Bone Marrow Sparing by Intensity Modulated Proton Beam Therapy in Postoperative Irradiation of Gynecologic Malignancies.

Purpose: The aim of this matched-pair cohort study was to evaluate the potential of intensity-modulated proton therapy (IMPT) for sparring of the pelvic bone marrow and thus reduction of hematotoxicity compared to intensity-modulated photon radiotherapy (IMRT) in the setting of postoperative irradiation of gynaecological malignancies. Secondary endpoint was the assessment of predictive parameters for the occurrence of sacral insufficiency fractures (SIF) when applying IMPT. Materials and Methods: Two cohorts were analyzed consisting of 25 patients each. Patients were treated with IMPT compared with IMRT and had uterine cervical (n = 8) or endometrial cancer (n = 17). Dose prescription, patient age, and diagnosis were matched. Dosimetric parameters delivered to the whole pelvic skeleton and subsites (ilium, lumbosacral, sacral, and lower pelvis) and hematological toxicity were evaluated. MRI follow-up for evaluation of SIF was only available for the IMPT group. Results: In the IMPT group, integral dose to the pelvic skeleton was significantly lower (23.4GyRBE vs 34.3Gy; p < 0.001), the average V5Gy, V10Gy, and V20Gy were reduced by 40%, 41%, and 28%, respectively, compared to the IMRT group (p < 0.001). In particular, for subsites ilium and lower pelvis, the low dose volume was significantly lower. Hematotoxicity was significantly more common in the IMRT group (80% vs 32%; p = 0009), especially hematotoxicity ≥ CTCAE II (36% vs 8%; p = 0.037). No patient in the IMPT group experienced hematotoxicity > CTCAE II. In the IMPT cohort, 32% of patients experienced SIF. Overall SIF occurred more frequently with a total dose of 50.4 GyRBE (37.5%) compared to 45 GyRBE (22%). No significant predictive dose parameters regarding SIF could be detected aside from a trend regarding V50Gy to the lumbosacral subsite. Conclusion: Low-dose exposure to the pelvic skeleton and thus hematotoxicity can be significantly reduced by using IMPT compared to a matched photon cohort. Sacral insufficiency fracture rates appear similar to reported rates for IMRT in the literature.

A review and bibliometric analysis of global research on proton radiotherapy.

Proton beam therapy (PBT) has great advantages as tumor radiotherapy and is progressively becoming a more prevalent choice for individuals undergoing radiation therapy. The objective of this review is to pinpoint collaborative efforts among countries and institutions, while also exploring the hot topics and future outlook in the field of PBT. Data from publications were downloaded from the Web of Science Core Collection. CiteSpace and Excel 2016 were used to conduct the bibliometric and knowledge map analysis. A total of 6516 publications were identified, with the total number of articles steadily increasing and the United States being the most productive country. Harvard University took the lead in contributing the highest number of publications. Paganetti Harald published the most articles and had the most cocitations. PHYS MED BIOL published the greatest number of PBT-related articles, while INT J RADIAT ONCOL received the most citations. Paganetti Harald, 2012, PHYS MED BIOL can be classified as classic literature due to its high citation rate. We believe that research on technology development, dose calculation and relative biological effectiveness were the knowledge bases in this field. Future research hotspots may include clinical trials, flash radiotherapy, and immunotherapy.

Bismuth Nanoparticles Increase Effectiveness of Proton Therapy of Ehrlich Carcinoma.

We studied the antitumor activity of the combined use of local proton irradiation in two modes (10 and 31 Gy) with preliminary intra-tumoral injection of two types of bismuth nanoparticles differing in surface coating: coated with the amphiphilic molecule Pluronic-F127 or Silane-PEG (5 kDa)-COOH polymer. Nanoparticles were used in doses of 0.75 and 1.5 mg/mouse. In two independent series on experimental tumor model (solid Ehrlich carcinoma), bismuth nanoparticles of both modifications injected directly into the tumor enhanced the antitumor effects of proton therapy. Moreover, the radiosensitizing effect of bismuth nanoparticles administered via this route increased with the increasing the doses of nanoparticles and the doses of radiation exposure. In our opinion, these promising data obtained for the first time extend the possibilities of treating malignant neoplasms.

