to provide more accurate segmentation and classification by the image processor over time.

21. The system of any one of claims 18 to 20, further configured to: Track the probe's position; As the probe position moves, one or more propagation correction factors are reassessed; and Store one or more propagation correction factors for each probe location to reduce computational load.

22. The system of any one of claims 18 to 20, further configured to: Track the in-plane and out-of-plane rhythmic movement of the medium in the target region; Reassess one or more propagation correction factors at each in-plane and out-of-plane location of the moving medium; and Store one or more propagation correction factors for each in-plane and out-of-plane location of the moving medium.

23. The system of claim 22, wherein the system is configured to track in-plane and out-of-plane rhythmic movement of the medium using a speckle tracking or machine learning algorithm.

24. The system of any one of claims 18 to 20, wherein the medium property comprises at least one of the following: attenuation, sound velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient.

Images