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.

Heparin treatment mitigates radiation-induced oral mucositis in mice by interplaying with repopulation processes.

PURPOSE: To investigate the mechanistic background of the muco-protective effect of systemic heparin treatment on the development of radiation-induced oral mucositis in mice. MATERIALS AND METHODS: Fractionated irradiation was given to the snouts of male C3H/Neu mice over 2 weeks (10â€¯× 3 Gy), either alone or in combination with daily subcutaneous application of unfractionated or low molecular weight heparin (40 or 200 I.U./mouse, respectively). Over this course of 14 days, groups of mice (n = 3) were sacrificed every second day, their tongues excised and processed for histological analysis. The epithelial radiation response with and without heparin treatment was evaluated in terms of tissue morphology, proliferation and expression of cell contact molecules. RESULTS: Systemic treatment with heparins significantly reduced the cellular effects of irradiation to the oral epithelium. Heparin treated animals showed significantly higher total epithelial cell numbers and thickness throughout the study course. Bromodeoxyuridine (BrdU) incorporation analyses revealed that markedly more epithelial cells retained their proliferative capacity in the beginning of the first treatment week, but the proliferation of the mucosa was not stimulated during the rest of the study course. The expression of the adherens junction protein ß­catenin was slightly elevated in heparin treated animals, on day 2 the increase was statistically significant. The expression of e­cadherin and occludin was mostly unaffected by the concomitant heparin treatment. CONCLUSION: The findings of this study indicate an interplay of additional heparin treatment with the repopulation processes, leading to an earlier onset of this adaptive radiation response in oral mucosa. Importantly, we could demonstrate that the protective potential of heparin did not rely on stimulation of normal tissue proliferation. Since both heparin preparations are already approved for clinical use, they are considered as promising candidates for future clinical studies.

Impact of androgen deprivation therapy on apparent diffusion coefficient and T2w MRI for histogram and texture analysis with respect to focal radiotherapy of prostate cancer.

PURPOSE: Accurate prostate cancer (PCa) detection is essential for planning focal external beam radiotherapy (EBRT). While biparametric MRI (bpMRI) including T2-weighted (T2w) and diffusion-weighted images (DWI) is an accurate tool to localize PCa, its value is less clear in the case of additional androgen deprivation therapy (ADT). The aim of this study was to investigate the value of a textural feature (TF) approach on bpMRI analysis in prostate cancer patients with and without neoadjuvant ADT with respect to future dose-painting applications. METHODS: 28 PCa patients (54-80 years) with (n = 14) and without (n = 14) ADT who underwent bpMRI with T2w and DWI were analyzed retrospectively. Lesions, central gland (CG), and peripheral zone (PZ) were delineated by an experienced urogenital radiologist based on localized pre-therapeutic histopathology. Histogram parameters and 20 Haralick TF were calculated. Regional differences (i. e., tumor vs. PZ, tumor vs. CG) were analyzed for all imaging parameters. Receiver-operating characteristic (ROC) analysis was performed to measure diagnostic performance to distinguish PCa from benign prostate tissue and to identify the features with best discriminative power in both patient groups. RESULTS: The obtained sensitivities were equivalent or superior when utilizing the TF in the no-ADT group, while specificity was higher for the histogram parameters. However, in the ADT group, TF outperformed the conventional histogram parameters in both specificity and sensitivity. Rule-in and rule-out criteria for ADT patients could exclusively be defined with the aid of TF. CONCLUSIONS: The TF approach has the potential for quantitative image-assisted boost volume delineation in PCa patients even if they are undergoing neoadjuvant ADT.

On the feasibility of automatic detection of range deviations from in-beam PET data.

In-beam PET is a clinically proven method for monitoring ion beam cancer treatment. The objective is predominantly the verification of the range of the primary particles. Due to different processes leading to dose and activity, evaluation is done by comparing measured data to simulated. Up to now, the comparison is performed by well-trained observers (clinicians, physicists). This process is very time consuming and low in reproducibility. However, an automatic method is desirable. A one-dimensional algorithm for range comparison has been enhanced and extended to three dimensions. System-inherent uncertainties are handled by means of a statistical approach. To test the method, a set of data was prepared. Distributions of ß(+)-activity calculated from treatment plans were compared to measurements performed in the framework of the German Heavy Ion Tumor Therapy Project at GSI Helmholtz Centre for Heavy Ion Research, Darmstadt, Germany. Artificial range deviations in the simulations served as test objects for the algorithm. Range modifications of different depth (4, 6 and 10 mm water equivalent path length) can be detected. Even though the sensitivity and specificity of a visual evaluation are higher, the method is feasible as the basis for the selection of patients from the data pool for retrospective evaluation of treatment and treatment plans and correlation with follow-up data. Furthermore, it can be used for the development of an assistance tool for a clinical application.