Search

Objective. Radiation-induced acoustic (RA) computed tomographic (RACT) imaging is being thoroughly explored for radiation dosimetry. It is essential to understand how key machine parameters like beam pulse, size, and energy deposition affect image quality in RACT. We investigate the intricate interplay of these parameters and how these factors influence dose map resolution in RACT. Approach. We first conduct an analytical assessment of time-domain RA signals and their corresponding frequency spectra for certain testcases, and computationally validate these analyses. Subsequently, we simulated a series of x-ray-based RACT (XACT) experiments and compared the simulations with experimental measurements. In-silico reconstruction studies have also been conducted to demonstrate the resolution limits imposed by the temporal pulse profiles on RACT. XACT experiments were performed using clinical machines and the reconstructions were analyzed for resolution capabilities. Main results. Our paper establishes the theory for predicting the time- and frequency-domain behavior of RA signals. We illustrate that the frequency content of RA signal is not solely dependent on the spatial energy deposition characteristics but also on the temporal features of radiation. The same spatial energy deposition through a Gaussian pulse and a rectangular pulse of equal pulsewidths results in different frequency spectra of the RA signals. RA signals corresponding to the rectangular pulse exhibit more high-frequency content than their Gaussian pulse counterparts and hence provide better resolution in the reconstructions. XACT experiments with ∼3.2 us and ∼4 us rectangular radiation pulses were performed, and the reconstruction results were found to correlate well with the in-silico results. Significance. Here, we discuss the inherent resolution limits for RACT-based radiation dosimetric systems. While our study is relevant to the broader community engaged in research on photoacoustics, x-ray-acoustics, and proto/ionoacoustics, it holds particular significance for medical physics researchers aiming to set up RACT for dosimetry and radiography using clinical radiation machines., (© 2024 Institute of Physics and Engineering in Medicine.)

X-ray-induced acoustic computed tomography (XACT) is a unique hybrid imaging modality that combines high X-ray absorption contrast with high ultrasonic resolution. X-ray radiography and computerized tomography (CT) are currently the gold standards for 2-D and 3-D imaging of skeletal tissues though there are important properties of bone, such as elasticity and speed of sound (SOS), that these techniques cannot measure. Ultrasound is capable of measuring such properties though current clinical ultrasound scanners cannot be used to image the interior morphology of bones because they fail to address the complicated physics involved for exact image reconstruction; bone is heterogeneous and composed of layers of both cortical and trabecular bone, which violates assumptions in conventional ultrasound imaging of uniform SOS. XACT, in conjunction with the time-reversal algorithm, is capable of generating precise reconstructions, and by combining elements of both X-ray and ultrasound imaging, XACT is potentially capable of obtaining more information than any single of these techniques at low radiation dose. This article highlights X-ray-induced acoustic detection through linear scanning of an ultrasound transducer and the time-reversal algorithm to produce the first-ever XACT image of a bone sample. The results of this study should prove to enhance the potential of XACT imaging in the evaluation of bone diseases for future clinical use.

Acoustic waves are induced via the thermoacoustic effect in objects exposed to a pulsed beam of ionizing radiation. This phenomenon has interesting potential applications in both radiotherapy dosimetry and treatment guidance as well as low-dose radiological imaging. After initial work in the field in the 1980s and early 1990s, little research was done until 2013 when interest was rejuvenated, spurred on by technological advances in ultrasound transducers and the increasing complexity of radiotherapy delivery systems. Since then, many studies have been conducted and published applying ionizing radiation-induced acoustic principles into three primary research areas: Linear accelerator photon beam dosimetry, proton therapy range verification, and radiological imaging. This review article introduces the theoretical background behind ionizing radiation-induced acoustic waves, summarizes recent advances in the field, and provides an outlook on how the detection of ionizing radiation-induced acoustic waves can be used for relative and in vivo dosimetry in photon therapy, localization of the Bragg peak in proton therapy, and as a low-dose medical imaging modality. Future prospects and challenges for the clinical implementation of these techniques are discussed., (© 2018 American Association of Physicists in Medicine.)

