1
|
Choi S, Park S, Kim J, Kim H, Cho S, Kim S, Park J, Kim C. X-ray free-electron laser induced acoustic microscopy (XFELAM). PHOTOACOUSTICS 2024; 35:100587. [PMID: 38312809 PMCID: PMC10835452 DOI: 10.1016/j.pacs.2024.100587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 01/11/2024] [Accepted: 01/11/2024] [Indexed: 02/06/2024]
Abstract
The X-ray free-electron laser (XFEL) has remarkably advanced X-ray imaging technology and enabled important scientific achievements. The XFEL's extremely high power, short pulse width, low emittance, and high coherence make possible such diverse imaging techniques as absorption/emission spectroscopy, diffraction imaging, and scattering imaging. Here, we demonstrate a novel XFEL-based imaging modality that uses the X-ray induced acoustic (XA) effect, which we call X-ray free-electron laser induced acoustic microscopy (XFELAM). Initially, we verified the XA effect by detecting XA signals from various materials, then we validated the experimental results with simulation outcomes. Next, in resolution experiments, we successfully imaged a patterned tungsten target with drilled various-sized circles at a spatial resolution of 7.8 ± 5.1 µm, which is the first micron-scale resolution achieved by XA imaging. Our results suggest that the novel XFELAM can expand the usability of XFEL in various areas of fundamental scientific research.
Collapse
Affiliation(s)
- Seongwook Choi
- Pohang University of Science and Technology (POSTECH), Medical Device Innovation Center, Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, Medical Science and Engineering, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| | - Sinyoung Park
- Pohang University of Science and Technology (POSTECH), Medical Device Innovation Center, Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, Medical Science and Engineering, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| | - Jiwoong Kim
- Pohang University of Science and Technology (POSTECH), Medical Device Innovation Center, Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, Medical Science and Engineering, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| | - Hyunhee Kim
- Pohang University of Science and Technology (POSTECH), Medical Device Innovation Center, Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, Medical Science and Engineering, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| | - Seonghee Cho
- Pohang University of Science and Technology (POSTECH), Medical Device Innovation Center, Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, Medical Science and Engineering, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| | - Sunam Kim
- Pohang Accelerator Laboratory, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| | - Jaeku Park
- Pohang Accelerator Laboratory, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| | - Chulhong Kim
- Pohang University of Science and Technology (POSTECH), Medical Device Innovation Center, Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, Medical Science and Engineering, 77 Cheongam-ro, Pohang 37673, Republic of Korea
| |
Collapse
|
2
|
Sun L, Gonzalez G, Pandey PK, Wang S, Kim K, Limoli C, Chen Y, Xiang L. Towards quantitative in vivo dosimetry using x-ray acoustic computed tomography. Med Phys 2023; 50:6894-6907. [PMID: 37203253 PMCID: PMC10656364 DOI: 10.1002/mp.16476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 04/05/2023] [Accepted: 04/30/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND Radiation 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. PURPOSE Most 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. METHODS Varian 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. RESULTS Applying 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. CONCLUSION Our 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.
Collapse
Affiliation(s)
- Leshan Sun
- Department of Biomedical Engineering, University of California, Irvine, California, USA
| | - Gilberto Gonzalez
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Prabodh Kumar Pandey
- Department of Radiological Sciences, University of California at Irvine, Irvine, California, USA
| | - Siqi Wang
- Department of Biomedical Engineering, University of California, Irvine, California, USA
| | - Kaitlyn Kim
- Department of Biomedical Engineering, University of California, Irvine, California, USA
| | - Charles Limoli
- Department of Radiation Oncology, University of California Irvine, Medical Sciences I, Irvine, California, USA
| | - Yong Chen
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Liangzhong Xiang
- Department of Biomedical Engineering, University of California, Irvine, California, USA
- Department of Radiological Sciences, University of California at Irvine, Irvine, California, USA
- Beckman Laser Institute, University of California at Irvine, Irvine, California, USA
| |
Collapse
|
3
|
Pandey PK, Wang S, Sun L, Xing L, Xiang L. Model-Based 3-D X-Ray Induced Acoustic Computerized Tomography. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2023; 7:532-543. [PMID: 38046375 PMCID: PMC10691826 DOI: 10.1109/trpms.2023.3238017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
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.
