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This study aimed to investigate a dose rate optimization framework based on the spot-scanning patterns to improve ultrahigh-dose-rate coverage of critical organs at risk (OARs) for proton pencil beam scanning (PBS) FLASH radiation therapy (ultrahigh dose-rate (often referred to as >40 Gy per second) delivery) and present implementation of a genetic algorithm (GA) method for spot sequence optimization to achieve PBS FLASH dose rate optimization under relatively low nozzle beam currents. First, a multifield FLASH plan was developed to meet all the dosimetric goals and optimal FLASH dose rate coverage by considering the deliverable minimum monitor unit constraint. Then, a GA method was implemented into the in-house treatment platform to maximize the dose rate by exploring the best spot delivery sequence. A phantom study was performed to evaluate the effectiveness of the dose rate optimization. Then, 10 consecutive plans for patients with lung cancer previously treated using PBS intensity-modulated proton therapy were optimized using 45 GyRBE in 3 fractions for both transmission and Bragg peak FLASH radiation therapy for further validation. The spot delivery sequence of each treatment field was optimized using this GA. The ultrahigh-dose-rate–volume histogram and dose rate coverage V 40GyRBE/s were investigated to assess the efficacy of dose rate optimization quantitatively. Using a relatively low monitor unit/spot of 150, corresponding to a nozzle beam current of 65 nA, the FLASH dose rate ratio V 40GyRBE/s of the OAR contour of the core was increased from 0% to ∼60% in the phantom study. In the patients with lung cancer, the ultrahigh-dose-rate coverage V 40GyRBE/s was improved from 15.2%, 15.5%, 17.6%, and 16.0% before the delivery sequence optimization to 31.8%, 43.5%, 47.6%, and 30.5% after delivery sequence optimization in the lungs-GTV (gross tumor volume), spinal cord, esophagus, and heart (for all, P <.001). When the beam current increased to 130 nA, V 40GyRBE/s was improved from 45.1%, 47.1%, 51.2%, and 51.4% to 65.3%, 83.5%, 88.1%, and 69.4% (P <.05). The averaged V 40GyRBE/s for the target and OARs increased from 12.9% to 41.6% and 46.3% to 77.5% for 65 and 130 nA, respectively, showing significant improvements based on a clinical proton system. After optimizing the dose rate for the Bragg peak FLASH technique with a beam current of 340 nA, the V 40GyRBE/s values for the lung GTV, spinal cord, esophagus, and heart were increased by 8.9%, 15.8%, 22%, and 20.8%, respectively. An optimal plan quality can be maintained as the spot delivery sequence optimization is a separate independent process after the plan optimization. Both the phantom and patient results demonstrated that novel spot delivery sequence optimization can effectively improve the ultrahigh-dose-rate coverage for critical OARs, which can potentially be applied in clinical practice for better OARs-sparing efficacy. [ABSTRACT FROM AUTHOR]

The social and health benefits that green areas and forests can provide are now recognized in the scientific community worldwide. There is a growing interest in and demand for forest care initiatives and nature-based therapy, also as a result of the impacts of Covid-19 pandemic. In Italy, the increasing interest in alternative and integrated solutions for care and healthcare promotion have laid the basis for the implementation of several projects and activities, particularly those known as Forest Therapy (FT). These initiatives provide a business opportunity for forestry and social sectors, for the development of rural areas, and they are a cost-saving opportunity for the National Health System because of the expected benefits (as assessed by several clinical studies confirming the therapeutic effectiveness of these activities). Despite the importance, in Italy there is not a specific legal basis and standardized procedures to determine the suitability of a FT site. As a result, FT initiatives have been carried out in different environments, whether in urban or extra-urban forest areas, with the implementation of activities deemed suitable in a "selfreferential" approach. Establishing a standard procedure for the recognition of FT suitable locations and related FT activities is a first step for the promotion of an important instrument that can meet several social needs. This work proposes (i) a standard procedure ("iter") for the validation of a Forest Therapy and Urban forest therapy (UFT) site by the competent authority to obtain the official "environmental recognition" of site suitability; (ii) the technical and objective criteria to assess the stationary and environmental parameters of a site in order to be qualified as a FT/UFT site, both in natural and urban contexts. The iter and criteria proposed take into account the relevant national regulations, the literature found on the subject, and the expertise of scientists and technicians. The procedure and criteria proposed can be used as basis of a regulation on FT in Italy, ensuring suitable sites officially recognised by public institutions and providing a high-quality service to society. Finally, a baseline regulation would also facilitate opportunities for dedicated funding, as well as the recognition of "green prescriptions" for the prevention and treatment of certain health problems. [ABSTRACT FROM AUTHOR]

