3D ultrasound coronary angiography, non-ionizing and non-invasive techniques for multiscale anatomical and functional imaging of the coronary circulation.
4D ultrafast ultrasound imaging using a 2D array probe allows non-invasive, high-resolution visualization of coronary vessels from epicardial to endocardial regions, addressing the limitations of current techniques in visualizing coronary microvessels and reducing radiation exposure.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- INST NAT DE LA SANTE & DE LA RECHERCHE MEDICALE (INSERM)
- Filing Date
- 2021-04-13
- Publication Date
- 2026-06-09
Smart Images
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Figure 0007872231000008
Abstract
Description
[Technical Field]
[0001] The coronary circulation is involved in cardiac perfusion, and changes in coronary blood flow, as seen in stable angina or myocardial infarction, have serious effects on cardiac function. The coronary vascular system consists of three compartments. The first compartment consists of the epicardial coronary arteries, which extend along the surface of the heart and range in diameter from a few millimeters to 500 μm. The second compartment includes the anterior arterioles, which penetrate the myocardium from the epicardium to the endocardium and range in diameter from 500 μm to 100 μm. The third compartment corresponds to the coronary microvessels, whose vessel diameter is less than 100 μm ([Non-Patent Literature 1]). [Background technology]
[0002] Currently, the epicardial coronary vascular system is the only compartment that can be imaged in vivo in humans using current angiographic techniques ([Non-Patent Literature 1], [Non-Patent Literature 2]), such as X-ray ([Non-Patent Literature 3]), CT angiography (CTA) ([Non-Patent Literature 4]), or cardiac magnetic resonance (CMR) imaging ([Non-Patent Literature 5]). Therefore, cardiological practice has focused on localized macroscopic coronary artery disease. For example, invasive coronary angiography (ICA) using catheters ([Non-Patent Literature 3]) remains the standard technique for examining coronary artery lesions when ischemia is suspected. ICA allows for not only anatomical analysis of severe epicardial stenosis but also an overall functional assessment based on fractional flow reserve (FFR). FFR assessment is indeed a primary tool for clinical decision-making in ischemic heart disease ([Non-Patent Document 2], [Non-Patent Document 6]) and a primary tool for subsequent pharmacological or invasive treatment via percutaneous coronary intervention or surgery ([Non-Patent Document 7]).
[0003] In many patients, the initial signs of coronary artery disease (CAD) are microvascular disorders, and coronary microvascular dysfunction, including anterior arteriole dysfunction, is now recognized as an important marker of myocardial ischemia ([Non-Patent Literature 1], [Non-Patent Literature 6]). However, there are still problems with evaluating this marker in clinical practice.
[0004] Indeed, clinical guidelines for the management of stable ischemic heart disease only consider coronary microvascular dysfunction after ruling out signs of epicardial disease ([Non-Patent Literature 8]). A large number of patients presenting with angina symptoms and ischemia on stress tests have normal coronary angiography ([Non-Patent Literature 9]). Current evidence indicates that the majority of these patients have coronary microvascular dysfunction (CMD), also known as microvascular angina ([Non-Patent Literature 9]). Patients with CMD have a poor prognosis and a significantly higher incidence of cardiovascular events, including hospitalization for heart failure, sudden cardiac death, and myocardial infarction (MI).
[0005] Despite the urgent need in clinical practice, techniques for directly visualizing coronary microvessels and evaluating the local coronary microvascular system are not clinically available. Currently, the only hemodynamic information available, such as myocardial blood flow (MBF) and coronary flow reserve (CFR), is provided by overall indirect measurements using functional tests (PET, CMR, and contrast echocardiography) in response to vasodilatory adenosine ([Non-Patent Literature 1]).
[0006] However, despite improvements in radiation dose management, cumulative exposure to ionizing modalities carries a risk of developing cancer ([Non-Patent Literature 10]). This risk is particularly important in pediatric patients, such as children with congenital or acquired heart disease, who may be exposed to relatively high lifetime cumulative doses of ionizing radiation from necessary medical imaging procedures, including radiography, fluoroscopy including diagnostic and interventional cardiac catheterization, electrophysiological examinations, cardiac computed tomography (CT) scans, and cardiac nuclear medicine examinations ([Non-Patent Literature 11]).
[0007] Blood flow imaging remains a challenging task in organs that move rapidly, such as the heart. The sensitivity of conventional ultrasound Doppler imaging has long been limited when imaging small blood vessels with low flow velocities (<1 cm / s), as tissue and blood motion overlap at this speed, making it difficult to separate tissue and blood signals. In recent years, ultrafast Doppler imaging has made it possible to significantly increase the sensitivity of blood flow imaging. This technique has been shown to enable the detection of subtle changes in cerebral blood flow due to neurovascular interactions in anesthetized and awake animals used in neuroscience research, and thus enable brain function imaging ([Non-Patent Literature 12]). Sensitivity has been further enhanced by the development of novel clutter filters adapted to ultrafast imaging, such as spatiotemporal singular value decomposition ([Non-Patent Literature 13]). However, in cardiac applications, ultrasound Doppler imaging of coronary blood flow remains limited due to the high speed of the heart's movement.
