3-D Protoacoustic Imaging Through a Planar Ultrasound Array: A Simulation Workflow.

Bragg peak range uncertainties are a persistent constraint in proton therapy. Pulsed proton beams generate protoacoustic emissions proportional to absorbed proton energy, thereby encoding dosimetry information in a detectable acoustic wave. Here, we seek to derive and model 3D protoacoustic imaging with an ultrasound array and examine the frequency characteristics of protoacoustic emissions. A formalism is presented through which protoacoustic signals can be characterized considering transducer bandwidth as well as pulse duration of the incident beam. We have also collected an experimental proton beam intensity signal from a Mevion S250 clinical machine to analyze our formalism. We also show that proton-acoustic image reconstruction is possible even when the noise amplitude is larger than the signal amplitude on individual transducers. We find that a 4µ s Gaussian proton pulse can generate a signal in the range of MHz as long as the spatial heating function has sufficiently high temperature gradients.

Machine learning for normal tissue complication probability prediction: Predictive power with versatility and easy implementation.

Background and purpose: A popular Normal tissue Complication (NTCP) model deployed to predict radiotherapy (RT) toxicity is the Lyman-Burman Kutcher (LKB) model of tissue complication. Despite the LKB model's popularity, it can suffer from numerical instability and considers only the generalized mean dose (GMD) to an organ. Machine learning (ML) algorithms can potentially offer superior predictive power of the LKB model, and with fewer drawbacks. Here we examine the numerical characteristics and predictive power of the LKB model and compare these with those of ML. Materials and methods: Both an LKB model and ML models were used to predict G2 Xerostomia on patients following RT for head and neck cancer, using the dose volume histogram of parotid glands as the input feature. Model speed, convergence characteristics and predictive power was evaluated on an independent training set. Results: We found that only global optimization algorithms could guarantee a convergent and predictive LKB model. At the same time our results showed that ML models remained unconditionally convergent and predictive, while staying robust to gradient descent optimization. ML models outperform LKB in Brier score and accuracy but compare to LKB in ROC-AUC. Conclusion: We have demonstrated that ML models can quantify NTCP better than or as well as LKB models, even for a toxicity that the LKB model is particularly well suited to predict. ML models can offer this performance while offering fundamental advantages in model convergence, speed, and flexibility, and so could offer an alternative to the LKB model that could potentially be used in clinical RT planning decisions.

The feasibility study of XACT imaging for characterizing osteoporosis.

BACKGROUND: Osteoporosis 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. PURPOSE: The purpose of our study is to investigate the feasibility of X-ray-induced acoustic computed tomography (XACT) imaging for osteoporosis detection. METHODS: An 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. RESULTS: Through 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. CONCLUSION: This 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.

Automated scripting of the dosimetric evaluation of adaptive versus non-adaptive radiotherapy.

Objective. To quantify the benefit of adaptive radiotherapy over non-adaptive radiotherapy it is useful to extract and compare dosimetric features of patient treatments in both scenarios. This requires Image-Guided Radiotherapy (IGRT) matching of baseline planning to adaptive fraction imaging, followed by extraction of relevant dose metrics. This can be impractical to retrospectively perform manually for multiple patients.Approach. Here we present an algorithm for automatic IGRT matching of baseline planning with fraction imaging and performing automated dosimetric feature extraction from adaptive and non-adaptive treatment plans, thereby allowing comparison of the two scenarios. This workflow can be done in an entirely automated way via scripting solutions given structure and dose Digital Imaging and Communications in Medicine (DICOM) files from baseline and adaptive fractions. We validate this algorithm against the results of manual IGRT matching. We also demonstrate automated dosimetric feature extraction. Lastly, we combine these two scripting solutions to extract daily adaptive and non-adaptive radiotherapy dosimetric features from an initial cohort of patients treated on an MRI guided linear accelerator (MR-LINAC).Results.Our results demonstrate that automated feature extraction and IGRT matching was successful and comparable to results performed by a manual operator. We have therefore demonstrated a method for easy analysis of patients treated on an adaptive radiotherapy platform.Significance.We believe that this scripting solution can be used for quantifying the benefits of adaptive therapy and for comparing adaptive therapy against various non-adaptive IGRT scenarios (e.g. 6 degree of freedom couch rotation).

