RESUMEN
The standard treatment for locally advanced cervical cancer typically includes concomitant chemoradiation, a regimen known to induce severe hematologic toxicity (HT). Particularly, pelvic bone marrow dose exposure has been identified as a contributing factor to this hematologic toxicity. Chemotherapy further increases bone marrow suppression, often necessitating treatment interruptions or dose reductions. A systematic search for original articles published between 1 January 2006 and 7 January 2024 that reported on chemoradiotherapy for locally advanced cervical cancer and hematologic toxicities was conducted. Twenty-four articles comprising 1539 patients were included in the final analysis. HT of grade 2 and higher was observed across all studies and frequently exceeded 50%. When correlating active pelvic bone marrow and HT, significant correlations were found for volumes between 10 and 45 Gy and HT of grade 3 and higher. Several dose recommendations for pelvic bone and pelvic bone marrow sparing to reduce HT were established, including V10 < 90-95%, V20 < 65-86.6% and V40 < 22.8-40%. Applying dose constraints to the pelvic bone/bone marrow is a promising approach for reducing HT, and thus reliable implementation of therapy. However, prospective randomized controlled trials are needed to define precise dose constraints and optimize clinical strategies.
RESUMEN
Background and purpose: Tools for auto-segmentation in radiotherapy are widely available, but guidelines for clinical implementation are missing. The goal was to develop a workflow for performance evaluation of three commercial auto-segmentation tools to select one candidate for clinical implementation. Materials and Methods: One hundred patients with six treatment sites (brain, head-and-neck, thorax, abdomen, and pelvis) were included. Three sets of AI-based contours for organs-at-risk (OAR) generated by three software tools and manually drawn expert contours were blindly rated for contouring accuracy. The dice similarity coefficient (DSC), the Hausdorff distance, and a dose/volume evaluation based on the recalculation of the original treatment plan were assessed. Statistically significant differences were tested using the Kruskal-Wallis test and the post-hoc Dunn Test with Bonferroni correction. Results: The mean DSC scores compared to expert contours for all OARs combined were 0.80 ± 0.10, 0.75 ± 0.10, and 0.74 ± 0.11 for the three software tools. Physicians' rating identified equivalent or superior performance of some AI-based contours in head (eye, lens, optic nerve, brain, chiasm), thorax (e.g., heart and lungs), and pelvis and abdomen (e.g., kidney, femoral head) compared to manual contours. For some OARs, the AI models provided results requiring only minor corrections. Bowel-bag and stomach were not fit for direct use. During the interdisciplinary discussion, the physicians' rating was considered the most relevant. Conclusion: A comprehensive method for evaluation and clinical implementation of commercially available auto-segmentation software was developed. The in-depth analysis yielded clear instructions for clinical use within the radiotherapy department.