Collapse
Affiliation(s)
- Prabodh Kumar Pandey
- Department of Radiological Sciences, University of California, Irvine, CA, 92697, USA
| | - Siqi Wang
- Department of Biomedical Engineering, University of California, Irvine, CA 92617, USA
| | - Leshan Sun
- Department of Biomedical Engineering, University of California, Irvine, CA 92617, USA
| | - Lei Xing
- Department of Radiological Sciences, University of California, Irvine, CA, 92697, USA.; Department of Biomedical Engineering, University of California, Irvine, CA 92617, USA.; Beckman Laser Institute, University of California, Irvine, CA 92612, USA
| | - Liangzhong Xiang
- Division of Medical Physics, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA,94305, USA
| |
Collapse
|
4
|
Jiang Z, Sun L, Yao W, Wu QJ, Xiang L, Ren L. 3D in vivodose verification in prostate proton therapy with deep learning-based proton-acoustic imaging. Phys Med Biol 2022; 67:10.1088/1361-6560/ac9881. [PMID: 36206745 PMCID: PMC9647484 DOI: 10.1088/1361-6560/ac9881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/07/2022] [Indexed: 02/10/2023]
Abstract
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.
Collapse
Affiliation(s)
- Zhuoran Jiang
- Medical Physics Graduate Program, Duke University, Durham, NC, 27705, USA
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, 27710, USA
| | - Leshan Sun
- Department of Biomedical Engineering, University of California, Irvine, California 92617, USA
| | - Weiguang Yao
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, 21201, USA
| | - Q. Jackie Wu
- Medical Physics Graduate Program, Duke University, Durham, NC, 27705, USA
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, 27710, USA
| | - Liangzhong Xiang
- Department of Biomedical Engineering, University of California, Irvine, California 92617, USA
- Department of Radiological Sciences, University of California, Irvine, CA 92697, USA
- Beckman Laser Institute & Medical Clinic, University of California, Irvine, Irvine, CA 92612, USA
| | - Lei Ren
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, 21201, USA
| |
Collapse
|
5
|
Pandey PK, Aggrawal HO, Wang S, Kim K, Liu A, Xiang L. Ring artifacts removal in X-ray-induced acoustic computed tomography. JOURNAL OF INNOVATIVE OPTICAL HEALTH SCIENCES 2022; 15:2250017. [PMID: 38645738 PMCID: PMC11031265 DOI: 10.1142/s1793545822500171] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
X-ray-induced acoustic computed tomography (XACT) is a hybrid imaging modality for detecting X-ray absorption distribution via ultrasound emission. It facilitates imaging from a single projection X-ray illumination, thus reducing the radiation exposure and improving imaging speed. Nonuniform detector response caused by the interference between multichannel data acquisition for ring array transducers and amplifier systems yields ring artifacts in the reconstructed XACT images, which compromises the image quality. We propose model-based algorithms for ring artifacts corrected XACT imaging and demonstrate their efficacy on numerical and experimental measurements. The corrected reconstructions indicate significantly reduced ring artifacts as compared to their conventional counterparts.