Towards in vivo Dosimetry for Prostate Radiotherapy with a Transperineal Ultrasound Array: A Simulation Study.

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.

X-Ray-Induced Acoustic Computed Tomography (XACT): Initial Experiment on Bone Sample.

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.

X-ray-induced acoustic computed tomography for guiding prone stereotactic partial breast irradiation: a simulation study.

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.

3-D X-Ray-Induced Acoustic Computed Tomography With a Spherical Array: A Simulation Study on Bone Imaging.

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.

Feasibility of Electroacoustic Tomography: A Simulation Study.

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.

Nanoscale photoacoustic tomography for label-free super-resolution imaging: simulation study (Erratum).

The erratum corrects an error in the article, "Nanoscale photoacoustic tomography for label-free super-resolution imaging: simulation study," by P. Samant et al.

Nanoscale photoacoustic tomography for label-free super-resolution imaging: simulation study.

Resolutions higher than the optical diffraction limit are often desired in the context of cellular imaging and the study of disease progression at the cellular level. However, three-dimensional super-resolution imaging without reliance on exogenous contrast agents has so far not been achieved. We present nanoscale photoacoustic tomography (nPAT), an imaging modality based on the photoacoustic effect. nPAT can achieve a dramatic improvement in the axial resolution of the photoacoustic imaging. We derive the theoretical resolution and sensitivity of nPAT and demonstrate that nPAT can achieve a maximum axial resolution of 9.2 nm. We also demonstrate that nPAT can theoretically detect smaller numbers of molecules (∼273) than conventional photoacoustic microscopy due to its ability to detect acoustic signals very close to the photoacoustic source. We simulate nPAT imaging of malaria-infected red blood cells (RBCs) using digital phantoms generated from real biological samples, showing nPAT imaging of the RBC at different stages of infection. These simulations show the potential of nPAT to nondestructively image RBCs at the nanometer resolutions for in vivo samples without the use of exogenous contrast agents. Simulations of nPAT-enabled functional imaging show that nPAT can yield insight into malarial metabolism and biocrystallization processes. We believe that the experimental realization of nPAT has important applications in biomedicine.

Characterization of the temperature rise in a single cell during photoacoustic tomography at the nanoscale.

We are developing a label-free nanoscale photoacoustic tomography (nPAT) for imaging a single living cell. nPAT uses a laser-induced acoustic pulse to generate a nanometer-scale image. The primary motivation behind this imaging technique is the imaging of biological cells in the context of diagnosis without fluorescent tagging. During this procedure, thermal damage due to the laser pulse is a potential risk that may damage the cells. A physical model is built to estimate the temperature rise and thermal relaxation during the imaging procedure. Through simulations using finite element methods, two lasers (532 nm at 5 ps pulse duration and 830 nm at 0.2 ps pulse duration) were simulated for imaging red blood cells (RBCs). We demonstrate that a single 5-ps pulse laser with a 400-Hz repetition rate will generate a steady state temperature rise of less than a Kelvin on the surface of the RBCs. All the simulation results show that there is no significant temperature rise in an RBC in either single pulse or multiple pulse illumination with a 532-nm laser with 219 W fluence. Therefore, our simulation results demonstrate the thermal safety of an nPAT system. The photoacoustic signal generated by this laser is on the order of 2.5 kPa, so it should still be large enough to generate high-resolution images with nPAT. Frequency analysis of this signal shows a peak at 1.47 GHz, with frequencies as high as 3.5 GHz still being present in the spectrum. We believe that nPAT will open an avenue for disease diagnosis and cell biology studies at the nanometer-level.

Transurethral Photoacoustic Endoscopy for Prostate Cancer: A Simulation Study.

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.