ArticleJournal of radiation research2026
Patient stratification for dose scaling in cervical cancer: a model-based analysis using image-guided adaptive brachytherapy.
Article in Journal of radiation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The purpose of this study was to identify the characteristics of cervical cancer patients who benefit most from dose scaling (DS) using a model-based approach in image-guided adaptive brachytherapy (IGABT). We retrospectively analyzed 57 cervical cancer patients who underwent IGABT and external beam radiotherapy. Model-based DS was simulated to increase the brachytherapy dose until predefined normal tissue complication probability thresholds were reached. Clinically significant therapeutic gain was predefined as a tumor control probability (TCP) increase of greater than 3%, consistent with prior radiobiological modeling studies. Patient characteristics were compared between groups with and without significant TCP gain. Of the 53 patients in whom dose escalation was feasible, 16 (30.2%) achieved a significant TCP gain. A significant gain was strongly associated with histopathological type and magnetic resonance imaging (MRI) findings. All four patients (100%) with adeno/adenosquamous carcinoma (AdSq) achieved a significant gain, compared with only 12 of 49 (24.5%) with squamous cell carcinoma (P = 0.006). Uterine corpus invasion (UCI) on MRI was also a significant predictor of benefit (P < 0.001). Conversely, larger high-risk clinical target volume limited the potential for dose increase. AdSq cases demonstrated substantial improvement, with TCP increases after DS often exceeding 10%. Patients with poor prognostic features on MRI, specifically UCI, and those with histological AdSq may benefit most from DS in IGABT for cervical cancer. This exploratory study suggests that model-based DS shows promise for personalized treatment planning, supporting a shift from fixed-dose prescriptions toward strategies tailored to individual patient and tumor characteristics.
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