Search

Background: Ultra-high dose rate proton therapy shows promise in tissue sparing by enhancing therapeutic ratio through the FLASH effect. In radiotherapy, accurate in vivo dosimetry is crucial for quality assurance, but remains challenging for UHDR as existing systems lack spatial and temporal resolution to verify dose and dose rate in complex anatomical regions, especially for PBS proton therapy. Purpose: To develop and evaluate a novel 3D surface dosimetry method for UHDR PBS proton therapy using high-speed imaging of a scintillator array for real-time, high-resolution surface dose monitoring. The spatial, temporal, and dosimetric components are validated via imaging of a QA phantom and comparison against TPS predictions. Methods: A deformable multi-element scintillator array was designed with 7.5mm element pitch and 0.5mm inter-element gap. Scintillation linearity with dose was evaluated with variation in response to increasing imaging and irradiation angles. WED testing evaluated beam attenuation at two energy levels. Scintillation emission was imaged at 1kHz and mesh position was monitored via 2-camera stereovision. System setup was validated using a 3D QA phantom to assess spatial accuracy and guide setup correction. Stereovision properties of array elements guided angular correction and geometric transformation. Kernel-based residual spot fitting derived cumulative dose maps compared to TPS dose profile of 5x5cm UHDR PBS delivery using 3%/2mm gamma analysis. PBS and maximum dose rate maps were calculated. Results: Setup achieved average localization error of 0.62 mm, surpassing typical 1+ mm clinical threshold. Intensity correction based on angular information yielded cumulative spot dose uncertainty of ~1% (5.428mGy). Processed dose map compared to TPS via gamma analysis showed 99.9% passing rate at 3%/2mm. WED of the array measured 1.1mm, minimizing impact on dose distribution., Comment: 17 pages, 9 figures, submitted to Medical Physics

Accurate patient positioning is critical for precise radiotherapy dose delivery, as positioning errors can significantly affect treatment outcomes. This study introduces a novel method for tracking loco-regional tissue deformation through Cherenkov image analysis during fractionated breast cancer radiotherapy. The primary goal was to develop and test an algorithm for Cherenkov-based regional position accuracy quantification, specifically for loco-regional deformations, which lack ideal quantification methods in radiotherapy. Blood vessel detection and segmentation were developed in Cherenkov images using a tissue phantom with incremental movements, and later applied to images from fractionated whole breast radiotherapy in human patients (n=10). A combined rigid and non-rigid registration technique was used to detect inter- and intra-fractional positioning variations. This approach quantified positioning variations in two parts: a global shift from rigid registration and a two-dimensional variation map of loco-regional deformation from non-rigid registration. The methodology was validated using an anthropomorphic chest phantom experiment, where known treatment couch translations and respiratory motion were simulated to assess inter- and intra-fractional uncertainties, yielding an average accuracy of 0.83 mm for couch translations up to 20 mm. Analysis of clinical Cherenkov data from ten breast cancer patients showed an inter-fraction setup variation of 3.7 plus minus 2.4 mm relative to the first fraction and loco-regional deformations (95th percentile) of up to 3.3 plus minus 1.9 mm. This study presents a Cherenkov-based approach to quantify global and local positioning variations, demonstrating feasibility in addressing loco-regional deformations that conventional imaging techniques fail to capture., Comment: 25 pages, 4 figures, 1 table, journal under review

Cherenkov imaging enables real-time visualization of megavoltage X-ray or electron beam delivery to the patient during Radiation Therapy (RT). Bio-morphological features, such as vasculature, seen in these images are patient-specific signatures that can be used for verification of positioning and motion management that are essential to precise RT treatment. However until now, no concerted analysis of this biological feature-based tracking was utilized because of the slow speed and accuracy of conventional image processing for feature segmentation. This study demonstrated the first deep learning framework for such an application, achieving video frame rate processing. To address the challenge of limited annotation of these features in Cherenkov images, a transfer learning strategy was applied. A fundus photography dataset including 20,529 patch retina images with ground-truth vessel annotation was used to pre-train a ResNet segmentation framework. Subsequently, a small Cherenkov dataset (1,483 images from 212 treatment fractions of 19 breast cancer patients) with known annotated vasculature masks was used to fine-tune the model for accurate segmentation prediction. This deep learning framework achieved consistent and rapid segmentation of Cherenkov-imaged bio-morphological features on another 19 patients, including subcutaneous veins, scars, and pigmented skin. Average segmentation by the model achieved Dice score of 0.85 and required less than 0.7 milliseconds processing time per instance. The model demonstrated outstanding consistency against input image variances and speed compared to conventional manual segmentation methods, laying the foundation for online segmentation in real-time monitoring in a prospective setting., Comment: 9 pages, 7 figures, 1 table, journal under review

