System, method and computer program product for three-dimensional super-resolution passive cavitation mapping

Abstract

A method of cavitation mapping in a region of interest is provided. Methods, systems and computer program products according to some embodiments include receiving ultrasound signals from a cavitation event with an ultrasound array; and localizing the cavitation event to determine a cavitation location. The method also includes mapping the cavitation location on an image; and providing information characterizing the cavitation event.

Description

Attorney Docket No.5405.533.WO SYSTEM, METHOD AND COMPUTER PROGRAM PRODUCT FOR THREE- DIMENSIONAL SUPER-RESOLUTION PASSIVE CAVITATION MAPPING RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application Serial No. 63 / 672,481 filed July 17, 2024, the disclosure of which is hereby incorporated by reference in its entirety. TECHNICAL FIELD

[0002] The present inventive concept relates to the methods, systems, and computer program products for super-resolution passive cavitation mapping. BACKGROUND

[0003] Kidney stone disease is a significant public health issue. Kidney stone disease is a condition where solid deposits of minerals and salts form inside the kidneys or urinary tract, which affects about 12% of the world’s population. Laser lithotripsy (LL) is used to break kidney stones with repeated laser irradiation. Monitoring the cavitation that occurs during LL may be challenging. SUMMARY

[0004] According to some embodiments of the present inventive concept, a system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions. One general aspect includes a method of cavitation mapping in a region of interest.

[0005] Methods, systems and computer program products according to some embodiments include receiving ultrasound signals from a cavitation event with an ultrasound array; localizing the cavitation event to determine a cavitation location. The method also includes mapping the cavitation location on an image; and providing information characterizing the cavitation event.Attorney Docket No.5405.533.WO Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

[0006] Implementations may include one or more of the following features. The method where localizing the cavitation event may include identifying a center location of the cavitation event based on the passive ultrasound signals received by the ultrasound array from the cavitation event as a point source. Localizing the cavitation event may include determining a radial symmetric point of the cavitation event as a point source, and identifying the cavitation location by a center point (“point source”) that is radially symmetric. Mapping the cavitation location may include mapping the cavitation location to a b-mode image or the ureteroscope image. The cavitation event is created by laser lithotripsy (LL). The ultrasound image(s) may include a laser fiber mounted on a ureteroscope used to create cavitation events in a kidney stone; and recording images from the ureteroscope may be performed while acquiring ultrasound image(s) and emitting the laser pulse; mapping the cavitation location on an image may include mapping the cavitation location on the ultrasound image(s) and / or ureteroscope. Emitting the laser pulse may include emitting a plurality of laser pulses, localizing the cavitation event may include localizing a plurality of cavitation events, and mapping the cavitation location on the image may include mapping the plurality of cavitation events on the ultrasound image or ureteroscope. Providing information characterizing the cavitation event may include information such as a cavitation size, a cavitation location, and / or a cavitation strength. Providing information characterizing the cavitation event(s) may include providing real-time visual information regarding kidney stone cavitation to a clinician using a laser lithotripsy device. Implementations of the described techniques may include hardware, a method or process, or computer software on a computer-accessible medium.

[0007] In some implementations, a system for cavitation mapping in a region of interest includes an ultrasound array; a controller configured to control the ultrasound array and to receive ultrasound signals from a cavitation event with the ultrasound array; and an analyzer configured to localize the cavitation event to determine a cavitation location, to map the cavitation location on an image; and to provide information characterizing the cavitation event. BRIEF DESCRIPTION OF THE DRAWINGSAttorney Docket No.5405.533.WO

[0008] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the inventive concept and, together with the description, serve to explain principles of the inventive concept.

[0009] FIG. 1A is a schematic diagram of systems, methods, and computer program products according to some embodiments of the inventive concept.

[0010] FIG. 1B is a flowchart of operations according to some embodiments of the inventive concept.

[0011] FIG. 1C is a schematic diagram of a laser fiber on a ureteroscope that generates a cavitation bubble and an ultrasound transducer array according to some embodiments of the inventive concept.

[0012] FIG.1D is a graph of a trigger sequence of a three dimensional super-resolution passive cavitation mapping ultrasound pulse in which the ultrasound B-mode image is acquired before laser lithotripsy (LL) firing followed by high-speed camera recording and passive cavitation mapping according to some embodiments of the inventive concept.

[0013] FIG.2A is schematic diagram of a three dimensional super-resolution passive cavitation mapping ultrasound pulse system illustrating the delay-and-sum beamforming to reconstruct the cavitation location according to some embodiments of the inventive concept.

[0014] FIG.2B is a graph illustrating the automatic identification of the collapse event and the reflection (shaded gray) according to some embodiments of the inventive concept.

[0015] FIG. 2C is a series of reconstructed passive cavitation mapping images with varied starting time points according to some embodiments of the inventive concept.

[0016] FIG. 3A is an illustration of a reconstructed sparse matrix according to some embodiments of the inventive concept.

[0017] FIG. 3B is an illustration of the stacked RF data for a page-wise sparse-matrix multiplication at different starting time points (STP) according to some embodiments of the inventive concept..

[0018] FIGS. 4A-4D are images of a three-dimensional (3D) super-resolution (SR) cavitation location showing the time-delay lapsed 3D image volume projected into 2D maximum intensity projections to enhance efficiency (FIG.4A), a mechanism of the radial symmetric method of 3D super-resolution localization (FIG. 4B), an example of the localizations of the delay-time lapsedAttorney Docket No.5405.533.WO 2D images from two cavitations (FIG.4C), and an example of tracking the converging points for two cavitations (FIG.4C) according to some embodiments of the inventive concept.

[0019] FIGS 5A-5D are illustrations of kidney phantoms and an experimental setup for imaging a kidney phantom showing an image of a kidney phantom model (FIG.5A), an image of a kidney phantom with an outer frame and a BegoTMstone (for simulating a kidney stone) inserted (FIG. 5B), an image of an example kidney phantom experimental setup (FIG. 5C), and a side view schematic of a kidney phantom experimental set up (FIG.5D) according to some embodiments of the inventive concept.

[0020] FIG.6A is a graph of the location and normalized pressure of a single-bubble validation using a 2D transducer array of a 3D super-resolution passive cavitation mapping illustrating a photoacoustic signal from the microbead at different positions in which x=0 is the central acoustic axis of the array according to some embodiments of the inventive concept.

[0021] FIG.6B are graphs of in-focus diffraction-limited spatial resolutions of the 2D transducer array of FIG.6A.

[0022] FIG.6C is a schematic illustration of on-axis and off-axis single-bubble detection for the graphs of FIGS.6A and 6B.

[0023] FIG. 6D is an image of bubble cavitation dynamics captured by the high-speed camera using the experimental configuration of FIG.6C.

[0024] FIG.6E is an example of a 3D-super-resolution passive cavitation mapping image of the on-axis and off-axis single bubbles of FIG.6D.