[0008] While ultrafast Doppler imaging has been shown to limit some of the effects of the above-mentioned motions and improve the sensitivity of Doppler imaging ([Non-Patent Document 14]), Doppler imaging remains impossible during the fast motion phase of the heart.
[0009] To overcome the limitations of actual imaging methods for coronary blood flow, the inventors have adapted the recently proposed 4D (3D + time) ultrafast ultrasound imaging method ([Patent Document 1]) to automatically detect periods of low myocardial motion velocity and to estimate flow velocity and tissue motion velocity from the same data acquisition.
[0010] Therefore, non-invasive, non-ionizing techniques are provided for imaging coronary blood flow at the patient's bedside at macro and microscopic scales. [Prior art documents] [Patent Documents]
[0011] [Patent Document 1] WO 2019 / 158741 A1 [Non-patent literature]
[0012] [Non-licensed document 1] PG Camici, G. d'Amati, O. Rimoldi, Nat. Rev. Cardiol. 12, 48-62 (2015). [Non-licensed document 2] SD Fihn et al., J. Thorac. Cardiovasc. Surg. 149, e5-23 (2015). [Non-licensed document 3] JA Ambrose, DH Israel, Curr. Opin. Cardiol. 5, 411-416 (1990).
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Non-licensed Document 6
Non-licensed Document 7
Non-licensed literature 9
Non-licensed literature 10
[0013] The scope of the present invention is defined by the claims. Any subject matter outside the claims is provided only for the purpose of information provision.
[0014] Non - invasive and non - ionizing imaging methods are disclosed for improving direct imaging of coronary blood flow and imaging of the biological structure and function of coronary vessels at the macroscale and microscopic scale from the epicardial region to the endocardial region.
[0015] Therefore, imaging methods, imaging devices, and computer - readable media for non - ionizing non - invasive anatomical and functional imaging of coronary vessels at the macroscale and microscopic scale are provided.
[0016] List of Abbreviations CAD = Coronary Artery Disease CFR = Coronary Flow Reserve CMD = Coronary Microvascular Dysfunction CMR = Cardiac Magnetic Resonance CT = Computed Tomography CTA = Computed Tomography Angiography DSP = Digital Signal Processor ECG = Electrocardiogram FFR = Percentage of coronary flow reserve ICA = Invasive Coronary Angiography MBF = Myocardial Blood Flow MI = Myocardial Infarction PET = Positron Emission Tomography SVD = Singular Value Decomposition TD = Transmission Delay
[0017] Other features and advantages of this disclosure will become apparent from the following detailed description of an unrestrictive example of this disclosure with reference to the attached drawings. [Brief explanation of the drawing]
[0018] [Figure 1] This is a schematic diagram showing a device for 4D imaging of the heart. [Figure 2] This is a block diagram showing a part of the apparatus in Figure 1. [Figure 3] This figure shows the virtual source of divergent ultrasound generated by the apparatus shown in Figures 1 and 2. [Figure 4] Figures 1 and 2 show the transmission of divergent ultrasound in the heart of a living organism using the devices shown. [Figure 5] These figures show the transmission of two consecutive divergent ultrasonic waves, each with a different propagation direction from two virtual sources. [Figure 6] This diagram illustrates the motion of the myocardial wall during the cardiac cycle. Blood flow can be reconstructed within two time windows with restricted tissue motion velocities. [Figure 7] This figure shows an example of coronary blood flow velocity imaging between baseline and reactive hyperemia. [Figure 8] This figure shows microbubble imaging and localization (average intensity projection). [Figure 9](A) The coronary artery network of an isolated heart perfused by ultrasound imaging and (B) Microbubble localization and tracking using mapped coronary blood flow velocity in an isolated perfused heart. [Modes for carrying out the invention]
[0019] In each figure, the same reference numeral indicates the same or similar elements.
[0020] The apparatus shown in Figures 1 and 2 is adapted for ultrafast 4D ultrasound imaging of organisms, such as mammals, particularly the human heart.
[0021] This apparatus may include, for example, at least a 2D array ultrasound probe 2 and a control system.
[0022] The 2D array ultrasound probe 2 has, for example, hundreds to thousands of transducer elements T with a pitch smaller than 1 mm. ij The 2D array ultrasonic probe 2 may have n*n transducer elements arranged as a matrix along two vertical axes X and Y, transmitting ultrasound along an axis Z perpendicular to the XY plane. In a particular example, the 2D array ultrasonic probe 2 has 1024 transducer elements T with a pitch of 0.3 mm. ij It may have (32*32). The transducer element may transmit, for example, between 1 MHz and 10 MHz, with a center frequency of, for example, 3 MHz.
[0023] The control system may include, for example, a specific control unit 3 and a computer 4. In this example, the control unit 3 is used to control the 2D array ultrasound probe 2 and to acquire signals from the 2D array ultrasound probe 2, while the computer 4 is used to control the control unit 3, generate a 3D image sequence from the signals acquired by the control unit 3, and determine quantification parameters from the 3D image sequence. In a modified embodiment, a single electronic device can implement all the functions of the control unit 3 and the computer 4.