Collapse
Affiliation(s)
- Prabodh Kumar Pandey
- Department of Radiological Sciences, University of California, Irvine, CA 92697, USA
| | - Hari Om Aggrawal
- Institute of Mathematics and Image Computing, University of Lübeck, Germany
- Independent Technical Consultant, India
| | - Siqi Wang
- Department of Biomedical Engineering, University of California, Irvine, CA 92617, USA
| | - Kaitlyn Kim
- Department of Biomedical Engineering, University of California, Irvine, CA 92617, USA
| | - An Liu
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte CA 91010, USA
| | - Liangzhong Xiang
- Department of Radiological Sciences, University of California, Irvine, CA 92697, USA
- Department of Biomedical Engineering, University of California, Irvine, CA 92617, USA
- Beckman Laser Institute, University of California, Irvine, CA 92612, USA
| |
Collapse
|
6
|
Choi S, Park S, Pyo A, Kim DY, Min JJ, Lee C, Kim C. In situ x-ray-induced acoustic computed tomography with a contrast agent: a proof of concept. OPTICS LETTERS 2022; 47:90-93. [PMID: 34951888 DOI: 10.1364/ol.447618] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 11/29/2021] [Indexed: 06/14/2023]
Abstract
X-ray-induced acoustic computed tomography (XACT) has shown great potential as a hybrid imaging modality for real-time non-invasive x-ray dosimetry and low-dose three-dimensional (3D) imaging. While promising, one drawback of the XACT system is the underlying low signal-to-noise ratio (SNR), limiting its in vivo clinical use. In this Letter, we propose the first use of a conventional x-ray computed tomography contrast agent, Gastrografin, for improving the SNR of in situ XACT imaging. We obtained 3D volumetric XACT images of a mouse's stomach with orally injected Gastrografin establishing the proposal's feasibility. Thus, we believe, in the future, our proposed technique will allow in vivo imaging and expand or complement conventional x-ray modalities, such as radiotherapy and accelerators.
Collapse
|
7
|
Pandey PK, Wang S, Aggrawal HO, Bjegovic K, Boucher S, Xiang L. Model-Based X-Ray-Induced Acoustic Computed Tomography. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2021; 68:3560-3569. [PMID: 34310297 PMCID: PMC8739265 DOI: 10.1109/tuffc.2021.3098501] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
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.
Collapse
|
8
|
Yao S, Hu Z, Xie Q, Yang Y, Peng H. Further investigation of 3D dose verification in proton therapy utilizing acoustic signal, wavelet decomposition and machine learning. Biomed Phys Eng Express 2021; 8. [PMID: 34768245 DOI: 10.1088/2057-1976/ac396d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 11/12/2021] [Indexed: 11/12/2022]
Abstract
Online dose verification in proton therapy is a critical task for quality assurance. We further studied the feasibility of using a wavelet-based machine learning framework to accomplishing that goal in three dimensions, built upon our previous work in 1D. The wavelet decomposition was utilized to extract features of acoustic signals and a bidirectional long-short-term memory (Bi-LSTM) recurrent neural network (RNN) was used. The 3D dose distributions of mono-energetic proton beams (multiple beam energies) inside a 3D CT phantom, were generated using Monte-Carlo simulation. The 3D propagation of acoustic signal was modeled using the k-Wave toolbox. Three different beamlets (i.e. acoustic pathways) were tested, one with its own model. The performance was quantitatively evaluated in terms of mean relative error (MRE) of dose distribution and positioning error of Bragg peak (ΔBP), for two signal-to-noise ratios (SNRs). Due to the lack of experimental data for the time being, two SNR conditions were modeled (SNR = 1 and 5). The model is found to yield good accuracy and noise immunity for all three beamlets. The results exhibit an MRE below 0.6% (without noise) and 1.2% (SNR = 5), andΔBPbelow 1.2 mm (without noise) and 1.3 mm (SNR = 5). For the worst-case scenario (SNR = 1), the MRE andΔBPare below 2.3% and 1.9 mm, respectively. It is encouraging to find out that our model is able to identify the correlation between acoustic waveforms and dose distributions in 3D heterogeneous tissues, as in the 1D case. The work lays a good foundation for us to advance the study and fully validate the feasibility with experimental results.