[0025] FIG. 6F is a graph of 3D super-resolution passive cavitation mapping pressures and camera-captured bubble diameters at different laser energy levels according to some embodiments of the inventive concept.

[0026] FIG.6G is a graph of the bubble collapse time in 3D super-resolution passive cavitation mapping and high speed cameras according to some embodiments of the inventive concept.

[0027] FIGS 7A-7C illustrate the processing speeds of a 3D-super-resolution passive cavitation mapping illustrating examples of ultrasound B-mode images, 3D passive cavitation images, and the 3D-super-resolution passive cavitation mapping images of cavitation activities using a flat BegoStone surface with a parallel LL fiber (FIG. 7A); a graph of the beamforming speed of different methods including page-wise (PW), sparse-matrix multiplication (SMM), vectorized operation (VEC) (FIG.7B); and a graph of the processing time by using the GPU-based page-wiseAttorney Docket No.5405.533.WO sparse-matrix beamforming algorithm for a collapse event (CE) (FIG. 7C) according to some embodiments of the inventive concept.

[0028] FIGS. 8A-8E are 3D passive cavitation mapping and 3D-super-resolution passive cavitation mapping of LL-induced cavitation according to some embodiments with a single laser pulse showing a series of images of bubble dynamics captured by a high-speed camera with a scale bar of 1mm (FIG.8A); a series of 3D-super-resolution passive cavitation mapping images of eight collapse bubbles (FIG.8B); the x-y maximum amplitude projection image of 3D-super-resolution passive cavitation mapping results of the eight collapse bubbles of FIG.8B in which the scale bar is 1mm (FIG.3C); a 3D-super-resolution passive cavitation mapping image of the locations of the eight collapse bubbles of FIG. 8B (FIG. 8D); and a graph of the collapse depth and pressure of each of the eight bubbles of FIG.8B (FIG.8E).

[0029] FIGS.9A-9D are 3D-super-resolution passive cavitation mapping images of accumulated LL-induced cavitations according to some embodiments of the inventive concept including images of craters on a stone surface with different pulse numbers (pN) and a scale bar of 1mm (FIG.9A); OCT images of the crater with different pulse numbers and a scale bar of 1mm (FIG.9B); images of maximum amplitude of projections of collapse pressures at the x-y plane, acquired by 3D-super- resolution passive cavitation mapping and a scale bar of 1mm (FIG.9C); and 3D-super-resolution passive cavitation mapping images of individual bubbles projected at the x-y plane and the y-z plane, with the bubble density shaded from sparse to condense.

[0030] FIGS. 10A-10I illustrate a dose-dependence analysis by 3D-super-resolution passive cavitation mapping according to some embodiments of the inventive concept including a three- dimensional graph of the accumulated collapse location of 800 bubbles, which are grouped into 7 positions from A to G (FIG.10A); a three-dimensional graph of accumulated 3D bubble density distribution (FIG.10B); a graph of the dose-dependence of the crater volume (V) by OCT (FIG. 10C); a graph of dose-dependence of bubble number (BBnum) (FIG. 10D); a graph of the dose- dependence of accumulated impact pressure (Acc IP) (FIG.10E); a graph of the dose-dependence of bubble density (FIG.10F); a Spearman’s correlation map between cavitation characterizations a crater damage illustrating the AVE Depth (averaged cavitation distance to the stone surface); Acc P (accumulated cavitation pressure on the transducer surface); Acc IP (accumulated impact pressure on the stone surface); AVE P (averaged collapse pressure); AVE IP (averaged impact pressure on the stone surface); Total BBnum (total number of bubbles in one treatment); V (craterAttorney Docket No.5405.533.WO volume); D (maximum crater depth); A (crater area) (FIG. 10G); a scatter plot of the averaged collapsed dept, accumulated impact pressure, and the crater volume (FIG.10H); and a scatter plot of the accumulated impact pressure and corresponding crater volume (FIG.10I).

[0031] FIGS. 11A-11H illustrate 3D-super-resolution passive cavitation mapping according to some embodiments of the inventive concept of LL-induced cavitation in a kidney phantom including an image of the crater on the stone surface in which the location of the fiber tip was marked by the box (FIG.11A)’ an image of bubble collapse (and the maximum bubble generation on the right bottom) captured by high-speed camera (FIG. 11B); a screenshot of the video recording captured by the endoscope camera (FIG.11C); a graph of the crater depth map by OCT (FIG.11D); a 3D-super-resolution passive cavitation mapping image of the accumulated cavitation pressure (FIG. 11E); a 3D-super-resolution passive cavitation mapping bubble density image of all individual cavitation bubbles, with the bubble density color-coded from sparse to dense (FIG. 11F); a scatter plot of eight different data sets of crater volume and accumulated impact pressure from 3D-super-resolution passive cavitation mapping (FIG 11G); and a scatter plot of eight different data sets of crater volume and bubble density (FIG.11G). DETAILED DESCRIPTION

[0032] A ureteroscope used with laser lithotripsy (LL) is used to apply a laser beam directly to a kidney stone to break it into small pieces that are passed more easily in the urine. A ureteroscope is passed through the urethra of a patient so that a medical practitioner or clinician may view the procedure, typically on a video screen. A laser fiber is inserted through the ureteroscope so that the energy from the laser fiber tip can be used to break apart stones within the view of the ureteroscope. Recent laboratory studies have demonstrated that the mechanism of stone damage in laser lithotripsy may relate to cavitation damage in dusting mode. The dusting technique uses the high-power laser to ablate stones into a fine powder.

[0033] Embodiments according to the present inventive concept may be used to provide a method of three-dimensional super-resolution passive cavitation mapping (3D-SRPCM) to monitor the cavitation activities during LL with a 2D semispherical array transducer. In the disclosed method, a bubble localization method is applied to achieve super-resolution reconstruction of the cavitation positions. The cavitation activities during LL can be closely corrected to the stone treatment efficiency. Although embodiments are illustrated with aAttorney Docket No.5405.533.WO semispherical array transducer, it should be understood that any suitable shaped array may be used, including any 2D array shape, such as a flat array or a random array.

[0034] Laser lithotripsy (LL) has been widely used for clinical treatment of kidney stones. The dusting-mode LL has become increasingly popular due to its high fragmenting efficiency and relatively simple procedure without the need for a stent and ureteral access sheath. The energy settings for the dusting mode is typically 0.2-0.7 J at a frequency of 20-50 Hz. Recent studies have shown that cavitation plays an important role in stone fragmentation in LL. Nevertheless, the mechanism of cavitation-induced stone damage during LL remains uncertain, and embodiments according to the inventive concept are not limited thereto. In some embodiments, the spatiotemporal distributions of cavitation activities may be used to study how the cavitation activities affect the stone damage and thus the treatment efficacy. Previous studies have explored various methods for detecting cavitation, such as active cavitation mapping (ACM) and high-speed photograph. For example, Xiang et al. (Phys. Fluids 35, 033303 (2023); doi 10.1063 / 5,0139741) used high-speed photograph to capture cavitation bubble collapse and investigated the transient dynamics of vapor bubbles induced by LL and confirmed their correlation with stone damage. Passive cavitation mapping (PCM) has also been demonstrated as a promising technology that provides cavitation monitoring in shockwave lithotripsy and other applications. A 2D-PCM system may be used to image and analyze laser-induced single cavitation bubbles and shock wave-induced cavitation clusters. Using a linear ultrasound transducer array, a 2D-PCM may be powered with a sliding-window delay-and-sum reconstruction (SW-DAS) method.

