Method and system for calculating point estimate of ultrasound dose

Abstract

A method for creating a media characteristic map of a target region of an object, where the media characteristic map provides a plurality of different media characteristic values in different sections of the target region, the media characteristic values depending on media in each of the sections, the method comprising: obtaining an image of the target region, wherein the target area comprises a target treatment area and a surrounding area of the target treatment area; processing the image to identify different components of the target area; segmenting the different components and classifying the different components into preset medium categories; media characteristic values associated with each media category are queried and assigned to respective respective components of the segmented destination region.

Description

[0001] background

[0002] Ultrasound has long been used for diagnostic imaging applications. Recently, there has been growing interest and development in the use of ultrasound in conjunction 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 is attenuated by several mechanisms, including scattering and absorption. Absorption mechanisms transfer energy from the ultrasound waves to the tissue, where the energy is dissipated as heat. Excessive heating of the tissue can lead to tissue destruction or other undesirable biological effects. When ultrasound is used for diagnostic purposes, such effects should be avoided. The thermal index (TI) is a dimensionless parameter that is intended 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 a diagnostic setting.

[0004] The combination of high rarefaction pressure and low frequency in ultrasound waves can lead to a mechanical effect known as cavitation. In cavitation, bubbles can form, oscillate and collapse with varying degrees of severity, and produce 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 are to use an MI of less than 1.9. During ultrasound imaging with microbubble contrast agents, it is recommended that the MI be below 0.7 to avoid harmful biological effects such as microbleeding and irreversible vascular damage. During ultrasound imaging with microbubble contrast agents, using an MI below 0.4 is considered a "best practice."

[0005] MI is defined as the peak negative (rarefaction) pressure (PNP) in the ultrasound field de-rated by an attenuation factor to account for acoustic attenuation in tissue, divided by the square root of the ultrasound field center frequency (Fc) in MHz according to the following formula.

[0006]

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

[0008] f awf is the acoustic operating frequency;

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

[0010] α is the derating factor.

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

[0012] These current recommendations are not tailored or optimized for ultrasound-mediated therapy. In order to effectively deploy the mechanical and thermal mechanisms of action involved in the application of ultrasound irradiation in therapy, it is important to have an optimal estimate of the ultrasound dose delivered to the tissue volume being treated. The present invention provides a method for real-time ultrasound dosimetry in ultrasound-mediated therapy. Summary of the Invention

[0013] According to a first aspect of the present invention, a method for calculating a point estimate of an ultrasound dose for a target treatment area is provided, the method comprising: calculating a unique ultrasound propagation correction factor for a specific ultrasound propagation path through a specific target area by: obtaining a medium property map of the target area, wherein the medium property map provides a plurality of different medium property values ​​in different segments of the target area, the medium property values ​​depending on the medium in each of the segments, the obtaining of the medium property map of the target area comprising: obtaining an image of the target area, wherein the target area includes a target treatment area and an area surrounding the target treatment area; processing the image to identify different components of the target area; segmenting and classifying the different components into predetermined media categories; querying media characteristic values ​​associated with each media category, which includes: estimating a category-specific ultrasound coupling bubble element correction for the media characteristic value caused by the presence of at least one ultrasound coupling bubble element in at least one component; and adjusting the media characteristic value of the at least one component to take the corresponding category-specific ultrasound coupling bubble element correction into account; and assigning the media characteristic value to each corresponding component of the segmented target area; depicting the propagation path from the ultrasound source to the target treatment area; summarizing the media characteristic values ​​of each segment on 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.

[0014] The media categories may include at least one of: different tissue types; different tissue types affected by one or more specific diseases; fluids; and gases.

[0015] The different tissue types include one or more of: soft tissue, which includes fat, muscle, parenchyma, tendons, and ligaments; and hard tissue, which includes bone.

[0016] Obtaining an image of the region of interest may include at least one of: querying a pre-scanned scan of the region of interest; performing a pre-scan scan of the region of interest; and using a real-time diagnostic imaging system image.

[0017] The scans may include one or more of: computed tomography images; and magnetic resonance images.

[0018] Category-specific media characteristic values ​​can be queried from a database.

[0019] The at least one ultrasound coupling bubble element may comprise one or more of the following: contrast agent microbubbles; cavitation seeds; large microbubbles; Bubble technology ultrasonic coupled bubble element, which Bubble Technology Ultrasonic Coupled Bubble Elements include: Microvesicle clusters and activated Bubble.

[0020] The at least one ultrasound-coupled bubble element may contain contrast agent microbubbles, and wherein estimating the contrast agent microbubble correction comprises: querying or estimating one or more contrast agent microbubble parameters, wherein the one or more contrast agent microbubble parameters comprise: a value of a dose of contrast agent microbubbles administered; contrast agent characteristics per unit concentration; a blood volume of the subject; a cardiac output of the subject; a value of blood volume associated with each category; an arrival time of each category after intravenous administration of the contrast agent; and a time-concentration curve; and calculating a contrast agent correction for each category using the contrast agent parameters.

[0021] The at least one ultrasound coupling bubble element may comprise Bubble technology ultrasonic coupled bubble elements, and wherein the calculation of additional Bubble correction includes: The additional correction caused by the microbubble clusters was estimated; the to estimate the additional correction caused by the bubbles; and The additional correction due to bubbles is estimated.

[0022] Calculate additional Bubble correction can also include estimating the number of categories associated with each component by Number of bubbles: Query or estimate one or more Bubble parameters, where The bubble parameters include: the blood volume of the subject; the cardiac output of the subject; the perfusion volume of each category of the component; and the time concentration curve; and the cardiac output fraction corresponding to the perfusion volume of each category of the component multiplied by The activation yield of the bubble clusters was used to calculate the amount of The number of bubbles.

[0023] For the categories associated with each segment The estimation of the number of bubbles can include time dependence by querying the number of bubbles in each category. The value of the bubble life is given in each category The decrease in the number of bubbles over time is modeled.

[0024] Calculation of the correction due to the presence of contrast agent in each class may be based on contrast mode imaging ultrasound.

[0025] Calculated by each category Additional correction for the presence of bubbles can be based on fundamental B-mode imaging ultrasound.

[0026] The method may further include using the unique propagation correction factor to calculate at least one of the following as an indication of delivered ultrasound dose: a generated pressure, a generated mechanical index, a generated intensity, a generated power, and a generated thermal index.

[0027] According to a second aspect of the present invention, a non-transitory computer-readable storage medium is provided, on which instructions are stored. When the instructions are executed on a processor, the method of the first aspect of the present invention is performed.

[0028] According to a third aspect of the present invention, a system for providing a point estimate of an ultrasound dose to a target area in an object is provided, the system comprising: an ultrasound source; an image processor module for processing an image to identify different components of the target area; a computer processor; a database module comprising medium characteristic values ​​associated with a plurality of categories of components in the target area; a data storage module comprising computer-readable instructions which, when executed on the processor, perform the following tasks: querying an image of the target area, wherein the target area comprises a target treatment area and an area surrounding the target treatment area; processing the image to identify different components of the target area; segmenting and classifying the different components into predetermined medium categories; querying the medium characteristic values ​​associated with each medium category, which comprises ; estimating a class-specific ultrasound coupling bubble element correction for a medium characteristic value caused by the presence of at least one ultrasound coupling bubble element in at least one component; and adjusting the medium characteristic value of the at least one component to take the corresponding class-specific ultrasound coupling bubble element correction into account; and assigning the medium characteristic values ​​to the respective components of the segmented target area; delineating an ultrasound propagation path from an ultrasound source to a target treatment area; summarizing the medium characteristic values ​​of each component on the propagation path to calculate an ultrasound propagation correction factor unique to the ultrasound propagation path through the target area; calculating a point estimate of an ultrasound dose to the target area based on the unique propagation correction factor; and adjusting the ultrasound source according to the calculated point estimate of the ultrasound dose if it is outside a predetermined ultrasound dose range.