Prospective phase II trial of preoperative hypofractionated proton therapy for extremity and truncal soft tissue sarcoma: the PRONTO study rationale and design.

BACKGROUND: Oncologic surgical resection is the standard of care for extremity and truncal soft tissue sarcoma (STS), often accompanied by the addition of pre- or postoperative radiation therapy (RT). Preoperative RT may decrease the risk of joint stiffness and fibrosis at the cost of higher rates of wound complications. Hypofractionated, preoperative RT has been shown to provide acceptable outcomes in prospective trials. Proton beam therapy (PBT) provides the means to decrease dose to surrounding organs at risk, such as the skin, bone, soft tissues, and adjacent joint(s), and has not yet been studied in patients with extremity and truncal sarcoma. METHODS: Our study titled "PROspective phase II trial of preoperative hypofractionated protoN therapy for extremity and Truncal soft tissue sarcOma (PRONTO)" is a non-randomized, prospective phase II trial evaluating the safety and efficacy of preoperative, hypofractionated PBT for patients with STS of the extremity and trunk planned for surgical resection. Adult patients with Eastern Cooperative Group Performance Status ≤ 2 with resectable extremity and truncal STS will be included, with the aim to accrue 40 patients. Treatment will consist of 30 Gy radiobiological equivalent of PBT in 5 fractions delivered every other day, followed by surgical resection 2-12 weeks later. The primary outcome is rate of major wound complications as defined according to the National Cancer Institute of Canada Sarcoma2 (NCIC-SR2) Multicenter Trial. Secondary objectives include rate of late grade ≥ 2 toxicity, local recurrence-free survival and distant metastasis-free survival at 1- and 2-years, functional outcomes, quality of life, and pathologic response. DISCUSSION: PRONTO represents the first trial evaluating the use of hypofractionated PBT for STS. We aim to prove the safety and efficacy of this approach and to compare our results to historical outcomes established by previous trials. Given the low number of proton centers and limited availability, the short course of PBT may provide the opportunity to treat patients who would otherwise be limited when treating with daily RT over several weeks. We hope that this trial will lead to increased referral patterns, offer benefits towards patient convenience and clinic workflow efficiency, and provide evidence supporting the use of PBT in this setting. TRIAL REGISTRATION: NCT05917301 (registered 23/6/2023).

Travel-Time Disparities in Access to Proton Beam Therapy for Cancer Treatment.

Importance: Proton beam therapy is an emerging radiotherapy treatment for patients with cancer that may produce similar outcomes as traditional photon-based therapy for many cancers while delivering lower amounts of toxic radiation to surrounding tissue. Geographic proximity to a proton facility is a critical component of ensuring equitable access both for indicated diagnoses and ongoing clinical trials. Objective: To characterize the distribution of proton facilities in the US, quantify drive-time access for the population, and investigate the likelihood of long commutes for certain population subgroups. Design, Setting, and Participants: This population-based cross-sectional study analyzed travel times to proton facilities in the US. Census tract variables in the contiguous US were measured between January 1, 2017, and December 31, 2021. Statistical analysis was performed from September to November 2023. Exposures: Drive time in minutes to nearest proton facility. Population totals and prevalence of specific factors measured from the American Community Survey: age; race and ethnicity; insurance, disability, and income status; vehicle availability; broadband access; and urbanicity. Main Outcomes and Measures: Poor access to proton facilities was defined as having a drive-time commute of at least 4 hours to the nearest location. Median drive time and percentage of population with poor access were calculated for the entire population and by population subgroups. Univariable and multivariable odds of poor access were also calculated for certain population subgroups. Results: Geographic access was considered for 327 536 032 residents of the contiguous US (60 594 624 [18.5%] Hispanic, 17 974 186 [5.5%] non-Hispanic Asian, 40 146 994 [12.3%] non-Hispanic Black, and 195 265 639 [59.6%] non-Hispanic White; 282 031 819 [86.1%] resided in urban counties). The median (IQR) drive time to the nearest proton facility was 96.1 (39.6-195.3) minutes; 119.8 million US residents (36.6%) lived within a 1-hour drive of the nearest proton facility, and 53.6 million (16.4%) required a commute of at least 4 hours. Persons identifying as non-Hispanic White had the longest median (IQR) commute time at 109.8 (48.0-197.6) minutes. Multivariable analysis identified rurality (odds ratio [OR], 2.45 [95% CI, 2.27-2.64]), age 65 years or older (OR, 1.09 [95% CI, 1.06-1.11]), and living below the federal poverty line (OR, 1.22 [1.20-1.25]) as factors associated with commute times of at least 4 hours. Conclusions and Relevance: This cross-sectional study of drive-time access to proton beam therapy found that disparities in access existed among certain populations in the US. These results suggest that such disparities present a barrier to an emerging technology in cancer treatment and inhibit equitable access to ongoing clinical trials.