Purpose: The objective of this study is to demonstrate the feasibility of x-ray-induced acoustic computed tomography (XACT) for early breast un-palpable microcalcification (μCa) detection in three dimensions (3D). The proposed technique provides the true 3D imaging for breast volume which overcomes the disadvantage of the tissue superposition in mammography., Methods: A 3D breast digital phantom was rendered from two-dimensional (2D) breast CT slices. Three different tissue types, including the skin, adipose tissue, and glandular tissue, were labeled in the 3D breast phantom. μCas were manually embedded in different locations inside the breast phantom. For each tissue type, the initial pressure rise caused by the x-ray-induced acoustic (XA) effect was calculated according to its themoacoustic properties. The XA wave's propagation from the point of generation and its detection by ultrasound detector array were simulated by Matlab K-Wave toolbox. The 3D breast XACT volume with μCa was acquired without tissue superposition, and the system was characterized by μCas placed at different locations., Results: The simulation results illustrated that the proposed breast XACT system has the ability to show the μCa cluster in 3D without any tissue superposition. Meanwhile, μCa as small as 100 μm in size can be detected with high imaging contrast, high signal to noise ratio (SNR), and high contrast to noise ratio (CNR). The dose required by the proposed XACT configuration was calculated to be 0.4 mGy for a 4.5 cm-thick compressed breast. This is one-tenth of the dose level of a typical two-view mammography for a breast with the same compression thickness., Conclusions: The initial exploration for the feasibility of 3D breast XACT has been conducted in this study. The system feasibility and characterization were illustrated through a 3D breast phantom and simulation works. The 3D breast XACT with the proposed system configuration has great potential to be applied as a low-dose screening and diagnostic technique for early un-palpable lesion in the breast., (© 2018 American Association of Physicists in Medicine.)

Absorption based CT imaging has been an invaluable tool in medical diagnosis, biology, and materials science. However, CT requires a large set of projection data and high radiation dose to achieve superior image quality. In this letter, we report a new imaging modality, X-ray Induced Acoustic Tomography (XACT), which takes advantages of high sensitivity to X-ray absorption and high ultrasonic resolution in a single modality. A single projection X-ray exposure is sufficient to generate acoustic signals in 3D space because the X-ray generated acoustic waves are of a spherical nature and propagate in all directions from their point of generation. We demonstrate the successful reconstruction of gold fiducial markers with a spatial resolution of about 350 μm. XACT reveals a new imaging mechanism and provides uncharted opportunities for structural determination with X-ray.

Purpose: Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits., Methods: An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1-10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum., Results: The calculated noise in the transducer was 12-28 mPa, depending on the transducer central frequency (70-380 kHz). The minimum number of protons detectable by the technique was on the order of 3-30 × 10(6) per pulse, with 30-800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz., Conclusions: The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 10(6) protons/pulse and beam current.

In this study, we monitor the progress of vasculature in early tumor growth using photoacoustic imaging over a 20 day period after subcutaneous inoculation of breast cancer tumor cells in a mouse. With 532 nm laser pulses employed as an irradiation source, the photoacoustic images were obtained through the photoacoustic signals received by a hydrophone in orthogonal mode. The morphological characteristics of vasculature in tumor region are clearly resolved in the photoacoustic images, and the change in structure as well as the increase in density can be identified. Moreover, the average photoacoustic signal strength of vasculature in tumor region, which is highly correlated with the total hemoglobin concentration of blood, is enhanced during early tumor growth. These results indicate the feasibility of detecting early stage tumor and monitoring the progress of anti-angiogenic therapy by photoacoustic imaging.

Photoacoustic imaging (PAI) is a noninvasive, nonionizing modality based on the differences in light absorption of various biological tissues. PAI utilizes the endogenous contrast characteristics of traditional optical imaging, while benefiting from high spatial resolution of the ultrasound imaging. A PAI system was developed to reconstruct the two-dimensional cross section image and to visualize the cerebrovascular activities of mouse in vivo. The spatial resolution of the PAI system was determined to be 0.110 mm by a two-point-source phantom with the Rayleigh criterion. The potential applications of the system were clearly demonstrated by successfully mapping a traumatic lesion in the mouse brain cerebral cortex, by its ability to monitor physiological changes in the brain due to carotid ligation and drug stimulation, and two-dimensional sliced images of a traumatic mouse brain at different depths were also provided. Our experimental results indicate that PAI has the potential for studying of traumatic brain injury and physiological functions of the brain.