[0029] According to a fourth aspect of the present invention, a system for providing a point estimate of an ultrasound dose of a target region in an object is provided, 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 comprising medium characteristic values ​​associated with multiple categories of components in the target region; a data storage module comprising 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 medium characteristic values ​​of each component on 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 of 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 it is outside a predetermined ultrasound dose range.

[0030] The image processor may be configured to segment and classify different components of the region of interest by identifying boundaries between different patterns in the image; analyzing the patterns within the boundaries; and comparing each of the patterns to image patterns of known tissue types for a match.

[0031] The system may be a machine learning system, and wherein each processed image and associated image data is accumulated as training data to provide more accurate segmentation and classification by the image processor over time.

[0032] The system may also be configured to: track the probe position; re-evaluate one or more propagation correction factors as the probe position moves; and store the one or more propagation correction factors for each probe position to reduce computational load.

[0033] The system can also be configured to: track the in-plane and out-of-plane rhythmic movement of the medium in the 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.

[0034] The system can be configured to track the in-plane and out-of-plane rhythmic movement of the medium through speckle tracking or machine learning algorithms.

[0035] The method of the first aspect, or the system of the second aspect, or the fourth aspect, wherein the medium property may include at least one of the following: attenuation, acoustic velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient.

[0036] The media properties may also include one or more derived properties that may be derived from any one or any combination of the listed media properties. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of a method for calculating a point estimate of ultrasound dose;

[0038] Figure 2 is a flow chart of a method for calculating a dielectric characteristic map for a target area;

[0039] Figure 3a is an example image of the target region of the object;

[0040] Figure 3b Has distinct components that are identified Figure 3a Example images of the target area;

[0041] Figure 3c A representation of the region of interest consisting of the identified components is shown;

[0042] Figure 4a is a graph of the normalized backscattered intensity curve of vesicles in human liver;

[0043] Figure 4bis a graph of the parenchymal concentration as a function of time, using Figure 5 a Backscatter intensity curve;

[0044] Figure 5 It is a system for calculating point estimates of ultrasound dose;

[0045] Figure 6a is a schematic diagram of a method implemented according to a first embodiment of the present invention;

[0046] Figure 6b is a graph of tissue layers versus depth according to the method of the first embodiment;

[0047] Figure 6c is a graph of MI versus depth according to the first embodiment;

[0048] Figure 7a is a schematic diagram of a method implemented according to a second embodiment of the present invention;

[0049] Figure 7b is a graph of tissue layers versus depth according to a second embodiment;

[0050] Figure 7c is a result graph of MI versus depth according to the second embodiment; and

[0051] Figure 8 Provided is a method for performing an insonation field with an enhanced step. Results of tumor-specific uptake of fluorescent dye after treatment. DETAILED DESCRIPTION

[0052] Unless otherwise defined, all technical terms, symbols and other scientific terms or terminology used herein are intended to have the meanings commonly understood by those skilled in the art to which the invention pertains. In some cases, for the sake of clarity and / or for ease of reference, terms with commonly understood meanings are defined herein, and the inclusion of such definitions herein should not necessarily be construed as representing a significant difference beyond what is generally understood in the art.

[0053] The term "ultrasound dosimetry" in the field of medical ultrasound technology as used herein describes the determination (eg, measurement, calculation, and evaluation) of the ultrasound radiation dose to be delivered to a target tissue to achieve a sought biological effect.

[0054] The terms "ultrasound irradiation" or "sonation" as used herein describe exposure to or treatment with ultrasound.

[0055] The term "speed of sound" as used herein refers to the group velocity and / or phase velocity and / or signal velocity of a longitudinal pressure wave.

[0056] The term "ultrasound dose" or "ultrasound dosage" as used herein refers to instantaneous, time-averaged, spatially averaged, time-integrated and spatially integrated ultrasound parameters in a point or area, such as the parameters defined in the international standards IEC 62127-1, IEC 62359, IEC 60601-2-37 in the field of medical diagnostic ultrasound.

[0057] As used herein, the term 'ACT bubble' or ' 'Bubbles' are used interchangeably and refer to large activated bubbles derived from ACT microbubble clusters following insonation by activating ultrasound.

[0058] In diagnostic imaging applications, there are many acoustic parameters used to quantify various aspects of the applied ultrasound dose, such as mechanical index (MI), thermal index (TI), intensity spatial peak temporal average (Ispta), etc. Generally speaking, therapeutic and diagnostic ultrasound treatments involve ultrasound irradiation of a target area of ​​a subject with a predetermined ultrasound dose delivered by a transducer located at or toward the target area.

[0059] Ultrasound technology is well established for the purposes of diagnostic applications, either alone or in combination with contrast agents (e.g., microbubble compositions). The interest and development of ultrasound for therapeutic applications is growing. There is a need for ultrasound and microbubble-mediated drug delivery, ultrasound and microbubble-mediated treatment, and ultrasound-mediated treatment ultrasound dose determination. In order to effectively deploy the mechanical mechanisms and thermal mechanisms of the effects involved when applying ultrasound irradiation in treatment, it is important to best estimate the ultrasound dose delivered to the volume of tissue being treated.

[0060] The actual ultrasound dose delivered by an ultrasound source to a target region (a point estimate of the ultrasound dose) depends on the configuration of the source and the ultrasound transmission parameters and characteristics of the medium through which the ultrasound propagates from the source to the target region. Thus, 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 actual ultrasound dose to the target region.

[0061] The present invention includes identifying and segmenting multiple tissue types in a region of interest, estimating the presence of at least one ultrasound-coupled bubble element (e.g., microbubbles and / or and calculating at least one propagation correction factor for use in calculating a more accurate ultrasound dose, and optionally reconfiguring an ultrasound source that provides the ultrasound dose.

[0062] The ultrasound coupling bubble element can be a contrast agent microbubble, Microbubble clusters, cavitation seed agents, macrobubbles and / or activated In other words, the ultrasound-coupled bubble element is microbubble technology. The large bubbles of microbubble technology have a diameter greater than 8 μm and can be retained in the capillary bed of a subject.

[0063] Sound Cluster Therapy ( ) is a technology used for ultrasound-mediated local drug delivery. The researchers used a novel phospholipid-based system to create a novel, low-energy, and high-performance microbubbles. The system consists of negatively charged microbubbles containing perfluorobutane (PFB) stabilized by a monolayer of phospholipid membranes, combined with positively charged microdroplets containing perfluoromethylcyclopentane (PFMCP), also stabilized by a monolayer of phospholipid membranes. These microbubbles and microdroplets are then mixed to form small clusters held together by electrostatic forces. The microclusters can be co-administered with therapeutic drugs. When insonated with pulsed ultrasound (common in clinical diagnostic protocols and at frequencies of 2 to 5 MHz), these clusters undergo an activation step that causes the microbubbles to oscillate to transfer energy to the microdroplets, resulting in the instantaneous vaporization of the microdroplets to form larger bubbles, hereinafter referred to as Bubble.

[0064] Spatially varying properties of the medium in the region through which ultrasound propagates include attenuation, acoustic velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient. At least one propagation correction factor may be calculated based on one or more of these properties or their derivatives.

[0065] The ultrasound dose is determined based on one or more established ultrasound parameters as defined in IEC62127-1, IEC62359, and IEC60601-2-37, such as: peak negative pressure, peak positive pressure, mechanical index (MI), thermal index (TI), spatial peak time average intensity (Ispta), spatial peak pulse average intensity (Ipa), spatial average temporal average intensity (Isata), and total acoustic power.

[0066] Figure 1 is a flow chart of a method 100 for calculating a point estimate of ultrasound dose.