[0035] According to some embodiments, LL- induced cavitation bubble distribution in three- dimensional (3D) space may be captured with high temporal and spatial resolution. 3D super- resolution passive cavitation mapping (3D-SRPCM) may be integrated with ultrasound imaging and clinical LL procedures. Using a semi-spherical ultrasound array or other shaped ultrasound arrays, in some embodiments, 3D-SRPCM can provide cavitation distribution with a 3D field of view (3D-FOV) of ~8 mm in diameter. A graphics processing unit (GPU) based sparse-matrix delay-and-sum (DAS) beamforming approach may be used for 3D-SRPCM reconstruction, which is 300 times faster than the traditional vector-based DAS method. To further enhance the spatial- temporal resolution, a super-resolution cavitation localization method was developed, which provides the collapse localization with sub-pixel accuracy of 40 µm, as well as a temporal resolution of 0.128 µs. Using 3D-SRPCM according to some embodiments, LL-induced cavitationAttorney Docket No.5405.533.WO bubbles in both free space and constricted space may be localized. The dose dependence of LL treatment on BegoStones may be determined and the correlation between cavitation activities and the stone damage may be quantified. Accordingly, 3D-SRPCM as described herein may be used during LL treatment.

[0036] Although embodiments according to the inventive concept are described with respect to cavitation events that are used to break up kidney stones, it should be understood that the invention is not limited to kidney stone treatment. As would be understood by one of skill in the art, embodiments according to the present inventive concept may be used to map and identify characteristics of a variety of cavitation events, including cavitation bubbles created during the treatment of gall bladder stones and cataracts, the blood clots in ischemic stroke and deep vein thrombosis, and the tumor cells in histotripsy of cancers.

[0037] As shown in FIG.1A, a system 10 according to some embodiments includes a controller 20, a user interface 30, an ultrasound transducer array 40, an imaging device 50 such as a ureteroscope, with a laser fiber 52 on an end thereof, and a display 60. The controller 20 may include an ultrasound imaging module 22 for controlling the ultrasound transducer array 40, and the user interface 30 may include an imaging analyzer 32 for imaging images from either the imaging device 50 or the ultrasound transducer. The controller 20, the ultrasound transducer array 40, and / or the display 60 and various components thereof may include hardware, such as control and / or analyzing circuits, and / or software stored on a non-transient computer readable medium for carrying out operations described herein. It should be understood that the present inventive concept should not be construed as limited to the configurations illustrated in FIG.1A. In some embodiments, the controller, the ultrasound transducer 22, the image analyzer 32, and / or the display 60 may be provided in the same processor or in a different processing unit as would be understood by those of skill in the art.

[0038] As illustrated in FIG. 1B and with continued reference to FIG. 1A, an ultrasound transducer, such as the ultrasound transducer 22 in FIG.1B, receives passive ultrasound signals, including signals from a cavitation event (Block 100). The cavitation event may occur in a region of tissue, including kidney tissue and a kidney stone, for example. The cavitation is localized, such by the image analyzer 32 after an LL pulse (Block 112). In some embodiments, the cavitation may be localized by identifying a central location of the cavitation based on the passive ultrasound signals, as described in further detail herein. The cavitation location may be mapped (Block 114).Attorney Docket No.5405.533.WO For example, the cavitation location may be mapped on an imaging frame of reference, such as an ultrasound image (including standard B-mode images) or the ureteroscope camera image; however, it should be understood that any suitable imaging technique may be used for mapping the cavitation location.

[0039] Information about the cavitation event and / or bubble may be provided to the clinician or user (Block 116). For example, the display of the localized cavitation may be displayed together with the image of the LL events from the ureteroscope or imaging device 50. In some embodiments, the image may be color coded to indicate additional information, such as a size of cavitation or the bursting / cavitation time of the cavitation. The cavitation locations may remain on a display to guide the medical professional for administering future laser pulses. However, it should be understood that any suitable user feedback or indicia may be used. In some embodiments, the cavitation locations are not displayed to the clinician, and an indicia or light color on the ureteroscope screen may be used to inform the clinician when the sufficient cavitation events or a percentage of cavitation events have been performed. In some embodiment, cavitation information may be provided in real time simultaneously with the treatment procedure, such as kidney stone treatment.

[0040] In some embodiments of the present inventive concept, localizing the cavitation event includes identifying a center location of the cavitation event based on the passive ultrasound signals received by the ultrasound array from the cavitation event. For example, a radial symmetric point of the cavitation event may be determined, and the cavitation location may be determined by a center point that is radially symmetric in the cavitation bubble. The cavitation may be defined as a point source such that the center point is defined as a point source.

[0041] In some embodiments of the present inventive concept, ultrasound images(s) are acquired from the region of interest. The ultrasound images may be images acquired through B-mode imaging with a transmit and receive pulse to detect ultrasound scattering in the region of interest. A laser pulse is emitted in the region of interest with a laser fiber mounted on a ureteroscope, and the ultrasound image(s) include the laser fiber. Images from a ureteroscope are acquired while acquiring ultrasound image(s) and emitting the laser pulse. The cavitation location is mapped on the ultrasound image(s), for example, by overlaying the images from a camera on the ureteroscope with the ultrasound images. A plurality of laser pulses may be emitted in laser lithotripsy (LL), and each corresponding bubble or cavitation event may be detected using passive ultrasoundAttorney Docket No.5405.533.WO signals from the event. The cavitation events may be mapped on standard ultrasound images as described herein.

[0042] Information about the cavitation event may be determined and provided to a clinician or user, including in real time during a laser lithotripsy procedure. The information can be provided visually, for example, on a display that includes camera images from a ureteroscope during an LL procedure or on a separate display, and the cavitation information may include a cavitation size, a cavitation location, a cavitation time, and / or a cavitation strength.

[0043] Non-limiting examples according to some embodiments will now be described.