[0024] As shown in Figure 2, the control unit 3 is, for example, - 2D array ultrasound probe 2 with n transducers T ij Each of the n*n analog-to-digital converters 5 (AD) is individually connected to them. ij )and, - n*n buffer memory 6(B) connected to n*n analog / digital converters 5, respectively. ij )and, - A central processing unit 7 (CPU) that communicates with buffer memory 6 and computer 4, - Memory 8 (MEM) connected to the central processing unit 7, - May also include a digital signal processor 9 (DSP) connected to the central processing unit 7.
[0025] This device may operate as follows:
[0026] (a) Acquisition The 2D array ultrasound probe 2 is positioned on the chest 10 of patient 1, usually between two ribs, in front of the patient's heart 12, as shown in Figure 4.
[0027] Because the intercostal spaces between the ribs 11 are limited compared to the size of the heart 12 to be imaged, the 2D array ultrasound probe 2 is controlled to transmit divergent ultrasound, such as spherical ultrasound (i.e., ultrasound with a spherical wavefront O1), within the chest 10. The control system may be programmed to transmit ultrasound at a rate of several thousand per second, and unfocused ultrasound at a rate of, for example, more than 10,000 per second.
[0028] Spherical waves can be generated (at low amplitude) by a single transducer element, or more advantageously, by one or more virtual sources T' that form a virtual array 2' positioned behind or in front of the 2D array ultrasonic probe 2, as shown in Figures 3-4. ij This can be generated with higher amplitude by the majority of the matrix array.
[0029]
number
[0030] transducer element e (at a predetermined position)
[0031]
number
[0032] The transmit delay TD added by the control system to the virtual source v located therein is:
[0033]
number
[0034] It is expressed as follows, where c is the speed of sound.
[0035] Each virtual source T' used ij The control system is capable of operating only a subset 2a of the 2D array ultrasound probe 2, which has a sub-aperture L that determines the aperture angle α of the diverging ultrasound. The aperture angle α may be, for example, 90°. The imaging depth along axis Z may be approximately 12 cm to 15 cm.
[0036] As will be explained later, each 3D image of the heart has one virtual source T' ij It uses only one ultrasound wave, and therefore, it is possible to use only one ultrasound wave.
[0037] However, to improve image resolution and contrast, it is useful to transmit non-focused ultrasound as a series of consecutive non-focused ultrasounds, and the consecutive non-focused ultrasounds in each series of non-focused ultrasounds have different propagation directions. In that case, each 3D image is synthesized from signals obtained from a series of consecutive non-focused ultrasounds among the series of consecutive non-focused ultrasounds as described later. The consecutive ultrasounds in each series of non-focused ultrasounds, as shown in FIG. 5, are virtual sources T’ ij alternately changed with respect to the wave, and thus may be obtained by changing wavefronts O1, O2, etc. Each series of non-focused ultrasounds may include 1 to 81 consecutive ultrasounds in different directions, for example, 3 to 25 consecutive ultrasounds in different directions, for example, 5 to 20 consecutive ultrasounds in different directions, for example, 10 to 20 consecutive ultrasounds in different directions.
[0038] In all cases, after each ultrasound is transmitted, the backscattered echo is acquired (e.g., sampled at a sampling rate of 12 MHz) and stored by the 2D array ultrasound probe. A sequence of 3D images is generated using this raw data (usually also called RF data or radio frequency data).
[0039] The acquisition duration may be included between 10 ms and several cardiac cycles, for example, at least a part of a cardiac cycle (e.g., cardiac diastole or systole, preferably cardiac diastole, or one cardiac cycle) to less than 10 cardiac cycles (e.g., less than 5 cardiac cycles). Such a duration may be included, for example, between 1 s and 10 s (e.g., less than 5 s). In a specific example, such a duration is about 1.5 s.
[0040] An electrocardiogram (ECG) may be simultaneously recorded during this acquisition.
[0041] (b) Imaging After receiving backscattered echoes, parallel beamforming can be directly applied by the control system, and a 3D image can be reconstructed from each single ultrasound. Delayed sum beamforming can be used in the time domain or the Fourier domain. In the time domain,
[0042]
number
[0043] The delay added to the signal received by each transducer element e in order to reconstruct the voxels arranged is the sum of the forward propagation time from the virtual source v to this voxel and the backscatter propagation time to the transducer element e. Delay = Forward delay + Backscattering delay
[0044]
number
[0045] Another possibility is to use Fourier domain imaging (spatial frequency, k-space).
[0046] As described above, when ultrasound is transmitted by a series of ultrasounds, each with a different propagation direction, each image can be acquired by a control system through a known composite imaging process. The voxels are beamformed for each virtual source using a delay-sum algorithm and then coherently composited to form a final high-quality 3D image. Details of such composite imaging are described, for example, in the following literature. Montaldo, G., Tanter, M., Bercoff, J., Benech, N., Fink, M., 2009. Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 56, 489-506. doi:10.1109 / TUFFC.2009.1067 Nikolov, S.I., 2001. Synthetic aperture tissue and flow ultrasound imaging. Orsted-DTU, Technical University of Denmark, Lyngby, Denmark. Nikolov, S.I., Kortbek, J., Jensen, J.A., 2010. Practical applications of synthetic aperture imaging, in: 2010 IEEE Ultrasonics Symposium (IUS). Presented at 2010 IEEE Ultrasonics Symposium (IUS), pp. 350-358. doi:10.1109 / ULTSYM.2010.5935627 Lockwood, G.R., Talman, J.R., Brunke, S.S., 1998. Real-time 3-D ultrasound imaging using sparse synthetic aperture beamforming. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 45, 980-988. doi:10.1109 / 58.710573 Papadacci, C., Pernot, M., Coade, M., Fink, M., and Tanter, M. High-contrast ultrafast imaging of the heart. IEEE transactions on ultrasonics, ferroelectrics, and frequency control 61, 288-301, doi:10.1109 / tuffc.2014.6722614 (2014).