Collapse
Affiliation(s)
- Songhuan Yao
- Department of Medical Physics, Wuhan University, 430072, People's Republic of China
| | - Zongsheng Hu
- Department of Medical Physics, Wuhan University, 430072, People's Republic of China
| | - Qiang Xie
- ProtonSmart Ltd, Wuhan, 430072, People's Republic of China
| | - Yidong Yang
- Department of Radiation Oncology, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China; Department of Engineering and Applied Physics, School of Physical Sciences, University of Science and Technology of China, Hefei, 230026, People's Republic of China
| | - Hao Peng
- Department of Medical Physics, Wuhan University, 430072, People's Republic of China.,ProtonSmart Ltd, Wuhan, 430072, People's Republic of China
| |
Collapse
|
9
|
Ba Sunbul NH, Zhang W, Oraiqat I, Litzenberg DW, Lam KL, Cuneo K, Moran JM, Carson PL, Wang X, Clarke SD, Matuszak MM, Pozzi SA, El Naqa I. A simulation study of ionizing radiation acoustic imaging (iRAI) as a real-time dosimetric technique for ultra-high dose rate radiotherapy (UHDR-RT). Med Phys 2021; 48:6137-6151. [PMID: 34431520 PMCID: PMC8943858 DOI: 10.1002/mp.15188] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 08/03/2021] [Accepted: 08/03/2021] [Indexed: 01/15/2023] Open
Abstract
PURPOSE Electron-based ultra-high dose rate radiation therapy (UHDR-RT), also known as Flash-RT, has shown the ability to improve the therapeutic index in comparison to conventional radiotherapy (CONV-RT) through increased sparing of normal tissue. However, the extremely high dose rates in UHDR-RT have raised the need for accurate real-time dosimetry tools. This work aims to demonstrate the potential of the emerging technology of Ionized Radiation Acoustic Imaging (iRAI) through simulation studies and investigate its characteristics as a promising relative in vivo dosimetric tool for UHDR-RT. METHODS The detection of induced acoustic waves following a single UHDR pulse of a modified 6 MeV 21EX Varian Clinac in a uniform porcine gelatin phantom that is brain-tissue equivalent was simulated for an ideal ultrasound transducer. The full 3D dose distributions in the phantom for a 1 × 1 cm2 field were simulated using EGSnrc (BEAMnrc∖DOSXYZnrc) Monte Carlo (MC) codes. The relative dosimetry simulations were verified with dose experimental measurements using Gafchromic films. The spatial dose distribution was converted into an initial pressure source spatial distribution using the medium-dependent dose-pressure relation. The MATLAB-based toolbox k-Wave was then used to model the propagation of acoustic waves through the phantom and perform time-reversal (TR)-based imaging reconstruction. The effect of the various linear accelerator (linac) operating parameters, including linac pulse duration and pulse repetition rate (frequency), were investigated as well. RESULTS The MC dose simulation results agreed with the film measurement results, specifically at the central beam region up to 80% dose within approximately 5% relative error for the central profile region and a local relative error of <6% for percentage dose depth. IRAI-based FWHM of the radiation beam was within approximately 3 mm relative to the MC-simulated beam FWHM at the beam entrance. The real-time pressure signal change agreed with the dose changes proving the capability of the iRAI for predicting the beam position. IRAI was tested through 3D simulations of its response to be based on the temporal changes in the linac operating parameters on a dose per pulse basis as expected theoretically from the pressure-dose proportionality. The pressure signal amplitude obtained through 2D simulations was proportional to the dose per pulse. The instantaneous pressure signal amplitude decreases as the linac pulse duration increases, as predicted from the pressure wave generation equations, such that the shorter the linac pulse the higher the signal and the better the temporal (spatial) resolutions of iRAI. The effect of the longer linac pulse duration on the spatial resolution of the 3D constructed iRAI images was corrected for linac pulse deconvolution. This correction has improved the passing rate of the 1%/1 mm gamma test criteria, between the pressure-constructed and dosimetric beam characteristics, to as high as 98%. CONCLUSIONS A full simulation workflow was developed for testing the effectiveness of iRAI as a promising relative dosimetry tool for UHDR-RT radiation therapy. IRAI has shown the advantage of 3D dose mapping through the dose signal linearity and, hence, has the potential to be a useful dosimeter at depth dose measurement and beam localization and, hence, potentially for in vivo dosimetry in UHDR-RT.