[0044] FIG. 1C shows the overall diagram of 3D-SRPCM used in free-space LL according to non-limiting example embodiments of the inventive concept. To monitor the 3D cavitation activities at the LL fiber tip, an ultrasound transducer 40 was used. In the current example, a customized 2D semispherical ultrasound transducer array (Imasonics, France), which has 256 piezoelectric elements and a central frequency of 4 MHz with a 60% bandwidth, was used; however, any suitable transducer may be used. As illustrated, the transducer elements are uniformly distributed over a spherical surface with a radius of 40.06 mm. In the current example, the data acquisition is performed by a programmable ultrasound scanner (e.g., Vantage 256, Verasonics) with a 15.625 MHz sampling rate; however, any suitable ultrasound data acquisition system may be used. A commercial Holmium:YAG (Ho:YAG) laser lithotripter (H Solvo 35-W laser, Dornier MedTech) was operated with a pulse energy Ep = 0.8 J with a pulse duration of 106 μs and a pulse repetition frequency PRF = 10 Hz. The laser pulse from LL may be delivered by using a 365-µm-core-diameter fiber to the stone surface. BegoStone samples (BEGO USA, Lincoln, RI) with similar mechanical properties to human kidney stones may be prepared (45x45x5 mm3) using 5:2 powder to water ratio by weight. The fiber tip may be positioned parallel to the stone surface with a stand-off (SD) distance SD = 1.0 mm. The parallel fiber setting may be chosen in this study to minimize the photothermal ablation effect. The fiber tip may be placed near the focal zone of the semispherical array to capture the bubble collapse around the fiber tip. To validate our SD-SRPCM method, high-speed optical imaging by using a high-speed camera (Vision Research, Wayne, NJ) with a frame rate of 90,909 Hz may be simultaneously performed to record bubble collapse from the side view.

[0045] 3D ultrasound imaging may be conducted before LL treatment to find the positions of the fiber tip and the stone surface.3D ultrasound images may be acquired with a 15-Hz frame rate andAttorney Docket No.5405.533.WO a field of view of 8x8x8 mm3. The triggering sequence of 3D-SRPCM is shown in FIG.1C. A LL laser pulse firing, high-speed camera recording, PCM acquisition, and 3D ultrasound imaging are synchronized. For example, as illustrated in FIG.1C, the master trigger signal was sent with the laser pulses from LL at 10 Hz. There was a 300-μs delay between the LL trigger and the PCM signal acquisition. The total acquisition time for PCM was 800 μs to capture all the cavitation activities. The high-speed camera acquired 90 images within 1 ms after each laser pulse to capture the whole process of bubble generation and collapse.

[0046] 3D-PCM image reconstruction

[0047] LL-induced cavitations may be approximated as sparsely distributed point sources, of which the radiofrequency (RF) signals are recorded by the 2D semispherical transducer array, as shown in FIG. 2A. As in our previously reported work, if the time of each bubble collapsing or cavitation is known, the 3D-PCM image can be reconstructed by using the delay-and-sum (DAS) beamforming method : ^ N^ ^ ^ ^^r− r ^A ( r , t s )=αn ( r ) ⋅ S n ^ t +n^ ,^ s ^pressure at the location ^^^^ and the collapsing time ^^^^^^^^; ^^^^^^^^refers to the angular sensitivity of the n-th transducer element at the location ^^^^; ^^^^^^^^denotesthe signal contributed from the location ^^^^ to n-th transducer element at ^�^�^�^^^⃑^^ after the propagationtime|^^^^−^�^�^�^^�^^⃑^ |^^^^ ; ^^^^ is the speed of sound. Note that the pressure amplitude is proportional to the

[0050] Since the bubble collapsing time ^^^^^^^^is unknown, a two-step method that searches for the optimized starting time point (STP) is used. First, automatic peak searching is applied to the RF data recorded by the center transducer element, which estimates the approximate time for the cavitations collapses. The typical bubble dynamics with SD = 1.0 mm include jet impact and non- circular toroidal bubble collapse, following the primary and secondary bubble collapses (i.e., a collapse event as shown in FIG.2B. Usually, multiple bubbles collapse within a period of ~10 μs. RF signals with relatively low intensities and short intervals are identified as reflection signals from the stone surface. Second, for each cavitation collapse, a series of images are reconstructed by using the 3D SW-DAS method with different STPs, shown in FIG. 2C. Using the SW-DAS images, the true collapsing time may be determined, which results in the most converged image ofAttorney Docket No.5405.533.WO the bubble. Therefore, the temporal resolution of 3D-PCM is determined by RF signal sampling rate. The spatial resolution of 3D-PCM is limited by acoustic diffraction. Nevertheless, SW-DAS is time-consuming for investigating the detailed bubble dynamics. Furthermore, precise cavitation localization beyond the acoustic diffraction is needed for studying the spatial dependence of the stone damage. To address this, techniques to accelerate the 3D-PCM image reconstruction and improve the spatial resolution may be used, as discussed herein.

[0051] Page-wise GPU-based sparse-matrix DAS beamforming

[0052] To reduce a time for 3D-PCM reconstruction, a page-wise, sparse-matrix-multiplication, and GPU-based method may be used. First, we adapt sparse matrix multiplication which is faster than vector-based DAS. The sparse matrix can reduce memory usage and speed up the processing as it only stores the non-zero elements. Second, the RF data sequences are stacked with different STPs into a hybrid matrix with multiple pages, allowing for sparse matrix multiplication for multiple beamforming instances. Third, sparse matrix multiplication is performed using a GPU (NVIDIA® GeForce RTXTM 3090) that can offer parallel processing with high computational throughput.

[0053] The construction of the sparse matrix prior to beamforming may be described as follows. Eq. (1) may be written into the matrix format: N A( V m )=∑Mult m mn⋅S n=Mult⋅S ,amplitude a^^^^t the voxel ^^^^ as in Eq. (1);^^^^^^^^^^^^^^^^^^^^^^^^ is a vector of 1 × ^^^^ with the same length ^^^^ as the single-channel RF samples ^^^^^^^^ (^^^^ × 1),and it only contains one single non-zero component determined by the distance between n-th transducer element and the voxel ^^^^^^^^. Additionally, the non-zero component includes the angular sensitivity of the n-th transducer element with regard to the voxel ^^^^^^^^. Next, by stacking the matrix ^^^^^^^^^^^^^^^^^^^^^^^^and the RF data ^^^^^^^^over all the transducer elements, A can be generated by multiplying two stacked matrixes. By repeating the operation for all elements, we can establish a sparse matrix(^^^^ × ^^^^^^^^, FIG. 3A) for a single DAS beamforming. Here, we assume the total number of STPs isK (i.e., the page number). To further accelerate the reconstructions with varied STPs, the RF data of each channel is shifted circularly to keep the same sample size (FIG. 3B) and stacked into amultiple-page matrix (^^^^ × ^^^^ × ^^^^). Then, the continuous set of transformed RF data is rearrangedinto a Casorati matrix (^^^^^^^^ × ^^^^). The outcome of multiplication between the sparse matrix and theAttorney Docket No.5405.533.WOstacked circular shifting RF data is reshaped into a series of 3D PCM images of ^^^^^^^^ × ^^^^^^^^ × ^^^^^^^^ × ^^^^,where ^^^^^^^^, ^^^^^^^^, and ^^^^^^^^denote the pixel numbers of the reconstructed FOV along x, y, and z.

