[Informed consent in radiotherapy care]. / Consentement aux soins en radiothérapie.

Obtaining consent to care requires the radiation oncologist to provide loyal information and to ensure that the patient understands it. Proof of such an approach rests with the practitioner. The French Society for Radiation Oncology (SFRO) does not recommend the signature of a consent form by the patient but recommends that the radiation oncologist be able to provide all the elements demonstrating the reality of a complete information circuit.

Causal analysis of radiotherapy safety incidents based on a hybrid model of HFACS and Bayesian network.

Objective: This research investigates the role of human factors of all hierarchical levels in radiotherapy safety incidents and examines their interconnections. Methods: Utilizing the human factor analysis and classification system (HFACS) and Bayesian network (BN) methodologies, we created a BN-HFACS model to comprehensively analyze human factors, integrating the hierarchical structure. We examined 81 radiotherapy incidents from the radiation oncology incident learning system (RO-ILS), conducting a qualitative analysis using HFACS. Subsequently, parametric learning was applied to the derived data, and the prior probabilities of human factors were calculated at each BN-HFACS model level. Finally, a sensitivity analysis was conducted to identify the human factors with the greatest influence on unsafe acts. Results: The majority of safety incidents reported on RO-ILS were traced back to the treatment planning phase, with skill errors and habitual violations being the primary unsafe acts causing these incidents. The sensitivity analysis highlighted that the condition of the operators, personnel factors, and environmental factors significantly influenced the occurrence of incidents. Additionally, it underscored the importance of organizational climate and organizational process in triggering unsafe acts. Conclusion: Our findings suggest a strong association between upper-level human factors and unsafe acts among radiotherapy incidents in RO-ILS. To enhance radiation therapy safety and reduce incidents, interventions targeting these key factors are recommended.

Which Modality of SFRT Should be Considered First for Bulky Tumor Radiation Therapy, GRID or LATTICE?

Spatially fractionated radiation therapy (SFRT), also known as the GRID and LATTICE radiotherapy (GRT, LRT), the concept of treating tumors by delivering a spatially modulated dose with highly non-uniform dose distributions, is a treatment modality of growing interest in radiation oncology, physics, and radiation biology. Clinical experience in SFRT has suggested that GRID and LATTICE therapy can achieve a high response and low toxicity in the treatment of refractory and bulky tumors. Limited initially to GRID therapy using block collimators, advanced, and versatile multi-leaf collimators, volumetric modulated arc technologies and particle therapy have since increased the capabilities and individualization of SFRT and expanded the clinical investigation of SFRT to various dosing regimens, multiple malignancies, tumor types and sites. As a 3D modulation approach outgrown from traditional 2D GRID, LATTICE therapy aims to reconfigure the traditional SFRT as spatial modulation of the radiation is confined solely to the tumor volume. The distinctively different beam geometries used in LATTICE therapy have led to appreciable variations in dose-volume distributions, compared to GRID therapy. The clinical relevance of the variations in dose-volume distribution between LATTICE and traditional GRID therapies is a crucial factor in determining their adoption in clinical practice. In this Point-Counterpoint contribution, the authors debate the pros and cons of GRID and LATTICE therapy. Both modalities have been used in clinics and their applicability and optimal use have been discussed in this article.

Navigating the Critical Translational Questions for Implementing FLASH in the Clinic.

The "FLASH effect" is an increased therapeutic index, that is, reduced normal tissue toxicity for a given degree of anti-cancer efficacy, produced by ultra-rapid irradiation delivered on time scales orders of magnitude shorter than currently conventional in the clinic for the same doses. This phenomenon has been observed in numerous preclinical in vivo tumor and normal tissue models. While the underlying biological mechanism(s) remain to be elucidated, a path to clinical implementation of FLASH can be paved by addressing several critical translational questions. Technological questions pertinent to each beam type (eg, electron, proton, photon) also dictate the logical progression of experimentation required to move forward in safe and decisive clinical trials. Here we review the available preclinical data pertaining to these questions and how they may inform strategies for FLASH cancer therapy clinical trials.

