High spatiotemporal resolution scintillation imaging of pulsed pencil beam scanning proton beams produced by a gantry-mounted synchrocyclotron.

BACKGROUND: A dosimeter with high spatial and temporal resolution would be of significant interest for pencil beam scanning (PBS) proton beams' characterization, especially when facing small fields and beams with high temporal dynamics. Optical imaging of scintillators has potential in providing sub-millimeter spatial resolution with pulse-by-pulse basis temporal resolution when the imaging system is capable of operating in synchrony with the beam-producing accelerator. PURPOSE: We demonstrate the feasibility of imaging PBS proton beams as they pass through a plastic scintillator detector to simultaneously obtain multiple beam parameters, including proton range, pencil beam's widths at different depths, spot's size, and spot's position on a pulse-by-pulse basis with sub-millimeter resolution. MATERIALS AND METHODS: A PBS synchrocyclotron was used for proton irradiation. A BC-408 plastic scintillator block with 30 × 30 × 5 cm3 size, and another block with 30 × 30 × 0.5 cm3 size, positioned in an optically sealed housing, were used sequentially to measure the proton range, and spot size/location, respectively. A high-speed complementary metal-oxide-semiconductor (CMOS) camera system synchronized with the accelerator's pulses through a gating module was used for imaging. Scintillation images, captured with the camera directly facing the 5-cm-thick scintillator, were corrected for background (BG), and ionization quenching of the scintillator to obtain the proton range. Spots' position and size were obtained from scintillation images of the 0.5-cm-thick scintillator when a 45° mirror was used to reflect the scintillation light toward the camera. RESULTS: Scintillation images with 0.16 mm/pixel resolution corresponding to all proton pulses were captured. Pulse-by-pulse analysis showed that variations of the range, spots' position, and size were within ± 0.2% standard deviation of their average values. The absolute ranges were within ± 1 mm of their expected values. The average spot-positions were mostly within ± 0.8 mm and spots' sigma agreed within 0.2 mm of the expected values. CONCLUSION: Scintillation-imaging PBS beams with high-spatiotemporal resolution is feasible and may help in efficient and cost-effective acceptance testing and commissioning of existing and even emerging technologies such as FLASH, grid, mini-beams, and so forth.

Trends and focal points in pelvic floor reconstruction for pelvic organ prolapse: A bibliometric analysis.

OBJECTIVE: This study aims to investigate the current research trends and focal points in the field of pelvic floor reconstruction for the management of pelvic organ prolapse (POP). METHODS: To achieve this objective, a bibliometric analysis was conducted on relevant literature using the Citespace database. The analysis led to the creation of a knowledge map, offering a comprehensive overview of scientific advancements in this research area. RESULTS: The study included a total of 607 publications, revealing a consistent increase in articles addressing pelvic floor reconstruction for POP treatment. Most articles originated from the United States (317 articles), followed by Chinese scholars (40 articles). However, it is important to note that the overall number of articles remains relatively low. The organization with the highest publication frequency was the Cleveland Clinic in Ohio, where Matthew D. Barber leads the academic group. Barber himself has the highest number of published articles (18 articles), followed by Zhu Lan, a Chinese scholar (10 articles). Key topics with high frequency and mediated centrality include stress urinary incontinence, quality of life, impact, and age. The journal with the largest number of papers from both domestic and international researchers is INT UROGYNECOL J. The study's hotspots mainly focus on the impact of pelvic floor reconstruction on the treatment and quality of life of POP patients. The United States leads in this field, but there is a lack of cooperation between countries, institutions, and authors. Moving forward, cross-institutional, cross-national, and cross-disciplinary exchanges and cooperation should be strengthened to further advance the field of pelvic floor reconstructive surgery for POP research.

Image quality characterization of an ultra-high-speed kilovoltage cone-beam computed tomography imaging system on an O-ring linear accelerator.

PURPOSE: The quality of on-board imaging systems, including cone-beam computed tomography (CBCT), plays a vital role in image-guided radiation therapy (IGRT) and adaptive radiotherapy. Recently, there has been an upgrade of the CBCT systems fused in the O-ring linear accelerators called HyperSight, featuring a high imaging performance. As the characterization of a new imaging system is essential, we evaluated the image quality of the HyperSight system by comparing it with Halcyon 3.0 CBCT and providing benchmark data for routine imaging quality assurance. METHODS: The HyperSight features ultra-fast scan time, a larger kilovoltage (kV) detector, a more substantial kV tube, and an advanced reconstruction algorithm. Imaging protocols in the two modes of operation, treatment mode with IGRT and the CBCT for planning (CBCTp) mode were evaluated and compared with Halcyon 3.0 CBCT. Image quality metrics, including spatial resolution, contrast resolution, uniformity, noise, computed tomography (CT) number linearity, and calibration error, were assessed using a Catphan and an electron density phantom and analyzed with TotalQA software. RESULTS: HyperSight demonstrated substantial improvements in contrast-to-noise ratio and noise in both IGRT and CBCTp modes compared to Halcyon 3.0 CBCT. CT number calibration error of HyperSight CBCTp mode (1.06%) closely matches that of a full CT scanner (0.72%), making it suitable for adaptive planning. In addition, the advanced hardware of HyperSight, such as ultra-fast scan time (5.9 s) or 2.5 times larger heat unit capacity, enhanced the clinical efficiency in our experience. CONCLUSIONS: HyperSight represented a significant advancement in CBCT imaging. With its image quality, CT number accuracy, and ultra-fast scans, HyperSight has a potential to transform patient care and treatment outcomes. The enhanced scan speed and image quality of HyperSight are expected to significantly improve the quality and efficiency of treatment, particularly benefiting patients.

