ArticleClinical and translational radiation oncology2020
Magnetic resonance imaging-derived radiomic signature predicts locoregional failure after organ preservation therapy in patients with hypopharyngeal squamous cell carcinoma.
Article in Clinical and translational radiation oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- Pilot Study on Contrast-Enhanced CT-Based 3D Cascaded Segmentation of Hypopharyngeal Cancer and the Stability of the Extracted Radiomics Features.Journal of imaging informatics in medicine · 2026Article
- An MRI-based radiomics nomogram for detecting cervical esophagus invasion in hypopharyngeal squamous cell carcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- Radiomics in Hypopharyngeal Cancer Management: A State-of-the-Art Review.Biomedicines · 2023Review
- An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study.European radiology · 2022Article
- Exploratory ensemble interpretable model for predicting local failure in head and neck cancer: the additive benefit of CT and intra-treatment cone-beam computed tomography features.Quantitative imaging in medicine and surgery · 2021Article
- Intensity standardization methods in magnetic resonance imaging of head and neck cancer.Physics and imaging in radiation oncology · 2021Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeTo develop and validate a magnetic resonance imaging (MRI)-derived radiomic signature (RS) for the prediction of 1-year locoregional failure (LRF) in patients with hypopharyngeal squamous cell carcinoma (HPSCC) who received organ preservation therapy (OPT). MATERIAL AND
methodsA total of 800 MRI-based features of pretreatment tumors were obtained from 116 patients with HPSCC who received OPT from two independent cohorts. The least absolute shrinkage and selection operator regression model were used to select the features used to develop the RS. Harrell's C-index and corrected C-index were used to evaluate the discriminative ability of RS. The Youden index was used to select the optimal cut-point for risk category.
resultsThe RS yielded 1000 times bootstrapping corrected C-index of 0.8036 and 0.78235 in the experimental (n = 82) and validation cohorts (n = 34), respectively. With respect to the subgroup of patients with stage III/IV and cT4 disease, the RS also showed good predictive performance with corrected C-indices of 0.760 and 0.754, respectively. The dichotomized risk category using an RS of 0.0326 as the cut-off value yielded a 1-year LRF predictive accuracy of 79.27%, 79.41%, 76.74%, and 71.15% in the experimental, validation, stage III/IV, and cT4a cohorts, respectively. The low-risk group was associated with a significantly better progression-free laryngectomy-free and overall survival outcome in two independent institutions, stage III/IV, and cT4a cohorts.
conclusionThe RS-based model provides a novel and convenient approach for the prediction of the 1-year LRF and survival outcome in patients with HPSCC who received OPT.
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