[0056] 3D super-resolution cavitation localization

[0057] LL-induced cavitation bubbles can be approximated as point sources. Super-resolution cavitation localization can be performed to extract the bubble collapse position. It is similar with 3D particle or microbubble trajectory tracking—if we consider the cavitation event as a single particle or a single microbubble. Hence, the 2D particle trajectory tracking method is modified on the maximum intensity projection (MIP) of the 3D-PCM images, and combined the 2D tracking results from different MIP views to generate 3D trajectories of a single cavitation (FIG.4A).

[0058] The radial symmetric (RS) method was adopted to provide SR localization with a sub- pixel accuracy of approximately 1 / 10 of the diffraction-limited resolutions. The RS method assumes that the cavitation signal is radially symmetric. In other words, all gradient vectors at each pixel point to the cavitation center (FIG.4B). For noisy images, this approach aims to minimize the total distance between the optimized center point and all gradient vectors. After storing the center positions of cavitations reconstructed with increasing STPs (FIG. 4C, the tracking was implemented based on the Kuhn-Munkres (KM) algorithm. The 2D distances from all cavitations between two STP images were calculated. By applying the KM algorithm, the optimal pairing between two STP images was selected by minimizing the total distance. Repeating this process over STPs, the 2D trajectories of all cavitation events were generated to identify the most converging time points for each cavitation (FIG.4D).

[0059] To extract 3D trajectories, the tracks from three-view MIP images were generated. A generalized distance between the tracks from different views was computed as: (I , J ) = C ⋅ ( A − A )+ C ⋅ ( X − XDis 1 ),total length of track after paring; T denotes the STP of each element in the track. Note that only those tracks from different views with the same STPs were considered for comparison. For the elements with the same STPs in two tracks, the normalized deviations were calculated including the localized central amplitude and the center position. The subscripts i and j indicate the elements corresponding to track I and J from different views. Note that the values of ^^^^^^^^and ^^^^^^^^for normalization is generated from the two paring tracks.Attorney Docket No.5405.533.WO ^^^^^^^^and ^^^^^^^^are the hyper parameters to adjust the pairing sensitivities to amplitude and position, respectively. By applying the generalized distance and KM algorithm, the track pairing process was able to reliably identify the same cavitation track from three-view MIP images. If two closely distributed cavitations overlap in one MIP view, only two MIP views were paired. Consequently, the 3D cavitation information (including intensity, positions, and collapsing time) was extracted by combining the paired 2D tracks.

[0062] Kidney Phantom and Experiment Setup

[0063] The LL-induced bubble collapse monitoring experiments were conducted both in the free space like water tank, and also the confined space as anatomically realistic kidney phantom. The kidney phantom was molded with transparent hydrogel (Gelatin #1, Humimic Medical, SC, USA), providing high optical and acoustic transparency. The kidney phantom structures were simplified while maintaining anatomical accuracy. The kidney phantom is split in two haves (FIG. 5A). A 3D-printed frame was used to hold the two halves. The phantom had three accessible regions: the pelviureteric junction (PUJ), upper pole, and lower pole, with a volume of 1.12 cm3, 1.63 cm3, and 0.61 cm3, respectively. Additionally, cylindrical channels were added to facilitate the insertion of the stone and the passage of stone fragments and fluid (FIG.5B).

[0064] FIGS. 5C and 5D show the LL experiment setup in the kidney phantom. A cylindrical BegoStone with a diameter of 6 mm and a length of 3 mm tethered to a soft wire was inserted into the renal pelvis. The stone’s flat surface was placed in the focal zone of the 2D transducer array. The LL fiber tip was inserted through the renal pelvis. High-speed camera was placed on the top of the kidney phantom to record the bubble activities. A layer of 2-cm-thick chicken tissue was placed between the 2D transducer array and the kidney phantom, mimicking the acoustic attenuation in biological tissues. The tissue thickness was not increased due to limits by the focal length of the ultrasound transducer array.

[0065] Experimental Results

[0066] Validation of 3D-SRPCM on Single Bubbles

[0067] Characterization experiments were conducted for the 2D transducer array as shown in FIG.6A-6G. All the elements in the 2D transducer array point to the center of the geometric sphere, forming a spherical FOV with the highest detection sensitivity. A microbead was embedded in agarose gel and excited by a pulse laser at 532 nm. The resultant photoacoustic signals from the microbead mimicked the cavitation signals. The photoacoustic signals were acquired with theAttorney Docket No.5405.533.WO microbead translated over a distance of 50 mm (laterally) by 20 mm (axially). FIG.6A shows the assembled images of the microbead at different locations. The detection sensitivity and the spatial resolution of the 2D transducer array deteriorate from its geometric center, with a −6 dB focal zone of ~8 mm in diameter. The diffraction-limited spatial resolutions of the 2D transducer array at the center was 433 µm (x-axis), 440 µm (y-axis) and 186 µm (z-axis), as shown in FIG.6B.

[0068] The single-bubble experiment was conducted with 3D-SRPCM. A nanosecond laser beam was focused into water through a convex lens (NA = 1.0), resulting in a ~0.81 μm optical focal spot, which was used as the ground truth of the bubble location. A single bubble was produced per laser pulse at the optical focus due to the optical breakdown. The first group of bubbles were generated 40 mm in depth along the z axis of the 2D transducer array. The second group of bubbles were generated 15 mm off the z axis. Five different laser pulse energy levels (1 mJ, 2 mJ, 3 mJ, 5 mJ and 8 mJ) were employed, producing different bubble sizes. For each energy level, eight bubbles were recorded. The bubble size and collapsing location were also measured by the high-speed camera. The experimental setup is shown in FIG.6C.

[0069] A series of representative camera images are shown in FIG.6D. FIG.6E shows the bubble collapse images acquired by 3D-SRPCM. The measured collapse pressure and the bubble size for on-axis and off-axis bubbles are shown in FIG. 6F. Both the bubble sizes and collapse pressure increased with the laser pulse energy. Limited by surface tension, the bubble size and collapse pressure reached a plateau when laser pulse energy was above 5 mJ. The collapse time of all 80 bubbles captured by the camera and 3D-SRPCM were consistent, as shown in FIG. 6G. By comparing the collapse locations of all 80 bubbles acquired by the high-speed camera and the 3D- SRPCM, the average localization accuracy of 3D-SRPCM is ~40 μm, which is about 1 / 10 of the acoustic diffraction limit of the 2D transducer array.