Prevalence and impact of viral myocarditis in patients with severe fever with thrombocytopenia syndrome.

To explore the association and impact between viral myocarditis and mortality in patients with severe fever with thrombocytopenia syndrome. A dynamic analysis was conducted between fatal group and nonfatal group regarding the daily epidemiology data, clinical symptoms, and electrocardiogram (ECG), echocardiogram, and laboratory findings. Outcomes of patients with and without viral myocarditis were compared. The association between viral myocarditis and mortality was analyzed. Among 183 severe fever with thrombocytopenia syndrome patients, 32 were in the fatal group and 151 in the nonfatal group; there were 26 (81.25%) with viral myocarditis in the fatal group, 66 (43.70%) with viral myocarditis in the nonfatal group (p < 0.001), 79.35% of patients had abnormal ECG results. The abnormal rate of ECG in the fatal group was 100%, and in the nonfatal group was 74.83%. Univariate analysis found that the number of risk factors gradually increased on Day 7 of the disease course and reached the peak on Day 10. Combined with the dynamic analysis of the disease course, alanine aminotransferase, aspartate aminotransferase, creatine kinase, creatine kinase fraction, lactate dehydrogenase, hydroxybutyrate dehydrogenase, neutrophil count, serum creatinine, Na, Ca, carbon dioxide combining power, amylase, lipase, activated partial thromboplastin time and thrombin time had statistically significant impact on prognosis. The incidence of fever with thrombocytopenia syndrome combined with viral myocarditis is high, especially in the fatal group of patients. Viral myocarditis is closely related to prognosis and is an early risk factor. The time point for changes in myocarditis is Day 7 of the course of the disease.

A comprehensive lung CT landmark pair dataset for evaluating deformable image registration algorithms.

PURPOSE: Deformable image registration (DIR) is a key enabling technology in many diagnostic and therapeutic tasks, but often does not meet the required robustness and accuracy for supporting clinical tasks. This is in large part due to a lack of high-quality benchmark datasets by which new DIR algorithms can be evaluated. Our team was supported by the National Institute of Biomedical Imaging and Bioengineering to develop DIR benchmark dataset libraries for multiple anatomical sites, comprising of large numbers of highly accurate landmark pairs on matching blood vessel bifurcations. Here we introduce our lung CT DIR benchmark dataset library, which was developed to improve upon the number and distribution of landmark pairs in current public lung CT benchmark datasets. ACQUISITION AND VALIDATION METHODS: Thirty CT image pairs were acquired from several publicly available repositories as well as authors' institution with IRB approval. The data processing workflow included multiple steps: (1) The images were denoised. (2) Lungs, airways, and blood vessels were automatically segmented. (3) Bifurcations were directly detected on the skeleton of the segmented vessel tree. (4) Falsely identified bifurcations were filtered out using manually defined rules. (5) A DIR was used to project landmarks detected on the first image onto the second image of the image pair to form landmark pairs. (6) Landmark pairs were manually verified. This workflow resulted in an average of 1262 landmark pairs per image pair. Estimates of the landmark pair target registration error (TRE) using digital phantoms were 0.4 mm ± 0.3 mm. DATA FORMAT AND USAGE NOTES: The data is published in Zenodo at https://doi.org/10.5281/zenodo.8200423. Instructions for use can be found at https://github.com/deshanyang/Lung-DIR-QA. POTENTIAL APPLICATIONS: The dataset library generated in this work is the largest of its kind to date and will provide researchers with a new and improved set of ground truth benchmarks for quantitatively validating DIR algorithms within the lung.

Millimeter wave-based patient setup verification and motion tracking during radiotherapy.