BackgroundRadiation delivery with ultra-high dose rate (FLASH) radiotherapy (RT) holds promise for improving treatment outcomes and reducing side effects but poses challenges in radiation delivery accuracy due to its ultra-high dose rates. This necessitates the development of novel imaging and verification technologies tailored to these conditions.PurposeOur study explores the effectiveness of proton-induced acoustic imaging (PAI) in tracking the Bragg peak in three dimensions and in real time during FLASH proton irradiations, offering a method for volumetric beam imaging at both conventional and FLASH dose rates.MethodsWe developed a three-dimensional (3D) PAI technique using a 256-element ultrasound detector array for FLASH dose rate proton beams. In the study, we tested protoacoustic signal with a beamline of a FLASH-capable synchrocyclotron, setting the distal 90% of the Bragg peak around 35 mm away from the ultrasound array. This configuration allowed us to assess various total proton radiation doses, maintaining a consistent beam output of 21 pC/pulse. We also explored a spectrum of dose rates, from 15 Gy/s up to a FLASH rate of 48 Gy/s, by administering a set number of pulses. Furthermore, we implemented a three-dot scanning beam approach to observe the distinct movements of individual Bragg peaks using PAI. All these procedures utilized a proton beam energy of 180 MeV to achieve the maximum possible dose rate.ResultsOur findings indicate a strong linear relationship between protoacoustic signal amplitudes and delivered doses (R2 = 0.9997), with a consistent fit across different dose rates. The technique successfully provided 3D renderings of Bragg peaks at FLASH rates, validated through absolute Gamma index values.ConclusionsThe protoacoustic system demonstrates effectiveness in 3D visualization and tracking of the Bragg peak during FLASH proton therapy, representing a notable advancement in proton therapy quality assurance. This method promises enhancements in protoacoustic image guidance and real-time dosimetry, paving the way for more accurate and effective treatments in ultra-high dose rate therapy environments.

BackgroundProtoacoustic (PA) imaging has the potential to provide real-time 3D dose verification of proton therapy. However, PA images are susceptible to severe distortion due to limited angle acquisition. Our previous studies showed the potential of using deep learning to enhance PA images. As the model was trained using a limited number of patients' data, its efficacy was limited when applied to individual patients.PurposeIn this study, we developed a patient-specific deep learning method for protoacoustic imaging to improve the reconstruction quality of protoacoustic imaging and the accuracy of dose verification for individual patients.MethodsOur method consists of two stages: in the first stage, a group model is trained from a diverse training set containing all patients, where a novel deep learning network is employed to directly reconstruct the initial pressure maps from the radiofrequency (RF) signals; in the second stage, we apply transfer learning on the pre-trained group model using patient-specific dataset derived from a novel data augmentation method to tune it into a patient-specific model. Raw PA signals were simulated based on computed tomography (CT) images and the pressure map derived from the planned dose. The reconstructed PA images were evaluated against the ground truth by using the root mean squared errors (RMSE), structural similarity index measure (SSIM) and gamma index on 10 specific prostate cancer patients. The significance level was evaluated by t-test with the p-value threshold of 0.05 compared with the results from the group model.ResultsThe patient-specific model achieved an average RMSE of 0.014 ( p