Patient Safety and Satisfaction With Fully Remote Management of Radiation Oncology Care.

Importance: Patients of Memorial Sloan Kettering Cancer Center in New York, New York, are now offered a choice of either in-person or remote telehealth visits for radiation oncology care. However, safety and satisfaction among patients receiving treatment with fully remote physician management is unclear. Objective: To analyze patient safety and satisfaction, financial implications, and environmental consequences associated with fully remote management among a cohort of patients treated with radiotherapy. Design, Setting, and Participants: This single-institution retrospective cohort study was performed at Memorial Sloan Kettering Cancer Center, with patients treated with radiation who opted for fully remote management between October 1, 2020, and October 31, 2022. Data on patient safety events were prospectively collected with an in-house quality improvement reporting system. Patient satisfaction surveys were distributed electronically before, during, and after treatment. Patient transportation costs and environmental consequences were estimated based on differences in travel distance. Data analysis was performed from March 14 through September 19, 2023. Exposure: Radiotherapy with fully remote physician management. Main Outcomes and Measures: Satisfaction rates among patients opting for fully remote management were analyzed via surveys administered electronically after visits with clinicians. Patient safety events, defined as staff-reported actual events and near misses that had the potential to affect patient care, were reviewed. Rates and types of safety events were analyzed and compared with patients treated by onsite clinicians. Distances between patient home zip codes and treatment site locations were compared with estimated cost savings and decreased emissions. Results: This study included 2817 patients who received radiation oncology care with fully remote physician management. The median age of patients was 65 (range, 9-99) years, and more than half were men (1467 [52.1%]). Of the 764 safety events reported, 763 (99.9%) did not reach patients or caused no harm to patients. Nearly all survey respondents (451 [97.6%]) rated patient satisfaction as good to very good across all domains. For treatment with fully remote physician management, out-of-pocket cost savings totaled $612 912.71 ($466.45 per patient) and decreased carbon dioxide emissions by 174 metric tons. Conclusions and Relevance: In this study, radiation oncology care provided by fully remote clinicians was safe and feasible, with no serious patient events. High patient satisfaction, substantial cost savings, and decreased environmental consequences were observed. These findings support the continuation of a fully remote management option for select patients in the post-COVID-19 era.

Insurance Denials and Patient Treatment in a Large Academic Radiation Oncology Center.

Importance: Insurance barriers to cancer care can cause significant patient and clinician burden. Objective: To investigate the association of insurance denial with changes in technique, dose, and time to delivery of radiation oncology treatment. Design, Setting, and Participants: In this single-institution cohort analysis, data were collected from patients with payer-denied authorization for radiation therapy (RT) from November 1, 2021, to December 8, 2022. Data were analyzed from December 15, 2022, to December 31, 2023. Exposure: Insurance denial for RT. Main Outcomes and Measures: Association of these denials with changes in RT technique, dose, and time to treatment delivery was assessed using χ2 tests. Results: A total of 206 cases (118 women [57.3%]; median age, 58 [range, 26-91] years) were identified. Most insurers (199 [96.6%]) were commercial payers, while 7 (3.4%) were Medicare or Medicare Advantage. One hundred sixty-one patients (78.2%) were younger than 65 years. Of 206 cases, 127 (61.7%) were ultimately authorized without any change to the requested RT technique or prescription dose; 56 (27.2%) were authorized after modification to RT technique and/or prescription dose required by the payer. Of 21 cases with required prescription dose change, the median decrease in dose was 24.0 (range, 2.3-51.0) Gy. Of 202 cases (98.1%) with RT delivered, 72 (34.9%) were delayed for a mean (SD) of 7.8 (9.1) days and median of 5 (range, 1-49) days. Four cases (1.9%) ultimately did not receive any authorization, with 3 (1.5%) not undergoing RT, and 1 (0.5%) seeking treatment at another institution. Conclusions and Relevance: In this cohort study of patients with payer-denied cases, most insurance denials in radiation oncology were ultimately approved on appeal; however, RT technique and/or effectiveness may be compromised by payer-mandated changes. Further investigation and action to recognize the time and financial burdens on clinicians and clinical effects on patients caused by insurance denials of RT is needed.