BACKGROUND: Position verification and motion monitoring are critical for safe and precise radiotherapy (RT). Existing approaches to these tasks based on visible light or x-ray are suboptimal either because they cannot penetrate obstructions to the patient's skin or introduce additional radiation exposure. The low-cost mmWave radar is an ideal solution for these tasks as it can monitor patient position and motion continuously throughout the treatment delivery. PURPOSE: To develop and validate frequency-modulated continuous wave (FMCW) mmWave radars for position verification and motion tracking during RT delivery. METHODS: A 77 GHz FMCW mmWave module was used in this study. Chirp Z Transform-based (CZT) algorithm was developed to process the intermediate frequency (IF) signals. Absolute distances to flat Solid Water slabs and human shape phantoms were measured. The accuracy of absolute distance and relative displacement were evaluated. RESULTS: Without obstruction, mmWave based on the CZT algorithm was able to detect absolute distance within 1 mm for a Solid Water slab that simulated the reflectivity of the human body. Through obstructive materials, the mmWave device was able to detect absolute distance within 5 mm in the worst case and within 3.5 mm in most cases. The CZT algorithm significantly improved the accuracy of absolute distance measurement compared with Fast Fourier Transform (FFT) algorithm and was able to achieve submillimeter displacement accuracy with and without obstructions. The surface-to-skin distance (SSD) measurement accuracy was within 8 mm in the anterior of the phantom. CONCLUSIONS: With the CZT signal processing algorithm, the mmWave radar is able to measure the absolute distance to a flat surface within 1 mm. But the absolute distance measurement to a human shape phantom is as large as 8 mm at some angles. Further improvement is necessary to improve the accuracy of SSD measurement to uneven surfaces by the mmWave radar.

A deep learning approach to remove contrast from contrast-enhanced CT for proton dose calculation.

PURPOSE: Non-Contrast Enhanced CT (NCECT) is normally required for proton dose calculation while Contrast Enhanced CT (CECT) is often scanned for tumor and organ delineation. Possible tissue motion between these two CTs raises dosimetry uncertainties, especially for moving tumors in the thorax and abdomen. Here we report a deep-learning approach to generate NCECT directly from CECT. This method could be useful to avoid the NCECT scan, reduce CT simulation time and imaging dose, and decrease the uncertainties caused by tissue motion between otherwise two different CT scans. METHODS: A deep network was developed to convert CECT to NCECT. The network receives a 3D image from CECT images as input and generates a corresponding contrast-removed NCECT image patch. Abdominal CECT and NCECT image pairs of 20 patients were deformably registered and 8000 image patch pairs extracted from the registered image pairs were utilized to train and test the model. CTs of clinical proton patients and their treatment plans were employed to evaluate the dosimetric impact of using the generated NCECT for proton dose calculation. RESULTS: Our approach achieved a Cosine Similarity score of 0.988 and an MSE value of 0.002. A quantitative comparison of clinical proton dose plans computed on the CECT and the generated NCECT for five proton patients revealed significant dose differences at the distal of beam paths. V100% of PTV and GTV changed by 3.5% and 5.5%, respectively. The mean HU difference for all five patients between the generated and the scanned NCECTs was ∼4.72, whereas the difference between CECT and the scanned NCECT was ∼64.52, indicating a ∼93% reduction in mean HU difference. CONCLUSIONS: A deep learning approach was developed to generate NCECTs from CECTs. This approach could be useful for the proton dose calculation to reduce uncertainties caused by tissue motion between CECT and NCECT.

A quality assurance framework for routine monitoring of deep learning cardiac substructure computed tomography segmentation models in radiotherapy.

BACKGROUND: For autosegmentation models, the data used to train the model (e.g., public datasets and/or vendor-collected data) and the data on which the model is deployed in the clinic are typically not the same, potentially impacting the performance of these models by a process called domain shift. Tools to routinely monitor and predict segmentation performance are needed for quality assurance. Here, we develop an approach to perform such monitoring and performance prediction for cardiac substructure segmentation. PURPOSE: To develop a quality assurance (QA) framework for routine or continuous monitoring of domain shift and the performance of cardiac substructure autosegmentation algorithms. METHODS: A benchmark dataset consisting of computed tomography (CT) images along with manual cardiac substructure delineations of 241 breast cancer radiotherapy patients were collected, including one "normal" image domain of clean images and five "abnormal" domains containing images with artifact (metal, contrast), pathology, or quality variations due to scanner protocol differences (field of view, noise, reconstruction kernel, and slice thickness). The QA framework consisted of an image domain shift detector which operated on the input CT images and a shape quality detector on the output of an autosegmentation model, and a regression model for predicting autosegmentation model performance. The image domain shift detector was composed of a trained denoising autoencoder (DAE) and two hand-engineered image quality features to detect normal versus abnormal domains in the input CT images. The shape quality detector was a variational autoencoder (VAE) trained to estimate the shape quality of the auto-segmentation results. The output from the image domain shift and shape quality detectors was used to train a regression model to predict the per-patient segmentation accuracy, measured by Dice coefficient similarity (DSC) to physician contours. Different regression techniques were investigated including linear regression, Bagging, Gaussian process regression, random forest, and gradient boost regression. Of the 241 patients, 60 were used to train the autosegmentation models, 120 for training the QA framework, and the remaining 61 for testing the QA framework. A total of 19 autosegmentation models were used to evaluate QA framework performance, including 18 convolutional neural network (CNN)-based and one transformer-based model. RESULTS: When tested on the benchmark dataset, all abnormal domains resulted in a significant DSC decrease relative to the normal domain for CNN models ( p < 0.001 $p < 0.001$ ), but only for some domains for the transformer model. No significant relationship was found between the performance of an autosegmentation model and scanner protocol parameters ( p = 0.42 $p = 0.42$ ) except noise ( p = 0.01 $p = 0.01$ ). CNN-based autosegmentation models demonstrated a decreased DSC ranging from 0.07 to 0.41 with added noise, while the transformer-based model was not significantly affected (ANOVA, p = 0.99 $p=0.99$ ). For the QA framework, linear regression models with bootstrap aggregation resulted in the highest mean absolute error (MAE) of 0.041 ± 0.002 $0.041 \pm 0.002$ , in predicted DSC (relative to true DSC between autosegmentation and physician). MAE was lowest when combining both input (image) detectors and output (shape) detectors compared to output detectors alone. CONCLUSIONS: A QA framework was able to predict cardiac substructure autosegmentation model performance for clinically anticipated "abnormal" domain shifts.

