Automation of ePROMs in radiation oncology and its impact on patient response and bias.

PURPOSE: This study evaluates the impact of integrating a novel, in-house developed electronic Patient-Reported Outcome Measures (ePROMs) tool with a commercial Oncology Information System (OIS) on patient response rates and potential biases in real-world data science applications. MATERIALS AND METHODS: We designed an ePROMs tool using the NodeJS web application framework, automatically sending e-mail questionnaires to patients based on their treatment schedules in the OIS. The tool is used across various treatment sites to collect PROMs data in a real-world setting. This research examined the effects of increasing automation levels on both recruitment and response rates, as well as potential biases across different patient cohorts. Automation was implemented in three escalating levels, from telephone reminders for missing reports to minimal intervention from study nurses. RESULTS: From August 2020 to December 2023, 1,944 patients participated in the PROMs study. Our findings indicate that automating the workflows substantially reduced the patient management workload. However, higher levels of automation led to lower response rates, particularly in collecting late-phase symptoms in breast and head-and-neck cancer cohorts. Additionally, email-based PROMs introduced an age bias when recruiting new patients for the ePROMs study. Nevertheless, age was not a significant predictor of early dropout or missing symptom reports among patients participating. Notably, increased automation was significantly correlated with lower response rates in breast (p = 0.026) and head-and-neck cancer patients (p < 0.001). CONCLUSION: Integrating ePROMs within the OIS can significantly reduce workload and personnel resources. However, this efficiency may compromise patient responses in certain groups. A balance must be achieved between workload, resource allocation, and the sensitivity needed to detect clinically significant effects. This may necessitate customized automation levels tailored to specific cancer groups, highlighting a fundamental trade-off between operational efficiency and data quality.

The role of artificial intelligence in informed patient consent for radiotherapy treatments-a case report.

Recent advancements in large language models (LMM; e.g., ChatGPT (OpenAI, San Francisco, California, USA)) have seen widespread use in various fields, including healthcare. This case study reports on the first use of LMM in a pretreatment discussion and in obtaining informed consent for a radiation oncology treatment. Further, the reproducibility of the replies by ChatGPT 3.5 was analyzed. A breast cancer patient, following legal consultation, engaged in a conversation with ChatGPT 3.5 regarding her radiotherapy treatment. The patient posed questions about side effects, prevention, activities, medications, and late effects. While some answers contained inaccuracies, responses closely resembled doctors' replies. In a final evaluation discussion, the patient, however, stated that she preferred the presence of a physician and expressed concerns about the source of the provided information. The reproducibility was tested in ten iterations. Future guidelines for using such models in radiation oncology should be driven by medical professionals. While artificial intelligence (AI) supports essential tasks, human interaction remains crucial.

Multidimensional dosimetry of ¹°6Ru eye plaques using EBT3 films and its impact on treatment planning.

PURPOSE: The purpose of this study was to establish a method to perform multidimensional radiochromic film measurements of (106)Ru plaques and to benchmark the resulting dose distributions against Monte Carlo simulations (MC), microdiamond, and diode measurements. METHODS: Absolute dose rates and relative dose distributions in multiple planes were determined for three different plaque models (CCB, CCA, and COB), and three different plaques per model, using EBT3 films in an in-house developed polystyrene phantom and the mcnp6 MC code. Dose difference maps were generated to analyze interplaque variations for a specific type, and for comparing measurements against MC simulations. Furthermore, dose distributions were validated against values specified by the manufacturer (BEBIG) and microdiamond and diode measurements in a water scanning phantom. Radial profiles were assessed and used to estimate dosimetric margins for a given combination of representative tumor geometry and plaque size. RESULTS: Absolute dose rates at a reference depth of 2 mm on the central axis of the plaque show an agreement better than 5% (10%) when comparing film measurements (mcnp6) to the manufacturer's data. The reproducibility of depth-dose profile measurements was <7% (2 SD) for all investigated detectors and plaque types. Dose difference maps revealed minor interplaque deviations for a specific plaque type due to inhomogeneities of the active layer. The evaluation of dosimetric margins showed that for a majority of the investigated cases, the tumor was not completely covered by the 100% isodose prescribed to the tumor apex if the difference between geometrical plaque size and tumor base ≤4 mm. CONCLUSIONS: EBT3 film dosimetry in an in-house developed phantom was successfully used to characterize the dosimetric properties of different (106)Ru plaque models. The film measurements were validated against MC calculations and other experimental methods and showed a good agreement with data from BEBIG well within published tolerances. The dosimetric information as well as interplaque comparison can be used for comprehensive quality assurance and for considerations in the treatment planning of ophthalmic brachytherapy.