[Protontherapy : principles, advantages, limitations, indications, perspectives...and some Belgian peculiarities]. / La protonthérapie : principes, avantages, limitations, indications, perspectives...et quelques histoires belges.

Most radiotherapy treatments are nowadays delivered with linear accelerators producing photons. This robust radiation technique improved outstandingly during the last three decades, allowing treatments for most tumoural indications with an exquisite accuracy, a formidable effectiveness, a low toxicity, and a very low cost for the society. Therefore, the reasons for using and developing the more expensive hadron therapy and more particularly proton therapy may seem futile. In the current article targeting the general practitioners readership, we look at the principles of this innovative technique, its inherent advantages and limitations, the current and future indications, the challenges and perspectives for the future. We conclude with an overview of the Belgian landscape in terms of installation, operation, access and reimbursement procedures.

L'essentiel des traitements de radiothérapie sont délivrés à l'aide d'accélérateurs linéaires produisant des photons. La technique est robuste et a connu une évolution fulgurante ces trois dernières décennies, apportant une efficacité redoutable et une extrême précision dans de nombreuses indications tumorales, avec les avantages d'un risque de toxicité réduit et d'un coût sociétal extrêmement faible. Dès lors, quel intérêt y aurait-il à utiliser et développer des traitements de radiothérapie par hadrons, et plus particulièrement par protons, sachant que les coûts d'installation et de production sont, au bas mot, décuplés par rapport aux photons ? Dans cet article destiné en première intention aux praticiens de santé généralistes, nous abordons les principes de fonctionnement, les avantages et limitations inhérents à la technique, les indications actuelles et celles qui se profilent, les défis et perspectives à venir. Nous terminons, enfin, par un tour d'horizon du paysage belge en termes d'installation, de fonctionnement, d'accès et de modalités de remboursement.

Moderately hypofractionated proton beam therapy for localized prostate cancer: 5-year outcomes of a phase II trial.

The usefulness of moderately hypofractionated radiotherapy for localized prostate cancer has been extensively reported, but there are limited studies on proton beam therapy (PBT) using similar hypofractionation schedules. The aim of this prospective phase II study is to confirm the safety of a shortened PBT course using 70 Gy relative biological effectiveness (RBE) in 28 fractions. From May 2013 to June 2015, 102 men with localized prostate cancer were enrolled. Androgen deprivation therapy was administered according to risk classification. Toxicity was assessed using Common Terminology Criteria for Adverse Events version 4.0. Of the 100 patients ultimately evaluated, 15 were classified as low risk, 43 as intermediate risk, and 42 as high risk. The median follow-up time of the surviving patients was 96 months (range: 60-119 months). The 5-year cumulative incidences of grade 2 gastrointestinal/genitourinary adverse events were 1% (95% CI: 0.1-6.9) and 4% (95% CI: 1.5-10.3), respectively; no grade ≥ 3 gastrointestinal/genitourinary adverse events were observed. The current study revealed a low incidence of late adverse events in prostate cancer patients treated with moderately hypofractionated PBT of 70 Gy (RBE) in 28 fractions, indicating the safety of this schedule.

Long-term effects of local radiotherapy on growth and vertebral features in children with high-risk neuroblastoma.