[0047] The frame rate, that is, the proportion of 3D images in the final animation sequence, may be several thousand 3D images per second, for example, 3,000 to 5,000 3D images per second.
[0048] (c) Identification of the time window The time window in which the tissue motion velocity reaches its minimum may be determined by the control system using known methods.
[0049] In certain cases, the time window in which tissue motion velocity reaches its minimum is: - A time window in which the myocardial velocity is less than 5 cm / s, or - This can be defined as a time window corresponding to the start and end times of cardiac diastole.
[0050] In certain cases, the time window is determined by electrophotography.
[0051] In another specific example, the time window is identified by the control system through organizational motion estimation performed using the method described below.
[0052] (d) Calculation of blood flow and tissue motion velocity Blood flow and tissue motion estimation may be performed by the control system using known methods.
[0053] For example, the Kasai algorithm may be used to estimate blood and tissue motion using half-wavelength spatial sampling (Kasai, C., Namekawa, K., Koyano, A., Omoto, R., 1985. Real-Time Two-Dimensional Blood Flow Imaging Using an Autocorrelation Technique. IEEE Trans. Sonics Ultrason. 32, 458-464. doi:10.1109 / T-SU.1985.31615). Blood flow can first be estimated by applying a high-pass filter to baseband data, and then, for each individual voxel, power Doppler may be obtained by integrating the power spectral density, pulsed Doppler may be obtained by calculating the short-time Fourier transform, or a color Doppler map may be obtained by estimating the first moment of the voxel-specific pulsed Doppler spectrogram. A power-velocity integral map can be obtained by calculating the time integral of power multiplied by velocity to obtain an image of flow rate parameters. Clutter signals can be more effectively removed using advanced filtering techniques such as spatiotemporal filtering based on singular value decomposition (Demene, C. et al. Spatiotemporal Clutter Filtering of Ultrafast Ultrasound Data Highly Increases Doppler and Ultrasound Sensitivity. IEEE Transactions on Medical Imaging 34, 2271-2285, doi:10.1109 / tmi.2015.2428634 (2015)).
[0054] In certain cases, - 4D tissue motion velocity may be calculated by performing 1D cross-correlation to obtain the volume of axial displacement between tissue volumes. Butterworth low-pass filtering with a 60 Hz cutoff frequency was then applied to the displacement. A myocardial 3D mask (a 3D mask specific to myocardial tissue) may be applied to remove signals outside the muscle. Amira® software may be used to surface the 4D tissue motion velocity. One tissue motion velocity curve may be derived for each voxel. - For example, 4D color Doppler may be calculated by performing SVD filtering to remove signals from tissue and retaining only signals from blood flow, as done in [Non-Patent Document 21] above. Color Doppler volume may be obtained by performing pixel-level 1D axial cross-correlation on the voxels after SVD filtering.
[0055] The myocardium may be segmented using tissue motion velocity integrated over the cardiac cycle and manual selection of contours on two mutually perpendicular 2D slices. A three-dimensional representation may be obtained using elliptic interpolation.
[0056] More generally, step (d) includes automatically calculating a 3D cartography of at least one parameter relating to blood flow velocity and / or tissue motion velocity within the imaged volume, based on the sequence of 3D images. The 3D cartography may consist of an animated sequence of 3D images of the calculated parameter. This parameter may be blood flow velocity and / or tissue motion velocity, or a combination thereof.
[0057] (e) Identifying the location of the point of interest Depending on the quantification parameters being pursued, the location of at least one point of interest having predetermined characteristics is identified in the sequence of 3D images. The location of this at least one point of interest having predetermined characteristics can be automatically identified by a control system or manually identified by an operator.
[0058] When the quantification parameters include blood flow velocity in a certain anatomical region, the point of interest may be automatically identified by the control system as a point of blood flow velocity within the anatomical region and in at least a portion of the sequence of 3D images, or it may be manually identified by the operator. In certain examples, a time-series Fourier transform may be performed by capturing a spectrogram of any position in the volume using a 60-sample sliding window for each voxel. Automatic dealiasing may be performed according to [Non-Patent Literature 21] above. The location of the point of interest may then be automatically detected by detecting the maximum blood flow value.
[0059] When the quantification parameters include tissue motion velocity at a specific anatomical location within the heart, the anatomical location in the sequence of 3D images may be automatically identified by the control system or manually identified by the operator. Such automatic localization may be performed according to an anatomical model of the heart stored in the computer 4, or by selecting a point within the tissue.
