Citations

Abstract The anticipated clinical demand for carbon ion radiotherapy (CIRT) in the United States is expected to include a substantial proportion of clinically complex disease sites that require accurate, highly conformal, and adaptive treatment. These clinical needs, together with the unique physical and biological characteristics of carbon ion beams, form the foundation of the design philosophy for the Mayo Clinic Florida (MCF) CIRT program. The program remains under active development, with clinical deployment planned for 2028. Building upon the clinical rationale and anticipated U.S. patient population discussed in Part I of this two‐part review, this Vision Article describes how MCF intends to develop an integrated CIRT treatment system. The program is guided by two overarching principles: fast, accurate, and safe beam delivery and accurate treatment planning and treatment delivery, supported by an integrated patient‐specific quality assurance framework. Key elements include high‐dose‐rate dose‐driven continuous scanning with advanced beam monitoring and irradiation control, delivery‐aware treatment planning, the Monte Carlo‐based BioPhys computational platform integrating physical and biological dose modeling, a hierarchical adaptive workflow, and patient‐specific quality assurance spanning pretreatment, on‐treatment, and post‐treatment verification. This framework provides a technical roadmap for the integrated clinical implementation of CIRT at MCF.

Abstract Purpose Modeling relative biological effectiveness (RBE) is central to carbon ion radiotherapy treatment planning. The modified Microdosimetric Kinetic Model (mMKM) is a clinically established RBE framework that has guided treatment protocols at many existing carbon centers, while the Mayo Clinic Florida Microdosimetric Kinetic Model (MCF MKM) is a recently developed alternative. This work aims to implement the MCF MKM in the open‐source treatment planning system matRad and to quantitatively compare its RBE‐weighted dose predictions with those of the clinically established mMKM using identical physical dose distributions across multiple disease sites. These findings will help assess their dosimetric equivalence and inform protocol development for carbon ion radiotherapy at MCF. Methods Monte Carlo simulations of the MCF carbon beamline were performed to generate physical (IDD, LET, lateral spread) and biological base data for integration of each RBE model into matRad . Treatment plans were generated for six patients, each corresponding to a different disease site, using clinical beam configurations with carbon‐reference dose prescriptions, and plans were optimized using the MCF MKM. To isolate differences attributable solely to the RBE model, the resulting physical dose distributions were held fixed and RBE‐weighted doses were recalculated using the mMKM. Dose volume histogram (DVH) metrics and spatial dose‐difference maps were used to compare target coverage and organ‐at‐risk doses between the two models. Results Across patient cases, RBE‐weighted dose distributions from MCF MKM and mMKM showed strong agreement. Differences in target coverage were small, with CTV D95% differing by less than 1.6% across all disease sites and maximum target dose differences not exceeding 0.88%. Organ‐at‐risk dose deviations were limited, with differences of 3.0% or less across evaluated DVH metrics. Spatial dose‐difference maps showed that the largest discrepancies occurred in regions of steep dose gradients near target to organ‐at‐risk interfaces, while overall dose conformity and plan quality remained comparable between the two models. Conclusions: This study served as the first systematic model comparison of the MCF MKM and mMKM within a treatment planning environment. These findings suggest that the MCF MKM and mMKM produce dosimetrically consistent RBE‐weighted dose predictions under realistic planning conditions using carbon‐reference parameters. Accordingly, the fractionation schemes developed from years of clinical experience with mMKM implementations may serve as a practical foundation for protocol development at MCF.

Introduction Proton dose driven continuous scanning (DDCS) is a form of proton pencil beam scanning (PBS) in which the beam may remain on during transitions between successive spots. Mayo Clinic Florida (MCF) is preparing to commission a synchrotron-based proton therapy system designed for DDCS, incorporating novel irradiation control features. Given the novelty and complexity of this system, a systematic risk-based analysis was performed to inform upcoming commissioning strategies. Methods A prospective risk analysis was conducted using the American Association of Physicists in Medicine (AAPM) Task Group 100 (TG 100) framework. A comprehensive process map of the DDCS irradiation control workflow was developed. Failure modes and effects analysis (FMEA) was performed to identify potential delivery system failure modes and to score each failure mode based on occurrence, severity, and lack of detectability. Targeted mitigation and commissioning strategies were then developed to address the highest-risk items. Results Twenty-nine delivery system failure modes were identified. The highest-risk failure modes were specific to DDCS operation. Targeted commissioning strategies were defined, including scan path measurement and modeling, validation of move and flap dose, dose monitor collection efficiency testing, spot position monitor performance evaluation, and verification of control system intervention behavior. Incorporation of these strategies into the commissioning plan reduced the mean RPN by more than 50%. Discussion This work provides a detailed description of the MCF proton DDCS irradiation control system and uses a TG 100 based approach for identifying system-specific risks. As new systems incorporate technologies for which limited guidance exists, institutions must perform their own risk analyses to determine appropriate quality management strategies.

