Furutani, Keith

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 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.

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.

AbstractBackgroundIntensity Modulated Proton Therapy (IMPT) is a sophisticated radiation treatment allowing for precise dose distributions. However, conventional spot selection strategies in IMPT face challenges, particularly with minimum monitor unit (MU) constraints, affecting planning quality and efficiency.PurposeThis study introduces an innovative Two‐Stage Mixed Integer Linear Programming (MILP) method to optimize spot intensity in IMPT with Lower Bound (LB) constraints. This method seeks to improve treatment planning efficiency and precision, overcoming limitations of existing strategies.MethodsOur approach evaluates prevalent IMPT spot selection strategies, identifying their limitations, especially concerning MU constraints. We integrated LB constraints into a MILP framework, using a novel three‐phase strategy for spot pool selection, to enhance performance over traditional heuristic methods and L1 + L∞ strategies. The method's efficacy was tested in eight study cases, using Dose‐Volume Histograms (DVHs), spot selection efficiency, and computation time analysis for benchmarking against established methods.ResultsThe proposed method showed superior performance in DVH quality, adhering to LB constraints while maintaining high‐quality treatment plans. It outperformed existing techniques in spot selection, reducing unnecessary spots and balancing precision with efficiency. Cases studies confirmed the method's effectiveness in producing clinically feasible plans with enhanced dose distributions and reduced hotspots, especially in cases with elevated LB constraints.ConclusionsOur Two‐Stage MILP strategy signifies a significant advancement in IMPT treatment planning. By incorporating LB constraints directly into the optimization process, it achieves superior plan quality and deliverability compared to current methods. This approach is particularly advantageous in clinical settings requiring minimum spot number and high MU LB constraints, offering the potential for improved patient outcomes through more precise and efficient radiation therapy plans.

Stereotactic radiosurgery (SRS) involves the delivery of a highly conformal ablative dose of radiation to both benign and malignant targets. This has traditionally been accomplished in a single fraction; however, fractionated approaches involving five or fewer treatments have been delivered for larger lesions, as well as lesions in close proximity to radiosensitive structures. The clinical utilization of SRS has overwhelmingly involved photon-based sources via dedicated radiosurgery platforms (e.g., Gamma Knife® and Cyberknife®) or specialized linear accelerators. While photon-based methods have been shown to be highly effective, advancements are sought for improved dose precision, treatment duration, and radiobiologic effect, among others, particularly in the setting of repeat irradiation. Particle-based techniques (e.g., protons and carbon ions) may improve many of these shortcomings. Specifically, the presence of a Bragg Peak with particle therapy at target depth allows for marked minimization of distal dose delivery, thus mitigating the risk of toxicity to organs at risk. Carbon ions also exhibit a higher linear energy transfer than photons and protons, allowing for greater relative biological effectiveness. While the data are limited, utilization of proton radiosurgery in the setting of brain metastases has been shown to demonstrate 1-year local control rates >90%, which are comparable to that of photon-based radiosurgery. Prospective studies are needed to further validate the safety and efficacy of this treatment modality. We aim to provide a comprehensive overview of clinical evidence in the use of particle therapy-based radiosurgery.

Abstract The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated with proton beams worldwide and the number of operating proton therapy (PT) facilities will soon reach one hundred. PT has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy. While PT has become mainstream and has established itself as a treatment option for many cancers, it is still an area of active research for various reasons: the advanced dose shaping capabilities of PT cause susceptibility to uncertainties, the high degrees of freedom in dose delivery offer room for further improvements, the limited experience and understanding of optimizing pencil beam scanning, and the biological effect difference compared to photon radiation. In addition to these challenges and opportunities currently being investigated, there is an economic aspect because PT treatments are, on average, still more expensive compared to conventional photon based treatment options. This roadmap highlights the current state and future direction in PT categorized into four different themes, ‘improving efficiency’, ‘improving planning and delivery’, ‘improving imaging’, and ‘improving patient selection’.

PurposeThis work aims to characterize a proton pencil beam scanning (PBS) and passive double scattering (DS) systems as well as to measure parameters relevant to the relative biological effectiveness (RBE) of the beam using a silicon on insulator (SOI) microdosimeter with well‐defined 3D sensitive volumes (SV). The dose equivalent downstream and laterally outside of a clinical PBS treatment field was assessed and compared to that of a DS beam.MethodsA novel silicon microdosimeter with well‐defined 3D SVs was used in this study. It was connected to low noise electronics, allowing for detection of lineal energies as low as 0.15 keV/μm. The microdosimeter was placed at various depths in a water phantom along the central axis of the proton beam, and at the distal part of the spread‐out Bragg peak (SOBP) in 0.5 mm increments. The RBE values of the pristine Bragg peak (BP) and SOBP were derived using the measured microdosimetric lineal energy spectra as inputs to the modified microdosimetric kinetic model (MKM). Geant4 simulations were performed in order to verify the calculated depth‐dose distribution from the treatment planning system (TPS) and to compare the simulated dose‐mean lineal energy to the experimental results.ResultsFor a 131 MeV PBS spot (124.6 mm R90 range in water), the measured dose‐mean lineal energy increased from 2 keV/μm at the entrance to 8 keV/μm in the BP, with a maximum value of 10 keV/μm at the distal edge. The derived RBE distribution for the PBS beam slowly increased from 0.97 ± 0.14 at the entrance to 1.04 ± 0.09 proximal to the BP, then to 1.1 ± 0.08 in the BP, and steeply rose to 1.57 ± 0.19 at the distal part of the BP. The RBE distribution for the DS SOBP beam was approximately 0.96 ± 0.16 to 1.01 ± 0.16 at shallow depths, and 1.01 ± 0.16 to 1.28 ± 0.17 within the SOBP. The RBE significantly increased from 1.29 ± 0.17 to 1.43 ± 0.18 at the distal edge of the SOBP.ConclusionsThe SOI microdosimeter with its well‐defined 3D SV has applicability in characterizing proton radiation fields and can measure relevant physical parameters to model the RBE with submillimeter spatial resolution. It has been shown that for a physical dose of 1.82 Gy at the BP, the derived RBE based on the MKM model increased from 1.14 to 1.6 in the BP and its distal part. Good agreement was observed between the experimental and simulation results, confirming the potential application of SOI microdosimeter with 3D SV for quality assurance in proton therapy.