Beltran, Chris

Abstract Background Toxicities to organs at risk adjacent to the target volume represent a critical limitation to dose escalation in radiotherapy. While external beam therapy with accelerated ions allows for a reduced dose to surrounding healthy organs, its biological effectiveness can be markedly higher than that of conventional x‐rays and should be considered during treatment planning. Current biophysical models possess limitations in computing in vivo normal tissue complication probability (NTCP) curves for clinically relevant ion beams. Purpose This study introduces and validates a novel computational framework capable of predicting NTCP curves for serial organs following ion exposures. Methods The proposed framework integrates the linear‐quadratic model, the critical volume NTCP model, a novel two‐stage fitting process of fractionated photon NTCP data, histological data, and the Mayo Clinic Florida Microdosimetric Kinetic Model (MCF MKM) of relative biological effectiveness. The model was applied to predict the NTCP for the spinal cord myelopathy of rats exposed at different depths along the spread‐out Bragg peaks (SOBPs) of protons, helium, carbon, and oxygen ions. Radiation transport simulations were conducted to assess the microdosimetric pattern of energy deposition at the subcellular scale. Results The two‐stage photon fitting process yielded a α photons /β photons ratio of 2.3 ± 0.6 Gy and NTCP model parameters for calculations considering either endothelial or glial cells as the primary targets for the spinal cord myelopathy. Without using any ion data for calibration, the predicted NTCP showed an overall good agreement with the corresponding animal data. The model successfully reproduced the experimentally observed trends in the NTCP dependence with respect to fractionation, ion type, and exposure position along the SOBPs. Conclusions The model's ability to predict the NTCP curves for ion exposures, based solely on photon in vivo data, provides mechanistic insights and can guide preclinical investigations into the biological effects of different ions and fractionation schemes.

Abstract Background Fluoroscopic‐gated proton therapy (FGPT) enables precise dose delivery to tumors affected by respiratory motion by tracking internal fiducial markers and delivering the proton beam when the marker is within a gating window. However, scatter radiation from fluoroscopic x‐rays may be detected by the dose monitor (DM) and mistakenly counted as proton monitor units (MU). To mitigate this issue, proton beam delivery is typically interrupted during the fluoroscopy pulse, a method known as interrupted continuous delivery (ICD). If the contamination from scattered fluoroscopic x‐rays is sufficiently low compared to the proton beam current, uninterrupted continuous delivery (UCD), in which fluoroscopic x‐rays are delivered concurrently with proton beams, may be feasible. UCD can enhance beam stability and improve treatment efficiency in particular for synchrotron‐based proton therapy systems using continuous beams. Purpose This study aimed to measure the contamination of scattered fluoroscopic x‐rays in DM and to evaluate the dose distribution when fluoroscopic x‐rays and proton beams are delivered simultaneously in FGPT. Methods x‐ray contamination was measured using a proton therapy system equipped with the FGPT system. Fluoroscopic x‐rays were delivered for 30 s under both in‐air and solid phantom conditions, with thicknesses of 10 and 30 cm, and DM counts were recorded. The dose rate was evaluated under various fluoroscopic conditions, both with and without the range shifter and mini ridge filter. To assess the dosimetric impact, six virtual treatment plans were created using anthropomorphic phantoms for cases involving the prostate, lung (both superficial and deep), liver (both superficial and deep), and pancreas. Scatter fluoroscopic x‐ray contamination was measured at the beam angles specified in the treatment plans under clinical setup conditions. Dose distributions were recalculated assuming simultaneous delivery with proton beam currents of 0.1, 1, 2, 4, 8, and 40 MU/s, and these were compared to the treatment plans. Results The scattered fluoroscopic x‐ray contamination in the DM increased with higher tube voltage, tube current, frame rate, and field size. The maximum dose rate was 0.247 MU/s with 125 kV tube voltage, 80 mA tube current, 30 s −1 frame rate, 19 × 19 cm 2 field size, and solid phantom of 10 cm. The dose rate of scattered fluoroscopic x‐rays peaked at a solid phantom thickness of approximately 5 cm. In an anthropomorphic phantom, scattered fluoroscopic x‐ray contamination varies based on anatomical site and beam angle. Dose evaluations indicated that if the proton beam current was ≥2 MU/s at the target and ≥1 MU/s at organs at risk, the differences in dose metrics were within 1% compared to the treatment plans. These beam currents are achievable with clinical systems. Conclusions Scattered fluoroscopic x‐rays were confirmed to contaminate the DM and be counted as proton MUs. However, under clinically realistic beam current conditions, their impact on dose distribution in UCD FGPT was negligible. These findings support the feasibility of implementing UCD FGPT.