Background: Quality assurance (QA) of patient‐specific treatment plans for intensity‐modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) necessitates prior validation. However, the standard methodology exhibits deficiencies and lacks sensitivity in the analysis of positional dose distribution data, leading to difficulties in accurately identifying reasons for plan verification failure. This issue complicates and impedes the efficiency of QA tasks. Purpose: The primary aim of this research is to utilize deep learning algorithms for the extraction of 3D dose distribution maps and the creation of a predictive model for error classification across multiple machine models, treatment methodologies, and tumor locations. Method: We devised five categories of validation plans (normal, gantry error, collimator error, couch error, and dose error), conforming to tolerance limits of different accuracy levels and employing 3D dose distribution data from a sample of 94 tumor patients. A CNN model was then constructed to predict the diverse error types, with predictions compared against the gamma pass rate (GPR) standard employing distinct thresholds (3%, 3 mm; 3%, 2 mm; 2%, 2 mm) to evaluate the model's performance. Furthermore, we appraised the model's robustness by assessing its functionality across diverse accelerators. Results: The accuracy, precision, recall, and F1 scores of CNN model performance were 0.907, 0.925, 0.907, and 0.908, respectively. Meanwhile, the performance on another device is 0.900, 0.918, 0.900, and 0.898. In addition, compared to the GPR method, the CNN model achieved better results in predicting different types of errors. Conclusion: When juxtaposed with the GPR methodology, the CNN model exhibits superior predictive capability for classification in the validation of the radiation therapy plan on different devices. By using this model, the plan validation failures can be detected more rapidly and efficiently, minimizing the time required for QA tasks and serving as a valuable adjunct to overcome the constraints of the GPR method. [ABSTRACT FROM AUTHOR]

In recent years, the application of positron emission tomography (PET) for the dose range verification of proton therapy has been proposed. However, the positron distribution is determined by the nuclear reaction cross section; hence, PET may not accurately reflect the dose range primarily influenced by ionization. Consequently, a proton dose range verification system based on scattered proton measurements has been suggested owing to the similarity in the reaction cross section between Rutherford scattering and ionization. While previous investigations have only verified the feasibility of dose range estimation through simple simulations, the objective of this study is to demonstrate this feasibility through experimental investigation. In this paper, we established an experimental framework for capturing scattered protons and introduced an algorithm that compares measured signal patterns with a reference database to estimate the dose range. A therapeutic beam was irradiated onto the abdominal region of a human phantom, and scattered protons were measured using scintillation detectors placed on the phantom surface. Consequently, the dose range was estimated with error margins of 4.22 ± 3.68 and 0.60 ± 1.03 mm along the beam axis and perpendicular directions to the Bragg peak, respectively. While providing the same level of Bragg peak positioning accuracy as conventional methods, our system features small size, cost-effectiveness, and system simplicity. One notable limitation of our method is the challenge in achieving precise detector positioning, which is crucial for accurate dose range estimation. Future research will focus on improving detector-position accuracy and exploring advanced algorithms for signal analysis to further refine dose range estimations. [ABSTRACT FROM AUTHOR]