Abstract Introduction: CD20xCD3 bispecific antibodies (BsAb) have been approved for use in relapsed/refractory (RR) large B-Cell lymphomas (LBCLs) with manageable toxicities. The main adverse events of clinical interest are cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). The risk factors for CRS and ICANS are not well understood. Knowledge of variables that contribute to increased risk may help clinicians identify and tailor management for high-risk patients (pts) and increase the comfort level for providers using these therapies in community practices. Methods: We performed a multicenter retrospective study at 21 US centers evaluating pts with RR LBCLs receiving commercially available epcoritamab (epco) or glofitamab (glofit) between 2023 and 2025. We obtained baseline characteristics, safety and efficacy outcomes. Univariate analysis was performed to identify associations between CRS, ICANS, and clinical variables of interest. Results: As of May 31, 2025, a total of 312 pts with RR LBCLs were treated with BsAb, Epco n=193 (62%), Glofit n= 119 (38%); median age 68; 63% male; 70% ECOG PS 0-1. Most common histologic type was diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS) (n=239, 84%) followed by high-grade B-cell lymphoma (HGBL) (n=46, 16%). 179 pts (57%) were previously treated with chimeric antigen receptor T-cell (CAR-T) therapy, with 47% receiving CAR-T <6 months (mo) prior to BsAb. Among pts with prior CAR-T, CRS with CAR-T therapy of any grade occurred in 63%, with 26% ≥ grade 2. ICANS of any grade (G) occurred in 25% of pts (9.4% ≥ G3). Overall and complete response (ORR and CR) rates to BsAb were 51% and 29%, respectively. With a median follow up of 5 mo, median progression-free and overall survival (PFS and OS) were 2.3 and 7.3 mo, respectively. With BsAb treatment, CRS of any grade occurred in 117 (39%) patients: 24% G1, 8.7% G2, 4% G3, 1% G4 and 1% G5. The max grade CRS occurred most frequently after the third dose of epco (35%) and the first dose of glofit (23%). CRS was managed with additional steroids in 24% of pts and tocilizumab in 22%. 13% of pts experienced ICANS: 5.8% G1, 3.4% G2, 2% G3, 1% G4 and 0.3% G5. Factors that increased the risk for any grade CRS included: bulky disease ≥ 7.5 cm at time of BsAb treatment (OR 2.04, 95% CI 1.17 – 3.55, p = 0.012), elevated LDH (OR 2.56, 95% CI 1.45– 4.76, p = 0.002) and treatment with epco compared to glofit (OR 1.69, 95% CI 1.04- 2.77, p = 0.036). As G ≥2 CRS generally requires inpatient monitoring and management, we next compared the risk factors between pts with no CRS or G1 CRS and G ≥2 CRS. Factors associated with increased risk for high grade CRS included: bone marrow involvement by lymphoma (OR 3.47, 95% CI 0.97 – 11.3, p = 0.043), platelet count ≤ 75 (OR 2.46, 95% CI 1.21 – 4.87, p = 0.011), ≥ 2 extra nodal sites (OR 2.04, 95% CI 1.07 – 3.97, p = 0.032) and ≥G2 CRS with prior CAR-T (OR 3.35, 95% CI 1.13 – 9.97, p = 0.027). Factors that increased the risk for ICANS included: bulky disease (OR 2.67, 95% CI 1.28 – 5.49, p = 0.008), elevated Cr ≥ 1.5x ULN (OR 3.79, 95% CI 1.25 – 10.4, p = 0.012), elevated AST/ALT ≥ 3x ULN (OR 4.65, 95% CI 0.92 – 19.9, p = 0.042), low albumin (OR 2.85, 95% CI 1.49 - 5.5, p = 0.002), and co-occurrence of CRS with BsAb (OR 9.1, 95% CI 3.85- 25, p < 0.001). No other clinical variables including older age, histologic subtype, ECOG PS, B symptoms, IPI score, cell of origin or histologic subtype, baseline labs such as ALC, CRP, fibrinogen or D-dimer were significantly associated with CRS or ICANS risk. There was no difference in ORR or CR rates in patients who experienced CRS or ICANS. Conclusions: Our analysis of pts treated with commercial BsAb for LBCL shows an increased risk for CRS and ICANs based on clinical variables that are routinely obtained at baseline including tumor bulk, sites of disease, laboratory parameters, and history of prior CRS with CAR-T therapy. Differences in baseline populations receiving epco and glofit treatments in this real-world analysis have been previously reported (Brooks et al, Blood 2025) and the comparative risk for CRS between these treatments remains unclear. Future plans including multivariable analysis may allow for development of a predictive model to identify pts at high risk of CRS and ICANS with BsAb treatment, potentially leading to prospective clinical trials evaluating prophylactic interventions for high-risk pts.

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.