Abstract Purpose This study investigates a novel optimization framework that integrates the newly developed MCF MKM relative biological effectiveness (RBE) model into intensity modulated particle therapy (IMPT) planning for carbon ion therapy. Unlike conventional RBE models such as MKM or LEM, the MCF MKM provides detailed microdosimetric information, which improves predictive accuracy of cell survival but elevates both memory and time requirement in the optimization process. Furthermore, to the implicit nature of the MCF MKM, the gradient information, which is essential in inverse planning, is hardly accessible. In response, a randomized gradient‐free optimization method (RGFM) was developed to mitigate the computational challenge and achieve improved RBE dose distributions. Materials and Methods An RBE dose optimization problem was formulated based on the discretized MCF MKM, known as the Abridged Microdosimetry Distribution Model (AMDM). The RGFM was derived to find feasible and high‐quality settings of monitor unit for IMPT plans without the need for explicit gradient calculations. To verify the clinical plausibility of the proposed method, it was tested on two clinical scenarios—prostate and brain cases in comparison with benchmark plans derived solely from physical dose optimization. Computational times and dose‐volume histograms (DVHs) for both physical and RBE doses were evaluated. Results The RGFM algorithm successfully optimized the MCF MKM‐based IMPT plans. Compared to the benchmark, the RBE dose distributions showed improved coverage of the target and reduced hot spots. Such improvements were observed to coincide with trade‐offs in physical dose distributions. The complexity of the MCF MKM extended the computational time, yet high‐quality solutions were attainable in a clinically reasonable timeframe. Multi‐field optimization (MFO) further enhanced target coverage and critical organ sparing over single‐field optimization (SFO). Conclusions This proof‐of‐principle study confirmed the feasibility of using a randomized gradient‐free method to optimize RBE dose based on the MCF MKM in IMPT planning for carbon ion therapy. The approach provides a pathway for clinical adoption of advanced RBE models, potentially leading to more biologically informed and effective carbon ion therapy treatments. Future work involves refining algorithms, incorporating parallel computing, and performing additional case studies to improve computational efficiency and generalizability.

Abstract Background Heavy ion radiotherapy offers distinct advantages over conventional treatments due to its superior dose distribution and enhanced biological effectiveness. However, the microdosimetric characteristics of high linear energy transfer (LET) ions, particularly near the Bragg peak, remain poorly characterized. Most experimental microdosimetry has been conducted at lower LETs, leaving a critical gap in high‐LET microdosimetric data. Purpose This study aims to extend microdosimetry to several different high‐LET ions (700–2500 keV/µm) using the novel ENCORE detector. Methods Microdosimetry was performed at the Florida State University John D. Fox Accelerator Laboratory using the ENCORE detector, a multi‐sampling ionization chamber filled with low‐pressure tissue‐equivalent gas capable of resolving energy deposition from approximately 200 keV to 3 MeV. 12 C, 16 O, and 28 Si beams were accelerated to 17–55 MeV and delivered to the segmented detector. Energy deposition patterns near the Bragg peak were recorded, and microdosimetric spectra were reconstructed. Monte Carlo was used to model the experimental setup. From each measured and simulated spectra, dose‐mean lineal energy () was calculated and compared. Results The 16 strips of the ENCORE corresponded to a tissue‐equivalent thickness of 17.6 µm, enabling resolution of energy deposition immediately proximal and distal to the Bragg peak. In six measurement configurations, the ion beam stopped within this range, allowing precise mapping of the profile around the peak; in the remaining configurations, the beam fully traversed the detector. Across all beams, difference between measured and simulated averaged 12%, based on one measurement per strip. Peak measured reached 920 ± 220, 1240 ± 206, and 2460 ± 620 keV/µm for 12 C, 16 O, and 28 Si beams, respectively. Conclusion This study demonstrated that ENCORE can resolve microdosimetric spectra with high spatial and LET resolution across a range of ion energies. Measured values reasonably agreed with Monte Carlo simulations, validating the potential of ENCORE for position‐resolved microdosimetry and model benchmarking in particle therapy.