[0060] When the quantification parameter includes the lowest tissue motion velocity within a certain anatomical region, the anatomical region in the 3D image sequence may be automatically identified by the control system or manually identified by the operator, and the point of interest may be automatically identified by the control system or manually identified by the operator as the point of lowest tissue motion velocity within the anatomical region in the 3D image sequence. For example, when it is necessary to calculate the lowest tissue motion velocity of myocardium, the system identifies the point of myocardium having the lowest velocity in the myocardium image sequence.
[0061] (f) Quantification Next, the control system (specifically the computer 4) can calculate the desired quantification parameters based on the already identified points of interest and based on the peak blood flow velocity or tissue movement velocity of such points of interest.
[0062] The following points should be noted. - In step (e) of locating the point of interest, the at least one point of interest is located solely based on the 3D cartography and its time profile. - In the quantification step (step (f)), the at least one velocity is automatically determined at the at least one point of interest based solely on the 3D cartography and its time profile.
[0063] More generally, in this disclosure, coronary blood flow can be localized using only spatial and temporal velocity information without any additional anatomical information.
[0064] Therefore, the point of interest and the velocity at this point of interest are determined without the need for anatomical images, particularly B-mode anatomical images, due to the method involving the identification of a 3D cartography of velocity across the entire imaged volume. Thus, no part of the method of this disclosure requires B-mode imaging, and more generally, no anatomical imaging, thereby allowing the method to obtain results more quickly.
[0065] Therefore, a method is provided for imaging coronary blood flow in the heart of a living organism, the method comprising at least the following steps, namely, Step a) An acquisition step in which non-focused ultrasound is transmitted within the heart by a 2D array ultrasound transducer, and raw data from the backscattered ultrasound is acquired by the 2D array ultrasound transducer, Step b) An imaging step in which a sequence of N 3D volumetric coronary blood flow images of the heart of the organism is generated from the raw data, wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart. Step c) A specific step in which at least one time window is identified, in which the movement of the heart is minimal, Step d) A calculation step in which a 3D cartography of at least one parameter relating to coronary blood flow velocity is automatically calculated in the acquired volume based on a sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), Step e) A localization step in which at least one point of interest having predetermined characteristics is located in the sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), based solely on the 3D cartography of step d), Step f) a quantification step in which a coronary blood flow velocity is automatically determined at at least one point of interest in step e) and predetermined quantification parameters including the coronary blood flow velocity are automatically calculated, wherein the coronary blood flow velocity is automatically determined at the at least one point of interest based solely on the 3D cartography of step d).
[0066] This method may further include one and / or the other of the following features: - At least one time window in specific step c) is identified by electrocardiography. - Specific step c) is the following step, namely, Step i) an imaging step in which a sequence of N 3D volumetric tissue images of the heart of the organism is generated from the raw data of step a), wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart, Step ii) A calculation step in which a 3D cartography of at least one parameter relating to cardiac tissue motion velocity is automatically calculated in the imaged volume based on the sequence of N 3D volumetric tissue images showing the movement of the imaged volume of the heart, Step iii) A cardiac tissue motion estimation step in which at least one point of interest having predetermined characteristics is located in the sequence of N 3D volumetric tissue images based solely on the 3D cartography of step ii), and the tissue motion velocity at the at least one point of interest is automatically determined. Step iv) The time window is identified, and this time window includes a specific step in which the tissue motion velocity quantified in step iii) reaches a minimum velocity. - The tissue imaging step in step i) is performed simultaneously with the blood flow imaging step in step b). - The minimum speed in step iv) is less than 5 cm / s. Steps a) through f) are repeated with each cardiac cycle. - At least one time window in step c) corresponds to the start and end times of cardiac diastole. - The quantification parameter in step f) is selected from the blood flow profile, peak velocity profile, average velocity profile, or time velocity profile. - A tracking step in which, in a patient who has already received microbubbles or an ultrasound contrast agent to be injected into the patient's own vascular system, the microbubbles or ultrasound contrast agent are tracked and their trajectories and velocities are determined. - Tissue motion estimation is performed using a Doppler estimator or speckle tracking. - Coronary blood flow 3D cartography is performed using Doppler energy imaging, Doppler color imaging, or speckle tracking. - Tissue motion during the time window in step c) is estimated, motion correction is applied, and the estimation of tissue motion proceeds to the following steps, i.e., Step 1) An imaging step in which a sequence of N 3D volumetric tissue images of the heart of the organism is generated from the raw data of step a) corresponding to the time window of step c), wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart during the time window of step c), Step 2) A calculation step in which a 3D cartography of at least one parameter relating to cardiac tissue motion velocity is automatically calculated in the imaged volume based on the sequence of N 3D volumetric tissue images showing the movement of the imaged volume of the heart during the time window of step c), Step 3) includes a motion estimation step in which at least one point of interest having predetermined characteristics is located in the sequence of N 3D volumetric tissue images, based solely on the 3D cartography of Step 2), and the tissue motion velocity at the at least one point of interest is automatically determined. - Automated image registration is performed, and a continuous 3D coronary blood flow cartography is calculated. - The bubble or ultrasound contrast agent tracking step consists of spatiotemporal filtering or machine learning. - Coronary vessel density is automatically quantified. - The volume of blood being perfused is automatically quantified in units of volume. - Stenosis is automatically detected by accelerating blood flow velocity. - Coronary blood flow reserve index is obtained by estimating changes in coronary blood flow velocity in patients who have already been administered vasodilators. - Automated segmentation step of the central cavity. - At least one point of interest having the predetermined characteristics of the location step e) is located automatically or manually by an operator. - At least one point of interest having the predetermined characteristics of motion estimation step iii) is automatically located or manually located by an operator. - At least one point of interest having the predetermined characteristics of motion estimation step 3) is automatically located or manually located by an operator.