On the sensitivity of common gamma-index evaluation methods to MLC misalignments in Rapidarc quality assurance.

PURPOSE: In this study the effects of small systematic MLC misalignments and gravitational errors on the quality of Rapidarc treatment plan delivery are investigated with respect to verification measurements with two detector arrays and the evaluation of clinical significance of the error-induced deviations. METHODS: Five prostate and six head and neck plans were modified by means of three error types: (1) both MLC banks are opened, respectively, in opposing directions, resulting in larger fields; (2) both MLC banks are closed, resulting in smaller fields; and (3) both MLC banks are shifted for lateral gantry angles, respectively, in the same direction to simulate the effects of gravity on the leaves. Measurements were evaluated with respect to a gamma-index of 3%/3 mm and 2%/2 mm. Dose in the modified plans was recalculated and the resulting dose volume histograms for target and critical structures were compared to those of the unaltered plans. RESULTS: The smallest introduced leaf position deviations which fail the >90% criterion for a gamma-index of 2%/2 mm are: (1) 1 mm; (2) 0.5 mm for prostate and 1.0 mm for head and neck cases; and (3) 3 mm corresponding to the error types, respectively. These errors would lead to significant changes in mean PTV dose and would not be detected with the more commonly used 3%/3 mm gamma-index criterion. CONCLUSIONS: A stricter gamma-index (2%/2 mm) is necessary in order to detect positional errors of the MLC. Nevertheless, the quality assurance procedure of Rapidarc treatment plans must include a thorough examination of where dose discrepancies occur, and professional judgment is needed when interpreting the gamma-index analysis, since even a >90% passing rate using the 2%/2 mm gamma-index criterion does not guarantee the absence of clinically significance dose deviation.

SU-E-T-129: Rescaling of IMRT Verification Deviations from Detector Arrays into the Patient.

PURPOSE: To discuss a method of "rescaling" failures detected in a Gamma-Index analysis with detector arrays into the patient as a re-evaluation method in IMRT verifications. METHODS: In a homogeneous phantom, plane signals measured with ionisation chamber arrays during IMRT field-by-field verifications can be understood as resulting from the convolution of the incident photon fluence with two spatially invariant kernels (dose deposition in the measurement plane and spatial detector response). In principle, Gamma-Index deviations between planned and the measured plane signal profiles can therefore be "back-projected" into a deviation of the photon fluence profile from the planned one which can be "forward-projected" as a dose deviation at test points in the patient. Assuming this model for each field under investigation, all Gamma-Index failures in a certain array region can thus be "rescaled" as deviations of the patient dose and evaluated by with patient related tolerances. The method is evaluated in the prostate and H&N region by use of the 2D-ARRAY729 and VeriSoft5.0. The software offers the possibility to project the position of the ionization chambers onto the patient's CT. Thereby, the field specific analysis of deviations between measurements and plan is supported by suitable imaging procedures. Simulated Gamma-Index failures (3mm/3%) have been evaluated according to the method described above and compared with direct dose calculations. RESULTS: The degree of consistency between relative dose deviations predicted from 2D-ARRAY evaluations and corresponding relative dose deviations calculated within the patient is found to be in an acceptable range. The applicability in regions of inhomogeneity boundaries (air-tissue) and out of field regions was not included in this study and will be analyzed in the future. CONCLUSIONS: In combination with the described visualization tools, the method offers the possibility to re-evaluate the dose deviations inside the patient when Gamma-Index failures have been detected with 2D-arrays.