Abstract Background Dose‐driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness. Purpose This study introduces a Break Spot‐Guided (BSG) method, combined with two acceleration strategies—dose rate skipping and bounding—to optimize beam intensity while minimizing beam delivery time (BDT). In addition, a ‐method is proposed for efficient move spot generation, aiming to balance computational efficiency and dose calculation accuracy. Methods The BSG framework simplifies the original mixed‐integer nonlinear programming (MINLP) problem by transforming it into a series of TSP evaluations using break‐spot dose rates. The two acceleration strategies are integrated to reduce computational complexity. The ‐method is introduced to efficiently generate move spots without compromising dose fidelity. The performance of the BSG method, with and without the acceleration strategies, and the ‐method, was evaluated across multiple clinical cases. Results By jointly optimizing the scan path and dose rate, the proposed BSG‐S‐B method offered the most efficient delivery, achieving a 64% reduction in BDT compared to DSS and a 57% reduction compared to Liu's method in the prostate case. These gains were consistently observed across all cases. Utilizing acceleration strategies, BSG‐S‐B significantly reduced computation time from hours to minutes (e.g., from 10 525.7 to 108.5 s in the prostate case, and from 6202.4 to 129.8 s in the head‐and‐neck case). When combined with the ‐method, it reduced the number of move spots by more than 50%, while still ensuring dosimetric quality. Conclusions The proposed framework significantly improves computational efficiency, making scan path optimization with dose rate selection feasible for clinical DDCS delivery. The ‐method effectively reduces computational complexity while maintaining dose calculation accuracy, demonstrating strong potential for clinical adoption in proton therapy treatment planning.

AbstractIntroductionThis study evaluates the feasibility of utilizing a commercial‐grade 3D LiDAR/RGB camera, combined with 3D reconstruction software, to create an accurate and hyper‐realistic digital model of a proton therapy treatment room. This reconstructed model aims to enhance collision avoidance strategies and improve 3D machine model accessibility. Utilization of a 3D LiDAR/RGB camera as a radiotherapy environment modeling has not been reported prior.MethodsTo create a comprehensive 3D model of a half‐gantry proton therapy system, colored point cloud data was captured using the Matterport Pro 3 camera, a hybrid LiDAR and RGB imaging system with high‐resolution capabilities (134.2 MP), a 360° horizontal field of view, and 20 mm accuracy at 10 m. A total of 117 acquisition points, distributed across the treatment room with three camera heights, ensured complete coverage and minimal occlusions. Scanning, completed in under 3 hours, was monitored in real time using the Matterport App. Post‐scan processing involved denoising and converting the point cloud into 3D mesh structures using MeshLab, followed by refined pair‐wise iterative closest point (ICP) alignments. Textures and materials were assigned to reflect real‐world objects, and a ray‐tracing engine simulated realistic lighting in Blender. Animations illustrating the kinematics of the treatment couch and gantry were simulated in Blender for enhanced visualization.ResultsThe scanning process achieved complete data capture without missing information, attributed to strategic oversampling during data acquisition. The mean root mean square error (RMSE) of the ICP registration was 0.008 m. The validation process confirmed that the dimensions of the treatment couch within the digital model closely matched the actual measurements with less than 2 cm deviation, indicating high accuracy. The resulting digital twin provided a photorealistic and immersive representation of the proton therapy treatment room, serving as a valuable digital asset for various applications.ConclusionIt is possible to generate vendor‐independent and highly accurate 3D models of the proton treatment room environment with a commercial grade LiDAR/RGB camera to expand future research opportunities and education endeavors.

Abstract Background Dose‐driven continuous scanning (DDCS) is a type of beam delivery in Hitachi pencil beam scanning (PBS) particle therapy system. Particle beam is irradiated continuously between spots to achieve a higher effective dose rate and a shorter beam delivery time. The beam is only turned off at break spots, the end of a treatment layer and during spill change. The break spot is a unique feature of the DDCS introduced by the treatment planning system (TPS) to interrupt continuous scanning. DDCS separates the dose delivery of a spot into a move dose and stop dose components. The move dose is controlled by the scanning speed and beam current, while the stop dose delivers the remaining monitor units (MUs). Hence, rigorous quality assurance (QA) of the scanning speed and functionality of break spot are required to ensure safe and successful DDCS delivery. Purpose We aim to report for the first time the QA methodology and result for DDCS, focusing on the scanning speed and break spot validation. Methods A rectangular spiral irradiation pattern with different degree of break spots were irradiated on a 2D strip ionization chamber (CROSSmini) detector using 50 time resolution to validate the break spots. Four methods of measuring scanning speeds were proposed. Using a spiral irradiation pattern, methods one and two applied linear regression to the scanning time measured by the CROSSmini for different inter‐spot distances, with measurements taken at sampling rates of 5 and 20 kHz, respectively. Methods three and four measured the scanning time of single inter‐spot distances in the X and Y directions. Method three measured the scanning time with the CROSSmini while method four measured the rise and fall time of the scanning magnet (SCM) current. All measurements were performed with 70.2, 150.2 and 228.7 MeV proton beam energies and three different beam currents of 8, 14 and 20 MU/s. Lastly, the scanning speed tolerance limit was calculated analytically under the requirement of avoiding a beam abort when the stop dose was less than zero. Results The data recorded by the CROSSmini under the spiral irradiation patterns with break spots was reconstructed into a 2D dose, and the break spots’ operations were visually validated for all the energies and beam currents. There were no statistically significant difference in the measured X and Y scanning speeds across the four methods. However, the last method involving the SCM current yielded the largest type A uncertainty of up to 25% () due to the noisy signal. The first method with the linear regression and 5 kHz acquisition rate was preferred due to a smaller type A uncertainty of up to 2.0% and a lower false negative rate in detecting the rising and falling edges during scanning. The calculated tolerance limit based on our current DDCS setting was found to be 0.50 times of the expected scanning speed. Conclusion We have introduced QA protocols for DDCS, designed to ensure complete and safe beam delivery without interruptions caused by move doses exceeding planned spot doses.