BackgroundApplying ultra-high dose rates to radiation therapy, otherwise known as FLASH, has been shown to be just as effective while sparing more normal tissue compared to conventional radiation therapy. However, there is a need for a dosimeter that is able to detect such high instantaneous dose, particularly in vivo. To fulfill this need, protoacoustics is introduced, which is an in vivo range verification method with submillimeter accuracy.PurposeThe purpose of this work is to demonstrate the feasibility of using protoacoustics as a method of in vivo real-time monitoring during FLASH proton therapy and investigating the resulting protoacoustic signal when dose per pulse and pulsewidth are varied through multiple simulation studies.MethodsThe dose distribution of a proton pencil beam was calculated through a Monte Carlo toolbox, TOPAS. Next, the k-Wave toolbox in MATLAB was used for performing protoacoustic simulations, where the initial proton dose deposition was inputted to model acoustic propagations, which were also used for reconstructions. Simulations involving the manipulation of the dose per pulse and pulsewidth were performed, and the temporal and spatial resolution for protoacoustic reconstructions were investigated as well. A 3D reconstruction was performed with a multiple beam spot profile to investigate the spatial resolution as well as determine the feasibility of 3D imaging with protoacoustics.ResultsOur results showed consistent linearity in the increasing dose-per-pulse, even up to rates considered for FLASH. The simulations and reconstructions were performed for a range of pulsewidths from 0.1 to 10 μs. The results show the characteristics of the proton beam after convolving the protoacoustic signal with the varying pulsewidths. 3D reconstruction was successfully performed with each beam being distinguishable using an 8 cm × 8 cm planar array. These simulation results show that measurements using protoacoustics has the potential for in vivo dosimetry in FLASH therapy during patient treatments in real time.ConclusionThrough this simulation study, the use of protoacoustics in FLASH therapy was verified and explored through observations of varying parameters, such as the dose per pulse and pulsewidth. 2D and 3D reconstructions were also completed. This study shows the significance of using protoacoustics and provides necessary information, which can further be explored in clinical settings.

BackgroundRadiation dosimetry is essential for radiation therapy (RT) to ensure that radiation dose is accurately delivered to the tumor. Despite its wide use in clinical intervention, the delivered radiation dose can only be planned and verified via simulation. This makes precision radiotherapy challenging while in-line verification of the delivered dose is still absent in the clinic. X-ray-induced acoustic computed tomography (XACT) has recently been proposed as an imaging tool for in vivo dosimetry.PurposeMost of the XACT studies focus on localizing the radiation beam. However, it has not been studied for its potential for quantitative dosimetry. The aim of this study was to investigate the feasibility of using XACT for quantitative in vivo dose reconstruction during radiotherapy.MethodsVarian Eclipse system was used to generate simulated uniform and wedged 3D radiation field with a size of 4 cm ×$ \times \ $ 4 cm. In order to use XACT for quantitative dosimetry measurements, we have deconvoluted the effects of both the x-ray pulse shape and the finite frequency response of the ultrasound detector. We developed a model-based image reconstruction algorithm to quantify radiation dose in vivo using XACT imaging, and universal back-projection (UBP) reconstruction is used as comparison. The reconstructed dose was calibrated before comparing it to the percent depth dose (PDD) profile. Structural similarity index matrix (SSIM) and root mean squared error (RMSE) are used for numeric evaluation. Experimental signals were acquired from 4 cm ×$ \times \ $ 4 cm radiation field created by Linear Accelerator (LINAC) at depths of 6, 8, and 10 cm beneath the water surface. The acquired signals were processed before reconstruction to achieve accurate results.ResultsApplying model-based reconstruction algorithm with non-negative constraints successfully reconstructed accurate radiation dose in 3D simulation study. The reconstructed dose matches well with the PDD profile after calibration in experiments. The SSIMs between the model-based reconstructions and initial doses are over 85%, and the RMSEs of model-based reconstructions are eight times lower than the UBP reconstructions. We have also shown that XACT images can be displayed as pseudo-color maps of acoustic intensity, which correspond to different radiation doses in the clinic.ConclusionOur results show that the XACT imaging by model-based reconstruction algorithm is considerably more accurate than the dose reconstructed by UBP algorithm. With proper calibration, XACT is potentially applicable to the clinic for quantitative in vivo dosimetry across a wide range of radiation modalities. In addition, XACT's capability of real-time, volumetric dose imaging seems well-suited for the emerging field of ultrahigh dose rate "FLASH" radiotherapy.