BACKGROUND: To evaluate the effects of local radiotherapy (RT) on growth, we evaluated the chronological growth profiles and vertebral features of children with high-risk neuroblastoma. METHODS: Thirty-eight children who received local photon or proton beam therapy to the abdomen or retroperitoneum between January 2014 and September 2019 were included. Simple radiography of the thoracolumbar spine was performed before and every year after RT. The height and vertical length of the irradiated vertebral bodies (VBs) compared with the unirradiated VBs (vertebral body ratio, VBR) were analyzed using the linear mixed model. Shape feature analysis was performed to compare the irradiated and unirradiated vertebrae. RESULTS: The follow-up was a median of 53.5 months (range, 21-81 months) after RT. A decline in height z-scores was mainly found in the early phase after treatment. In the linear mixed model with height, the initial height (fixed, p < 0.001), sex (time interaction, p = 0.008), endocrine dysfunction (time interaction, 0.019), and age at diagnosis (fixed and time interaction, both p = 0.002) were significant. Unlike the trend in height, the change in VBR (ΔVBR) decreased gradually (p < 0.001). The ΔVBR in the group that received more than 30 Gy decreased more than in the group that received smaller doses. In the shape feature analysis, the irradiated VBs changed to a more irregular surface that were neither round nor rectangular. CONCLUSION: The irradiated VBs in children were gradually restricted compared to the unirradiated VBs in long-term follow-up, and higher RT doses were significantly affected. Radiation-induced irregular features of VBs were observed.

Proton versus photon adjuvant radiotherapy: a multicenter comparative evaluation of recurrence following spinal chordoma resection.

OBJECTIVE: Chordomas are rare tumors of the skull base and spine believed to arise from the vestiges of the embryonic notochord. These tumors are locally aggressive and frequently recur following resection and adjuvant radiotherapy. Proton therapy has been introduced as a tissue-sparing option because of the higher level of precision that proton-beam techniques offer compared with traditional photon radiotherapy. This study aimed to compare recurrence in patients with chordomas receiving proton versus photon radiotherapy following resection by applying tree-based machine learning models. METHODS: The clinical records of all patients treated with resection followed by adjuvant proton or photon radiotherapy for chordoma at Mayo Clinic were reviewed. Patient demographics, type of surgery and radiotherapy, tumor recurrence, and other variables were extracted. Decision tree classifiers were trained and tested to predict long-term recurrence based on unseen data using an 80/20 split. RESULTS: Fifty-three patients with a mean ± SD age of 55.2 ± 13.4 years receiving surgery and adjuvant proton or photon therapy to treat chordoma were identified; most patients were male. Gross-total resection was achieved in 54.7% of cases. Proton therapy was the most common adjuvant radiotherapy (84.9%), followed by conventional or external-beam radiation therapy (9.4%) and stereotactic radiosurgery (5.7%). Patients receiving proton therapy exhibited a 40% likelihood of having recurrence, significantly lower than the 88% likelihood observed in those treated with nonproton therapy. This was confirmed on logistic regression analysis adjusted for extent of tumor resection and tumor location, which revealed that proton adjuvant radiotherapy was associated with a decreased risk of recurrence (OR 0.1, 95% CI 0.01-0.71; p = 0.047) compared with photon therapy. The decision tree algorithm predicted recurrence with an accuracy of 90% (95% CI 55.5%-99.8%), with the lowest risk of recurrence observed in patients receiving gross-total resection with adjuvant proton therapy (23%). CONCLUSIONS: Following resection, adjuvant proton therapy was associated with a lower risk of chordoma recurrence compared with photon therapy. The described machine learning models were able to predict tumor progression based on the extent of tumor resection and adjuvant radiotherapy modality used.

A high-resolution large-area detector for quality assurance in radiotherapy.

Hadron therapy is an advanced radiation modality for treating cancer, which currently uses protons and carbon ions. Hadrons allow for a highly conformal dose distribution to the tumour, minimising the detrimental side-effects due to radiation received by healthy tissues. Treatment with hadrons requires sub-millimetre spatial resolution and high dosimetric accuracy. This paper discusses the design, fabrication and performance tests of a detector based on Gas Electron Multipliers (GEM) coupled to a matrix of thin-film transistors (TFT), with an active area of 60 × 80 mm2 and 200 ppi resolution. The experimental results show that this novel detector is able to detect low-energy (40 kVp X-rays), high-energy (6 MeV) photons used in conventional radiation therapy and protons and carbon ions of clinical energies used in hadron therapy. The GEM-TFT is a compact, fully scalable, radiation-hard detector that measures secondary electrons produced by the GEMs with sub-millimetre spatial resolution and a linear response for proton currents from 18 pA to 0.7 nA. Correcting known detector defects may aid in future studies on dose uniformity, LET dependence, and different gas mixture evaluation, improving the accuracy of QA in radiotherapy.