[0067] Furthermore, an apparatus for 4D imaging of coronary blood flow in the heart of a living organism according to the method described above is also disclosed, wherein the apparatus includes at least a 2D array ultrasound probe (2) and a control system (3, 4), the control system (3, 4) (a) Transmitting non-focused ultrasound within the heart using a 2D array ultrasound transducer, and acquiring raw data from the backscattered ultrasound through the 2D array ultrasound transducer, (b) To generate a sequence of N 3D volumetric coronary blood flow images of the heart of the organism from the raw data, wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart. (c) Identify at least one time window in which cardiac activity is minimized, (d)(c)( (e) Based exclusively on the 3D cartography of (d), identify the location of at least one point of interest having predetermined characteristics in the sequence of N 3D coronary blood flow images corresponding to at least one time window identified in (c), (f) The system is configured to automatically identify the coronary blood flow velocity at at least one point of interest in (e) based solely on the 3D cartography in (d), and to automatically calculate predetermined quantifiable parameters, including the coronary blood flow velocity.
[0068] This device may further include one and / or the other of the following features: - The apparatus in (c) (i)(a)(a)(i (ii) Based on the sequence of N 3D volumetric tissue images showing the movement of the imaged volume of the heart, automatically calculate a 3D cartography of at least one parameter relating to the cardiac tissue motion velocity in the imaged volume, (iii) Based solely on the 3D cartography of (ii), identify the location of at least one point of interest having predetermined characteristics in the sequence of N 3D volumetric tissue images, and automatically determine the tissue motion velocity at the at least one point of interest. (iv)(iii) is configured to identify the time window in which the quantified tissue movement velocity reaches the lowest velocity. - The device is configured to identify at least one time window in (c) by electrocardiography.
[0069] A computer-readable medium for 4D imaging of coronary blood flow in the heart of a living organism is disclosed in accordance with the method described above, wherein the computer-readable medium includes instructions, and when the instructions are executed by the computer, the computer performs the following steps, namely: Step a) Transmitting non-focused ultrasound within the heart using a 2D array ultrasound transducer, and acquiring raw data from the backscattered ultrasound through the 2D array ultrasound transducer, Step b) A step of generating a sequence of N 3D volumetric coronary blood flow images of the heart of the organism from the raw data, wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart. Step c) Identify at least one time window in which cardiac activity is minimized, Step d) Automatically calculate a 3D cartography of at least one parameter relating to coronary blood flow velocity in the acquired volume based on a sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), Step e) Based solely on the 3D cartography of step d), the step of identifying the location of at least one point of interest having predetermined characteristics in the sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), Step f) is performed to automatically identify the coronary blood flow velocity at at least one point of interest in step e) based solely on the 3D cartography of step d), and to automatically calculate predetermined quantifiable parameters including the coronary blood flow velocity.
[0070] The computer-readable medium may further contain instructions that, when executed by the computer, cause the computer to perform the following steps: - In step c), the computer performs the following steps, namely, (i) A step of generating a sequence of N 3D volumetric tissue images of the heart of the organism from the raw data of (a), wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart, (ii) A step of automatically calculating a 3D cartography of at least one parameter relating to cardiac tissue motion velocity in the imaged volume based on the sequence of N 3D volumetric tissue images showing the movement of the imaged volume of the heart, (iii) Based exclusively on the 3D cartography of (ii), the step of identifying the location of at least one point of interest having predetermined characteristics in the sequence of N 3D volumetric tissue images, and automatically determining the tissue motion velocity at the at least one point of interest, (iv)(iii) is configured to perform the step of identifying the time window in which the quantified tissue movement velocity reaches the lowest velocity. - A computer-readable medium is configured to perform step c) by electrocardiogram testing. [Examples]
[0071] In a particular embodiment, a method for imaging coronary blood flow in a living organism's heart involves the following steps: Step a) An acquisition step in which non-focused ultrasound is transmitted within the heart by a 2D array ultrasound transducer, and raw data from the backscattered ultrasound is acquired by the 2D array ultrasound transducer, Step b) An imaging step in which a sequence of N 3D volumetric tissue images and N 3D volumetric coronary blood flow images of the heart of the organism is generated from the raw data of step a), wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart. Step c) A specific step in which at least one time window in which the heart movement is minimal is identified, namely, (i) A calculation step in which a 3D cartography of at least one parameter relating to cardiac tissue motion velocity is automatically calculated in the imaged volume based on a sequence of N 3D volumetric tissue images from step b) showing the movement of the imaged volume of the heart, (ii) A cardiac tissue motion estimation step in which at least one point of interest having predetermined characteristics is located in the sequence of N 3D volumetric tissue images based solely on the 3D cartography of step (i), and the tissue motion velocity at the at least one point of interest is automatically determined, (iii) A specific step in which a time window is identified when the tissue motion velocity quantified in step (ii) reaches a minimum velocity, Step d) A calculation step in which a 3D cartography of at least one parameter relating to coronary blood flow velocity is automatically calculated in the acquired volume based on a sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), Step e) A localization step in which at least one point of interest having predetermined characteristics is automatically located in the sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), based solely on the 3D cartography of step d), Step f) a quantification step in which a coronary blood flow velocity is automatically determined at at least one point of interest in step e) and predetermined quantification parameters including the coronary blood flow velocity are automatically calculated, wherein the coronary blood flow velocity is automatically determined at the at least one point of interest based solely on the 3D cartography of step d).