Background: To carry out a validation questionnaire that assesses beliefs about inhaled treatments in patients with chronic obstructive pulmonary disease (COPD), as knowing patients' beliefs could help to improve medication adherence and health outcomes. Methods: We evaluated data from 260 COPD patients from electronic medical record databases from five primary healthcare centers, in a descriptive, cross-sectional study with a sample size calculated for a 10-item questionnaire, with an estimated Cronbach's alpha of 0.70 and a 95% confidence level. Study participants were selected via systematic random sampling. Variables: Ten-item Inhaled Therapy Beliefs Questionnaire, CCTI-Questionnaire v.2.0, time for completion, age, sex, educational level, spirometry severity (GOLD criteria), exacerbations (previous year), characteristics of inhaled treatment, and smoking habit. A two-year follow-up in a subsample of 77 patients from one health center was utilized. The Morisky–Green test, pharmacy dispensing data, test–retest (kappa coefficient), and an exploratory analysis of the adherence–belief relationship (ji-squared) were measured. Results: The 10-item questionnaire showed good viability (3 min completion time) when performed face-to-face or telephonically; its psychometric properties were acceptable, with an internal consistency (Cronbach's alpha) score of 0.613. Three factors explained 47.58% of the total variance (p < 0.0001): use (factor 1), effects (factor 2), and objectives (factor 3) of inhalers. The two-year follow-up ultimately considered 58 out of the 77 patients (10 deceased, 4 unlocated, 2 mistakes, 2 no inhaled treatment, and 1 withdrawal). Non-adherence was 48.3% in terms of the Morisky–Green test; 31% in terms of pharmacy dispensing data; and 40.4% considering both methods. There was low test–retest reliability, indicated by items 4, 8, and 9 of the CCTI-Questionnaire (Kappa = 0.4, 0.26, and 0.34; p-value < 0.0001, 0.008, and 0.001, respectively). There was mild correlation between beliefs and adherence. Conclusions: The ten-item CCTI-Questionnaire v.2.0 demonstrated acceptable psychometric properties regarding feasibility, reliability, and content validity. [ABSTRACT FROM AUTHOR]

Objectives: To assess the therapeutic response of HCC to antiangiogenic therapy plus immunotherapy by integrating RECIST 1.1 and alpha-fetoprotein (AFP) response at the 6th week to predict overall survival (OS). Methods: This retrospective study included 150 and 214 patients with HCC who received combination therapy in training and validation cohorts. The medical images and AFP levels obtained at baseline and 6th week were collected. AFP response stratification: partial response (PR): AFP% ≥ 75% decline; stable disease (SD): AFP% < 75% decline and ≤ 10% elevation; progressive disease (PD): AFP% > 10% elevation. The alpha-RECIST was: PR: RECIST 1.1-PR or AFP-PR; PD: AFP-PD or RECIST 1.1-PD and does not satisfy AFP-PR; SD: neither PR nor PD. OS was compared using Kaplan–Meier curves. The predictive ability of various criteria was evaluated using the concordance index and time-dependent area under the receiver-operating characteristic curve. Results: RECIST 1.1 achieved significant OS stratification (p = 0.020) for AFP < 20 ng/mL. For AFP ≥ 20 ng/mL, alpha-RECIST showed better performance than RECIST 1.1, mRECIST, and AFP response according to C-index (0.73 vs 0.66 vs 0.68 vs 0.69). The National Cancer Center (NCC) strategy utilized RECIST 1.1 for AFP < 20 ng/mL and alpha-RECIST for AFP ≥ 20 ng/mL and showed better performance than RECIST 1.1, mRECIST and AFP response according to C-index (0.73 vs 0.67 vs 0.69 vs 0.64). The performances of alpha-RECIST and NCC Strategy were confirmed in the validation cohort (C-index = 0.77 and 0.74). Conclusions: The alpha-RECIST and NCC Strategy achieved better survival stratification in patients with HCC under combination therapy in the AFP ≥ 20 ng/mL group and the whole cohort compared to the RECIST 1.1, mRECIST, and AFP response. Clinical translational relevance: The alpha-RECIST and National Cancer Center strategy are optimal methods for determining therapeutic response to a combination of anti-angiogenic therapy plus immunotherapy and facilitating accurate prognostic stratification for HCC in the AFP ≥ 20 ng/mL group and the whole cohort, which may help oncologists for early identification of responders and progression at 6 weeks and clinical decision-making. Key Points: • RECIST 1.1 is indicated for patients with baseline alpha-fetoprotein (AFP) < 20 ng/mL. • For patients with baseline AFP ≥ 20 ng/mL, integrating RECIST 1.1 and AFP response (alpha-RECIST) may aid in the early identification of survival benefits and progression definition prior to the administration of additional efficacious drugs. • The National Cancer Center strategy is an optimal stratified strategy for determining therapeutic response to a combination of anti-angiogenic therapy and immunotherapy for HCC based on baseline AFP levels. [ABSTRACT FROM AUTHOR]