EStore: A User-Friendly Encrypted Storage Scheme for Distributed File Systems.

In this paper, we propose a user-friendly encrypted storage scheme named EStore, which is based on the Hadoop distributed file system. Users can make use of cloud-based distributed file systems to collaborate with each other. However, most data are processed and stored in plaintext, which is out of the owner's control after it has been uploaded and shared. Meanwhile, simple encryption guarantees the confidentiality of uploaded data but reduces availability. Furthermore, it is difficult to deal with complex key management as there is the problem whereby a single key encrypts different files, thus increasing the risk of leakage. In order to solve the issues above, we put forward an encrypted storage model and a threat model, designed with corresponding system architecture to cope with these requirements. Further, we designed and implemented six sets of protocols to meet users' requirements for security and use. EStore manages users and their keys through registration and authentication, and we developed a searchable encryption module and encryption/decryption module to support ciphertext retrieval and secure data outsourcing, which will only minimally increase the calculation overhead of the client and storage redundancy. Users are invulnerable compared to the original file system. Finally, we conducted a security analysis of the protocols to demonstrate that EStore is feasible and secure.

Initial clinical experience building a dual CT- and MR-guided adaptive radiotherapy program.

Introduction: Our institution was the first in the world to clinically implement MR-guided adaptive radiotherapy (MRgART) in 2014. In 2021, we installed a CT-guided adaptive radiotherapy (CTgART) unit, becoming one of the first clinics in the world to build a dual-modality ART clinic. Herein we review factors that lead to the development of a high-volume dual-modality ART program and treatment census over an initial, one-year period. Materials and Methods: The clinical adaptive service at our institution is enabled with both MRgART (MRIdian, ViewRay, Inc, Mountain View, CA) and CTgART (ETHOS, Varian Medical Systems, Palo Alto, CA) platforms. We analyzed patient and treatment information including disease sites treated, radiation dose and fractionation, and treatment times for patients on these two platforms. Additionally, we reviewed our institutional workflow for creating, verifying, and implementing a new adaptive workflow on either platform. Results: From October 2021 to September 2022, 256 patients were treated with adaptive intent at our institution, 186 with MRgART and 70 with CTgART. The majority (106/186) of patients treated with MRgART had pancreatic cancer, and the most common sites treated with CTgART were pelvis (23/70) and abdomen (20/70). 93.0% of treatments on the MRgART platform were stereotactic body radiotherapy (SBRT), whereas only 72.9% of treatments on the CTgART platform were SBRT. Abdominal gated cases were allotted a longer time on the CTgART platform compared to the MRgART platform, whereas pelvic cases were allotted a shorter time on the CTgART platform when compared to the MRgART platform. Our adaptive implementation technique has led to six open clinical trials using MRgART and seven using CTgART. Conclusions: We demonstrate the successful development of a dual platform ART program in our clinic. Ongoing efforts are needed to continue the development and integration of ART across platforms and disease sites to maximize access and evidence for this technique worldwide.

Characterization of the Targeting Accuracy of a Neuronavigation-Guided Transcranial FUS System In Vitro, In Vivo, and In Silico.