[0067] The method begins at 102, where a media property (MP) map of a target region of an object is obtained, wherein the MP map provides specific and different MP values ​​in the target region. The MP map is based on the specific composition and anatomical structure and / or presence of other components in the target region. Figure 2 The MP map and an example method of how to obtain the MP map are described in more detail.

[0068] An example MP map is an attenuation map, wherein the attenuation map provides specific and different attenuation values ​​in the target area, the attenuation values ​​being based on the specific composition and anatomical structure of the target area and the presence of other components, particularly the presence of one or more ultrasonic coupling bubble elements. Another example MP map is a sound velocity map, wherein the mass density and bulk modulus of the changing medium through which the ultrasound travels are changed to affect the speed of sound of the ultrasound wave. The sound velocity map provides specific and different sound velocity values ​​in the target area, the sound velocity values ​​being based on the specific composition and anatomical structure of the target area and the presence of other components. Another example is a phase map, which can be a combination of a sound velocity map and an attenuation map. In a preferred embodiment, two or more of the individual MP maps of attenuation, sound velocity, nonlinear coefficient and phase are combined to provide a combined media property (CMP) map of the target area.

[0069] At 104, a dose-defining propagation path (PP) is approximated (projected). In a first example, 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, one originating from each of the elements in the transducer array. In a preferred example, the PP is an acoustic model of the transmitted ultrasound field. Ultrasound is typically applied to the external or internal surface of the body, or generated inside the body by inserting a transducer (e.g., via a laparoscope). As the wave passes through each component along the path, the ultrasound wave will experience different absorption, scattering, refraction, and aberration.

[0070] At 106, the MP values ​​over the PPs may be calculated (ie, integrated) to calculate 108 a propagation correction factor (PCF) unique to the PPs through the particular destination region. In some examples, the PCF is complex valued.

[0071] At 110, the MI or TI generated by the ultrasound field along the PP is estimated based on a preselected set of ultrasound parameters and the PCF.

[0072] A preselected set of ultrasound parameters may be modified based on the initial MI or TI estimate and used with the PCF to give a refined / improved MI / TI estimate.

[0073] The further optimized parameter set can be used with PCF to converge to the best estimate of MI / TI in an iterative manner. r,α Any point in the ultrasound field emitted by a source can be defined by:

[0074] P r，α =P r 10 -α / 20 Equation 2

[0075] The optimal MI can be calculated using a modified version of Equation 1, where α is replaced by the attenuation correction factor (α CF )

[0076] α→α CF

[0077] and

[0078]

[0079] where N t is the number of different tissue types between the transducer and the target depth, Δd i is the tissue layer thickness per unit depth of the corresponding tissue type i, and α i is the attenuation coefficient of the tissue layer per unit depth measured in dB / unit depth.

[0080] Alternatively, the attenuation coefficient can be modeled as a spatially varying function in is the spatial position such that

[0081]

[0082] Thus, in the example where PCF is the attenuation correction factor, the attenuation correction factor may be used in an adjusted equation involving the attenuation factor, ultrasound operating frequency, and mechanical index:

[0083]

[0084] in and is included to provide MI as a dimensionless parameter, f awf is the acoustic operating frequency; and is the decay time peak rarefaction pressure at the target region that depends on the decay correction factor.

[0085] At 112, the calculated MI can be transmitted to the ultrasound source to automatically adjust the output settings of the ultrasound source 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.

[0086] Steps 104 to 110 can be performed in real time in a continuous loop 103 during ultrasound imaging and / or treatment. 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 spatially tracking 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 example, the PCF is recalculated when the region of interest moves due to other external factors, such as subject movement or respiratory motion.

[0087] In one example, the PCF is determined by an attenuation correction factor and a phase change correction factor. In this case, steps 104 to 110 may be performed in real time in a continuous loop 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 region of interest. An example of such a point scatterer is an active cluster.

[0088] Figure 2 Flowchart of method 200 for creating a unique (C)MP map for a specific area of ​​interest. Method 200 provides step 102 of method 100. A (C)MP map is composed of segments of known volume / area with associated MP values ​​for each segment. The MP map can be an attenuation map, a sound velocity map, a shear wave velocity map, an acoustic impedance map, a dispersion coefficient map, a nonlinear coefficient map, or a map of parameters derived from these properties. The MP map can be a CMP that combines two or more of the above maps.

[0089] At 202, an image of a target region in a subject is obtained. The target region is the target region and the surrounding area of ​​the target region. The target region is the area in which the ultrasound dose is to be delivered. For example, the target region may be a metastasis in the subject's liver, and the surrounding area may 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.

[0090] There may already be a scan of the target area, particularly a volume scan, such as magnetic resonance imaging (MRI), computerized tomography (CT), or an earlier ultrasound scan that can provide an image of the target area in method 100. Alternatively, a new scan (such as an MRI or CT scan) can be performed on the target area to provide an image of the target area. Another method for obtaining an image of the target area is to use an ultrasound source. The ultrasound source used in method 100 can first be used to obtain an ultrasound scan of the target area by insonating the target area. Before finding an accurate estimate of the calculated radiation dose, the pressure amplitude of the ultrasound for the purpose of obtaining an image of the target area can be 0.3 dB cm -1 MHz -1 The imaging may include a step of identifying a target volume, if not already known. The imaging may include an additional step of identifying a tumor or metastasis in the target area.

[0091] refer to Figure 3a , shows an example image 300 of a region of interest 301 of an object, and is an example of an image to be processed by an image processor. Figure 3a The images in this example are obtained via ultrasound scanning.

[0092] At 204, the image of the target area is processed to identify different components and the image is segmented into different categories 206 based on the identified components. The components to be identified and classified can be different tissue types in both healthy and diseased states. To name a few non-limiting examples, different tissue types can include soft tissue (e.g., fat, muscle, tendon, and ligament) and hard tissue (e.g., bone). Metastasis can also be identified and classified differently from other components. The target area is segmented in this way because each component can affect ultrasound differently.

[0093] Figure 3b It is segmented into different components by the image processor Figure 3a An example image 300 of a target area 301. Figure 3b In the example of , the identified components are muscle 304 , metastasis 306 , healthy liver 302 , and aorta 308 .

[0094] At 208, for each component in the region of interest, at least one of the component's associated class-specific MP values, such as attenuation and / or acoustic velocity, is queried from the database and assigned to the component. An example database is shown in Table 1 below.

[0095] Table 1

[0096]

[0097] Figure 3c An example MP diagram is shown in the form of an example attenuation map 500 of the region of interest 301 consisting solely of its component components. The attenuation map 500 is a graphical representation of a collection 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 a segment representing the region of healthy liver 502, a segment representing the region of muscle 504, several segments representing the region of metastasis 506, and a segment representing the region of the aorta 508. The attenuation map 500 can be stored in a database for access by ultrasound scanner software. The attenuation map can be stored in long-term or short-term data storage for later query.

[0098] The method incorporates correction 210 for unique PCFs based on the presence of one or more ultrasound coupling bubble elements in at least some tissue layers.

[0099] exist Figure 2 In a specific example, at step 210a, a correction to the PCF is calculated based on the presence of microbubbles (eg, contrast agent microbubbles) in at least one component in the region of interest.