Abstract Background Cone‐beam computed tomography (CBCT) is essential for image‐guided particle therapy (IGPT), providing daily patient positioning, anatomical monitoring, and treatment verification. However, conventional single‐detector CBCT suffers from poor soft‐tissue contrast, long acquisition times, and motion artifacts, reducing its effectiveness for adaptive radiotherapy workflows. Addressing these challenges requires an advanced CBCT reconstruction approach capable of enhancing image quality while reducing scan time and radiation exposure. Purpose This study introduces a Dual Detector Combined Scanning (DDCS) CBCT reconstruction algorithm to overcome conventional CBCT limitations. By integrating a dual‐source, orthogonal imaging setup, DDCS significantly reduces scanning time and imaging artifacts. A modified Parker‐weighting algorithm further improves image reconstruction accuracy, ensuring high‐fidelity visualization. The goal is to enhance adaptive radiotherapy by improving real‐time patient positioning, dose verification, and motion management. Methods A dual‐detector CBCT system was designed to acquire orthogonal projections simultaneously, reducing scan time and improving data completeness. A modified Parker‐weighting algorithm corrected angular overlap distortions, ensuring better reconstruction accuracy. The system was evaluated using numerical and physical phantom studies to assess spatial resolution, contrast‐to‐noise ratio (CNR), and artifact reduction. Additionally, a dynamic phantom simulated respiratory motion, validating motion robustness for adaptive radiotherapy. Performance was compared against single‐detector CBCT, focusing on image fidelity, noise suppression, and computational efficiency. Results DDCS‐CBCT demonstrated higher CNR, reduced motion artifacts, and improved spatial resolution, leading to more accurate anatomical visualization. The system's efficiency enables faster, more reliable patient setup in IGPT while maintaining a lower imaging dose. Conclusion The proposed DDCS‐CBCT approach significantly improves imaging accuracy, reduces scan time, and enhances real‐time volumetric guidance in IGRT/IGPT. These findings support the clinical feasibility of the DDCS system and its integration into online adaptive radiotherapy workflows.

Abstract Background Proton therapy offers precise tumor targeting while minimizing damage to surrounding healthy tissue, making it especially valuable for treating tumors near critical organs and in pediatric patients. However, its success depends on accurate beam delivery, requiring rigorous quality assurance (QA) to maintain treatment precision and effectiveness. Purpose This study aims to standardize the measurement of key aspects of proton therapy delivery, such as gantry and couch isocentricity, spot position accuracy, and spot size consistency. The goal is to enhance the delivery accuracy of proton therapy across various clinical settings, improving patient outcomes. Methods The QA framework uses the Octopoint phantom, Gafchromic film, and spot position monitor (SPM) log data to evaluate proton beam isocentricity, spot position, and spot size. The Octopoint phantom, made from acrylic, was used with Gafchromic films at various gantry and couch angles to measure isocentricity. MATLAB tools were used to analyze spot positions, and SPM logs provided verification. Sensitivity tests were conducted to assess the system's response to intentional shifts and errors, ensuring alignment with clinical QA standards. Results The Octopoint phantom's stepwise two‐dimensional (2D) fitting process, validated against film‐measured dose profiles, accurately identified beam and ball bearing (BB) centroid locations. Isocentricity tests conducted over 8 months across four gantries demonstrated consistent beam‐to‐BB radial offsets. The phantom showed excellent repeatability, with a maximum standard deviation of 0.1 mm across various couch‐gantry combinations. Sensitivity testing across all axes revealed a strong alignment between intended shifts and measured values. Over the course of a year, film measurements tracked spot position and size consistency, with deviations remaining within acceptable clinical limits. Comparisons with SPM data further confirmed the system's reliability in maintaining beam accuracy across different gantry angles and energy levels. Conclusions This study presents a reliable QA framework for ensuring precision in proton therapy delivery. By combining the Octopoint phantom, Gafchromic film analysis, and SPM log file evaluation, we effectively measured isocentricity, spot position accuracy, and spot size stability. The framework demonstrated adaptability across various clinical QA tasks, enhancing the accuracy and safety of proton therapy treatments.