[0070] Processing Speed of 3D-SRPCM

[0071] FIG. 7A shows an example of 3D ultrasound image of a flat square BegoStone with a parallel LL fiber, 3D-PCM reconstruction image, and 3D-SRPCM bubble collapse localization image. The 3D-PCM image has a reconstruction volume of 5 mm x 5 mm x 5 mm and a pixel size of 80 μm. We compared our GPU-based page-wise beamforming algorithm with traditional methods (FIG.7B). The CPU is Intel® CoreTM i9-12900K and the GPU is NVIDIA® GeForce RTXTM 3090. The GPU-based page-wise sparse matrix beamforming has the shortest processing time of <1 ms, which is >300 times faster than the traditional vectorized CPU-based method. TheAttorney Docket No.5405.533.WO most significant improvement is achieved by applying GPU-accelerated sparse-matrix multiplication. It is interesting to note that the page-wise data assembly has a larger impact on GPU (8.51 times faster) than on CPU (4.05 times faster). Using the GPU-based page-wise sparse- matrix beamforming algorithm, we evaluated the total processing speed of the entire 3D-SRPCM pipeline for a single laser pulse from LL (FIG.7C). The processing time is 29.38±0.62 ms for the ultrasound reconstruction, 73.93±1.57 ms for 3D-PCM reconstruction, and 31.33±3.60 ms for localization in 3D-SRPCM. Thus, the total processing time for a single collapse event in 3D- SRPCM is ~140 ms.

[0072] 3D-SRPCM with Single LL Pulse

[0073] 3D-SRPCM was tested with a single LL pulse. Different from the single bubble by the optical breakdown at the optical focus, the bubbles generated by a LL pulse are spread out near the stone surface. SD = 1.0 mm was used and produced relatively large bubbles. The long LL pulse and solid boundary interaction create an elongated “pear-shaped” bubble that collapses asymmetrically and forms multiple water jets in sequence. The high-speed camera images of bubble generation and collapse were shown in FIG.8A. Between 0 to 351 μs after the laser pulse, the cavitation bubble was generated and expanded to its maximum size. The first collapse (jet impact and toroidal bubble collapse in sequence) happened between 702 μs and 729 μs and the second collapse (rebound bubble collapse) happened between 972 μs and 999 μs. There were multiple collapse events which were not resolved by the camera due to its limited temporal resolution. FIG. 8B shows eight individual collapse events reconstructed by 3D-PCM, showing much higher temporal resolution than the high-speed camera. For example, 3D-PCM distinguished toroidal bubble collapses between 702 μs and 729 μs. FIG. 8C shows the maximum amplitude projection (MAP) of the accumulated cavitation intensity of all eight collapse events, as reconstructed by 3D-PCM. It can be observed that the collapse intensity was highly location dependent near the stone surface. The super-resolution localization of the bubbles by 3D-SRPCM were shown in FIG.8D, providing much higher accuracy than 3D-PCM. In the 3D-SRPCM image, the center of the sphere represents the collapse location of each cavitation event, and the color of the spheres is coded by their collapsing time. The classic self-intensified phenomenon can be observed from the 3D-SRPCM results. The toroidal bubbles collapse started from the fiber tip and then followed a quarter arc to both sides. Quantitative analysis from the 3D-SRPCM results was shown in FIG. 8E. Cavitations at location #6 and #7 had the highest collapse pressure, whileAttorney Docket No.5405.533.WO cavitation at location #1 was the closest to the stone surface (i.e., smallest collapse depth). This experiment demonstrated that 3D-SRPCM is capable of mapping the individual cavitation events induced by laser pulses from LL, with higher temporal resolution than the high-speed camera and higher spatial resolution than 3D-PCM.

[0074] 3D-SRPCM with Accumulated LL Pulses

[0075] Dose-dependence in LL refers to the relationship between the accumulated laser energy delivered to the target stone and its effect on the stone. Using 3D-SRPCM, the accurate location and time of bubble collapse may be determined and the correlation between the accumulated cavitation activities with the stone damage may be analyzed, allowing for better understanding of LL-induced cavitation and optimized treatment parameters. To study the dose-dependence during LL treatment, we treated the flat surface of the BegoStone with different pulse numbers (pN), ranging from 10 to 100 pulses with the same laser setting. Similar to the single LL pulse experiment, ultrasound B-mode images were acquired before each treatment. 3D-SRPCM and high-speed camera were used to monitor each treatment. After each treatment, optical coherence tomography (OCT) was used to measure the LL-generated craters on the stone surface. FIG.9A shows the stone surface treated with different pNs. The craters were distributed along an arc pattern near the fiber tip, with the two largest craters on the side of the fiber tip and another major crater at the far end. The OCT images are shown in FIG. 9B, from which the crater depth, size, and volume were quantified. As shown in FIG. 9C, the 3D-PCM images reflect the accumulated cavitation pressure distribution. For pN =10 and 20, although the accumulated cavitation pressure maps showed the arc pattern around the fiber tip, there were no significant craters formed on the stone surface. The 3D-SRPCM results are shown in FIG.9D, providing accurate location and time of each cavitation bubble, consistent with the crater pattern on stone surface quantified by OCT. 3D-SRPCM also resolved the bubbles inside the crater, which were shown below the stone surface in FIG.9D. More analysis of the dose-dependent cavitation activities is provided.

[0076] Dose-dependence Analysis

[0077] From the dose-dependence 3D-SRPCM results in FIG.9D, the cavitation characteristics and studied their correlation with the stone damage may be analyzed. Super-resolution localization in 3D-SRPCM may be used for analyzing the cavitation characteristics on the bubble-by-bubble basis, such as the collapse location, impact pressure, and spatial bubble density. FIG.10A shows the accumulated collapse location of the 100 LL pulses. Approximately 800 bubbles were groupedAttorney Docket No.5405.533.WO into seven locations labeled as A to G. FIG.10B shows the 3D cavitation density distribution. It can be observed that the cavitation densities at positions A, D, E and G were higher than the other positions, consistent with the crater volume in FIG. 9B. The dose-dependent crater volumes at different locations were shown in FIG. 10C. FIGS. 10D-10F illustrate the dose-dependent accumulated bubble number, accumulated impact pressure (Acc IP), and cavitation density at various locations. Here, impact pressure on the stone surface is quantified based on the cavitation pressure on the transducer surface and the cavitation-stone distance. In general, all the cavitation characteristics from 3D-SRPCM are highly location-dependent and have shown positive- dependence on the pulse number pN. The total bubble number has approximately linear dependence on pN, while Acc IP and cavitation density have multi-phased dependence on pN. The dose-dependence results indicate that the accumulated effects of cavitation activities on the stone damage are not a linear process. There is clearly a threshold effect that requires a minimal number of 30 laser pulses from LL to generate a visible impact on the stone surface (FIG. 9A). The accumulated damage on the stone surface is noted to modulate the dynamics of bubble collapse and damage progression during laser lithotripsy. This suggests that the mechanical properties of the stone, such as its hardness or composition, can influence the formation and evolution of craters during the cavitation process.