[0100] When metastases are treated with ultrasound, contrast agent microbubbles are usually present in the tissue of the target area because the contrast agent is usually added in a previous ultrasound image capture phase. The addition of contrast agent to the area changes the acoustic properties of the area. Depending on the frequency of ultrasound scattering, the absorption, reflection and refraction properties of the area can be changed. For example, the decrease in density at the interface between the contrast agent and the surrounding tissue causes ultrasound to be strongly scattered and reflected back to the ultrasound probe. This acoustic property is called backscatter and results in a higher contrast between different areas on the captured ultrasound image. Since the contrast agent changes the acoustic properties of the area, it can have a significant impact on the derating factor applied to the ultrasound pulses delivered to the target area. Therefore, additional corrections for the contrast agent and its amount are needed to improve the estimate of the ultrasound dose delivered to the target area. There are at least four commercially available diagnostic ultrasound imaging (contrast) agents on the market; Sonazoid TM 、Definity TM 、Optison TM and SonoVue TM, which 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 being lodged in capillaries. The term 'microbubble' or 'conventional contrast microbubble' is used herein 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 toward the clinic, such as Acoustic Cluster (Exact ) and SonoTrans TM (Oxsonics TM ).

[0101] In the specific example where the correction factor is an attenuation correction factor to account for the additional attenuation due to the presence of a contrast agent, the contrast agent characteristics, in terms of attenuation per unit concentration, can be queried or calculated from in vivo experiments. For example, the in vivo environment can be whole blood at 37°C and 85% gas saturation, or 5% human serum albumin. Ultrasound of a predetermined frequency is then applied to the contrast agent-containing environment. The 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.

[0102] Next, an approximation is made for the subject's blood volume, e.g., a 70 kg subject has about 5 liters of blood. The subject's cardiac output is then estimated, e.g., 5 liters of blood per minute for the 70 kg subject. For each segmented tissue type, an estimate of the typical value for the blood volume that is not in large compliant vessels is also needed. For example, the liver has about 15% blood volume, and resting skeletal muscle, skin, and adipose tissue have only a small fraction of that percentage of blood volume compared to the liver. A table of typical arrival times for each component class following intravenous administration of the contrast agent is then needed. For each component class, a table of concentration time curves for free-flowing contrast agents administered intravenously is also needed. Tables providing values ​​for concentration time curves for free-flowing contrast agents administered intravenously can be found in the art.

[0103] For free-flowing microvesicles, the kinetics of vesicle influx and wash-out from various organs are well known and have also been investigated for activated microvesicles. For example, in a dog model, as measured by backscatter intensity from ultrasound imaging, The bubble half-life is 70 seconds. Figure 4a Shows free-flowing microvesicles Sonazoid and Typical normalized backscattered intensity curve of a bubble. Vesicles accumulate in the liver over time as they are activated. Sonazoid influx is faster and decreases rapidly as vesicles are partially washed out of the liver. Some vesicles are taken up by Kupffer cells in the liver, which produce a residual concentration after washout is complete. Similar curves can be created for other organs, in which case the absence of Kupffer cells results in The injected free-flowing component follows the dashed line 402 . Figure 4b Shows the use of Figure 4a The backscatter intensity curve of the parenchymal concentration as a function of time. The attenuation in each tissue type will depend on a time-varying curve, such as these. These curves can be predetermined or calculated for each patient by, for example, using the injection duration τ and the tissue-specific washout time θ to parameterize a tissue-type-specific function of the form

[0104]

[0105] Similarly, by approximating the above integral

[0106]

[0107] 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 the treatment process and based on an a priori model of concentration. The calculated concentration is used to calculate the attenuation experienced by the ultrasound pulse as it passes through the tissue structures between the probe and the target tissue at each time point. For each time point, the ultrasound source configuration 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 excitation.

[0108] Thus, based on the values ​​of attenuation per unit concentration in each component class, blood volume, arrival time 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 class attenuation value, preferably each class attenuation value associated with the component contrast agent concentration.

[0109] The peak additional attenuation of the ultrasound pulse caused by contrast agent microbubbles was calculated based on the data provided in the database. The peak attenuation caused by free-flowing contrast agent microbubbles can be approximated by using the formula for calculating the concentration of free-flowing bubbles 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 were used. B , injection duration τ and activation efficiency η, the peak dose can be calculated as

[0110]

[0111] After calculating the correction due to the presence of contrast agent, the method may then proceed to step 214 where an MP map of the region of interest is generated.

[0112] Alternatively or additionally, the method may proceed to step 210b so that the sound clusters in at least one category are treated. A (further) additional correction due to the presence of bubbles is taken into account.

[0113] exist In this study, small clusters of charged microbubbles attached to oppositely charged oil droplets are injected into the bloodstream. Ultrasound is applied to cause the microbubbles to vibrate and transfer energy to the clusters, resulting in the fusion of particles in the clusters into single particles. The oil then vaporizes into the gas contributed by the microbubbles, producing enlarged microbubbles ( Apply to The ultrasonic pulse of the bubble causes a large gas Bubble vibration.

[0114] More specifically, the formulation is a cluster dispersion of clusters formed by microdroplets with a median diameter of 2 to 3 μm, stabilized by a lipid membrane with a net positive surface charge, and microbubbles with a median diameter of 2 to 3 μm, stabilized by a lipid shell with a negative surface charge. It is the opposite charges on the surface of the oil droplets and microbubbles that enable the formation of small clusters through electrostatic interactions. These clusters are about 5 μm in diameter and flow freely in the vasculature. When exposed to medical diagnostic ultrasound frequencies, the microbubbles in the cluster oscillate and the particles fuse into a single entity and the oil vaporizes to produce enlarged microbubbles ( Bubble).

[0115] The frequency of medical diagnostic ultrasound is 1 to 15 MHz, preferably 2 to 10 MHz, more preferably 5 MHz. Even with the short imaging pulses, low MI (e.g., MI of less than 0.1), and low duty cycles typically used in medical imaging systems, the process of oil droplet-microbubble fusion can be generated. Once fused, the oil droplets vaporize into the gas that forms the bubble core and form the resulting 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 persist for several minutes before dissolving. After intravenous administration, the clusters flow in the bloodstream and, under the application of an ultrasound field (activation ultrasound), macrobubbles are formed (activated) from the clusters. bubbles, spatially localizing their generation only in the tissue irradiated with ultrasound. The bubbles are large enough to be retained in the first capillary bed into which they flow and remain for several minutes. During this time, a lower frequency ultrasound field (enhanced ultrasound) is applied at a 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, and more preferably 0.5 MHz.

[0116] MI is preferably between 0.1 and 0.4. The treatment performed by the technology requires full control of the high frequency (activated ultrasound) generated by the cluster The ultrasound field of the bubbles and the ultrasound field at low frequency (enhanced ultrasound) driving the mechanical action for treatment are used to achieve the best therapeutic effect.

[0117] Because of the use The ultrasound dose applied for treatment requires a certain energy lower limit, and undesirable biological effects and tissue damage must still be controlled. Therefore, accurate estimation of ultrasound dose is very important for the treatment of For example, the conservative lower derating factors in current ultrasound control standards may not provide adequate Treatment outcomes and the need for target region-specific PCF are crucial Therapy is particularly helpful.

[0118] Since the activation ultrasound is high frequency and the enhancement ultrasound is low frequency, There are three elements of the treatment process that can each affect the medium properties (i.e., attenuation, acoustic velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient of the target area segment). Therefore, it is preferred to calculate the MP correction for each element. The first element is the microbubbles in the presence of high-frequency activated ultrasound. The second element is the microbubbles generated in the presence of high-frequency activated ultrasound. The third element is in the presence of low frequency enhanced ultrasound Preferably, an MP correction is calculated for each component class for each of the three elements mentioned above. Thus, for treatment, targeting tissue type, number of free-flowing microbubbles, and Therapeutic corrections of both the bubble generation and its lifetime can potentially be corrected to change ultrasound dosimetry parameters during both the high frequency ultrasound activation step and the low frequency ultrasound therapy boost step.