Abstract Background Despite advances in clinical microbiology, the diagnosis of invasive fungal infections remains challenging. Giant magnetoresistance (GMR) is a novel technology that enables the detection of trace amounts of cell-free DNA (cfDNA). We evaluated a high-multiplex molecular diagnostic assay coupled with GMR-enabled lab-on-a-chip technology that can detect 18 different fungal species. Methods Analytical performance was evaluated in spiked plasma samples. After amplification, cfDNA was digested. Residual single-stranded DNA was flowed over a GMR sensor that was surface-coated with probes specific to different fungal species. After hybridization, magnetic beads bound to the probe complexes produced a GMR signal that was detected by the sensors. Clinical performance was determined using residual serum samples collected before the initiation of antifungal treatment from 20 patients with infection. Results The limit of detection of the assay ranged from 5 to 50 copies per polymerase chain reaction (PCR) reaction. Nonspecific signals were not observed in the spiked samples. Fungal cfDNA was detected in 80% of patients with invasive candidiasis (3/4 with candidemia, 5/6 with invasive candidiasis without candidemia), all 3 cases of invasive pulmonary aspergillosis, and all 3 cases of disseminated histoplasmosis. cfDNA was not detected in 2 patients with cryptococcosis (both had negative blood cultures) and 2 patients with Pneumocystis pneumonia. Conclusions We developed a novel GMR-enabled multiplex PCR assay detecting fungal pathogens that have been prioritized for public health action. Clinical sensitivity was highest in cases of presumed angioinvasion and dissemination. This technology has the potential for use in the clinical microbiology laboratory setting.

Abstract The immune system is a key player in the onset and progression of neurodegenerative disorders. While brain resident immune cell‐mediated neuroinflammation and peripheral immune cell (eg, T cell) infiltration into the brain have been shown to significantly contribute to Alzheimer's disease (AD) pathology, the nature and extent of immune responses in the brain in the context of AD and related dementias (ADRD) remain unclear. Furthermore, the roles of the peripheral immune system in driving ADRD pathology remain incompletely elucidated. In March of 2023, the Alzheimer's Association convened the Alzheimer's Association International Conference (AAIC), Advancements: Immunity, to discuss the roles of the immune system in ADRD. A wide range of topics were discussed, such as animal models that replicate human pathology, immune‐related biomarkers and clinical trials, and lessons from other fields describing immune responses in neurodegeneration. This manuscript presents highlights from the conference and outlines avenues for future research on the roles of immunity in neurodegenerative disorders. Highlights The immune system plays a central role in the pathogenesis of Alzheimer's disease. The immune system exerts numerous effects throughout the brain on amyloid‐beta, tau, and other pathways. The 2023 AAIC, Advancements: Immunity, encouraged discussions and collaborations on understanding the role of the immune system.

Abstract Background All Hitachi proton pencil beam scanning facilities currently use discrete spot scanning (DSS). Mayo Clinic Florida (MCF) is installing a Hitachi particle therapy system with advanced technologies, including fast scan speeds, high beam intensity, rapid beam off control (RBOC), a skip spot function, and proton pencil beam scanning using dose driven continuous scanning (DDCS). A potential concern of RBOC is the generation of a shoulder at the end of the normal spot delivery due to a flap spot (FS) with a flap dose (FD), which has been investigated for carbon synchrotron but not for proton delivery. While investigated, for instance, for Hitachi's installation at MCF, this methodology could be applicable for all future high intensity proton deliveries. Purpose No Hitachi proton facility currently uses the proposed RBOC. This study aimed to understand the dosimetric impact of proton FD at MCF by simulating the FS with a Hitachi proton machine in research mode, reflecting the higher proton intensities expected with RBOC at MCF. Method Experiments were conducted to simulate MCF RBOC at Kyoto Prefecture University of Medicine (KPUM) in research mode, reducing delay time (Td) from 1.5 ms to 0.1 ms. 5,000 contiguous spots were delivered on the central axis for proton energies of 70.2, 142.5, and 220.0 MeV; at normal, high dose rate (HDR), and ultra‐high dose rate (uHDR) intensities; and at vertical and horizontal gantry angles for different Td. Measurements were taken using a fast oscilloscope and the nozzle's spot position monitor (SPM) and dose monitor (DM). A model was developed to predict FD dependence on beam intensity and assess the dosimetric impact for prostate and brain treatment plans. Two simulation types were planned: a flap DSS plan with FS at every spot and a flap DDCS plan with FS only at the end of each layer. Result FD was observed for RBOC with Td = 0.1 ms, showing no gantry angle dependence. FD increased with higher delayed dose rate (DDR), that is, beam intensity. The planning study showed dose volume histogram deterioration with increased FD compared to the clinical plan, but it was only significant for uHDR intensities. Deterioration was marginal in flap DSS plans for the HDR intensities planned at MCF, and flap DDCS plans were even less sensitive than flap DSS plans. Conclusion MCF is installing proton DDCS with higher beam intensities, a skip spot function, and fast beam‐off control. The resulting FD had an insignificant impact on dose distribution for two patient plans with both DSS and DDCS at the anticipated MCF intensities. However, significant dependence was observed in the case of uHDR. A method to measure the position and dose of the FS during commissioning is described in addition to recommendations for regular QA and log‐based proton patient‐specific quality assurance.