X-ray-induced acoustic (XA) computerized tomography (XACT) is an evolving imaging technique that aims to reconstruct the X-ray energy deposition from XA measurements. Main challenges in XACT are the poor signal-to-noise ratio and limited field-of-view, which cause artifacts in the images. We demonstrate the efficacy of model-based (MB) algorithms for three-dimensional XACT and compare with the traditional algorithms. The MB algorithm is based on iterative, matrix-free approach for regularized-least-squares minimization corresponding to XACT. The matrix-free-LSQR (MF-LSQR) and the non-iterative model-backprojection (MBP) reconstructions were evaluated and compared with universal backprojection (UBP), time-reversal (TR) and fast-Fourier transform (FFT)-based reconstructions for numerical and experimental XACT datasets. The results demonstrate the capability of MF-LSQR algorithm to reduce noisy artifacts thus yielding better reconstructions. MBP and MF-LSQR algorithms perform particularly well with the experimental XACT dataset, where noise in signals significantly affects the reconstruction of the target in UBP and FFT-based reconstructions. The TR reconstruction for experimental XACT are comparable to MF-LSQR, but takes thrice as much time and filters the frequency components greater than maximum frequency supported by the grid, resulting loss of resolution. The MB algorithms are able to overcome the challenges in XACT and hence are vital for the clinical translation of XACT.

BackgroundOsteoporosis is a progressive bone disease that is characterized by a decrease in bone mass and the deterioration in bone microarchitecture, which might be related to age and space travel. An unmet need exists for the development of novel imaging technologies to characterize osteoporosis.PurposeThe purpose of our study is to investigate the feasibility of X-ray-induced acoustic computed tomography (XACT) imaging for osteoporosis detection.MethodsAn in-house simulation workflow was developed to assess the ability of XACT for osteoporosis detection. To evaluate this simulation workflow, a three-dimensional digital bone phantom for XACT imaging was created by a series of two-dimensional micro-computed tomography (micro-CT) slices of normal and osteoporotic bones in mice. In XACT imaging, the initial acoustic pressure rise caused by the X-ray induce acoustic (XA) effect is proportional to bone density. First, region growing was deployed for image segmentation of different materials inside the bone. Then k-wave simulations were deployed to model XA wave propagation, attenuation, and detection. Finally, the time-varying pressure signals detected at each transducer location were used to reconstruct the XACT image with a time-reversal reconstruction algorithm.ResultsThrough the simulated XACT images, cortical porosity has been calculated, and XA signal spectra slopes have been analyzed for the detection of osteoporosis. The results have demonstrated that osteoporotic bones have lower bone mineral density and higher spectra slopes. These findings from XACT images were in good agreement with porosity calculation from micro-CT images.ConclusionThis work explores the feasibility of using XACT imaging as a new imaging tool for Osteoporosis detection. Considering that acoustic signals are generated by X-ray absorption, XACT imaging can be combined with traditional X-ray imaging that holds potential for clinical management of osteoporosis and other bone diseases.

Dose delivery uncertainty is a major concern in proton therapy, adversely affecting the treatment precision and outcome. Recently, a promising technique, proton-acoustic (PA) imaging, has been developed to provide real-timein vivo3D dose verification. However, its dosimetry accuracy is limited due to the limited-angle view of the ultrasound transducer. In this study, we developed a deep learning-based method to address the limited-view issue in the PA reconstruction. A deep cascaded convolutional neural network (DC-CNN) was proposed to reconstruct 3D high-quality radiation-induced pressures using PA signals detected by a matrix array, and then derive precise 3D dosimetry from pressures for dose verification in proton therapy. To validate its performance, we collected 81 prostate cancer patients' proton therapy treatment plans. Dose was calculated using the commercial software RayStation and was normalized to the maximum dose. The PA simulation was performed using the open-source k-wave package. A matrix ultrasound array with 64 × 64 sensors and 500 kHz central frequency was simulated near the perineum to acquire radiofrequency (RF) signals during dose delivery. For realistic acoustic simulations, tissue heterogeneity and attenuation were considered, and Gaussian white noise was added to the acquired RF signals. The proposed DC-CNN was trained on 204 samples from 69 patients and tested on 26 samples from 12 other patients. Predicted 3D pressures and dose maps were compared against the ground truth qualitatively and quantitatively using root-mean-squared-error (RMSE), gamma-index (GI), and dice coefficient of isodose lines. Results demonstrated that the proposed method considerably improved the limited-view PA image quality, reconstructing pressures with clear and accurate structures and deriving doses with a high agreement with the ground truth. Quantitatively, the pressure accuracy achieved an RMSE of 0.061, and the dose accuracy achieved an RMSE of 0.044, GI (3%/3 mm) of 93.71%, and 90%-isodose line dice of 0.922. The proposed method demonstrates the feasibility of achieving high-quality quantitative 3D dosimetry in PA imaging using a matrix array, which potentially enables the online 3D dose verification for prostate proton therapy.