[0119] In the calculation due to An optional intermediate step in the process of additional MP correction caused by bubbles is to destroy the free-flowing microbubbles with high amplitude and power diagnostic imaging pulses. These high amplitude and power diagnostic imaging pulses can be incorporated into diagnostic scanners as part of a 'flash' sequence or 'decorrelation' imaging mode. The MI of such pulses is typically 0.7 and above. Such pulses can be used to more effectively image the free-flowing microbubble component or to remove free-flowing microbubbles in the scan plane or tissue volume. However, such high intensity pulses do not destroy Therefore, these imaging pulses can be used to clear the free-flowing microbubble fraction while The bubble component is unaffected. Thus, the need for MP correction due to the presence of contrast agents can be reduced or even eliminated. For example, by destroying substantially all free-flowing microbubbles prior to insonating the treatment area with a therapeutic ultrasound dose, the attenuation component from free-flowing microbubbles can be eliminated up to completely.

[0120] To calculate To correct for bubble-related MP, we first estimate the amount of MP retained in the capillaries. The number of bubbles is calculated. Estimate or query the values ​​of the subject's total blood volume and cardiac output. Then, an estimate of the perfusion rate is calculated for each component class. The amount of perfusion delivered 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 activation yield was 24% in a large animal dog model. In addition, the number of cells present in each class of components as a function of time was The reduction in the number of vesicles can be estimated or queried from a database. Bubble life is estimated The decrease of bubbles with respect to time.

[0121] An example database giving component specific information is shown in Table 2, where only two frequencies are shown for simplicity.

[0122] Table 2

[0123]

[0124] Where MP is the attenuation, contrast-mode ultrasound imaging is suitable for estimating the attenuation of free-flowing contrast agents, and basic B-mode imaging is suitable for estimating the attenuation due to This is due to the following reasons.

[0125] Contrast imaging mode will be more specific to the backscattered signal produced by free-flowing microbubble components (such as commercially available microbubble contrast agents). These imaging modes utilize the nonlinear behavior of bubbles and extract nonlinear oscillation characteristics to form an image more dominated by microbubble components and selectively suppress the backscattered signal from tissue components. These microbubbles are strongly coupled to diagnostic imaging pulses because the frequency of these pulses is about 2 to 10 MHz, close to the mechanical resonance of the bubble system. Therefore, compared with the acoustic action with non-resonant pulses, bubble oscillations are significantly increased. In contrast, The resonant frequency of the bubble is about 300kHz. This resonant frequency is significantly lower than the diagnostic imaging frequency range. At diagnostic imaging frequencies, The bubbles are insonated above resonance and in this state the scattering efficiency of the bubbles is much higher than that of the contrast agent, where the scattering efficiency is defined as the ratio of the scattering to the absorption cross section. As the size of the bubbles increases, they also produce significantly more backscatter (increased scattering cross section compared to free-flowing agents), making them easily visualized in basic B-mode. In this imaging mode, tissue contrast enhancement during basic B-mode imaging is achieved by contrast agents compared to Therefore, contrast-mode imaging ultrasound is preferred for attenuation estimation of free-flowing contrast agents, and basic B-mode imaging is preferred for estimating the attenuation of free-flowing contrast agents due to the presence of bubbly components. Attenuation caused by bubbles.

[0126] Or, another Specific imaging modalities can be used to estimate Attenuation caused by bubbles.

[0127] Query active Attenuation values ​​of clusters and their microbubble components over a range of frequencies. An example of such a database is given in Table 3, where only two frequencies are shown for simplicity. The attenuation values ​​are proportional to the concentration.

[0128] Table 3

[0129]

[0130] Calculated based on the data provided in the database The injection of clusters causes additional attenuation of the peak of the ultrasound pulse. The peak attenuation caused by microbubble clusters can be approximated by using the formula for calculating the concentration of free-flowing bubbles for each tissue type. Using the patient's weight M, per body weight Injection dose D, cardiac output Q, organ blood volume fraction R B, injection duration τ, the proportion of free-flowing bubbles in the injection preparation r and the activation efficiency η, the peak dose can be calculated as

[0131]

[0132] Similarly, the % of each tissue type can be calculated using the following formula The peak concentration of bubbles, where V is the total blood volume

[0133]

[0134] Using the additional information and assigning values ​​to the different segments of the identified tissue types, 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 maximum attenuation from microbubbles and Attenuation of bubble components.

[0135] Table 4

[0136]

[0137] Once each class-specific MP value is adjusted to Once up to three further elements of treatment course correction specific to the respective class have been taken into account and assigned to each respective component, the method may then proceed to step 214 where a (C)MP map is generated.

[0138] Microbubbles and The presence of bubbles can affect the speed of sound and phase change. In a similar way to adding additional attenuation to each component of the segmented region of interest, the components in the MP map (e.g., speed of sound map or phase change map) can also be affected by microbubbles and The presence of bubbles is adjusted in a similar way as for the additional attenuation.

[0139] It is particularly important to precisely control the targeting Bubble and aim to make The ultrasound dose for bubble oscillation is determined because if the ultrasound dose is far below the effective dose range, the bubbles will not oscillate sufficiently. Insufficient bubble oscillation will not achieve the desired effect. However, ultrasound doses that are too high in the effective dose range If the bubbles are too strong, they will oscillate too strongly, potentially leading to undesirable biological effects. These undesirable biological effects may include damage to blood vessels and destruction of capillary walls. This can lead to obstruction of blood flow and result in more severe symptoms than without the bubbles. Therapeutic chemotherapy delivery smaller chemotherapy is delivered to the tissue site. Therefore, there are suitable methods to drive drug delivery and achieve the desired Ultrasound energy window for therapeutic action. Using the method of the present invention described herein, this ultrasound energy (ultrasound dose) window can be more easily and reliably controlled regardless of the anatomical structure and composition of the subject and the ultrasound energy used for imaging and / or The presence of additional ingredients of treatment.

[0140] Once the (C)MP is generated, method 200 is complete and the method according to 100 may proceed to step 104 where attenuation values ​​on the PP are calculated to calculate the PCF including additional contrast correction for bubbles, e.g., including additional contrast attenuation and / or Attenuation correction factor including bubble attenuation.

[0141] Figure 5 Schematic diagram of a system 500 for both generating a (C)MP map of a region of interest of a subject (method 200) and for calculating a point estimate of ultrasound dose (method 100). System 500 has 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 is in data communication with each other module, either directly or via one of the other modules. Data storage module 510 contains computer-readable instructions 502 that, when executed on computer processor 205, perform the tasks described subsequently. From now on, for simplicity, computer-readable instructions, when executed on a computer processor, are referred to as 'programs'.

[0142] First, the program instructs the image processor module 506 to process an image of the target region of the subject 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 the boundaries for comparison with patterns of known tissue types to find the closest match. 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.

[0143] The program then instructs accessing the MP value database 508, querying the MP value for each of the identified categories, and assigning the appropriate value to the corresponding identified component. An example of a database containing ultrasound parameter (MP) values ​​for each of the identified categories (e.g., tissue types) is shown in Table 1. 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 range of frequencies. Such data is publicly available in the art.

[0144] Preferably, the database module 508 also includes a contrast agent microbubble (or other ultrasound coupling bubble element) database 516, which contains additional correction (e.g., attenuation) values ​​per unit concentration of different contrast agents. The database 516 may also contain the following queryable values:

[0145] - Blood volume at different subject weights;

[0146] - Cardiac output estimation for different subject weights;

[0147] - Typical values ​​of blood volume for each component category;

[0148] - typical arrival times of each component class after intravenous administration of different contrast agents; and - concentration-time profiles of free-flowing contrast agents administered intravenously for each component class.

[0149] The program can look up the required values ​​from another database 516 to estimate additional corrections, such as additional attenuation, based on the presence of contrast agents in each class. The additional corrections can then be added to each corresponding component MP value, such as the attenuation value, before the program performs the step of calculating the PCF on the PP.

