TY - JOUR T1 - Can Computer-Aided CT Analysis Redefine Mediastinal Lymph Node Diagnosis? TT - Can Computer-Aided CT Analysis Redefine Mediastinal Lymph Node Diagnosis? AU - Arık, Şeref Barbaros AU - Canoğlu, Kadir PY - 2025 DA - September Y2 - 2025 JF - Yüksek İhtisas Üniversitesi Sağlık Bilimleri Dergisi JO - YIU Saglik Bil Derg PB - Yüksek İhtisas Üniversitesi WT - DergiPark SN - 2717-8439 SP - 41 EP - 47 VL - 6 IS - 2 LA - en AB - AbstractBackground: Accurate mediastinal lymph node evaluation is essential in the diagnosis and staging of malignant tumors. Traditional size-based criteria pose challenges, particularly for smaller nodes, necessitating alternative approaches.Objective: To investigate the diagnostic value of volume, calculated diameter, and HU values obtained using computer-aided software in distinguishing between benign and malignant mediastinal lymph nodes on contrast-enhanced and non-contrast thoracic CT.Methods: A retrospective analysis of 103 patients with 172 lymph nodes. Quantitative metrics were derived using the "Vitrea Lung Nodule Analysis" software. Diagnostic performance was assessed using ROC analysis, and statistical associations were examined through univariate and multivariate logistic regression models.Results: Age and male gender were significant predictors of malignancy (p KW - Mediastinal Lymph Nodes KW - Computed Tomography (CT) KW - Lung Cancer KW - Artificial Intelligence KW - Lymph Node Metastasis KW - Computer-Aided Diagnosis N2 - Background: Accurate mediastinal lymph node evaluation is essential in the diagnosis and staging of malignant tumors. Traditional size-based criteria pose challenges, particularly for smaller nodes, necessitating alternative approaches.Objective: To investigate the diagnostic value of volume, calculated diameter, and HU values obtained using computer-aided software in distinguishing between benign and malignant mediastinal lymph nodes on contrast-enhanced and non-contrast thoracic CT.Methods: A retrospective analysis of 103 patients with 172 lymph nodes. Quantitative metrics were derived using the "Vitrea Lung Nodule Analysis" software. Diagnostic performance was assessed using ROC analysis, and statistical associations were examined through univariate and multivariate logistic regression models.Results: Age and male gender were significant predictors of malignancy (p CR - Panunzio A, Sartori P. Lung cancer and radiological imaging. Curr Radiopharm. 2020;13(3):238–242. https://doi.org/10.2174/1874471013666200523161849 CR - Barta JA, Powell CA, Wisnivesky JP. Global epidemiology of lung cancer. Ann Glob Health. 2019;85(1). https://doi.org/10.5334/aogh.2419 CR - Ning J, Ge T, Jiang M, Jia K, Wang L, Li W, et al. Early diagnosis of lung cancer: which is the optimal choice? Aging (Albany NY). 2021;13(4):6214 6227. https://doi.org/10.18632/aging.202504 CR - Polat G, Polat M, Meletlioglu E. Effect of contrast medium on early detection and analysis of mediastinal lymph nodes in computed tomography (1992). 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