[0072] In another specific embodiment, a method for imaging coronary blood flow in a living organism's heart involves the following steps: Step a) An acquisition step in which non-focused ultrasound is transmitted within the heart by a 2D array ultrasound transducer, and raw data from the backscattered ultrasound is acquired by the 2D array ultrasound transducer, Step b) An imaging step in which a sequence of N 3D volumetric coronary blood flow images of the heart of the organism is generated from the raw data, wherein the sequence of 3D images forming an animation shows the movement of the imaged volume of the heart. Step c) Identification step in which at least one time window in which cardiac movement is minimized is identified, wherein the time window is identified by an electrocardiogram, and at least one time window preferably corresponds to the start and end times of cardiac diastole. Step d) A calculation step in which a 3D cartography of at least one parameter relating to coronary blood flow velocity is automatically calculated in the acquired volume based on a sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), Step e) A localization step in which at least one point of interest having predetermined characteristics is located in the sequence of N 3D coronary blood flow images corresponding to at least one time window identified in step c), based solely on the 3D cartography of step d), Step f) a quantification step in which a coronary blood flow velocity is automatically determined at at least one point of interest in step e) and predetermined quantification parameters including the coronary blood flow velocity are automatically calculated, wherein the coronary blood flow velocity is automatically determined at the at least one point of interest based solely on the 3D cartography of step d). [Explanation of symbols]
[0073] 1 living things 2 2D Array Ultrasound Probes 2' virtual array 2a Subset 3. Control Unit 4 Computers 5 n*n analog-to-digital converter (AD) ij ) 6 n*n buffer memory (B ij ) 7. Central Processing Unit (CPU) 8. Memory (MEM) 9. Digital Signal Processor (DSP) 10 Chest 12 Heart T ij , e transducer element T' ij , v virtual source
Claims
1. A method for imaging coronary blood flow in the heart of a living organism, comprising at least the following steps: Step a) An acquisition step in which unfocused ultrasound is transmitted within the heart by a 2D array ultrasound transducer, and raw data from the backscattered ultrasound is acquired by the 2D array ultrasound transducer, Step b) An imaging step in which a sequence of N 3D volumetric coronary blood flow images of the heart is generated from the raw data, wherein the sequence of N 3D volumetric coronary blood flow images forming an animation shows the movement of the heart in the imaged volume of the heart, Step c) A specific step in which at least one time window is identified, in which the movement of the heart is minimized, Step d) A calculation step in which a 3D cartography of at least one parameter relating to coronary blood flow velocity is automatically calculated in the acquired volume based on the sequence of N 3D volumetric coronary blood flow images corresponding to the at least one time window identified in step c), Step e) A localization step in which at least one point of interest having predetermined characteristics is located in the sequence of N 3D volumetric coronary blood flow images corresponding to the at least one time window identified in step c) based solely on the 3D cartography and its time profile in step d), A method comprising step f) a quantification step in which the coronary blood flow velocity is automatically determined at the at least one point of interest in step e) and predetermined quantification parameters including the coronary blood flow velocity are automatically calculated, wherein the coronary blood flow velocity is automatically determined at the at least one point of interest based solely on the 3D cartography and its time profile in step d).
2. Step c) above is the following step, namely, Step i) an imaging step in which a sequence of N 3D volumetric tissue images of the heart is generated from the raw data of step a), wherein the sequence of N 3D volumetric tissue images of the heart forming an animation shows the movement of the heart in the imaged volume of the heart, Step ii) A calculation step in which a 3D cartography of at least one parameter relating to cardiac tissue motion velocity is automatically calculated in the imaged volume based on the sequence of N 3D volumetric tissue images showing the movement of the heart in the imaged volume of the heart, Step iii) A step of estimating cardiac tissue motion in which at least one point of interest having predetermined characteristics is located in the sequence of N 3D volumetric tissue images based solely on the 3D cartography of step ii), and the tissue motion velocity at the at least one point of interest is automatically determined. The method according to claim 1, comprising step iv) a specific step in which the time window is identified, in which the tissue motion velocity quantified in step iii) reaches a minimum velocity.
3. The method according to claim 2, wherein the minimum speed in step iv) is less than 5 cm / s.
4. The method according to claim 1, wherein the at least one time window in step c) is determined by an electrocardiogram.
5. The method according to any one of claims 1 to 4, wherein the at least one time window in step c) corresponds to the start and end times of cardiac diastole, and the quantification parameter in step f) is selected from the peak velocity profile, average velocity profile, or time velocity profile of the coronary blood flow.