A reference-point-method-based online proton treatment plan re-optimization strategy and a novel solution to planning constraint infeasibility problem.

Objective. Propose a highly automated treatment plan re-optimization strategy suitable for online adaptive proton therapy. The strategy includes a rapid re-optimization method that generates quality replans and a novel solution that efficiently addresses the planning constraint infeasibility issue that can significantly prolong the re-optimization process.Approach. We propose a systematic reference point method (RPM) model that minimizes the l-infinity norm from the initial treatment plan in the daily objective space for online re-optimization. This model minimizes the largest objective value deviation among the objectives of the daily replan from their reference values, leading to a daily replan similar to the initial plan. Whether a set of planning constraints is feasible with respect to the daily anatomy cannot be known before solving the corresponding optimization problem. The conventional trial-and-error-based relaxation process can cost a significant amount of time. To that end, we propose an optimization problem that first estimates the magnitude of daily violation of each planning constraint. Guided by the violation magnitude and clinical importance of the constraints, the constraints are then iteratively converted into objectives based on their priority until the infeasibility issue is solved.Main results.The proposed RPM-based strategy generated replans similar to the offline manual replans within the online time requirement for six head and neck and four breast patients. The average targetD95and relevant organ at risk sparing parameter differences between the RPM replans and clinical offline replans were -0.23, -1.62 Gy for head and neck cases and 0.29, -0.39 Gy for breast cases. The proposed constraint relaxation solution made the RPM problem feasible after one round of relaxation for all four patients who encountered the infeasibility issue.Significance. We proposed a novel RPM-based re-optimization strategy and demonstrated its effectiveness on complex cases, regardless of whether constraint infeasibility is encountered.

MRI-only based material mass density and relative stopping power estimation via deep learning for proton therapy: a preliminary study.

Magnetic Resonance Imaging (MRI) is increasingly being used in treatment planning due to its superior soft tissue contrast, which is useful for tumor and soft tissue delineation compared to computed tomography (CT). However, MRI cannot directly provide mass density or relative stopping power (RSP) maps, which are required for calculating proton radiotherapy doses. Therefore, the integration of artificial intelligence (AI) into MRI-based treatment planning to estimate mass density and RSP directly from MRI has generated significant interest. A deep learning (DL) based framework was developed to establish a voxel-wise correlation between MR images and mass density as well as RSP. To facilitate the study, five tissue substitute phantoms were created, representing different tissues such as skin, muscle, adipose tissue, 45% hydroxyapatite (HA), and spongiosa bone. The composition of these phantoms was based on information from ICRP reports. Additionally, two animal tissue phantoms, simulating pig brain and liver, were prepared for DL training purposes. The phantom study involved the development of two DL models. The first model utilized clinical T1 and T2 MRI scans as input, while the second model incorporated zero echo time (ZTE) MRI scans. In the patient application study, two more DL models were trained: one using T1 and T2 MRI scans as input, and another model incorporating synthetic dual-energy computed tomography (sDECT) images to provide accurate bone tissue information. The DECT empirical model was used as a reference to evaluate the proposed models in both phantom and patient application studies. The DECT empirical model was selected as the reference for evaluating the proposed models in both phantom and patient application studies. In the phantom study, the DL model based on T1, and T2 MRI scans demonstrated higher accuracy in estimating mass density and RSP for skin, muscle, adipose tissue, brain, and liver. The mean absolute percentage errors (MAPE) were 0.42%, 0.14%, 0.19%, 0.78%, and 0.26% for mass density, and 0.30%, 0.11%, 0.16%, 0.61%, and 0.23% for RSP, respectively. The DL model incorporating ZTE MRI further improved the accuracy of mass density and RSP estimation for 45% HA and spongiosa bone, with MAPE values of 0.23% and 0.09% for mass density, and 0.19% and 0.07% for RSP, respectively. These results demonstrate the feasibility of using an MRI-only approach combined with DL methods for mass density and RSP estimation in proton therapy treatment planning. By employing this approach, it is possible to obtain the necessary information for proton radiotherapy directly from MRI scans, eliminating the need for additional imaging modalities.

Investigating the biochemical response of proton minibeam radiation therapy by means of synchrotron-based infrared microspectroscopy.