Collapse
Affiliation(s)
- Noora H Ba Sunbul
- Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Wei Zhang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Ibrahim Oraiqat
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Machine Learning, Moffitt Cancer Center, Tampa, Florida, USA
| | - Dale W Litzenberg
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Kwok L Lam
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Kyle Cuneo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jean M Moran
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Paul L Carson
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Xueding Wang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Shaun D Clarke
- Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, Michigan, USA
| | - Martha M Matuszak
- Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Sara A Pozzi
- Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, Michigan, USA
| | - Issam El Naqa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Machine Learning, Moffitt Cancer Center, Tampa, Florida, USA
| |
Collapse
|
10
|
Wang M, Samant P, Wang S, Merill J, Chen Y, Ahmad S, Li D, Xiang L. Towards in vivo Dosimetry for Prostate Radiotherapy with a Transperineal Ultrasound Array: A Simulation Study. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2021; 5:373-382. [PMID: 33969250 PMCID: PMC8104130 DOI: 10.1109/trpms.2020.3015109] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
X-ray-induced acoustic computed tomography (XACT) is a promising imaging modality to monitor the position of the radiation beam and the deposited dose during external beam radiotherapy delivery. The purpose of this study was to investigate the feasibility of using a transperineal ultrasound transducer array for XACT imaging to guide the prostate radiotherapy. A customized two-dimensional (2D) matrix ultrasound transducer array with 10000 (100×100 elements) ultrasonic sensors with a central frequency of 1 MHz was designed on a 5 cm×5 cm plane to optimize three-dimensional (3D) volumetric imaging. The CT scan and dose treatment plan for a prostate patient undergoing intensity modulated radiation therapy (IMRT) were obtained. In-house simulation was developed to model the time varying X-ray induced acoustic (XA) signals detected by the transperineal ultrasound array. A 3D filtered back projection (FBP) algorithm has been used for 3D XACT image reconstruction. Results of this study will greatly enhance the potential of XACT imaging for real time in vivo dosimetry during radiotherapy.
Collapse
Affiliation(s)
- Mengxiao Wang
- Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, School of Physics and Electronics, Shandong Normal University, Jinan, Shandong, 250358, China
| | - Pratik Samant
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, 73019, USA
| | - Siqi Wang
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, 73019, USA
| | - Jack Merill
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, 73019, USA
| | - Yong Chen
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma city, OK, USA
| | - Salahuddin Ahmad
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma city, OK, USA
| | - Dengwang Li
- Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, School of Physics and Electronics, Shandong Normal University, Jinan, Shandong, 250358, China
| | - Liangzhong Xiang
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, 73019, USA
| |
Collapse
|
11
|
Choi S, Park EY, Park S, Kim JH, Kim C. Synchrotron X-ray induced acoustic imaging. Sci Rep 2021; 11:4047. [PMID: 33603050 PMCID: PMC7893053 DOI: 10.1038/s41598-021-83604-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 02/01/2021] [Indexed: 11/09/2022] Open
Abstract
X-ray induced acoustic imaging (XAI) is an emerging biomedical imaging technique that can visualize X-ray absorption contrast at ultrasound resolution with less ionizing radiation exposure than conventional X-ray computed tomography. So far, medical linear accelerators or industrial portable X-ray tubes have been explored as X-ray excitation sources for XAI. Here, we demonstrate the first feasible synchrotron XAI (sXAI). The synchrotron generates X-rays, with a dominant energy of 4 to 30 keV, a pulse-width of 30 ps, a pulse-repetition period of 2 ns, and a bunch-repetition period of 940 ns. The X-ray induced acoustic (XA) signals are processed in the Fourier domain by matching the signal frequency with the bunch-repetition frequency. We successfully obtained two-dimensional XA images of various lead targets. This novel sXAI tool could complement conventional synchrotron applications.
