ArticleBMC medical imaging2026
Longitudinal bilateral parotid delta-radiomic kinetics and variance signatures for prediction of late xerostomia following radiotherapy.
Article in BMC medical imaging, 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
background and purposeRadiation-induced xerostomia remains a significant concern in head-and-neck cancer radiotherapy, inadequately predicted, with unidentified kinetic signatures of parotid injury. This study aimed to identify predictive metrics and reproducible bilateral parotid delta-radiomic kinetics and variance features for late xerostomia. MATERIALS AND
methodsThis retrospective study included 131 HNC patients treated with VMAT-based radiochemotherapy. Weekly CBCT images (weeks 1-7) were collected (2020-2023). Twelve-month xerostomia was graded using CTCAE v5.0. IBSI-compliant bilateral parotid radiomics were extracted and converted to delta-radiomic kinetics. Patient-level data were split (training n: 91; testing n: 40), and feature selection combined univariate filtering with recursive feature elimination. Machine-learning models with stratified 5-fold cross-validation integrated clinical-dosimetric (CD), clinical-dosimetric + delta-radiomic (CDR), and clinical-dosimetric + delta-radiomic + kinetics (CDRK). Performance was evaluated using AUC (95% CI) and other metrics, with SHAP interpretability. Reliability (ICC, CCC, R
resultsThe prevalence of 12-month grade ≥ 2 xerostomia was nearly identical between cohorts (76.9%, 77.5%; SMD: 0.014), with no significant difference observed. Predictive performance enhanced with feature incorporation and peaked mid-treatment. Clinical-dosimetric models demonstrated limited early discrimination (AUC 0.38-0.45). Delta-radiomics improved performance at week-3, while combined kinetic models achieved optimal predictive performance at week-4 (SVM-CDRK AUC 0.81, p: 0.002, sensitivity 100%, specificity 86%, Brier score 0.06, F1-score 91%). LASSO- and MLP-CDRK yielded AUCs of 0.75 (p: 0.009) and 0.73 (p: 0.011) and F1-score (86%; 79%). Texture-based GLCM features (AUC 0.79, p: 0.003) outperformed first-order and morphological descriptors. S
conclusionsLongitudinal bilateral parotid delta-radiomic kinetics significantly enhance late xerostomia prediction, identify mid-treatment as the optimal risk-stratification window, and support adaptive radiotherapy and personalized toxicity mitigation.
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