Focused ultrasound (FUS)-enabled liquid biopsy (sonobiopsy) is an emerging technique for the noninvasive and spatiotemporally controlled diagnosis of brain cancer by inducing blood-brain barrier (BBB) disruption to release brain tumor-specific biomarkers into the blood circulation. The feasibility, safety, and efficacy of sonobiopsy were demonstrated in both small and large animal models using magnetic resonance-guided FUS devices. However, the high cost and complex operation of magnetic resonance-guided FUS devices limit the future broad application of sonobiopsy in the clinic. In this study, a neuronavigation-guided sonobiopsy device is developed and its targeting accuracy is characterized in vitro, in vivo, and in silico. The sonobiopsy device integrated a commercially available neuronavigation system (BrainSight) with a nimble, lightweight FUS transducer. Its targeting accuracy was characterized in vitro in a water tank using a hydrophone. The performance of the device in BBB disruption was verified in vivo using a pig model, and the targeting accuracy was quantified by measuring the offset between the target and the actual locations of BBB opening. The feasibility of the FUS device in targeting glioblastoma (GBM) tumors was evaluated in silico using numerical simulation by the k-Wave toolbox in glioblastoma patients. It was found that the targeting accuracy of the neuronavigation-guided sonobiopsy device was 1.7 ± 0.8 mm as measured in the water tank. The neuronavigation-guided FUS device successfully induced BBB disruption in pigs with a targeting accuracy of 3.3 ± 1.4 mm. The targeting accuracy of the FUS transducer at the GBM tumor was 5.5 ± 4.9 mm. Age, sex, and incident locations were found to be not correlated with the targeting accuracy in GBM patients. This study demonstrated that the developed neuronavigation-guided FUS device could target the brain with a high spatial targeting accuracy, paving the foundation for its application in the clinic.

A clinical and time savings evaluation of a deep learning automatic contouring algorithm.

Automatic contouring algorithms may streamline clinical workflows by reducing normal organ-at-risk (OAR) contouring time. Here we report the first comprehensive quantitative and qualitative evaluation, along with time savings assessment for a prototype deep learning segmentation algorithm from Siemens Healthineers. The accuracy of contours generated by the prototype were evaluated quantitatively using the Sorensen-Dice coefficient (Dice), Jaccard index (JC), and Hausdorff distance (Haus). Normal pelvic and head and neck OAR contours were evaluated retrospectively comparing the automatic and manual clinical contours in 100 patient cases. Contouring performance outliers were investigated. To quantify the time savings, a certified medical dosimetrist manually contoured de novo and, separately, edited the generated OARs for 10 head and neck and 10 pelvic patients. The automatic, edited, and manually generated contours were visually evaluated and scored by a practicing radiation oncologist on a scale of 1-4, where a higher score indicated better performance. The quantitative comparison revealed high (> 0.8) Dice and JC performance for relatively large organs such as the lungs, brain, femurs, and kidneys. Smaller elongated structures that had relatively low Dice and JC values tended to have low Hausdorff distances. Poor performing outlier cases revealed common anatomical inconsistencies including overestimation of the bladder and incorrect superior-inferior truncation of the spinal cord and femur contours. In all cases, editing contours was faster than manual contouring with an average time saving of 43.4% or 11.8 minutes per patient. The physician scored 240 structures with > 95% of structures receiving a score of 3 or 4. Of the structures reviewed, only 11 structures needed major revision or to be redone entirely. Our results indicate the evaluated auto-contouring solution has the potential to reduce clinical contouring time. The algorithm's performance is promising, but human review and some editing is required prior to clinical use.

Binary acoustic metasurfaces for dynamic focusing of transcranial ultrasound.

Transcranial focused ultrasound (tFUS) is a promising technique for non-invasive and spatially targeted neuromodulation and treatment of brain diseases. Acoustic lenses were designed to correct the skull-induced beam aberration, but these designs could only generate static focused ultrasound beams inside the brain. Here, we designed and 3D printed binary acoustic metasurfaces (BAMs) for skull aberration correction and dynamic ultrasound beam focusing. BAMs were designed by binarizing the phase distribution at the surface of the metasurfaces. The phase distribution was calculated based on time reversal to correct the skull-induced phase aberration. The binarization enabled the ultrasound beam to be dynamically steered along wave propagation direction by adjusting the operation frequency of the incident ultrasound wave. The designed BAMs were manufactured by 3D printing with two coding bits, a polylactic acid unit for bit "1" and a water unit for bit "0." BAMs for single- and multi-point focusing through the human skull were designed, 3D printed, and validated numerically and experimentally. The proposed BAMs with subwavelength scale in thickness are simple to design, easy to fabric, and capable of correcting skull aberration and achieving dynamic beam steering.

Improvement of IMRT QA prediction using imaging-based neural architecture search.