X-ray-induced acoustic computed tomography (XACT) provides X-ray absorption-based contrast with acoustic detection. For its clinical translation, XACT imaging often has a limited field of view. This can result in image artifacts and overall loss of quantification accuracy. In this article, we aim to demonstrate model-based XACT image reconstruction to address these problems. An efficient matrix-free implementation of the regularized LSQR (MF-LSQR)-based minimization scheme and a noniterative model back-projection (MBP) scheme for computing XACT reconstructions have been demonstrated in this article. The proposed algorithms have been numerically validated and then used to perform reconstructions from experimental measurements obtained from an XACT setup. While the commonly used back-projection (BP) algorithm produces limited-view and noisy artifacts in the region of interest (ROI), model-based LSQR minimization overcomes these issues. The model-based algorithms also reduce the ring artifacts caused due to the nonuniformity response of the multichannel data acquisition. Using the model-based reconstruction algorithms, we are able to obtain reasonable XACT reconstructions for acoustic measurements of up to 120° view. Although the MBP is more efficient than the model-based LSQR algorithm, it provides only the structural information of the ROI. Overall, it has been demonstrated that the model-based image reconstruction yields better image quality for XACT than the standard BP. Moreover, the combination of model-based image reconstruction with different regularization methods can solve the limited-view problem for XACT imaging (in many realistic cases where the full-view dataset is unavailable), and hence pave the way for future clinical translation.

PurposeThe aim of this study is to investigate the feasibility of x-ray-induced acoustic computed tomography (XACT) as an image guidance tool for tracking x-ray beam location and monitoring radiation dose delivered to the patient during stereotactic partial breast irradiation (SPBI).MethodsAn in-house simulation workflow was developed to assess the ability of XACT to act as an in vivo dosimetry tool for SPBI. To evaluate this simulation workflow, a three-dimensional (3D) digital breast phantom was created by a series of two-dimensional (2D) breast CT slices from a patient. Three different tissue types (skin, adipose tissue, and glandular tissue) were segmented and the postlumpectomy seroma was simulated inside the digital breast phantom. A treatment plan was made with three beam angles to deliver radiation dose to the seroma in breast to simulate SPBI. The three beam angles for 2D simulations were 17°, 90° and 159° (couch angles were 0 degrees) while the angles were 90 degrees (couch angles were 0°, 27°, 90°) in 3D simulation. A multi-step simulation platform capable of modelling XACT was developed. First, the dose distribution was converted to an initial pressure distribution. The propagation of this pressure disturbance in the form of induced acoustic waves was then modeled using the k-wave MATLAB toolbox. The waves were then detected by a hemispherical-shaped ultrasound transducer array (6320 transducer locations distributed on the surface of the breast). Finally, the time-varying pressure signals detected at each transducer location were used to reconstruct an image of the initial pressure distribution using a 3D time-reversal reconstruction algorithm. Finally, the reconstructed XACT images of the radiation beams were overlaid onto the structure breast CT.ResultsIt was found that XACT was able to reconstruct the dose distribution of SPBI in 3D. In the reconstructed 3D volumetric dose distribution, the average doses in the GTV (Gross Target Volume) and PTV (Planning Target Volume) were 86.15% and 80.89%, respectively. When compared to the treatment plan, the XACT reconstructed dose distribution in the GTV and PTV had a RMSE (root mean square error) of 2.408 % and 2.299 % over all pixels. The 3D breast XACT imaging reconstruction with time-reversal reconstruction algorithm can be finished within several minutes.ConclusionsThis work explores the feasibility of using the novel imaging modality of XACT as an in vivo dosimeter for SPBI radiotherapy. It shows that XACT imaging can provide the x-ray beam location and dose information in deep tissue during the treatment in real time in 3D. This study lays the groundwork for a variety of future studies related to the use of XACT as a dosimeter at different cancer sites.

