Furutani, Keith M

The sharp dose gradients that underpin the dosimetric advantage of particle therapy over photon therapy can be undermined by the interplay effects due to intra-fraction motion in modern pencil beam scanning systems. Fluoroscopy-Guided Particle Therapy (FGPT) offers a promising path to improved motion management through real-time tracking of tumors or surrogate signals. The advent of flat-panel detector (FPD)-based technology has enabled tighter integration of fluoroscopy/fluorography into treatment units and accelerated clinical adoption and research, with commercial systems such as Hitachi’s Real-time Gated Particle Therapy (RGPT) now available. However, the need for implanted fiducial markers, with the associated invasiveness and risk of complications, limits the utility of RGPT to a few anatomic sites in selected patients. The full potential of FGPT, therefore, depends on reliable marker-less tumor tracking, which remains challenging because soft-tissue targets are obscured by overlapping anatomy along the X-ray path, leading to reduced reliability of traditional image-registration algorithms in the projection domain. Recent advances in deep learning and AI-driven image registration have renewed hope for overcoming these barriers, enabling real-time marker-less tracking for particle therapy. This review outlines the evolution of fluoroscopy technology from image intensifier (II) to FPD-based systems, summarizes historical and recent vendor-supported FGPT strategies, and surveys emerging AI-based algorithms in the literature. A general review of machine learning-based image registration is provided, challenges in generalizability and interpretability are highlighted, and potential paths toward reliable, clinically deployable FGPT are discussed.

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.

Microdosimetry plays a critical role in particle therapy by quantifying energy deposition within microscopic domains to assess biological effects. This study evaluates the influence of different microdosimetric functions (MFs) and domain geometries (DGs) on relative biological effectiveness (RBE) predictions in carbon ion radiotherapy. Specifically, we compare the analytical microdosimetric function (AMF), calculated for spherical domains and implemented in PHITS, with the Kiefer–Chatterjee (KC) track structure model, which is conventionally applied to cylindrical geometries. To enable a direct comparison, we also introduce a novel implementation of the KC model for spherical domains. Using both models, specific energy distributions were calculated across a range of domain sizes and geometries. These distributions were input into the modified microdosimetric kinetic model (mMKM) to calculate RBE for the HSG cell line and compared against published in vitro data. The results show that both microdosimetric function and domain geometry significantly affect microdosimetric spectra and the resulting RBE, with deviations exceeding 10% when fixed mMKM parameters are used. Parameter optimization within the mMKM enables alignment across models. Our findings emphasize that microdosimetric function and domain geometry selection must be explicitly accounted for in microdosimetry-based RBE modeling, and that model parameters must be tuned accordingly to ensure consistent and biologically accurate predictions.

Ion radiotherapy requires accurate relative biological effectiveness (RBE) calculations to account for the markedly different biological effects of ions compared to photons. Microdosimetric RBE models rely on descriptions of the energy deposition at the microscopic scale, either through radial dose distributions (RDDs) or microdosimetric probability density distributions. While RDD approaches focus on the theoretical description of the energy deposition around the ion track, microdosimetric distributions offer the advantage of being experimentally measurable, which is crucial for quality assurance programs. As the results of microdosimetric RBE models depend on whether RDD or microdosimetric distributions are used, the model parameters are not interchangeable between these approaches. This study presents and validates a method to reproduce the published reference biological and clinical dose calculations at NIRS-QST for only carbon ion radiotherapy by using the modified microdosimetric kinetic model (MKM) alongside microdosimetric distributions instead of the reference RDD approach. To achieve this, Monte Carlo simulations were performed to estimate the variation of the radiation quality within and outside the field of pristine and spread-out Bragg peaks. By appropriately optimizing the modified MKM parameters for microdosimetric distributions assessed within water spheres, we successfully reproduced the results of calculations using the reference NIRS-QST RDD, generally within 2%.

Proton therapy is increasingly widespread and requires an accelerator to provide the high energy protons. Most often, the accelerators used for proton therapy are cyclotrons and the maximum initial beam energy (MIBE) is about 230 MeV or more to be able to achieve a range of approximately 30 cm in water. We ask whether such a high energy is necessary for adequate dosimetry for pathologies to be treated with proton beams. Eight patients of different clinical sites (brain, prostate, and head and neck cancers) were selected to conduct this study. We analyzed the tumor dose coverage and homogeneity, as well as healthy tissue protection for MIBE values of 120, 160, 180, 200 and 230 MeV. For each patient, a proton plan was developed using the particular MIBE and then using multifield optimization (MFO). In this way, 34 plans in total were generated to fulfill the unique clinical goals. This study found that MIBE of 120 MeV for brain tumors; 160 MeV for head and neck cancer; and remarkably, for prostate cancer, only 160 MeV for one patient case and 180 MeV for the remainder satisfied the clinical goals (words: 187 < approx. 200 words or less)

The analytical microdosimetric function (AMF) implemented in the Monte Carlo code PHITS is a unique tool that bridges the gap between macro- and microscopic scales of radiation interactions, enabling accurate microdosimetric calculations over macroscopic bodies. The original AMF was published in 2006, based on the results of track structure calculations. Recently, a newer version of the AMF was proposed, incorporating an improved description of the energy loss at the microscopic scale. This study compares the older and the newer AMFs in computing microdosimetric probability distributions, mean values, and the relative biological effectiveness (RBE). To this end, 16000 microdosimetric lineal energy probability density distributions were simulated with PHITS for ions from 1H to 238U over a broad energy range (1–1000 MeV/n). The newer AMF was found to offer superior performance, particularly for very heavy ions, producing results that align more closely with published in vitro clonogenic survival experiments. These findings suggest that the updated AMF provides a more reliable tool for microdosimetric calculations and RBE modeling, essential for ion radiation therapy and space radiation protection.