[0150] As described above, the peak additional attenuation of the ultrasound pulse due to contrast agent microbubbles can be calculated from the data provided in the database.The peak attenuation from free-flowing contrast agent microbubbles can be approximated by using Equation 8 which calculates the free-flowing bubble concentration for each tissue type.

[0151] In existence In the case of treatment, the database module 508 may include a database 518 containing information for estimating Three elements of the treatment process result in additional corrected values.

[0152] Database 518 may also contain the following queryable values:

[0153] - Total blood volume of subjects of different weights;

[0154] - Cardiac output of subjects of different weights;

[0155] - perfusion rate for each component category (Table 2, row 4);

[0156] - activation yield of microvesicle clusters ( Table 2 , row 8);

[0157] - The presence of each class component as a function of time A decrease in the number of blebs (Table 2, row 7); and

[0158] - In different tissue types The lifespan of the bubble (Table 2, row 6).

[0159] As an alternative to querying from a database, the patient's total blood volume and cardiac output may be determined via examination of the patient or by utilizing approximate values. For example, blood volume and cardiac output may be estimated based on the patient's weight.

[0160] The program can calculate the The injection of clusters causes additional attenuation of the peak of the ultrasound pulse. For example, The peak decay of the microbubble clusters can be approximated by using Equation 9 to calculate the free-flowing bubble concentration for each tissue type. The peak decay of the bubble can be approximated using Equation 10.

[0161] The program can query the required values ​​from another database 518 to The estimated additional correction is then added to each corresponding component MP value before the program performs the step of calculating the PCF on the PP.

[0162] Thus, the imaging results are determined by the geometry and tissue type, the presence of contrast agents and / or The C(MP) map of the presence of bubbles is generated and stored in the data storage module 510.

[0163] The values ​​in the database module 516 may also be queried and used to estimate corrections to the following media properties due to the presence of microbubbles: acoustic velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient, or derived properties depending on the desired MP map. Additional values ​​in the database module 518 may also be queried and used to estimate corrections to the following media properties due to the presence of microbubbles: acoustic velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient, or derived properties depending on the desired MP map. The presence of bubbles can be used to correct for the above-mentioned medium properties. The corresponding sound velocity map, shear wave velocity map, acoustic impedance map, nonlinear compressibility coefficient map and dispersion coefficient map (and any derived characteristic maps) indicating the presence of bubbles are stored in the data storage module 510.

[0164] The database 508 and the data storage module 510 can be contained on the same or separate hardware devices. Alternatively, the database 508 and / or the data storage module 510 can be contained on a cloud-based platform.

[0165] 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 zone. The locations of the ultrasound source 504 and the target treatment zone are identified by the program or manually entered by the user. The program then aggregates the MP (e.g., attenuation) values ​​for each component on the PP to generate a PCF, such as a PCF for attenuation.

[0166] The program uses the PCF (e.g., attenuation) to calculate the associated MI resulting from a particular PP, indicating the ultrasound dose insonated at the target region. Where the program generates a CMP map, it uses several media properties to calculate one or several PCFs to calculate the associated MI and ultrasound dose.

[0167] The calculated path-specific MI / ultrasound dose is transmitted to the ultrasound source 504 (ie, ultrasound scanner).The ultrasound source may be adjusted according to the calculated MI / ultrasound dose and the desired US dose for the target region.

[0168] In some embodiments of the present invention, system 500 is configured to perform the process of calculating a unique path-specific PCF, and therefore, an MI / ultrasound dose value, on a continuous basis. In this way, the ultrasound dose can be tracked as the ultrasound source 504 moves relative to the target area and / or adjusts the ultrasound frequency. If the ultrasound source remains within the target area, system 500 does not need to generate a new (C)MP (e.g., attenuation) map, thereby saving time and processing power.

[0169] 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 non-optimal when a point estimate 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 the attenuation and a single conservative value for tissue (for an upper safety 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. Therefore, a more accurate method according to the present invention involves the following steps: classifying the tissue type present between the ultrasound transducer and the tissue volume to be treated, identifying the bubbles (contrast agent, Microbubble clusters and / or ) in the corresponding tissue type, and in order to identify and define the ultrasound dose to be used in treatment.

[0170] The PCF is required to adapt to the specific environment of the ultrasound field from the ultrasound source to the target area. As mentioned above, the specific environment depends on the anatomical structure and composition of the object and the imaging and / or The presence of additional ingredients of treatment.

[0171] In the specific example where MP is attenuated, the current conservative lower derating factor is used to effectively Treatment presents particular challenges. This is because the excess fat in the ultrasound path leads to higher-than-average attenuation of the insonating ultrasound field and, therefore, can result in insufficient ultrasound dose delivered to the target treatment area. Because the methods described herein can be tailored to specific tissue types and geometries, they are particularly useful for ultrasound treatment in obese subjects.

[0172] Example

[0173] The first example of the method of the present invention described above is performed in Figures 6a to 6c Shown in.

[0174] Figure 6a A cross-section of the abdomen 610 of a human subject is shown. The cross-section has muscle 603, liver 604, blood vessels 605, kidney 606, bone 607, spleen 608, intestine 609, stomach 610, and pancreas 611. An ultrasound transducer 600 is placed in contact with the external skin surface of the abdomen 610 of the human subject. The ultrasound transducer 600 transmits an ultrasound field along an acoustic path 601 toward a target depth indicated by a cross 602. As shown in the figure, the acoustic path 601 passes through several different types of organs between the ultrasound transducer 600 and the target 602, namely, skin, muscle 603, fat, liver 604, intestine 609, and pancreas 611.

[0175] exist Figure 6a In the example of FIG6 , the acoustic path 601 is shown as a single linear path from a discrete point of the transducer 600 to the target 602. However, as described above, the acoustic path may be composed of multiple ultrasound rays having their respective paths.

[0176] Figure 6b shows the attenuation coefficient relative to the Figure 6a A graph of the depth of the acoustic path 601, with the attenuation coefficient depending on the type of tissue traversed at that depth. Figure 6b In the example, the attenuation coefficient at a depth of 0 cm to approximately 0.5 cm is 0.4, which is the attenuation coefficient of skin. The attenuation coefficient at depths of approximately 0.5 cm to 1.0 cm and 2.0 cm to 2.5 cm is 0.3, which is the attenuation coefficient of fat. The attenuation coefficient at a depth of approximately 1.0 cm to 2.0 cm is 0.5, which is the attenuation coefficient of muscle. The attenuation coefficient at a depth of approximately 2.5 cm to 5.5 cm is approximately 0.35, which is the attenuation coefficient of the liver. At a depth of 5.5 to 6.5 cm, the acoustic path passes through the intestine, where the attenuation coefficient of intestinal tissue is approximately 1.5. The final tissue type that the ultrasound field passes through before reaching the target is pancreas 608 organ tissue, which has an attenuation coefficient of approximately 0.25 dB / cm.

[0177] Figure 6cA plot of the resulting mechanical index (Equation 5) versus depth along the acoustic path 602 is shown. Figure 6c In the example (for Figure 6b The solid line represents the mechanical index adjusted for the standard derating of 0.3 dB / cm / MHz, and the thick solid line with dots represents the mechanical index adjusted for the medium-specific attenuation. CF The thick solid line with dots represents the pressure according to Equation 5. At the target, the mechanical index is about 0.15.

[0178] The second example of the above-mentioned method of the present invention is performed in Figures 7a to 7c Shown in.

[0179] Figure 7a A cross section of the abdomen 710 of a human subject is shown. The cross section shows tissue from muscle 703, liver 704, fat 705, and skin 706. An ultrasound transducer 700 is placed in contact with the outer skin surface of the abdomen 710 of a human subject. The ultrasound transducer 700 transmits an ultrasound field along an acoustic path 701 toward a target depth indicated by a cross 702. As shown in the figure, 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, fat 705, and liver, all containing microbubbles and Bubble.