The biology underlying proton minibeam radiation therapy (pMBRT) is not fully understood. Here we aim to elucidate the biological effects of pMBRT using Fourier Transform Infrared Microspectroscopy (FTIRM). In vitro (CTX-TNA2 astrocytes and F98 glioma rat cell lines) and in vivo (healthy and F98-bearing Fischer rats) irradiations were conducted, with conventional proton radiotherapy and pMBRT. FTIRM measurements were performed at ALBA Synchrotron, and multivariate data analysis methods were employed to assess spectral differences between irradiation configurations and doses. For astrocytes, the spectral regions related to proteins and nucleic acids were highly affected by conventional irradiations and the high-dose regions of pMBRT, suggesting important modifications on these biomolecules. For glioma, pMBRT had a great effect on the nucleic acids and carbohydrates. In animals, conventional radiotherapy had a remarkable impact on the proteins and nucleic acids of healthy rats; analysis of tumour regions in glioma-bearing rats suggested major nucleic acid modifications due to pMBRT.

Evaluation of an automated clinical decision system with deep learning dose prediction and NTCP model for prostate cancer proton therapy.

Objective.To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model.Approach.Two 3D UNets were established to predict photon and proton doses. A dataset of 95 patients with localized prostate cancer was randomly partitioned into 55, 10, and 30 for training, validation, and testing, respectively. We selected NTCP models for late rectum bleeding and acute urinary urgency of grade 2 or higher to quantify the benefit of proton therapy. Propagated uncertainties of predicted ΔNTCPs resulting from the dose prediction errors were calculated. Patient selection accuracies for a single endpoint and a composite evaluation were assessed under different ΔNTCP thresholds.Main results.Our deep learning-based dose prediction technique can reduce the time spent on plan comparison from approximately 2 days to as little as 5 seconds. The expanded uncertainty of predicted ΔNTCPs for rectum and bladder endpoints propagated from the dose prediction error were 0.0042 and 0.0016, respectively, which is less than one-third of the acceptable tolerance. The averaged selection accuracies for rectum bleeding, urinary urgency, and composite evaluation were 90%, 93.5%, and 93.5%, respectively.Significance.Our study demonstrates that deep learning dose prediction and NTCP evaluation scheme could distinguish the NTCP differences between photon and proton treatment modalities. In addition, the dose prediction uncertainty does not significantly influence the decision accuracy of NTCP-based patient selection for proton therapy. Therefore, automated deep learning dose prediction and NTCP evaluation schemes can potentially be used to screen large patient populations and to avoid unnecessary delays in the start of prostate cancer radiotherapy in the future.

Prompt-gamma track-length estimator with time tagging from proton tracking.

The design of prompt-gamma detectors necessitates numerous Monte Carlo simulations to precisely develop and optimize the detection stages in proton therapy. Alongside the advancement of MC simulations, various variance reduction methods have been explored to speed-up calculations. Among these techniques, track-length estimators are interesting scoring methods for achieving both speed and accuracy in Monte Carlo simulations of rare events. This paper introduces an extension of the GATE vpgTLE module that incorporates the prompt-gamma emission time, which is tagged from the proton tracking, enhancing its utility for studies focused on detector design and optimization that rely on time measurements. The results obtained from a clinical radiotherapy plan are presented. We demonstrate that the new vpgTLE tally with time tagging is accurate, except for certain prompt-gamma lines corresponding to long mean-life nuclei.

Biological optimization for hybrid proton-photon radiotherapy.

Objective.Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose.Approach.The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method.Main results.Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies.Significance.This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

Assessing the Impact of Charged Particle Radiation Therapy for Head and Neck Adenoid Cystic Carcinoma: A Systematic Review and Meta-Analysis.