X-ray-induced acoustic computed tomography (XACT) is a promising imaging modality combining high X-ray absorption contrast with the 3-D propagation advantages provided by high-resolution ultrasound waves. The purpose of this study was to optimize the configuration of a 3-D XACT imaging system for bone imaging. A 280 ultrasonic sensors with peak frequency of 10 MHz was designed to distribute on a spherical surface to optimize the 3-D volumetric imaging capability. We performed both theoretical calculations and simulations of this optimized XACT imaging configuration on a mouse-sized digital phantom containing various X-ray absorption coefficients. Iteration algorithm based on total variation has been used for 3-D XACT image reconstruction. The spatial resolution of imaging was estimated to about [Formula: see text] along both axial and lateral directions. We simulate XACT imaging of bone microstructures using digital phantoms generated from micro-CT images of real biological samples, showing that XACT imaging can provide high-resolution imaging of the mouse paw. Results of this study will greatly enhance the potential of XACT imaging in the evaluation of bone diseases for future clinical use.

The feasibility of electroacoustic tomography (EAT) was investigated for in situ monitoring the electric field distribution in soft tissue. EAT exploits the phenomenon that the amplitude of acoustic emission generated by an electric field is proportional to the electrical energy deposition in tissue. After detecting these acoustic waves with ultrasound transducers, an image of the electric field distribution can be reconstructed in real-time. In our computer simulations, the electric field distribution in soft tissue was generated by solving general partial differential equations (PDEs) using finite element analysis (FEA). The electric field distributions were converted into initial pressure distributions, and the propagation of the induced acoustic waves was simulated using K-Wave simulation. A circular array of 128 ultrasound transducers was placed around the target to detect the acoustic waves, and a time reversal reconstruction algorithm was used to reconstruct the EAT image. A different number of electrodes set at different distances with different voltage inputs on the electrodes were performed to simulate different electric field distributions during electroporation. It was found that the electrical energy deposition in reconstructed EAT imaging is decreased as the distance of the electrodes increases. We also have investigated the sensitivity of the EAT imaging with different voltage inputs. The minimal voltage we can detect with EAT is 970 V at the pulsewidth of 180 ns. The results of this study demonstrated that EAT is a feasible technique for monitoring the electric field distribution and guiding the electrotherapy in future clinical practice. [ABSTRACT FROM AUTHOR]

The purpose of this study was to optimize the configuration of a photoacoustic endoscope (PAE) for prostate cancer detection and therapy monitoring. The placement of optical fiber bundles and ultrasound detectors was chosen to maximize the photoacoustic imaging penetration depth. We performed both theoretical calculations and simulations of this optimized PAE configuration on a prostate-sized phantom containing tumor and various photosensitizer concentrations. The optimized configuration of PAE with transurethral light delivery simultaneously increases the imaging penetration depth and improves image quality. Thermal safety, investigated via COMSOL Multiphysics, shows that there is only a 4 mK temperature rise in the urethra during photoacoustic imaging, which will cause no thermal damage. One application of this PAE has been demonstrated for quasi-quantifying photosensitizer concentrations during photodynamic therapy. The sensitivity of the photoacoustic detection for TOOKAD was 0.18 ng/mg at a 763 nm laser wavelength. Results of this study will greatly enhance the potential of prostate PAE for in vivo monitoring of drug delivery and guidance of the laser-induced therapy for future clinical use. [ABSTRACT FROM AUTHOR]