This study evaluates the potential of radiometric texture analysis (radiomics) of multislice computed tomography (MSCT) images in differentiating between malignant (adenocarcinoma, neuroendocrine tumors) and benign (chronic pancreatitis, cysts) pancreatic pathologies. Unlike conventional visual assessment methods, radiometric criteria (first- and higher-order texture matrices: entropy, homogeneity, asymmetry) enable the quantification of imperceptible microstructural tissue heterogeneity using mathematical models. The results demonstrated that radiometric texture analysis provides high accuracy in the differential diagnosis of visually similar hypodense lesions (sensitivity – 88.5%, specificity – 84.2%). The clinical implementation of this method reduces the number of invasive procedures, enhances early-stage disease detection, and improves the efficacy of personalized treatment strategy selection for patients.
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Munisa Normurod qizi Ikromova (2026) studied this question.
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