PURPOSE: Machine learning (ML) has been used to predict the gamma passing rate (GPR) of intensity-modulated radiation therapy (IMRT) QA results. In this work, we applied a novel neural architecture search to automatically tune and search for the best deep neural networks instead of using hand-designed deep learning architectures. METHOD AND MATERIALS: One hundred and eighty-two IMRT plans were created and delivered with portal dosimetry. A total of 1497 fields for multiple treatment sites were delivered and measured by portal imagers. Gamma criteria of 2%/2 mm with a 5% threshold were used. Fluence maps calculated for each plan were used as inputs to a convolution neural network (CNN). Auto-Keras was implemented to search for the best CNN architecture for fluence image regression. The network morphism was adopted in the searching process, in which the base models were ResNet and DenseNet. The performance of this CNN approach was compared with tree-based ML models previously developed for this application, using the same dataset. RESULTS: The deep-learning-based approach had 98.3% of predictions within 3% of the measured 2%/2-mm GPRs with a maximum error of 3.1% and a mean absolute error of less than 1%. Our results show that this novel architecture search approach achieves comparable performance to the machine-learning-based approaches with handcrafted features. CONCLUSIONS: We implemented a novel CNN model using imaging-based neural architecture for IMRT QA prediction. The imaging-based deep-learning method does not require a manual extraction of relevant features and is able to automatically select the best network architecture.

A reconstruction approach for proton computed tomography by modeling the integral depth dose of the scanning proton pencil beam.

PURPOSE: To present a proton computed tomography (pCT) reconstruction approach that models the integral depth dose (IDD) of the clinical scanning proton beam into beamlets. Using a multilayer ionization chamber (MLIC) as the imager, the proposed pCT system and the reconstruction approach can minimize extra ambient neutron dose and simplify the beamline design by eliminating an additional collimator to confine the proton beam. METHODS: Monte Carlo simulation was applied to digitally simulate the IDDs of the exiting proton beams detected by the MLIC. A forward model was developed to model each IDD into a weighted sum of percentage depth doses of the constituent beamlets separated laterally by 1 mm. The water equivalent path lengths (WEPLs) of the beamlets were determined by iteratively minimizing the squared L2-norm between the forward projected and simulated IDDs. The final WEPL values were reconstructed to pCT images, that is, proton stopping power ratio (SPR) maps, through simultaneous algebraic reconstruction technique with total variation regularization. The reconstruction process was tested with a digital cylindrical water-based phantom and an ICRP adult reference computational phantom. The mean of SPR within regions of interest (ROIs) and the WEPL along a 4 mm-wide beam ( WEP L 4 mm ${\rm{WEP}}{{\rm{L}}_{4{\rm{mm}}}}$ ) were compared with the reference values. The spatial resolution was analyzed at the edge of a cortical insert of the cylindrical phantom. RESULTS: The percentage deviations from reference SPR were within ±1% in all selected ROIs. The mean absolute error of the reconstructed SPR was 0.33%, 0.19%, and 0.27% for the cylindrical phantom, the adult phantom at the head and lung region, respectively. The corresponding percentage deviations from reference WEP L 4 mm ${\rm{WEP}}{{\rm{L}}_{4{\rm{mm}}}}$ were 0.48 ± 0.64%, 0.28 ± 0.48%, and 0.22 ± 0.49%. The full width at half maximum of the line spread function (LSF) derived from the radial edge spread function (ESF) of a cortical insert was 0.13 cm. The frequency at 10% of the modulation transfer function (MTF) was 6.38 cm-1 . The mean signal-to-noise ratio (SNR) of all the inserts was 2.45. The mean imaging dose was 0.29 and 0.25 cGy at the head and lung region of the adult phantom, respectively. CONCLUSION: A new pCT reconstruction approach was developed by modeling the IDDs of the uncollimated scanning proton beams in the pencil beam geometry. SPR accuracy within ±1%, spatial resolution of better than 2 mm at 10% MTF, and imaging dose at the magnitude of mGy were achieved. Potential side effects caused by neutron dose were eliminated by removing the extra beam collimator.

Visually guided respiratory motion management for Ethos adaptive radiotherapy.

PURPOSE: Ethos adaptive radiotherapy (ART) is emerging with AI-enhanced adaptive planning and high-quality cone-beam computed tomography (CBCT). Although a respiratory motion management solution is critical for reducing motion artifacts on abdominothoracic CBCT and improving tumor motion control during beam delivery, our institutional Ethos system has not incorporated a commercial solution. Here we developed an institutional visually guided respiratory motion management system to coach patients in regular breathing or breath hold during intrafractional CBCT scans and beam delivery with Ethos ART. METHODS: The institutional visual-guidance respiratory motion management system has three components: (1) a respiratory motion detection system, (2) an in-room display system, and (3) a respiratory motion trace management software. Each component has been developed and implemented in the clinical Ethos ART workflow. The applicability of the solution was demonstrated in installation, routine QA, and clinical workflow. RESULTS: An air pressure sensor has been utilized to detect patient respiratory motion in real time. Either a commercial or in-house software handled respiratory motion trace display, collection and visualization for operators, and visual guidance for patients. An extended screen and a projector on an adjustable stand were installed as the in-room visual guidance solution for the closed-bore ring gantry medical linear accelerator utilized by Ethos. Consistent respiratory motion traces and organ positions on intrafractional CBCTs demonstrated the clinical suitability of the proposed solution in Ethos ART. CONCLUSION: The study demonstrated the utilization of an institutional visually guided respiratory motion management system for Ethos ART. The proposed solution can be easily applied for Ethos ART and adapted for use with any closed bore-type system, such as computed tomography and magnetic resonance imaging, through incorporation with appropriate respiratory motion sensors.