[0078] The correlation between the cavitation characteristics and the stone damage (i.e., the crater characteristics) may also be analyzed. Here, the Spearman’s correlation coefficient may be used to assess the accuracy with which the relationship between two variables can be described using a monotonic function. Shown in FIG. 10G, the Spearman’s coefficients was assessed between the main crater characteristics (volume, depth, and area) and the main cavitation characteristics, including the averaged cavitation distance to the stone surface (AVE Depth), accumulated cavitation pressure on the transducer surface (Acc P), accumulated impact pressure on the stone surface (Acc IP), averaged collapse pressure (AVE P), averaged impact pressure on the stone surface (AVE IP), and total number of bubbles in one treatment (Total BBnum). The coefficient map reveals that the accumulated impact pressure (Acc IP) had the highest correlation coefficient of 0.93 with the crater volume, while the averaged pressure (AVE P) had the least correlation of 0.17 with the crater volume. The location-dependence of the correlation between the AVE Depth / Acc IP and the crater volume (FIG.10H) was assessed, clearly showing that stronger Acc IP and larger AVE Depth resulted in larger crater volume, for example, at position D and E.Attorney Docket No.5405.533.WO Moreover, the strong correlation between Acc IP and the crater volume is shown in FIG. 10I, indicating that mechanical fracturing instead of the photothermal effect is the dominating factor for the stone damage in Ho: YAG LL.

[0079] 3D-SRPCM of LL Treatment in a Kidney Phantom

[0080] To mimic the clinical setting, the 3D-SRPCM system was applied for LL in a constrained space inside a kidney phantom. FIGS.11A-11H show representative 3D-SRPCM results with 100 LL pulses. A fish-shaped crater was formed around the fiber tip as shown in FIG.11A, which was confirmed by the OCT image as shown in FIG.11D. The high-speed camera captured the bubble collapsing dynamics in FIG.11B and the treatment process was recorded by the endoscope camera in FIG.11C. The 3D-PCM intensity map was consistent with the crater shape in FIG.11E, which, however, cannot resolve the individual cavitation locations. The 3D-SRPCM results, on the other hand, can clearly distinguish the bubble localizations generated by each laser pulse (FIG. 11F). According to our dose-dependency study in FIGS.10A-10I, we analyzed 8 groups of 3D-SRPCM data sets performed in the kidney phantom and quantified the correlation between Acc IP and crater volume V (FIG.11G), as well as total bubble numbers (BB num) and crater volume V (FIG. 11H). Again, both Acc IP and BB num have strong correlation with the crater volume. The smiling- face-shaped crater pattern in the parallel fiber setting was not generated in the kidney phantom experiment. This is mainly because during the LL treatment inside the kidney phantom, the angle of the fiber tip and the SD were not consistent.

[0081] Cavitation is a mechanism for stone damage during LL treatment of kidney stone disease. In this work, we used the parallel fiber setting to minimize thermal ablation and maximize the contribution of cavitation activities. Our 3D-SRPCM system was demonstrated for localizing the cavitation bubbles with the parallel fiber setting. Vertical and tilted fiber orientation settings will be investigated in future work. A representative SD of 1 mm and laser pulse rate of 10 Hz were used in our experiments in this work. To evaluate the correlation between stone damage and cavitation activities, more correlation studies with a stone damage prediction model will be conducted under different laser conditions, which can provide more information for assessing the effectiveness of the treatment procedure.

[0082] Another potential aspect of 3D-SRPCM includes providing real-time feedback of cavitation activities for each laser pulse during clinical procedure, which may be used in guiding urologists for increased efficiency. Currently, a 3D-SRPCM frame rate of 10 Hz with an FOV ofAttorney Docket No.5405.533.WO 8x8x8 mm3has been achieved, which may be accelerated further to accommodate higher lase pulse rates and increasing the efficiency of the data processing pipeline, such as using the curving fitting method to identify the bubble collapse time.

[0083] Accordingly, 3D-SRPCM system with a 2D transducer array, which can monitor the cavitation activities during LL treatment of stones, is provided. 3D-SRPCM provides the localization of each cavitation center and bubble collapse time with high spatial-temporal accuracy. Particularly, a particle-tracking-based cavitation localization method was adopted to achieve super-resolution reconstruction of the cavitation positions, with an average accuracy of ~40 µm. Moreover, a GPU-accelerated page-wise sparse-matrix-multiplication-based reconstruction method is provided which aims to provide near real-time feedback during LL treatment. The 3D-SRPCM results are validated using high-speed camera in both free-space water and in a space-constrained kidney phantom. The stone damage is quantified by using OCT and analyzed the correlation between the cavitation characteristics with the stone damage. High- resolution 3D-SRPCM for cavitation mapping during LL may increase the efficiency of the clinical stone treatment and improve the patient outcome.

[0084] The present inventive concepts are described herein with reference to the accompanying drawings and examples, in which embodiments are shown. Additional embodiments may take on many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the inventive concepts to those skilled in the art.

[0085] Like numbers refer to like elements throughout. In the figures, the thickness of certain lines, layers, components, elements or features may be exaggerated for clarity.

[0086] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting thereof. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items. As used herein, phrases such as “between X and Y” and “between about X and Y” should be interpreted to includeAttorney Docket No.5405.533.WO X and Y. As used herein, phrases such as “between about X and Y” mean “between about X and about Y.” As used herein, phrases such as “from about X to Y” mean “from about X to about Y.” The term “about” should be understood to include variations of up to 20%.

[0087] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and relevant art and should not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Well-known functions or constructions may not be described in detail for brevity and / or clarity.

[0088] It will be understood that when an element is referred to as being “on,” “attached” to, “connected” to, “coupled” with, “contacting,” etc., another element, it may be directly on, attached to, connected to, coupled with or contacting the other element or intervening elements may also be present. In contrast, when an element is referred to as being, for example, “directly on,” “directly attached” to, “directly connected” to, “directly coupled” with or “directly contacting” another element, there are no intervening elements present. It will also be appreciated by those of skill in the art that references to a structure or feature that is disposed “adjacent” another feature may have portions that overlap or underlie the adjacent feature.

[0089] Spatially relative terms, such as “under,” “below,” “lower,” “over,” “upper” and the like, may be used herein for ease of description to describe one element or feature's relationship to another element(s) or feature(s) as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is inverted, elements described as “under” or “beneath” other elements or features would then be oriented “over” the other elements or features. Thus, the exemplary term “under” may encompass both an orientation of “over” and “under.” The device may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly. Similarly, the terms “upwardly,” “downwardly,” “vertical,” “horizontal” and the like are used herein for the purpose of explanation only unless specifically indicated otherwise.

[0090] It will be understood that, although the terms “first,” “second,” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms areAttorney Docket No.5405.533.WO only used to distinguish one element from another. Thus, a “first” element discussed below could also be termed a “second” element without departing from the teachings of the present disclosure. The sequence of operations (or steps) is not limited to the order presented in the claims or figures unless specifically indicated otherwise.