Purpose: Head and neck adenoid cystic carcinoma (HNACC) is a radioresistant tumor. Particle therapy, primarily proton beam therapy and carbon-ion radiation, is a potential radiotherapy treatment for radioresistant malignancies. This study aims to conduct a meta-analysis to evaluate the impact of charged particle radiation therapy on HNACC. Methods: A comprehensive search was conducted in Pubmed, Cochrane Library, Web of Science, Embase, and Medline until December 31, 2022. The primary endpoints were overall survival (OS), local control (LC), and progression-free survival (PFS), while secondary outcomes included treatment-related toxicity. Version 17.0 of STATA was used for all analyses. Results: A total of 14 studies, involving 1297 patients, were included in the analysis. The pooled 5-year OS and PFS rates for primary HNACC were 78% (95% confidence interval [CI] = 66-91%) and 62% (95% CI = 47-77%), respectively. For all patients included, the pooled 2-year and 5-year OS, LC, and PFS rates were as follows: 86.1% (95% CI = 95-100%) and 77% (95% CI = 73-82%), 92% (95% CI = 84-100%) and 73% (95% CI = 61-85%), and 76% (95% CI = 68-84%) and 55% (95% CI = 48-62%), respectively. The rates of grade 3 and above acute toxicity were 22% (95% CI = 13-32%), while late toxicity rates were 8% (95% CI = 3-13%). Conclusions: Particle therapy has the potential to improve treatment outcomes and raise the quality of life for HNACC patients. However, further research and optimization are needed due to the limited availability and cost considerations associated with this treatment modality.

Binary Proton Therapy of Ehrlich Carcinoma Using Targeted Gold Nanoparticles.

Proton therapy can treat tumors located in radiation-sensitive tissues. This article demonstrates the possibility of enhancing the proton therapy with targeted gold nanoparticles that selectively recognize tumor cells. Au-PEG nanoparticles at concentrations above 25 mg/L and 4 Gy proton dose caused complete death of EMT6/P cells in vitro. Binary proton therapy using targeted Au-PEG-FA nanoparticles caused an 80% tumor growth inhibition effect in vivo. The use of targeted gold nanoparticles is promising for enhancing the proton irradiation effect on tumor cells and requires further research to increase the therapeutic index of the approach.

In-beam PET monitoring of proton therapy: a method for filtering prompt radiation events.

Objective. In-beam positron emission tomography (PET) is a promising technology for real-time monitoring of proton therapy. Random coincidences between prompt radiation events and positron annihilation photon pairs can deteriorate imaging quality during beam-on operation. This study aimed to improve the PET image quality by filtering out the prompt radiation events.Approach. We investigated a prompt radiation event filtering method based on the accelerator radio frequency phase and assessed its performance using various prompt gamma energy thresholds. An in-beam PET prototype was used to acquire the data when the 70 MeV proton beam irradiated a water phantom and a mouse. The signal-to-background ratio (SBR) indicator was utilized to evaluate the quality of the PET reconstruction image.Main results. The selection of the prompt gamma energy threshold will affect the quality of the reconstructed image. Using the optimal energy threshold of 580 keV can obtain a SBR of 1.6 times for the water phantom radiation experiment and 2.0 times for the mouse radiation experiment compared to those without background removal, respectively.Significance. Our results show that using this optimal threshold can reduce the prompt radiation events, enhancing the SBR of the reconstructed image. This advancement contributes to more accurate real-time range verification in subsequent steps.

Combination of proton- or X-irradiation with anti-PDL1 immunotherapy in two murine oral cancers.

Combining radiation therapy with immunotherapy is a strategy to improve both treatments. The purpose of this study was to compare responses for two syngeneic head and neck cancer (HNC) tumor models in mice following X-ray or proton irradiation with or without immune checkpoint inhibition (ICI). MOC1 (immunogenic) and MOC2 (less immunogenic) tumors were inoculated in the right hind leg of each mouse (C57BL/6J, n = 398). Mice were injected with anti-PDL1 (10 mg/kg, twice weekly for 2 weeks), and tumors were treated with single-dose irradiation (5-30 Gy) with X-rays or protons. MOC2 tumors grew faster and were more radioresistant than MOC1 tumors, and all mice with MOC2 tumors developed metastases. Irradiation reduced the tumor volume in a dose-dependent manner. ICI alone reduced the tumor volume for MOC1 with 20% compared to controls, while no reduction was seen for MOC2. For MOC1, there was a clear treatment synergy when combining irradiation with ICI for radiation doses above 5 Gy and there was a tendency for X-rays being slightly more biologically effective compared to protons. For MOC2, there was a tendency of protons being more effective than X-rays, but both radiation types showed a small synergy when combined with ICI. Although the responses and magnitudes of the therapeutic effect varied, the optimal radiation dose for maximal synergy appeared to be in the order of 10-15 Gy, regardless of tumor model.