ArticleBioMed research international2023
A CT-Based Radiomics Nomogram Model for Differentiating Primary Malignant Melanoma of the Esophagus from Esophageal Squamous Cell Carcinoma.
Article in BioMed research international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Review
- Predictive value of CT-based imaging model forTranslational cancer research · 2025Article
- Application of predictive model based on CT radiomics and machine learning in diagnosis for occult locally advanced esophageal squamous cell carcinoma before treatment: A two-center study.Translational oncology · 2024Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The diagnosis of primary malignant melanoma of the esophagus (PMME) before treatment is essential for clinical decision-making. However, PMME may be misdiagnosed as esophageal squamous cell carcinoma (ESCC) sometimes. This research is aimed at devising a radiomics nomogram model of CT for distinguishing PMME from ESCC. Methods: In this retrospective analysis, 122 individuals with proven pathologically PMME ( Results: For the purpose of differentiation between PMME and ESCC, a radiomics model was constructed using 5 radiomics features obtained from nonenhanced CT and 4 radiomics features derived from enhanced CT. A radiomics model including multiple radiomics features showed excellent discrimination efficiency with AUCs of 0.975 and 0.906 in the primary and validation cohorts, respectively. Then, a radiomics nomogram model was developed. The decision curve analysis has shown remarkable performance of this nomogram model for distinguishing PMME from ESCC. Conclusions: The proposed radiomics nomogram model based on CT could be used for distinguishing PMME from ESCC. Moreover, this model also contributed to helping clinicians determine an appropriate treatment strategy for esophageal neoplasms.
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Registered trials
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