In this study, a radiomics approach was extended to optical fluorescence molecular imaging data for tissue classification, termed 'optomics'. Fluorescence molecular imaging is emerging for precise surgical guidance during head and neck squamous cell carcinoma (HNSCC) resection. However, the tumor-to-normal tissue contrast is confounded by intrinsic physiological limitations of heterogeneous expression of the target molecule, epidermal growth factor receptor (EGFR). Optomics seek to improve tumor identification by probing textural pattern differences in EGFR expression conveyed by fluorescence. A total of 1,472 standardized optomic features were extracted from fluorescence image samples. A supervised machine learning pipeline involving a support vector machine classifier was trained with 25 top-ranked features selected by minimum redundancy maximum relevance criterion. Model predictive performance was compared to fluorescence intensity thresholding method by classifying testing set image patches of resected tissue with histologically confirmed malignancy status. The optomics approach provided consistent improvement in prediction accuracy on all test set samples, irrespective of dose, compared to fluorescence intensity thresholding method (mean accuracies of 89% vs. 81%; P = 0.0072). The improved performance demonstrates that extending the radiomics approach to fluorescence molecular imaging data offers a promising image analysis technique for cancer detection in fluorescence-guided surgery., Comment: 21 pages, 8 figures, 1 table, submitted as a manuscript at Frontiers in Medical Technology

Objective: In this study, a fast imaging technique was developed for the first in vivo Cherenkov emission imaging from an ultra-high dose rate (UHDR) electron beam source at single pulse (360 Hz) submillimeter resolution. Approach: A CMOS camera, gated to the UHDR LINAC, imaged the Cherenkov emission profiles pulse by pulse passively during the irradiation of mice on their limbs and intestinal region. The utility of an intensifier was investigated for its effect on image quality including signal to noise and spatial resolution. Pulse by pulse variability in Cherenkov emission profile were quantified spatially and temporally. Main results: An intensifier improved the emission profile signal to noise ratio from 15 to 280, with reduced spatial resolution. The profile extended beyond of the treatment field due to the lateral scattering of the electrons in tissue and its optical properties. The CMOS camera with an intensifier detected the changes in Cherenkov emission profile during expiration and inspiration of the respiration cycle for the mice to be about 3 mm. Significance: This fast imaging technique can be utilized for in vivo intrafraction monitoring of FLASH patient treatments at single pulse resolution. It can display delivery differences during respiration, and variability in the delivered treatment's surface profile, which may perturb from the intended UHDR treatment more for pencil beam scanning systems. The technique may leverage Cherenkov emission surface profile to gate the treatment delivery via respiratory gating systems under FLASH conditions., Comment: 16 pages, 3 figures

Purpose: A diode EDGE Detector with a newly designed electrometer has been characterized for use in an UHDR electron beam and demonstrated appropriateness for UHDR FLASH radiotherapy dosimetry. Methods: Dose linearity, mean dose rate, and dose per pulse dependencies of the EDGE Detector were quantified and compared with dosimeters including a W1 scintillator detector, radiochromic film, and ionization chamber that were irradiated with a 10 MeV UHDR beam. The dose, dose rate and dose per pulse were controlled via an in-house developed scintillation-based feedback mechanism, repetition rate of the linear accelerator, and source-to-surface distance, respectively. Depth-dose profiles and temporal profiles at individual pulse resolution were compared to the film and scintillation measurements, respectively. The radiation-induced change in response sensitivity was quantified via irradiation of ~5kGy. Results: The EDGE Detector agreed with film measurements in the measured range with varying dose (up to 70 Gy), dose rate (nearly 200 Gy/s), and dose per pulse (up to 0.63 Gy/pulse) on average to within 2%, 5%, and 1%, respectively. The detector also agreed with W1 scintillation detector on average to within 2% for dose per pulse (up to 0.78 Gy/pulse). The EDGE Detector signal was proportional to ion chamber (IC) measured dose, and mean dose rate in the bremsstrahlung tail to within 0.4% and 0.2% respectively. The EDGE Detector measured percent depth dose agreed with film to within 3% and per pulse output agreed with W1 scintillator to within -6% to +5%. Conclusions: The EDGE Detector demonstrated dose linearity, mean dose rate independence, and dose per pulse independence for UHDR electron beams. It can quantify the beam spatially, and temporally at sub millisecond resolution., Comment: 22 Pages, 7 Figures

