دورية أكاديمية

Nomogram based on dual-energy CT-derived extracellular volume fraction for the prediction of microsatellite instability status in gastric cancer

التفاصيل البيبلوغرافية
العنوان: Nomogram based on dual-energy CT-derived extracellular volume fraction for the prediction of microsatellite instability status in gastric cancer
المؤلفون: Wenjun Hu, Ying Zhao, Hongying Ji, Anliang Chen, Qihao Xu, Yijun Liu, Ziming Zhang, Ailian Liu
المصدر: Frontiers in Oncology, Vol 14 (2024)
بيانات النشر: Frontiers Media S.A., 2024.
سنة النشر: 2024
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: dual-energy CT, extracellular volume fraction, gastric cancer, microsatellite instability, nomogram, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: PurposeTo develop and validate a nomogram based on extracellular volume (ECV) fraction derived from dual-energy CT (DECT) for preoperatively predicting microsatellite instability (MSI) status in gastric cancer (GC).Materials and methodsA total of 123 patients with GCs who underwent contrast-enhanced abdominal DECT scans were retrospectively enrolled. Patients were divided into MSI (n=41) and microsatellite stability (MSS, n=82) groups according to postoperative immunohistochemistry staining, then randomly assigned to the training (n=86) and validation cohorts (n=37). We extracted clinicopathological characteristics, CT imaging features, iodine concentrations (ICs), and normalized IC values against the aorta (nICs) in three enhanced phases. The ECV fraction derived from the iodine density map at the equilibrium phase was calculated. Univariate and multivariable logistic regression analyses were used to identify independent risk predictors for MSI status. Then, a nomogram was established, and its performance was evaluated by ROC analysis and Delong test. Its calibration performance and clinical utility were assessed by calibration curve and decision curve analysis, respectively.ResultsThe ECV fraction, tumor location, and Borrmann type were independent predictors of MSI status (all P < 0.05) and were used to establish the nomogram. The nomogram yielded higher AUCs of 0.826 (0.729–0.899) and 0.833 (0.675–0.935) in training and validation cohorts than single variables (P
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2234-943X
Relation: https://www.frontiersin.org/articles/10.3389/fonc.2024.1370031/full; https://doaj.org/toc/2234-943X
DOI: 10.3389/fonc.2024.1370031
URL الوصول: https://doaj.org/article/afd0373b34fa4c028ed7afbdb5e30b63
رقم الأكسشن: edsdoj.fd0373b34fa4c028ed7afbdb5e30b63
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2234943X
DOI:10.3389/fonc.2024.1370031