[0091] Moreover, the present disclosure also contemplates that in some embodiments, any feature or combination of features set forth herein can be excluded or omitted. To illustrate, if the specification states that a complex comprises components A, B and C, it is specifically intended that any of A, B or C, or a combination thereof, can be omitted and disclaimed singularly or in any combination.

[0092] Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. For example, if a concentration range is stated as 1% to 50%, it is intended that values such as 2% to 40%, 10% to 30%, or 1% to 3%, etc., are expressly enumerated in this specification. These are only examples of what is specifically intended, and all possible combinations of numerical values between and including the lowest value and the highest value enumerated are to be considered to be expressly stated in this disclosure. As used herein, "treatment,” “therapy” and / or “therapy regimen” refer to the clinical intervention made in response to a disease, disorder or physiological condition manifested by a patient or to which a patient may be susceptible. The aim of treatment includes the alleviation or prevention of symptoms, slowing or stopping the progression or worsening of a disease, disorder, or condition and / or the remission of the disease, disorder, or condition.

[0093] As used herein, the term "subject" and "patient" are used interchangeably herein and refer to both human and nonhuman animals. The term "nonhuman animals" of the disclosure includes all vertebrates, e.g., mammals and non-mammals, such as nonhuman primates, sheep, dog, cat, horse, cow, chickens, amphibians, reptiles, and the like. The methods and compositions disclosed herein can be used on a sample either in vitro (for example, on isolated cells or tissues) or in vivo in a subject (i.e., living organism, such as a patient). In some embodiments, the subject comprises a human who is undergoing a procedure using a system and / or method as prescribed herein.

[0094] Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0095] The foregoing is illustrative of the present inventive concept and is not to be construed as limiting thereof. Although a few example embodiments have been described, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodimentsAttorney Docket No.5405.533.WO without materially departing from the novel teachings of this inventive concept. Accordingly, all such modifications are intended to be included within the scope of this inventive concept as defined in the claims. Therefore, it is to be understood that the foregoing is illustrative of the present inventive concept and is not to be construed as limited to the specific embodiments disclosed, and that modifications to the disclosed embodiments, as well as other embodiments, are intended to be included within the scope of the appended claims.

Claims

Attorney Docket No.5405.533.WO WHAT IS CLAIMED IS:

1. A method of cavitation mapping in a region of interest, the method comprising: receiving ultrasound signals from a cavitation event with an ultrasound array; localizing the cavitation event to determine a cavitation location; mapping the cavitation location on an image; and providing information characterizing the cavitation event.

2. The method of claim 1, wherein localizing the cavitation event comprises identifying a center location of the cavitation event based on the ultrasound signals received by the ultrasound array, wherein the ultrasound signals comprise passive ultrasound signals from the cavitation event.

3. The method of any preceding claim, wherein localizing the cavitation event comprises determining a radial symmetric point of the cavitation event as a point source, and identifying the cavitation location by a center point that is radially symmetric.

4. The method of any preceding claim, wherein mapping the cavitation location comprising mapping the cavitation location to a B-mode image.

5. The method of any preceding claim, wherein the cavitation event is created by laser lithotripsy (LL).

6. The method of any preceding claim, further comprising: acquiring ultrasound images(s) from the region of interest; emitting a laser pulse in the region of interest with a laser fiber mounted on a ureteroscope, wherein the ultrasound image(s) include the laser fiber; and recording images from the ureteroscope while acquiring ultrasound image(s) and emitting the laser pulse; wherein mapping the cavitation location on an image comprises mapping the cavitation location on the ultrasound image(s).Attorney Docket No.5405.533.WO 7. The method of claim 6, wherein emitting the laser pulse comprises emitting a plurality of laser pulses, localizing the cavitation event comprises localizing a plurality of cavitation events, and mapping the cavitation location on the image comprises mapping the plurality of cavitation events on the ultrasound image(s) or the ureteroscope image(s).

8. The method of claim 7, wherein providing information characterizing the cavitation event comprises providing information characterizing the cavitation events comprising: a cavitation size, a cavitation location, a cavitation time, and / or a cavitation strength.

9. The method of any preceding claim, wherein providing information characterizing the cavitation event(s) comprises providing real-time visual information regarding kidney stone cavitation to a clinician using a laser lithotripsy device.

10. A system for cavitation mapping in a region of interest, the system comprising: an ultrasound array; a controller configured to control the ultrasound array and to receive ultrasound signals from a cavitation event with the ultrasound array; and an analyzer configured to localize the cavitation event to determine a cavitation location, to map the cavitation location on an image; and to provide information characterizing the cavitation event.

11. The system of claim 10, wherein the analyzer is configured to localize the cavitation event by identifying a center location of the cavitation event based on the ultrasound signals received by the ultrasound array, wherein the ultrasound signals are passive ultrasound signals from the cavitation event.

12. The system of claims 10-11, wherein the analyzer is configured to localize the cavitation event by determining a radial symmetric point of the cavitation event, and identifying the cavitation location by a center point that is radially symmetric.Attorney Docket No.5405.533.WO 13. The system of claims 10-12, wherein the analyzer is configured to map the cavitation location by mapping the cavitation location to a B-mode image or a ureteroscope image.

14. The system of claims 10-13, wherein the cavitation event is created by laser lithotripsy (LL).

15. The system of claims 10-14, wherein the ultrasound array is configured to acquire ultrasound images(s) from the region of interest; the system further comprising a laser fiber mounted on a ureteroscope, wherein the ultrasound image(s) include the laser fiber, and the laser fiber is configured to emit a laser pulse in the region of interest to create the cavitation event, and the ureteroscope is configured to acquire optical images in the region of interest while the ultrasound array is acquiring ultrasound image(s) and the laser fiber is emitting the laser pulse; wherein the analyzer is configured to map the cavitation location on an image comprises mapping the cavitation location on the ultrasound image(s) or the ureteroscope image(s).

16. The system of claim 15, wherein the laser fiber is configured to emit a plurality of laser pulses, the analyzer is configured to localize a corresponding plurality of cavitation events, and to map the plurality of cavitation events on the ultrasound image(s) or the ureteroscope image(s).

17. The system of claim 16, wherein the analyzing is configured to provide information characterizing the cavitation events comprising: a cavitation size, a cavitation location, a caviation time, and / or a cavitation strength.

18. The system of claims 10-17, wherein the controller is configured to provide real- time visual information regarding kidney stone cavitation to a clinician using a laser lithotripsy device.Attorney Docket No.5405.533.WO 19. A computer program product for cavitation mapping in a region of interest, the computer program product comprising a non-transient computer readable medium having computer readable program code embodied therein, the computer readable program code comprising: computer readable program code configured to receive ultrasound signals from a cavitation event with an ultrasound array; computer readable program code configured to localize the cavitation event to determine a cavitation location; computer readable program code configured to map the cavitation location on an image; and computer readable program code configured to provide information characterizing the cavitation event.

Images