Background: Use of a linear accelerator in ultra-high dose rate (UHDR) mode can provide a conduit for wider access to UHDR FLASH effects, sparing normal tissue, but care needs to be taken in the use of such systems to ensure errors are minimized. Purpose: Failure Modes and Effects Analysis (FMEA) was carried out in a team that has been involved in converting a LINAC between clinical use and UHDR experimental mode for more than one year, following the proposed methods of TG100. Methods: A team of 9 professionals with extensive experience were polled to outline the process map and workflow for analysis, and developed fault trees for potential errors, as well as failure modes that would results. The team scored the categories of severity magnitude (S), occurrence likelihood (O), and detectability potential (D) in a scale of 1 to 10, so that a risk priority number (RPN=S*O*D) could be assessed for each. Results: A total of 46 potential failure modes were identified, including 5 with RPN>100. These failure modes involved 1) patient set up, 2) gating mechanisms in delivery, and 3) detector in the beam stop mechanism. Identified methods to mitigate errors included 1) use of a checklist post conversion, 2) use of robust radiation detectors, 3) automation of QA and beam consistency checks, and 4) implementation of surface guidance during beam delivery. Conclusions: The FMEA process was considered critically important in this setting of a new use of a LINAC, and the expert team developed a higher level of confidence in the ability to safely move UHDR LINAC use towards expanded research access., Comment: 26 Pages, 6 Figures, 4 Tables

Ultra-high dose rate electron sources require dose rate independent dosimeters and a calibrated dose control system for accurate delivery. In this study, we developed a single-pulse dose monitoring and a real-time dose-based control system for a converted clinical linear accelerator (LINAC). A point scintillator detector was coupled to a gated amplifier and a real-time controller for dose monitoring and feedback control loop. The controller was programmed to integrate dose and measure pulse width of each radiation pulse and gate the LINAC beam when the prescribed dose was delivered. The scintillator was mounted in solid water phantom and placed underneath mice skin for in vivo dose monitoring. Additionally, the scintillator was characterized in terms of its radiation stability, mean dose-rate, and dose per pulse dependence. Dose integration was performed for each radiation pulse and displayed in real-time. The scintillator was shown to be linear with mean dose-rate (40-380 Gy/s) and dose per pulse (0.3-1.3 Gy/Pulse) to within +/- 3%. However, the plastic scintillator was subject to significant radiation damage (16%/kGy) and would need to be calibrated frequently. Pulse-counting control was accurately implemented with direct correspondence between the intended and the actual delivered pulses. The dose-based control was sufficient to gate on any pulse of the LINAC. In-vivo dosimetry monitoring with a 1 cm circular cut-out revealed that a ramp-up of 4-5 pulses was present during which the average dose per pulse was ~0.045 +/- 0.004 Gy/Pulse, whereas after the ramp-up it stabilized at 0.65 +/- 0.01 Gy/Pulse. The tools presented in this study can be used to determine the beam parameter space pertinent to the FLASH effect. Additionally, this study is the first instance of real-time dose-based control for a modified LINAC at ultra-high dose rates., Comment: 30 Pages, 7 Figures