• Incidence of radiation-induced alopecia (RIA) in brain tumours patients treated with Proton Therapy is reported. • We independently validate previously published NTCP models for grade 2 RIA. • External validity of models was assessed in terms of discrimination and calibration. • Differences in reporting RIA outcomes could undermine the validation of NTCP models and impede their use in clinical settings. Radiation-induced alopecia (RIA) is one of the most frequent and upsetting cosmetic side effects after radiotherapy (RT) for brain cancer. We report the incidence of RIA in a cohort of brain tumours patients treated with Proton Therapy (PT) and externally validate published NTCP models of grade 2 (G2) RIA for their implementation in clinical practice. Data for patients treated for brain tumours with scanning beam PT between 2018 and 2022 were extracted. Acute, late and permanent RIA events were evaluated according to CTCAE 5.0. Lyman-Kutcher-Burman (LKB) and multivariable logistic regression (MLR) published models were computed from the relative dose-surface histogram of the scalp. External validity of models was assessed in terms of discrimination and calibration. In the 264 patients analysed, rates of any grade acute (≤90 days after PT completion), late (>90 days) and permanent RIA (persisting for> 12 months) were 61.8 %, 24.7 % and 14.4 %, respectively. In our independent cohort, LKB- and MLR-NTCP showed a good discrimination for G2 RIA (0.71≤ROC-AUC≤0.83) while model calibration was unsatisfactory possibly due to a different outcome evaluation between training and validation cohorts, as well as differences in clinical and treatment related variables between the two groups. Despite the reasonable sensitivity and specificity of the NTCP models for RIA in the validation cohort, our study emphasizes the significance of differences between the cohorts utilized for model development and validation. Specifically, variations in the reporting of clinical outcomes inevitably jeopardize the validation of NTCP models. A standardize and objective RIA scoring system is essential. [ABSTRACT FROM AUTHOR]

• A sensitive method for quantifying decitabine in mouse plasma was developed and validated. • Robust, accurate, and precise results were demonstrated, with a lower limit of quantitation of 0.4 ng/mL. • Decitabine was determined in microvolumes of mouse plasma. • Increased oral bioavailability of decitabine was observed when given with cedazuridine. • The mouse model was found useful for evaluating pharmacokinetic drug-drug interactions with decitabine. Decitabine is a DNA methyltransferase inhibitor used in the treatment of acute myeloid leukemia and myelodysplastic syndrome. The notion that ongoing trials are presently exploring the combined use of decitabine, with or without the cytidine deaminase inhibitor cedazuridine, and other antileukemic drugs necessitates a comprehensive understanding of pharmacokinetic properties and an evaluation of drug-drug interaction liabilities. We report here the development and validation of a sensitive UHPLC-MS/MS method for quantifying decitabine in mouse plasma, which should be useful for such studies. The method involved a one-step protein precipitation extraction, and chromatographic separation on an XBridge HILIC column using gradient elution. The method was found to be robust, accurate, precise, and sufficiently sensitive (lower limit of quantitation, 0.4 ng/mL) to determine decitabine concentrations in microvolumes of plasma from mice receiving the agent orally or intravenously in the presence or absence of cedazuridine. [ABSTRACT FROM AUTHOR]