Autologous Peripheral Blood Stem Cell Transplantation and Timing of Local Radiation Therapy in Patients With Malignant Lymphoma: Results of the Japanese Radiation Oncology Study Group Questionnaire Survey.

BACKGROUND/AIM: Malignant lymphoma (ML) including Hodgkin's lymphoma and non-Hodgkin's lymphoma is often treated with local radiation therapy (RT) in combination with autologous hematopoietic stem cell transplantation (ASCT) to prevent relapse; however, the efficacy and optimal timing of this approach is unclear. In this study, a national survey conducted by the Japanese Radiation Oncology Study Group reviewed ML cases from 2011 to 2019 to determine whether RT should be added to ASCT, focusing on the use of autologous peripheral blood stem cell transplantation (auto-PBSCT), a predominant form of ASCT. PATIENTS AND METHODS: The survey encompassed 92 patients from 11 institutes, and assessed histological ML types, treatment regimens, timing of RT relative to auto-PBSCT, and associated adverse events. RESULTS: The results indicated no significant differences in adverse events, including myelosuppression, based on the timing of RT in relation to auto-PBSCT. However, anemia was more prevalent when RT was administered before auto-PBSCT, and there was a higher incidence of neutropenia recovery delay in patients receiving RT after auto-PBSCT. CONCLUSION: This study provides valuable insights into the variable practices of auto-PBSCT and local RT in ML treatment, emphasizing the need for optimized timing of these therapies to improve patient outcomes and reduce complications.

Artificial intelligence solution to accelerate the acquisition of MRI images: Impact on the therapeutic care in oncology in radiology and radiotherapy departments.

PURPOSE: MRI is essential in the management of brain tumours. However, long waiting times reduce patient accessibility. Reducing acquisition time could improve access but at the cost of spatial resolution and diagnostic quality. A commercially available artificial intelligence (AI) solution, SubtleMR™, can increase the resolution of acquired images. The objective of this prospective study was to evaluate the impact of this algorithm that halves the acquisition time on the detectability of brain lesions in radiology and radiotherapy. MATERIAL AND METHODS: The T1/T2 MRI of 33 patients with brain metastases or meningiomas were analysed. Images acquired quickly have a matrix divided by two which halves the acquisition time. The visual quality and lesion detectability of the AI images were evaluated by radiologists and radiation oncologist as well as pixel intensity and lesions size. RESULTS: The subjective quality of the image is lower for the AI images compared to the reference images. However, the analysis of lesion detectability shows a specificity of 1 and a sensitivity of 0.92 and 0.77 for radiology and radiotherapy respectively. Undetected lesions on the IA image are lesions with a diameter less than 4mm and statistically low average gadolinium-enhancement contrast. CONCLUSION: It is possible to reduce MRI acquisition times by half using the commercial algorithm to restore the characteristics of the image and obtain good specificity and sensitivity for lesions with a diameter greater than 4mm.

Evaluating ChatGPT to test its robustness as an interactive information database of radiation oncology and to assess its responses to common queries from radiotherapy patients: A single institution investigation.