[0180] Similar to Example 6a, Figure 7a In the example of FIG, the acoustic path 701 is shown as a single linear path from a discrete point of the transducer 700 to the target 702. However, as described above, the acoustic path may be composed of multiple ultrasound rays having their respective paths.

[0181] Figure 7b shows the attenuation coefficient relative to the Figure 7a A graph of the depth of the acoustic path 701, with the attenuation coefficient depending on the type of tissue traversed at that depth. Figure 7b In the example of FIG. 5 , the attenuation coefficient at a depth of 0 cm to about 0.5 cm is 0.96 dB / cm, i.e., there are microbubbles and The attenuation coefficient at a depth of about 0.5 cm to 1.0 cm and 2.0 cm to 2.5 cm is 0.37 dB / cm, i.e., there are microbubbles and The attenuation coefficient of fat with microbubbles is 0.41 dB / cm at a depth of about 1.0 cm to 2.0 cm. The attenuation coefficient at a depth between about 2.5 cm and about 5.0 cm at the target 502 is 0.71 dB and is the result of the presence of microbubbles and The attenuation coefficient of the liver tissue with bubbles.

[0182] Figure 7c A graph of the resulting mechanical index versus depth along the acoustic path 702 is shown. Figure 7c In the example (for Figure 7b The thick solid line with dots represents the resulting mechanical index adjusted for medium-specific attenuation, while the solid line represents the resulting mechanical index adjusted for standard attenuation (0.3 dB / cm / MHz). At the target depth, the mechanical index is approximately 0.15.

[0183] As according to Figures 6a to 6c Example 1 and based on Figures 7a to 7c The example of the method shown in Example 2 demonstrates the correlation of pressure with tissue type and the presence and absence of bubbles in the tissue.

[0184] As an example, the target area is a metastatic lesion located in the patient's liver. The patient receives treatment consisting of a chemotherapy drug injected as an infusion and Clusters are activated and enhanced with ultrasound at the target lesion to enhance treatment. Figure 6a and Figure 7a As shown in , therapeutic ultrasound is provided from an ultrasound scanner with an attached ultrasound probe that is placed in contact with the skin on the abdomen of the patient. Prior to treatment, a preferred probe placement is determined based on ultrasound imaging of the patient. When the preferred placement is determined, the tissue type present between the probe and the target lesion is identified. This process can be accomplished by using a segmentation algorithm that is trained with artificial intelligence that has access to ultrasound scanner data. One or more lines of sight are traced from the probe face to the target lesion, and the thickness of each segment along the line is calculated. Typically for this scenario, the ultrasound field emitted by the probe passes through the skin, fat, muscle, and liver parenchyma layers before reaching the target lesion. For each tissue type, the ultrasound scanner determines the tissue perfusion volume, Bubble life, Bubble half-life, The data is then used to create a medium property map based on the values ​​of bubble activation yield and ultrasonic attenuation over a range of frequencies. An example of such a database is given in Table 2.

[0185] In addition, query the activated Attenuation values ​​of clusters and their microbubble components over a range of frequencies. An example of such a database is given in Table 3, where only two frequencies are shown for simplicity. The attenuation values ​​are proportional to the concentration.

[0186] The patient's total blood volume and cardiac output can be determined through examination of the patient or by using approximate values. For example, blood volume and cardiac output can be estimated based on the patient's weight. In this example, the patient weighs 70 kg and is provided as input to the ultrasound scanner. The algorithm uses this number to calculate a blood volume of 4.6 L and a cardiac output of 5 L / min. Clusters were injected over a 30 second period so that for the first pass through the circulatory system the dose was mixed in a limited blood pool.

[0187] Calculated based on the data provided in the database The injection of clusters causes an additional attenuation of the peak of the ultrasound pulse. For example, the peak attenuation from free-flowing microbubbles can be approximated by using Eq.

[0188] Similarly, the following equation 10 can be used to calculate the Peak bubble concentration.

[0189] Using the additional information, and assigning values ​​to the different segments of the identified tissue types, the algorithm can calculate the expected maximum attenuation for a given dose, as shown in Table 4, where a dose of 40 uL / kg has been used to calculate the maximum attenuation from microbubbles and Attenuation of bubble components.

[0190] In the example described, given the values ​​and using discrete integration along the specified line of sight, this gives a total attenuation of 5.0 and 15.2 dB at 0.5 and 2 MHz respectively, compared to the standard derating of 1.4 and 5.5 dB obtained by using standard derating.

[0191] As mentioned above, it is particularly important to precisely control the targeting Bubble and aims to make The ultrasound dose for bubble oscillation is determined because if the ultrasound dose is much lower than the effective dose range, the bubbles will not oscillate sufficiently. Figure 8 It is proved in Figure 8 The present invention provides a method for performing an insonation process using an enhanced step insonation field at 500 kHz and a mechanical index (MI) of 0, 0.1, 0.2, 0.3 and 0.4. Results of tumor-specific uptake of a fluorescent dye (Evans Blue) after treatment (lower graph). The Y-axis shows tumor-specific uptake in mg Evans Blue / mg tumor tissue. The X-axis shows the mechanical index. The top four graphs show modeling results of the activated bubble response to the incident US field at the different MIs studied. The Y-axis shows the radius of the activated bubble in μm. The X-axis shows the time in microseconds.

[0192] In order to study the effect of MI change of US enhancement field, the tumor-specific uptake of Evans Blue (EB, fluorescent dye) was studied in a mouse subcutaneous prostate cancer model (PC3). Five groups (N=3 animals / group) with MI of 0, 0.1, 0.2, 0.3 and 0.4 for the enhanced acoustic wave effect were studied. Immediately after iv injection of EB, a single dose of cluster composition (2mL / kg, (iv)) was given, followed by 45 seconds of activation US (2.25MHz, MI 0.4) and 5 minutes of enhancement US (0.5MHz, variable MI), which was focused on tumor volume. 30 minutes after treatment, the tumor was excised, and the amount of EB was measured at 620nm by spectrophotometry.

[0193] Tissue uptake of Evans blue and vesicle oscillations as a function of MI.

[0194] The results are Figure 8 . It can be noted that tissue uptake increases from no US (MI=0) to MI=0.1, and further increases at MI=0.2, but then decreases again at MI=0.3, and further decreases at MI=0.4. At MI=0.2, an increase of nearly 60% in tumor-specific uptake was observed compared to MI=0 (no ultrasound). At the same time, from the embedded bubble oscillation diagram, the maximum radial oscillation increased from about 3 μm at MI=0.1 to about 6 μm at MI=0.2, to about 10 μm at MI=0.3, and to more than 20 μm at MI=0.4. Importantly, the onset of the subsequent decrease in tissue uptake (from MI=0.2 to MI=0.3) coincides with the onset of significant nonlinear behavior, where inertial cavitation begins to occur.

[0195] The present invention should not be limited to the embodiments and examples shown. Although a plurality of embodiments of the present disclosure are described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Without departing from the present disclosure, it will be apparent to those skilled in the art that many modifications and changes as well as variations and replacements of the embodiments described herein may be made. It will be appreciated that, in practicing the present disclosure, a variety of alternatives to the embodiments described herein may be employed.

[0196] It should be understood that each embodiment of the present disclosure may be optionally combined with any one or more of the other embodiments described herein.

[0197] 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.Should also be understood that each amount / value or the range of amount / value of each component, compound or parameter disclosed herein should be interpreted as also being disclosed in combination with each amount / value or the range of amount / value of any other component, compound or parameter disclosed herein, and therefore, for the purpose of this specification, any combination of the amount / value or the range of amount / value of two or more components, compounds or parameters disclosed herein is also disclosed in combination with each other.Any and all features described herein and the combination of such features are all included within the scope of the present invention, provided that the features are not mutually inconsistent.

