Financial toxicity in cancer patients treated with radiotherapy in Germany-a cross-sectional study.

PURPOSE: Financial toxicity arises in cancer patients from subjective financial distress due to objective financial burden from the disease or treatment. Financial toxicity associates with worse outcomes. It has not been described in cancer patients undergoing radiotherapy in Germany and its publicly funded health system. In this context, we therefore investigated the prevalence of financial toxicity, associated risk factors, and patient preferences on communication of financial burden. METHODS: We conducted a preregistered ( https://doi.org/10.17605/OSF.IO/KH6VX ) cross-sectional study surveying patients at the end of their course of radiotherapy in two institutions. Objective financial burden was assessed by direct costs and loss of income. Financial toxicity was measured by subjective financial distress per EORTC QLQ-C30. We used Spearman's correlation and Fisher's exact test for univariate analysis, an ordinal regression for multivariate analysis. A p-value < 0.05 was considered statistically significant. RESULTS: Of the 100 patients participating in the study, 68% reported direct costs, 25% loss of income, and 31% subjective financial distress. Per univariate analysis, higher subjective financial distress was significantly associated with active employment, lower quality of life, lower household income, higher direct costs, and higher loss of income. The latter three factors remained statistically significant in the multivariate analysis. A relative majority of the patients welcomed communication regarding financial burden with their radiation oncologist. CONCLUSION: Financial toxicity is prevalent in cancer patients treated with radiotherapy in Germany. The reported risk factors may help to identify patients at risk. Future studies should validate these results and investigate interventions for financial toxicity to potentially improve outcomes.

Automatic image segmentation based on synthetic tissue model for delineating organs at risk in spinal metastasis treatment planning.

PURPOSE: One of the main goals in software solutions for treatment planning is to automatize delineation of organs at risk (OARs). In this pilot feasibility study a clinical validation was made of computed tomography (CT)-based extracranial auto-segmentation (AS) using the Brainlab Anatomical Mapping tool (AM). METHODS: The delineation of nine extracranial OARs (lungs, kidneys, trachea, heart, liver, spinal cord, esophagus) from clinical datasets of 24 treated patients was retrospectively evaluated. Manual delineation of OARs was conducted in clinical routine and compared with AS datasets using AM. The Dice similarity coefficient (DSC) and maximum Hausdorff distance (HD) were used as statistical and geometrical measurements, respectively. Additionally, all AS structures were validated using a subjective qualitative scoring system. RESULTS: All patient datasets investigated were successfully processed with the evaluated AS software. For the left lung (0.97 ± 0.03), right lung (0.97 ± 0.05), left kidney (0.91 ± 0.07), and trachea (0.93 ± 0.04), the DSC was high with low variability. The DSC scores of other organs (right kidney, heart, liver, spinal cord), except the esophagus, ranged between 0.7 and 0.9. The calculated HD values yielded comparable results. Qualitative assessment showed a general acceptance in more than 85% of AS OARs-except for the esophagus. CONCLUSIONS: The Brainlab AM software is ready for clinical use in most of the OARs evaluated in the thoracic and abdominal region. The software generates highly conformal structure sets compared to manual contouring. The current study design needs revision for further research.

Clinical relevance of metal artefact reduction in computed tomography (iMAR) in the pelvic and head and neck region: Multi-institutional contouring study of gross tumour volumes and organs at risk on clinical cases.

INTRODUCTION: Artefacts caused by dental implants and hip replacements may impede target volume definition and dose calculation accuracy. The iterative metal artefact reduction (iMAR) algorithm can provide a solution for this problem. The present study compares delineation of gross tumour volumes (GTVs) and organs at risk (OARs) in the pelvic and the head and neck (H & N) regions using computed tomography (CT) with and without iMAR, and thus the practical applicability of iMAR for routine clinical use. METHODS: The native planning CT and CT-iMAR data of two typical clinical cases with image-distorting artefacts were used for multi-institutional contouring and analysis using the Dice similarity coefficient (DSC). GTV/OAR contours were compared with an intraobserver approach and compared to predefined reference structures. RESULTS: Mean volume for GTVprostate in the intraobserver approach decreased from 87 ± 44 cm3 (native CT) to 75 ± 22 cm3 (CT-iMAR) (P = 0.168). Compared to the reference, DSC values for GTVP rostate increased from 0.68 ± 0.15 to 0.78 ± 0.07 (CT vs. iMAR) (P < 0.05). In the H & N region, the reference for GTVT ongue (34 cm3 ) was underestimated on both data sets. No significant improvement in DSC values (0.83 ± 0.06 (native CT) versus 0.86 ± 0.06 (CT-iMAR)) was observed. CONCLUSION: The use of iMAR improves the anatomical delineation at the transition of prostate and bladder in cases of bilateral hip replacement. In the H & N region, anatomical residual structures and experience were apparently sufficient for precise contouring.