PURPOSE: Commercial vendors have created artificial intelligence (AI) tools for use in all aspects of life and medicine, including radiation oncology. AI innovations will likely disrupt workflows in the field of radiation oncology. However, limited data exist on using AI-based chatbots about the quality of radiation oncology information. This study aims to assess the accuracy of ChatGPT, an AI-based chatbot, in answering patients' questions during their first visit to the radiation oncology outpatient department and test knowledge of ChatGPT in radiation oncology. MATERIAL AND METHODS: Expert opinion was formulated using a set of ten standard questions of patients encountered in outpatient department practice. A blinded expert opinion was taken for the ten questions on common queries of patients in outpatient department visits, and the same questions were evaluated on ChatGPT version 3.5 (ChatGPT 3.5). The answers by expert and ChatGPT were independently evaluated for accuracy by three scientific reviewers. Additionally, a comparison was made for the extent of similarity of answers between ChatGPT and experts by a response scoring for each answer. Word count and Flesch-Kincaid readability score and grade were done for the responses obtained from expert and ChatGPT. A comparison of the answers of ChatGPT and expert was done with a Likert scale. As a second component of the study, we tested the technical knowledge of ChatGPT. Ten multiple choice questions were framed with increasing order of difficulty - basic, intermediate and advanced, and the responses were evaluated on ChatGPT. Statistical testing was done using SPSS version 27. RESULTS: After expert review, the accuracy of expert opinion was 100%, and ChatGPT's was 80% (8/10) for regular questions encountered in outpatient department visits. A noticeable difference was observed in word count and readability of answers from expert opinion or ChatGPT. Of the ten multiple-choice questions for assessment of radiation oncology database, ChatGPT had an accuracy rate of 90% (9 out of 10). One answer to a basic-level question was incorrect, whereas all answers to intermediate and difficult-level questions were correct. CONCLUSION: ChatGPT provides reasonably accurate information about routine questions encountered in the first outpatient department visit of the patient and also demonstrated a sound knowledge of the subject. The result of our study can inform the future development of educational tools in radiation oncology and may have implications in other medical fields. This is the first study that provides essential insight into the potentially positive capabilities of two components of ChatGPT: firstly, ChatGPT's response to common queries of patients at OPD visits, and secondly, the assessment of the radiation oncology knowledge base of ChatGPT.

Associations Between Radiation Oncologist Demographic Factors and Segmentation Similarity Benchmarks: Insights From a Crowd-Sourced Challenge Using Bayesian Estimation.

PURPOSE: The quality of radiotherapy auto-segmentation training data, primarily derived from clinician observers, is of utmost importance. However, the factors influencing the quality of clinician-derived segmentations are poorly understood; our study aims to quantify these factors. METHODS: Organ at risk (OAR) and tumor-related segmentations provided by radiation oncologists from the Contouring Collaborative for Consensus in Radiation Oncology data set were used. Segmentations were derived from five disease sites: breast, sarcoma, head and neck (H&N), gynecologic (GYN), and GI. Segmentation quality was determined on a structure-by-structure basis by comparing the observer segmentations with an expert-derived consensus, which served as a reference standard benchmark. The Dice similarity coefficient (DSC) was primarily used as a metric for the comparisons. DSC was stratified into binary groups on the basis of structure-specific expert-derived interobserver variability (IOV) cutoffs. Generalized linear mixed-effects models using Bayesian estimation were used to investigate the association between demographic variables and the binarized DSC for each disease site. Variables with a highest density interval excluding zero were considered to substantially affect the outcome measure. RESULTS: Five hundred seventy-four, 110, 452, 112, and 48 segmentations were used for the breast, sarcoma, H&N, GYN, and GI cases, respectively. The median percentage of segmentations that crossed the expert DSC IOV cutoff when stratified by structure type was 55% and 31% for OARs and tumors, respectively. Regression analysis revealed that the structure being tumor-related had a substantial negative impact on binarized DSC for the breast, sarcoma, H&N, and GI cases. There were no recurring relationships between segmentation quality and demographic variables across the cases, with most variables demonstrating large standard deviations. CONCLUSION: Our study highlights substantial uncertainty surrounding conventionally presumed factors influencing segmentation quality relative to benchmarks.

Addressing challenges in low-income and middle-income countries through novel radiotherapy research opportunities.