[0198] Should be understood that, for identical component, compound or parameter, the respective lower limit of each scope disclosed herein should be interpreted as disclosed in combination with the respective upper limit of each scope disclosed herein.Therefore, the disclosure of two scopes will be interpreted as the disclosure of four scopes obtained by combining the respective lower limit of each scope with the respective upper limit of each scope.The disclosure of three scopes will be interpreted as the disclosure of nine scopes obtained by combining the respective lower limit of each scope with the respective upper limit of each scope, etc.In addition, the concrete amount / value of component, compound or parameter disclosed in specification sheets or the embodiment will be interpreted as the disclosure of the lower limit or the upper limit of scope, and therefore can be combined with any other lower limit or upper limit or scope or concrete amount / value of the same component, compound or parameter disclosed elsewhere in the application, to form the scope of this component, compound or parameter.

[0199] Having described preferred embodiments of the present invention, it will be apparent to those skilled in the art that other embodiments incorporating the present invention may be used. These and other embodiments of the present invention illustrated above are intended to be examples only and the true scope of the invention will be determined by the appended claims.

Claims

1. A method for calculating a point estimate of an ultrasound dose to a target treatment area, the method comprising: A unique ultrasound propagation correction factor is calculated for a specific ultrasound propagation path through a specific area of ​​interest by: Obtaining a medium property map of the target area, wherein the medium property map provides a plurality of different medium property values ​​in different sections of the target area, the medium property values ​​depending on the medium in each of the sections, the obtaining of the medium property map of the target area comprising: obtaining an image of the target area, wherein the target area includes a target treatment area and an area surrounding the target treatment area; processing the image to identify different components of the region of interest; segmenting and classifying the different components into predetermined media categories; Querying media characteristic values ​​associated with each media category, including: estimating a class-specific ultrasonic coupling bubble element correction for the media property value caused by the presence of at least one ultrasonic coupling bubble element in at least one component; and adjusting a medium property value of the at least one component to take into account a corresponding class-specific ultrasound coupling bubble element correction; and assigning the medium property values ​​to respective components of the segmented target regions; Describing a propagation path from an ultrasound source to the target treatment area; aggregating the medium characteristic values ​​of each segment on the propagation path to calculate a unique propagation correction factor; and The unique propagation correction factor is used to indicate an ultrasound dose delivered to the target treatment area.

2. The method of claim 1, wherein the media category comprises at least one of the following: Different tissue 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: 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 area comprises at least one of: Querying a pre-scanned scan of the target area; Performing a pre-scan scan on the target area; and Use real-time diagnostic imaging system images.

5. The method of claim 4, wherein the scans include one or more of: Computed tomography images; and Magnetic resonance imaging.

6. A method as claimed in any preceding claim, wherein class-specific media property values ​​are queried from a database.

7. The method of any preceding claim, wherein the at least one ultrasound coupling bubble element comprises one or more of: 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 microvesicle 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 a contrast agent microbubble correction comprises: Querying or estimating one or more contrast agent microbubble parameters, wherein the one or more contrast agent microbubble parameters include: the value of the dose of contrast medium microbubbles administered; Contrast agent characteristics per unit concentration; The subject's blood volume; the subject's cardiac output; the value of blood volume associated with each category; arrival time of each category after intravenous contrast administration; and Time-concentration curves; as well as The contrast agent correction for each class is calculated using the contrast agent microbubble parameters.

9. The method of claim 7 or 8, wherein the at least one ultrasound coupling bubble element comprises an ACT bubble technology ultrasound coupling bubble element, and wherein calculating the additional ACT bubble correction comprises: To estimate the additional correction caused by ACT microbubble clusters in the presence of high-frequency activated ultrasound; estimating the additional correction caused by the ACT bubbles generated in the presence of high frequency activated ultrasound; and The additional correction caused by ACT bubbles in the presence of low-frequency enhanced ultrasound was estimated.

10. The method of claim 9, wherein calculating additional ACT bubble corrections further comprises: The number of ACT bubbles in the class associated with each component was estimated by: Query or estimate one or more ACT bubble parameters, wherein the ACT bubble parameters include: The subject's blood volume; the subject's cardiac output; the fill volume for each category of component; and time-concentration curves; and The number of ACT bubbles delivered to each component was calculated by multiplying the fraction of cardiac output 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 estimate of the number of ACT bubbles in the class associated with each segment incorporates time dependency by: The value of the lifetime of the ACT bubbles in each class is queried to model the decrease in the number of ACT bubbles in each class over time.

12. The method of any one of claims 8 to 11, wherein calculating the correction caused by the presence of contrast agent in each class is based on contrast mode imaging ultrasound.

13. The method of any one of claims 10 to 12, wherein calculating 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 preceding claim, further comprising using the unique propagation correction factor to calculate at least one of the following as an indication of delivered ultrasound dose: a generated pressure, a generated mechanical index, a generated intensity, a generated power, and a generated thermal index.

15. A non-transitory computer-readable storage medium having instructions stored thereon, the instructions performing the method of any one of claims 1 to 15 when executed on a processor.

16. A system for providing a point estimate of ultrasound dose to a region of interest in a subject, the system comprising: Ultrasound source; an image processor module for processing the image to identify different components of the region of interest; Computer processors; a database module containing medium characteristic values ​​associated with a plurality of categories of components in the target region; A data storage module comprising computer readable instructions that, when executed on the processor, perform the following tasks: querying an image of the target area, wherein the target area includes a target treatment area and an area surrounding the target treatment area; processing the image to identify different components of the region of interest; segmenting and classifying the different components into predetermined media categories; Query the media characteristic values ​​associated with each media category, including: estimating a class-specific ultrasonic coupling bubble element correction for the media property value caused by the presence of at least one ultrasonic coupling bubble element in at least one component; and adjusting a medium property value of the at least one component to take into account a corresponding class-specific ultrasound coupling bubble element correction; and assigning the medium property values ​​to respective components of the segmented target regions; and Describing an ultrasound propagation path from the ultrasound source to the target treatment area; Summarizing the medium characteristic values ​​of each component on the propagation path to calculate an ultrasonic propagation correction factor unique to the ultrasonic propagation path through the target area; calculating a point estimate of ultrasound dose to the target region based on the unique propagation correction factor; and If outside a predetermined ultrasound dose range, the ultrasound source is adjusted according to the calculated point estimate of the ultrasound dose.

17. The system of claim 17, wherein the image processor is configured to segment and classify different components of the region of interest by: identifying boundaries between different patterns in the image; analyzing patterns within the boundaries; and Each of the patterns is compared to image patterns of known tissue types to find a match.

18. The system of claim 18, wherein the system is a machine learning system and wherein each processed image and associated image data is accumulated as training data to provide more accurate segmentation and classification by the image processor over time.

19. The system of any one of claims 17 to 19, further configured to: Tracking probe position; re-evaluating one or more propagation correction factors as the probe position is moved; and One or more propagation correction factors are stored for each probe position to reduce computational load.

20. The system of any one of claims 17 to 20, further configured to: Tracking in-plane and out-of-plane rhythmic movement of a medium in the region of interest; re-evaluating one or more propagation correction factors for each in-plane and out-of-plane position of the moving medium; and One or more propagation correction factors are stored for each in-plane and out-of-plane position of the moving medium.

21. The system of claim 21, wherein the system is configured to track the in-plane and out-of-plane rhythmic movement of the medium by speckle tracking or a machine learning algorithm.

22. The method of any one of claims 1 to 15 or the system of any one of claims 17 to 22, wherein the medium property comprises at least one of: attenuation, acoustic velocity, shear wave velocity, acoustic impedance, nonlinear compressibility coefficient, and dispersion coefficient.

23. The method of claim 23, wherein the media properties further comprise one or more derived properties that can be derived from any one or any combination of the listed media properties.

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