ArticleRadiation oncology (London, England)2024
Predictive value of delta radiomics in xerostomia after chemoradiotherapy in patients with stage III-IV nasopharyngeal carcinoma.
Article in Radiation oncology (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 12 citations in OpenAlex.
- High-Recall Biomedical Language Models for Radiation Oncology Evidence Synthesis: An Integrated Systematic Review of Prediction Models for Radiotherapy-Induced Complications in Nasopharyngeal Carcinoma.Life (Basel, Switzerland) · 2026Review
- Longitudinal bilateral parotid delta-radiomic kinetics and variance signatures for prediction of late xerostomia following radiotherapy.BMC medical imaging · 2026Article
- SHAP-based interpretable machine learning with longitudinal delta-radiomics across seven weeks of treatment for xerostomia prediction in head-and-neck cancer.Radiation oncology (London, England) · 2026Article
- Enhancing colorectal cancer diagnosis with the ferroptosis marker GPX4 and serum biomarkers: A retrospective analysis and machine learning approach.Biochemistry and biophysics reports · 2026Article
- Delta radiomics-based nomogram for preoperative prediction vessels encapsulating tumor clusters (VETC) and prognosis in hepatocellular carcinoma using dynamic contrast-enhanced CT.BMC medical imaging · 2026Article
- Integrating MR dynamic radiomics and clinical parameters for machine learning-based prediction of short-term response to induction chemotherapy in nasopharyngeal carcinoma.Frontiers in oncology · 2026Article
- An interpretable delta ultrasound radiomics model for predicting live birth outcomes in single vitrified-warmed blastocyst transfer.Journal of ovarian research · 2025Article
- A deep learning model for predicting radiation-induced xerostomia in patients with head and neck cancer based on multi-channel fusion.BMC medical imaging · 2025Article
- Poly (hydroxyethyl methacrylate) Saliva-Gel: A Polymer-Based Solution for Xerostomia Treatment.ACS applied polymer materials · 2025Article
- Parotid preservation or immune protection? The dual dilemma in head and neck cancer radiotherapy.Frontiers in immunology · 2025Review
- Delta-radiomics analysis based on magnetic resonance imaging to identify radiation proctitis in patients with cervical cancer after radiotherapy.Frontiers in oncology · 2025Article
- Enhanced MRI Radiomics Based Model for Predicting Recurrence or Metastasis of Nasopharyngeal Cancer (NC) Undergoing Concurrent Chemoradiotherapy: A Retrospective Study.Cancer control : journal of the Moffitt Cancer CenterArticle
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6 authors at 3 institutions in 1 country.
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Abstract
backgroundXerostomia is one of the most common side effects in nasopharyngeal carcinoma (NPC) patients after chemoradiotherapy. To establish a Delta radiomics model for predicting xerostomia secondary to chemoradiotherapy for NPC based on magnetic resonance T1-weighted imaging (T1WI) sequence and evaluate its diagnostic efficacy.
methodsClinical data and Magnetic resonance imaging (MRI) data before treatment and after induction chemotherapy (IC) of 255 NPC patients with stage III-IV were collected retrospectively. Within one week after CCRT, the patients were divided into mild (92 cases) and severe (163 cases) according to the grade of xerostomia. Parotid glands in T1WI sequence images before and after IC were delineated as regions of interest for radiomics feature extraction, and Delta radiomics feature values were calculated. Univariate logistic analysis, correlation, and Gradient Boosting Decision Tree (GBDT) methods were applied to reduce the dimension, select the best radiomics features, and establish pretreatment, post-IC, and Delta radiomics xerostomia grading predictive models. The receiver operating characteristic (ROC) curve and decision curve were drawn to evaluate the predictive efficacy of different models.
resultsFinally, 15, 10, and 12 optimal features were selected from pretreatment, post-IC, and Delta radiomics features, respectively, and a xerostomia prediction model was constructed with AUC values of 0.738, 0.751, and 0.843 in the training set, respectively. Only age was statistically significant in the clinical data of both groups (P < 0.05).
conclusionDelta radiomics can predict the degree of xerostomia after chemoradiotherapy for NPC patients and it has certain guiding significance for clinical early intervention measures.
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