Tetrahedron beam imaging with a multi-pixel thermionic emission X-ray source and a photon-counting detector: A benchtop experimental study.

PURPOSE: A tetrahedron beam (TB) X-ray system with a linear X-ray source array and a linear detector array positioned orthogonal to each other may overcome the X-ray scattering problem of traditional cone-beam X-ray systems. We developed a TB imaging benchtop system using a linear array X-ray source to demonstrate the principle and benefits of TB imaging. METHODS: A multi-pixel thermionic emission X-ray (MPTEX) source with 48 focal spots in 4-mm spacing was developed in-house. The X-ray beams are collimated to a stack of fan beams that are converged to a 6-mm wide multi-row photon-counting detector (PCD). The data collected with a sequential scan of the sources at a fixed view angle were synthesized to a 2D radiography image by a shift-and-add algorithm. The data collected with a full rotation of the system were reconstructed into 3D TB CT (TBCT) images using an Feldkamp, Davis, and Kress (FDK)-based computed tomography (CT) algorithm modified for the TB geometry. RESULTS: With an 18.8-cm long source array and a 35-cm long detector array, the TB benchtop system provides a 25-cm cross-sectional and 8-cm axial field of view (FOV). The scatter-to-primary ratio (SPR) was approximately 17% for TB, as compared with 120% for cone beam geometry. The TBCT system enables reconstructions in two-dimensional radiography and three-dimensional volumetric CT. The TBCT images were free of "cupping" artifacts and have similar image quality as diagnostic helical CT. CONCLUSIONS: A TB imaging benchtop imaging system was successfully developed with MPTEX source and PCD. Phantom and animal cadaver imaging demonstrated that the TB system can produce satisfactory radiographic X-ray images and 3D CT images with image quality comparable to diagnostic helical CTs.

Development of a storage phosphor imaging system for proton pencil beam spot profile determination.

PURPOSE: Accurate two-dimensional (2D) profile measurements at submillimeter precision are necessary for proton beam commissioning and periodic quality assurance (QA) purposes and are currently performed at our institution with a commercial scintillation detector (Lynx PT) with limited means for independent checks. The purpose of this work was to create an independent dosimetry system consisting of an in-house optical scanner and a BaFBrI:Eu2+ storage phosphor dosimeter by: (a) determining the optimal settings for the optical scanner, (b) measuring 2D proton spot profiles with the storage phosphors, and (c) comparing them to similar measurements using a commercial scintillation detector. METHODS: An in-house 2D laboratory optical scanner was constructed and spatially calibrated for accurate 2D photostimulated luminescence (PSL) dosimetry. Square 5 × 5 cm2 BaFBrI:Eu2+ dosimeter samples were uniformly irradiated with line scans performed to determine the physical and electronic scanner settings resulting in the highest signal-to-noise ratios (SNR) at a sub-millimeter spatial resolution. The resultant spatial resolution of the scanner was then quantitatively assessed by measuring (a) line pairs on a standard X-ray lead bar phantom and (b) modulation transfer functions. Following this, 2D proton spot profiles from a Mevion S250i Hyperscan proton unit were obtained at 1, 10, 20, 30, 40, and 50 monitor unit (MU) settings at maximum energy (E0  = 227.1 MeV) and compared to baseline profiles from a commercial scintillation detector, where 1 MU is calibrated to deliver 1 Gy absolute proton dose-to-water under reference conditions, that is, 41 × 41 proton spots uniformly spaced by 0.25 cm within a 10 × 10 cm2 square field size at maximum energy (227.1 MeV) in water at depth of 5 cm at isocenter. The dosimetric system's sensitivities to (a) ±1 mm positional shifts and (b) ±0.3 mm beam lateral spread changes were quantitatively evaluated through a Gaussian fitting of the crossline and inline plots of the respective artificially shifted beam profiles. RESULTS: The physical scanner settings of (a) Δτ = 27 ms time interval between data samples, (b) vx  = 1.235 cm/s scanning speed, (c) 1% laser transmission (0.02 mW power) and (d) (Δx, Δy) = (0.33, 0.50 mm) pixel sizes with electronic settings of (a) 300 microseconds time constant, (b) normal dynamic reserve, (c) 24 dB/oct low pass filter slope, and (d) 160 Hz chopping frequency resulted in the highest SNR while maintaining sub-millimeter spatial resolution. The BaFBr0.85 I0.15 :Eu2+ storage phosphor dosimeters were linear from 1 to 50 MU and their profiles did not saturate up to 150 MU. The scanner was able to detect lateral displacements of ±1 mm in both the crossline and inline directions and ±0.3 mm beam spread changes that were artificially introduced by varying the incident proton energy. Specific to our proton unit, proton energy changes of ±1 MeV can also be detected indirectly via beam spread measurements. CONCLUSION: Our combined dosimetric system including an in-house laboratory optical scanner and reusable BaFBr0.85 I0.15 :Eu2+ storage phosphors demonstrated a sufficient spatial resolution and dosimetric accuracy to support its use as an independent proton spot measurement dosimeter system. Its wide dynamic range allows for other versatile applications such as proton halo measurements.