Proton therapy has emerged as a crucial tool in the treatment of head and neck and skull-base cancers, offering advantages over photon therapy in terms of decreasing integral dose and reducing acute and late toxicities, such as dysgeusia, feeding tube dependence, xerostomia, secondary malignancies, and neurocognitive dysfunction. Despite its benefits in dose distribution and biological effectiveness, the application of proton therapy is challenged by uncertainties in its relative biological effectiveness (RBE). Overcoming the challenges related to RBE is key to fully realizing proton therapy’s potential, which extends beyond its physical dosimetric properties when compared with photon-based therapies. In this paper, we discuss the clinical significance of RBE within treatment volumes and adjacent serial organs at risk in the management of head and neck and skull-base tumors. We review proton RBE uncertainties and its modeling and explore clinical outcomes. Additionally, we highlight technological advancements and innovations in plan optimization and treatment delivery, including linear energy transfer/RBE optimizations and the development of spot-scanning proton arc therapy. These advancements show promise in harnessing the full capabilities of proton therapy from an academic standpoint, further technological innovations and clinical outcome studies, however, are needed for their integration into routine clinical practice.

Abstract Objectives . (1) To examine to what extent the cell- and exposure- specific information neglected in the phenomenological proton relative biological effectiveness (RBE) models could influence the computed RBE in proton therapy. (2) To explore similarities and differences in the formalism and the results between the linear energy transfer (LET)-based phenomenological proton RBE models and the microdosimetry-based Mayo Clinic Florida microdosimetric kinetic model (MCF MKM). (3) To investigate how the relationship between the RBE and the dose-mean proton LET is affected by the proton energy spectrum and the secondary fragments. Approach . We systematically compared six selected phenomenological proton RBE models with the MCF MKM in track-segment simulations, monoenergetic proton beams in a water phantom, and two spread-out Bragg peaks. A representative comparison with in vitro data for human glioblastoma cells (U87 cell line) is also included. Main results . Marked differences were observed between the results of the phenomenological proton RBE models, as reported in previous studies. The dispersion of these models’ results was found to be comparable to the spread in the MCF MKM results obtained by varying the cell-specific parameters neglected in the phenomenological models. Furthermore, while single cell-specific correlation between RBE and the dose-mean proton LET seems reasonable above 2 keV μ m −1 , caution is necessary at lower LET values due to the relevant contribution of secondary fragments. The comparison with in vitro data demonstrates comparable agreement between the MCF MKM predictions and the results of the phenomenological models. Significance . The study highlights the importance of considering cell-specific characteristics and detailed radiation quality information for accurate RBE calculations in proton therapy. Furthermore, these results provide confidence in the use of the MCF MKM for clonogenic survival RBE calculations in proton therapy, offering a more mechanistic approach compared to phenomenological models.

Abstract Introduction . Dispersion in an accelerator quantifies the deviation of the proton trajectory when there is a momentum deviation. We present for the first time a safe method of measuring dispersion in the clinic, using a scintillator detector and the momentum deviations within a spill. This is an important accelerator quantity as we found that this is the reason behind the large dose fluctuation in our absolute dosimetry measurement. Methods . Dispersions are measured for nine energies in a Hitachi ProBeat system at three locations (isocenter and at two profile monitors) and at two gantry angles (0 and 90 degrees) by first measuring the spot position and momentum drift within a spill. The spot position drift is measured by the XRV-4000 at the isocenter, and by the two profile monitors located at 0.57 and 2.27 m from the isocenter. The momentum drift is calculated from the intra-spill range drift which is measured using the Ranger accessory. The dispersion at isocenter and its gradient are calculated using the weighted least square regression on the measured dispersions at the three locations. A constraint is formulated on the dispersion and its gradient to ensure minimal intra-spill spot position deviation around the isocenter. Results . The measured intra-spill range and spot positional drift at isocenter are less than 0.25 mm and 0.7 mm respectively. The momentum spread calculated from the range drift are less than 0.08%. The dispersion at the isocenter ranged from 0.50 to 4.30 m and the zero-crossing happens upstream of isocenter for all energies. 2 of the 9 energies (168.0 and 187.5 MeV) violated the constraint and has an intra-spill spot positional deviation greater than 1.0 within 5 cm from the isocenter. Conclusion . This measurement is recommended as part of commissioning and annual quality assurance for accelerator monitoring and to ensure intra-spill spot deviations remain low.