Purpose: Cherenkov imaging is now clinically available to track the course of radiation therapy as a treatment verification tool. The aim of this work was to discover the benefits of always-on Cherenkov images as a novel incident detection and quality improvement system through retrospective review of imaging in our center. Methods: Continuous imaging of all patients was attempted during a 12-month period by automating the acquisition of Cherenkov imaging using an always-on commercial system. Multi-camera systems were installed in two treatment bunkers in the radiation oncology clinic at our center and one bunker in an affiliated satellite clinic. Images were acquired as part of normal treatment procedure and reviewed retrospectively with potential incidents flagged for evaluation by the physician and medical physics teams. Results: In total, 622 patients were imaged as part of this study. In this summary, 9 patients were identified with incidents occurring during their course of treatment that were detected only with Cherenkov imaging. Incidents were found relating to issues during simulation, planning, pre-treatment review, and treatment delivery, however none of the incidents were detected prior to treatment delivery. Primary areas of improvement identified in this study are dose to unintended areas in planning, dose to unintended areas due to positioning, and non-ideal bolus placement during setup. Case studies are presented highlighting the detection of these issues using Cherenkov imaging. Conclusions: All detected events were deemed below the threshold for reporting, but their observation could lead to quality improvement in practice. Perhaps most importantly, the imaging was seamless with no effort required by the radiotherapy team and provided both real-time and permanent records of what was delivered in each fraction., Comment: 22 pages, 1 table, 12 figures

Purpose: A Monte Carlo (MC) beam model and its implementation in a clinical treatment planning system (TPS, Varian Eclipse) are presented for a modified ultra-high dose-rate electron FLASH radiotherapy (eFLASH-RT) LINAC. Methods: The gantry head without scattering foils or targets, representative of the LINAC modifications, was modelled in Geant4. The energy spectrum ({\sigma}E) and beam source emittance cone angle ({\theta}cone) were varied to match the calculated and Gafchromic film measured central-axis percent depth dose (PDD) and lateral profiles. Its Eclipse configuration was validated with measured profiles of the open field and nominal fields for clinical applicators. eFLASH-RT plans were MC forward calculated in Geant4 for a mouse brain treatment and compared to a conventional (Conv-RT) plan in Eclipse for a human patient with metastatic renal cell carcinoma. Results: The beam model and its Eclipse configuration agreed best with measurements at {\sigma}E=0.5 MeV and {\theta}cone=3.9+/-0.2 degrees to clinically acceptable accuracy (the absolute average error was within 1.5% for in-water lateral, 3% for in-air lateral, and 2% for PDD). The forward dose calculation showed dose was delivered to the entire mouse brain with adequate conformality. The human patient case demonstrated the planning capability with routine accessories in relatively complex geometry to achieve an acceptable plan (90% of the tumor volume receiving 95% and 90% of the prescribed dose for eFLASH and Conv-RT, respectively). Conclusion: To the best of our knowledge, this is the first functional beam model commissioned in a clinical TPS for eFLASH-RT, enabling planning and evaluation with minimal deviation from Conv-RT workflow. It facilitates the clinical translation as eFLASH-RT and Conv-RT plan quality were comparable for a human patient. The methods can be expanded to model other eFLASH irradiators., Comment: 14 Pages, 6 Figures, 1 Supplementary Material

Purpose: In this study, procedures were developed to achieve efficient reversible conversion of a clinical linear accelerator (LINAC) and deliver electron FLASH (eFLASH) or conventional beams to the treatment room isocenter. Material & Methods: The LINAC was converted to deliver eFLASH beam within 20 minutes by retracting the x-ray target from the beam's path, positioning the carousel on an empty port, and selecting 10 MV photon beam energy in the treatment console. Dose per pulse and average dose rate were measured in a solid water phantom at different depths with Gafchromic film and OSLD. A pulse controller counted the pulses via scattered radiation signal and gated the delivery for preset pulse count. A fast photomultiplier tube-based Cherenkov detector measured per pulse beam output at 2 ns sampling rate. After conversion back to clinical mode, conventional beam output, flatness, symmetry, field size and energy were measured for all clinically commissioned energies. Results: Dose per pulse of 0.86 +/- 0.01 Gy (310 +/- 7 Gy/s average dose rate) were achieved at isocenter. The dose from simultaneous irradiation of film and OSLD were within 1%. The PMT showed the LINAC required about 5 pulses before the output stabilized and its long-term stability was within 3% for measurements performed at 3 minutes intervals. The dose, flatness, symmetry, and photon energy were unchanged from baseline and within tolerance (1%, 3%, 2%, and 0.1% respectively) after reverting to conventional beams. Conclusion: 10 MeV FLASH beams were achieved at the isocenter of the treatment room. The beam output was reproducible but requires further investigation of the ramp up time in the first 5 pulses, equivalent to <100 cGy. The eFLASH beam can irradiate both small and large subjects in minimally modified clinical settings and dose rates can be further increased by reducing the source to surface distance., Comment: Manuscript: 21 Pages, 1 Table, 8 Figures; Supplementary Material A: 2 Pages, 2 Figures; Appendix: Film Dosimetry: 2 Pages, 2 Tables