Spread-out Bragg peak proton FLASH irradiation using a clinical synchrocyclotron: Proof of concept and ion chamber characterization.

PURPOSE: The purpose of this work is to (a) demonstrate the feasibility of delivering a spread-out Bragg peak (SOBP) proton beam in ultra-high dose rate (FLASH) using a proton therapy synchrocyclotron as a major step toward realizing an experimental platform for preclinical studies, and (b) evaluate the response of four models of ionization chambers in such a radiation field. METHODS: A clinical Mevion HYPERSCAN® synchrocyclotron was adjusted for ultra-high dose rate proton delivery. Protons with nominal energy of 230 MeV were delivered in pulses with temporal width ranging from 12.5 µs to 24 µs spanning from conventional to FLASH dose rates. A boron carbide absorber and a range modulator block were placed in the beam path for range modulation and creating an SOBP dose profile. The radiation field was defined by a brass aperture with 11 mm diameter. Two Faraday cups were used to determine the number of protons per pulse at various dose rates. The dosimetric response of two cylindrical (IBA CC04 and CC13) and two plane-parallel (IBA PPC05 and PTW Advanced Markus® ) ionization chambers were evaluated. The dose rate was measured using the plane-parallel ionization chambers. The integral depth dose (IDD) was measured with a PTW Bragg Peak® ionization chamber. The lateral beam profile was measured with EBT-XD radiochromic film. Monte Carlo simulation was performed in TOPAS as the secondary check for the measurements and as a tool for further optimization of the range modulators' design. RESULTS: Faraday cups measurement showed that the maximum protons per pulse is 39.9 pC at 24 µs pulse width. A good agreement between the measured and simulated IDD and lateral beam profiles was observed. The cylindrical ionization chambers showed very high ion recombination and deemed not suitable for absolute dosimetry at ultra-high dose rates. The average dose rate measured using the PPC05 ionization chamber was 163 Gy/s at the pristine Bragg peak and 126 Gy/s at 1 cm depth for the SOBP beam. The SOBP beam range and modulation were measured 24.4 mm and 19 mm, respectively. The pristine Bragg peak beam had 25.6 mm range. Simulation results showed that the IDD and profile flatness can be improved by the cavity diameter of the range modulator and the number of scanned spots, respectively. CONCLUSIONS: Feasibility of delivering protons in an SOBP pattern with >100 Gy/s average dose rate using a clinical synchrocyclotron was demonstrated. The dose heterogeneity can be improved through optimization of the range modulator and number of delivered spots. Plane-parallel chambers with smaller gap between electrodes are more suitable for FLASH dosimetry compared to the other ion chambers used in this work.

Application programming interface guided QA plan generation and analysis automation.

PURPOSE: Linear accelerator quality assurance (QA) in radiation therapy is a time consuming but fundamental part of ensuring the performance characteristics of radiation delivering machines. The goal of this work is to develop an automated and standardized QA plan generation and analysis system in the Oncology Information System (OIS) to streamline the QA process. METHODS: Automating the QA process includes two software components: the AutoQA Builder to generate daily, monthly, quarterly, and miscellaneous periodic linear accelerator QA plans within the Treatment Planning System (TPS) and the AutoQA Analysis to analyze images collected on the Electronic Portal Imaging Device (EPID) allowing for a rapid analysis of the acquired QA images. To verify the results of the automated QA analysis, results were compared to the current standard for QA assessment for the jaw junction, light-radiation coincidence, picket fence, and volumetric modulated arc therapy (VMAT) QA plans across three linacs and over a 6-month period. RESULTS: The AutoQA Builder application has been utilized clinically 322 times to create QA patients, construct phantom images, and deploy common periodic QA tests across multiple institutions, linear accelerators, and physicists. Comparing the AutoQA Analysis results with our current institutional QA standard the mean difference of the ratio of intensity values within the field-matched junction and ball-bearing position detection was 0.012 ± 0.053 (P = 0.159) and is 0.011 ± 0.224 mm (P = 0.355), respectively. Analysis of VMAT QA plans resulted in a maximum percentage difference of 0.3%. CONCLUSION: The automated creation and analysis of quality assurance plans using multiple APIs can be of immediate benefit to linear accelerator quality assurance efficiency and standardization. QA plan creation can be done without following tedious procedures through API assistance, and analysis can be performed inside of the clinical OIS in an automated fashion.