6. The method according to any one of claims 1 to 5, further comprising a tracking step in which, in a patient who has already been administered microbubbles or an ultrasound contrast agent to be injected into the patient's own vascular system, the microbubbles or ultrasound contrast agent are tracked and the trajectory and velocity of the microbubbles or the ultrasound contrast agent are determined.
7. The method according to any one of claims 1, 2, 5, and 6, wherein the tissue motion of the heart is estimated by a Doppler estimator or speckle tracking.
8. The method according to claim 6, wherein the bubble or ultrasound contrast agent tracking step comprises spatiotemporal filtering or machine learning.
9. The method according to any one of claims 1 to 8, wherein the density of coronary vessels in a unit volume is automatically quantified, the volume of blood perfused in a unit volume is automatically quantified, stenosis is automatically detected when acceleration of blood flow velocity is determined, and a coronary flow reserve index is obtained by estimating the variation in coronary blood flow velocity in a patient who has already been administered a vasodilator.
10. An apparatus for 4D imaging of coronary blood flow in the heart of a living organism, wherein the apparatus includes at least a 2D array ultrasound probe (2) and a control system (3, 4), and the control system (3, 4) (a) Transmitting non-focused ultrasound within the heart using a 2D array ultrasound transducer, and acquiring raw data from the backscattered ultrasound through the 2D array ultrasound transducer, (b) Generating a sequence of N 3D volumetric coronary flow images of the heart from the raw data, wherein the sequence of N 3D volumetric coronary flow images forming an animation shows the movement of the heart in the imaged volume of the heart, (c) Identifying at least one time window in which the cardiac movement is minimized, (d)(c)( (e) Based exclusively on the 3D cartography and its time profile in (d), identify the location of at least one point of interest having predetermined characteristics in the sequence of N 3D volumetric coronary blood flow images corresponding to the at least one time window identified in (c), (f) an apparatus configured to automatically identify the coronary blood flow velocity at at least one point of interest in (e) based solely on the 3D cartography and its time profile in (d), and to automatically calculate predetermined quantifiable parameters including the coronary blood flow velocity.
11. (c) In, (i) To generate a sequence of N 3D volumetric tissue images of the heart from the raw data of (a), wherein the sequence of N 3D volumetric tissue images forming an animation shows the movement of the heart in the imaged volume of the heart, (ii) Based on the sequence of N 3D volumetric tissue images showing the movement of the heart in the imaged volume of the heart, to automatically calculate a 3D cartography of at least one parameter relating to the velocity of cardiac tissue movement in the imaged volume, (iii) Based solely on the 3D cartography of (ii), the location of at least one point of interest having predetermined characteristics in the sequence of N 3D volumetric tissue images, and the tissue motion velocity at the at least one point of interest, The apparatus according to claim 10, configured to identify the time window in which the tissue motion velocity quantified in (iv)(iii) reaches the minimum velocity.
12. The apparatus according to claim 11, wherein in (c), the apparatus is configured to identify the at least one time window in (c) by an electrocardiogram.
13. A computer-readable medium containing instructions, wherein when the instructions are executed by a computer, the computer performs the following steps, namely: Step a) Transmitting non-focused ultrasound within the heart using a 2D array ultrasound transducer, and acquiring raw data from the backscattered ultrasound through the 2D array ultrasound transducer, Step b) A step of generating a sequence of N 3D volumetric coronary flow images of the heart from the raw data, wherein the sequence of N 3D volumetric coronary flow images forming an animation shows the movement of the heart in the imaged volume of the heart, Step c) Identifying at least one time window in which the cardiac movement is minimized, Step d) Automatically calculate a 3D cartography of at least one parameter relating to coronary blood flow velocity in the acquired volume based on the sequence of N 3D volumetric coronary blood flow images corresponding to the at least one time window identified in step c), Step e) Based solely on the 3D cartography and its time profile from step d), the step of identifying the location of at least one point of interest having predetermined characteristics in the sequence of N 3D volumetric coronary blood flow images corresponding to the at least one time window identified in step c), A computer-readable medium that causes step f) to automatically identify the coronary blood flow velocity at at least one point of interest in step e) based solely on the 3D cartography and its time profile in step d), and to automatically calculate predetermined quantifiable parameters including the coronary blood flow velocity.
14. The instruction further includes an instruction to perform step c), and when the instruction is executed by the computer, the computer performs the following steps, namely: (i) A step of generating a sequence of N 3D volumetric tissue images of the heart from the raw data of (a), wherein the sequence of N 3D volumetric tissue images forming an animation shows the movement of the heart in the imaged volume of the heart, (ii) A step of automatically calculating a 3D cartography of at least one parameter relating to the cardiac tissue motion velocity in the imaged volume, based on the sequence of N 3D volumetric tissue images showing the movement of the heart in the imaged volume of the heart, (iii) The steps of (iii) identifying the location of at least one point of interest having predetermined characteristics in the sequence of N 3D volumetric tissue images, based exclusively on the 3D cartography of (ii), and automatically determining the tissue motion velocity at the at least one point of interest, The computer-readable medium according to claim 13, which causes (iv) to perform the step of identifying the time window in which the tissue movement velocity quantified in (iii) reaches the minimum velocity.
15. The computer-readable medium according to claim 14, which includes an instruction that, when executed by a computer, causes the computer to perform step c) by an electrocardiogram examination method.