While spatial dose conformity delivered to a target volume has been pushed to its practical limits with advanced treatment planning and delivery, investigations in novel temporal dose delivery are unfolding new mechanisms. Recent advances in ultra-high dose radiotherapy, abbreviated as FLASH, indicate the potential for reduction in healthy tissue damage while preserving tumor control. FLASH therapy relies on very high dose rate of > 40Gy/sec with sub-second temporal beam modulation, taking a seemingly opposite direction from the conventional paradigm of fractionated therapy. FLASH brings unique challenges to dosimetry, beam control, and verification, as well as complexity of radiobiological effective dose through altered tissue response. In this review, we compare the dosimetric methods capable of operating under high dose rate environments. Due to excellent dose-rate independence, superior spatial (~<1 mm) and temporal (~ns) resolution achievable with Cherenkov and scintillation-based detectors, we show that luminescent detectors have a key role to play in the development of FLASH-RT, as the field rapidly progresses towards clinical adaptation. Additionally, we show that the unique ability of certain luminescence-based methods to provide tumor oxygenation maps in real-time with submillimeter resolution can elucidate the radiobiological mechanisms behind the FLASH effect. In particular, such techniques will be crucial for understanding the role of oxygen in mediating the FLASH effect., Comment: Number of Pages: 26, Figures: 14, Table: 1 Updated Reference List and Table 1 was referred to as Table 2 in the original text. Submitted to Frontiers in Medical Physics and Imaging (Research Topic: Applications of Cherenkov and Radioluminescence Imaging to Medicine and Biology)

Purpose: This work advances a Monte Carlo (MC) method to combine ionizing radiation physics with optical physics, in a manner which was implicitly designed for deployment with the most widely accessible parallelization and portability possible. Methods: The current work updates a previously developed optical propagation plugin for GEANT4 architecture for medically oriented simulations (GAMOS). Both virtual-machine (VM) and container based instances were validated using previously published scripts, and improvements in execution time using parallel simulations are demonstrated. A method to programmatically deploy multiple containers to achieve parallel execution using an on-demand cloud-based infrastructure is presented. Results: A container-based GAMOS deployment is demonstrated using a multi-layer tissue model and both optical and X-ray source inputs. As an example, the model was split into 154 simulations which were run simultaneously on 64 separate containers across 4 servers. Conclusions: The container-based model provides the ability to execute parallel simulations of applications which are not inherently thread-safe or GPU-optimized. In the current demonstration, this reduced the time by at most 97% compared to sequential execution. The code and examples are available through an interactive online interface through links at: https://sites.dartmouth.edu/optmed/research-projects/monte-carlo-software/, Comment: 13 pages; 3 figures; Keywords: Monte Carlo, cloud computing, high-performance computing, medical physics, Cherenkov, luminescence, tissue optics

The following work presents how autoencoding all the possible hidden activations of a network for a given problem can provide insight about its structure, behavior, and vulnerabilities. The method, termed self-introspection, can show that a trained model showcases similar activation patterns (albeit randomly distributed due to initialization) when shown data belonging to the same category, and classification errors occur in fringe areas where the activations are not as clearly defined, suggesting some form of random, slowly varying, implicit encoding occurring within deep networks, that can be observed with this representation. Additionally, obtaining a low-dimensional representation of all the activations allows for (1) real-time model evaluation in the context of a multiclass classification problem, (2) the rearrangement of all hidden layers by their relevance in obtaining a specific output, and (3) the obtainment of a framework where studying possible counter-measures to noise and adversarial attacks is possible. Self-introspection can show how damaged input data can modify the hidden activations, producing an erroneous response. A few illustrative are implemented for feedforward and convolutional models and the MNIST and CIFAR-10 datasets, showcasing its capabilities as a model evaluation framework., Comment: 16 pages, 7 figures