Although radiotherapy continues to evolve as a mainstay of the oncological armamentarium, research and innovation in radiotherapy in low-income and middle-income countries (LMICs) faces challenges. This third Series paper examines the current state of LMIC radiotherapy research and provides new data from a 2022 survey undertaken by the International Atomic Energy Agency and new data on funding. In the context of LMIC-related challenges and impediments, we explore several developments and advances-such as deep phenotyping, real-time targeting, and artificial intelligence-to flag specific opportunities with applicability and relevance for resource-constrained settings. Given the pressing nature of cancer in LMICs, we also highlight some best practices and address the broader need to develop the research workforce of the future. This Series paper thereby serves as a resource for radiation professionals.

Perceptions on and roadblocks to implementation of standardized nomenclature in radiation oncology: A survey from TG-263U1.

PURPOSE: AAPM Task Group No. 263U1 (Update to Report No. 263 - Standardizing Nomenclatures in Radiation Oncology) disseminated a survey to receive feedback on utilization, gaps, and means to facilitate further adoption. METHODS: The survey was created by TG-263U1 members to solicit feedback from physicists, dosimetrists, and physicians working in radiation oncology. Questions on the adoption of the TG-263 standard were coupled with demographic information, such as clinical role, place of primary employment (e.g., private hospital, academic center), and size of institution. The survey was emailed to all AAPM, AAMD, and ASTRO members. RESULTS: The survey received 463 responses with 310 completed survey responses used for analysis, of whom most had the clinical role of medical physicist (73%) and the majority were from the United States (83%). There were 83% of respondents who indicated that they believe that having a nomenclature standard is important or very important and 61% had adopted all or portions of TG-263 in their clinics. For those yet to adopt TG-263, the staffing and implementation efforts were the main cause for delaying adoption. Fewer respondents had trouble adopting TG-263 for organs at risk (29%) versus target (44%) nomenclature. Common themes in written feedback were lack of physician support and available resources, especially in vendor systems, to facilitate adoption. CONCLUSIONS: While there is strong support and belief in the benefit of standardized nomenclature, the widespread adoption of TG-263 has been hindered by the effort needed by staff for implementation.  Feedback from the survey is being utilized to drive the focus of the update efforts and create tools to facilitate easier adoption of TG-263.

Radiation Oncology Training in the Philippines: Bridging Gaps for Improved Cancer Care in Low- and Middle-Income Countries.

PURPOSE: Radiation oncology in the Philippines, a large lower- and middle-income country in Southeast Asia, is facing a critical shortage in manpower, with only 113 radiation oncologists (ROs) over 55 radiotherapy (RT) centers serving 100 million population. Paramount to workforce expansion is ensuring that training programs can produce adequately trained specialists. In this study, we describe the current state of radiation oncology training programs in the Philippines. METHODS: This is a cross-sectional observational analysis of the nine radiation oncology residency training programs in the Philippines. Data were collected from a survey of the program directors, the Philippine Radiation Oncology Society database, and a PubMed literature search. RESULTS: Eight of the nine programs are in the National Capital Region. Since program standardization in 2005, there have been 82 four-year residency graduates, with up to 18 new graduates annually. Faculty-to-trainee ratio ranges from 0.5 to 2.67. In terms of technology, all programs have intensity-modulated RT and high-dose-rate brachytherapy, but only six are equipped with computed tomography-based image guidance and stereotactic capabilities. Clinical education schemes vary per institution regarding curriculum implementation, resident activities, and methods of evaluation. Required resident case logs are not met for lung, GI, genitourinary, bone and soft tissue, and hematologic malignancies. In total, there are only 22 resident-led publications from 10 unique individuals in two training programs. CONCLUSION: Program expansions are warranted to meet the projected demand for ROs in the Philippines, but training programs must first improve key aspects of staffing, technology, clinical education, and research. Addressing training challenges related to resource limitations necessitates local and international collaborations with higher-capacity centers to bridge gaps for continued quality improvement with the aim of ultimately delivering better overall cancer care.