Collapse
Affiliation(s)
- Seongwook Choi
- Department of Electrical Engineering and Creative IT Engineering, Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Eun-Yeong Park
- Department of Electrical Engineering and Creative IT Engineering, Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Sinyoung Park
- Department of Electrical Engineering and Creative IT Engineering, Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Jong Hyun Kim
- Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea.
- Pohang Accelerator Laboratory, Pohang, Republic of Korea.
| | - Chulhong Kim
- Department of Electrical Engineering and Creative IT Engineering, Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, Republic of Korea.
- Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea.
| |
Collapse
|
12
|
Yao S, Hu Z, Zhang X, Lou E, Liang Z, Wang Y, Peng H. Feasibility study of range verification based on proton-induced acoustic signals and recurrent neural network. ACTA ACUST UNITED AC 2020; 65:215017. [DOI: 10.1088/1361-6560/abaa5e] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
13
|
Samant P, Trevisi L, Ji X, Xiang L. X-ray induced acoustic computed tomography. PHOTOACOUSTICS 2020; 19:100177. [PMID: 32215251 PMCID: PMC7090367 DOI: 10.1016/j.pacs.2020.100177] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 03/10/2020] [Accepted: 03/10/2020] [Indexed: 05/22/2023]
Abstract
X-ray imaging has proved invaluable in medical diagnoses and non-destructive testing (NDT) in the past century. However, there remain two major limitations: radiation harm and inaccessibility to the sample. A recent imaging modality, X-ray induced acoustic computed tomography (XACT), allows a novel solution. In XACT, x-ray induced excitation causes localized heating (<mK) and thermoelastic expansion. This induces a detectable ultrasonic emission, thereby enabling imaging. XACT has the potential to enable low-dose, fast, 3D imaging requiring only single side access. We discuss the fundamentals of XACT and summarize milestones in its evolution over the past several years since its first demonstration using a Medical Linear Accelerator. We highlight XACT's potential applications in biomedical imaging and NDT, and discuss the latest advanced concepts and future directions.
Collapse
Affiliation(s)
- P. Samant
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, 73071, USA
- Department of Oncology, University of Oxford, Oxford, OX3 7DQ, UK
| | - L. Trevisi
- Chemical, Biological, & Materials Engineering, University of Oklahoma, Norman, 73071, USA
| | - X. Ji
- School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, Guangdong, China
| | - L. Xiang
- Electrical and Computer Engineering, University of Oklahoma, Norman, 73071, USA
- Corresponding author at: 101 David L Boren Blvd Room 2022, Norman, 73071, USA.
| |
Collapse
|
14
|
Zheng Y, Samant P, Merill J, Chen Y, Ahmad S, Li D, Xiang L. X-ray-induced acoustic computed tomography for guiding prone stereotactic partial breast irradiation: a simulation study. Med Phys 2020; 47:4386-4395. [PMID: 32428252 PMCID: PMC7674271 DOI: 10.1002/mp.14245] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 04/22/2020] [Accepted: 05/11/2020] [Indexed: 12/31/2022] Open
Abstract
PURPOSE The 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). METHODS An 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. RESULTS It 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. CONCLUSIONS This 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.
Collapse
Affiliation(s)
- Yue Zheng
- Shandong Key Laboratory of Medical Physics and Image Processing & Shandong Provincial Engineering and Technical Center of Light Manipulations, School of Physics and Electronics, Shandong Normal University, Jinan 250358, China; School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Pratik Samant
- School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Jack Merill
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Yong Chen
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Salahuddin Ahmad
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Dengwang Li
- Shandong Key Laboratory of Medical Physics and Image Processing & Shandong Provincial Engineering and Technical Center of Light Manipulations, School of Physics and Electronics, Shandong Normal University, Jinan 250358, China
| | - Liangzhong Xiang
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA
| |
Collapse
|