ArticleJapanese journal of radiology2026
Role of extracellular volume fraction determined by dual-layer spectral detector CT in predicting the tumor grade of pancreatic neuroendocrine neoplasms.
Article in Japanese journal of radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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- Comment on "Role of extracellular volume fraction determined by dual-layer spectral detector CT in predicting the tumor grade of pancreatic neuroendocrine neoplasms".Japanese journal of radiology · 2026Article
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Abstract
purposeTo evaluate the CT imaging features including extracellular volume (ECV) fraction measured by dual-layer spectral detector CT for differentiating G1 from G2 tumors in pancreatic neuroendocrine neoplasms (pNENs), as compared with single-energy CT (SECT). MATERIALS AND
methodsThis retrospective study included 45 patients with histologically confirmed pNENs (G1, n = 28; G2, n = 17) who underwent dynamic contrast-enhanced CT using a dual-layer spectral detector system. Attenuation values were measured on unenhanced and the equilibrium-phase 120-kVp equivalent CT images for tumor and the aorta, and SECT-ECV fraction was calculated. Iodine densities of the tumor and aorta were measured in the equilibrium phase, and dual-energy CT (DECT)-ECV fraction of the tumor was calculated. Histological tumor cell density and Ki-67 index were also assessed to evaluate the correlations with ECV fractions. Statistical analysis was performed to identify independent predictors of tumor grade and evaluate diagnostic performance using receiver operating characteristic (ROC) analysis.
resultsDECT-ECV fractions were significantly lower in G2 tumors than in G1 tumors (p = 0.0045). G2 tumors tended to be larger than G1 tumors (p = 0.0591), while no other CT features were significantly different between G1 and G2 tumors. The multivariable analysis showed that only DECT-ECV fraction was significantly associated with tumor grade (p = 0.0115). ROC analysis for the DECT-ECV fraction showed an area under the curve of 0.756. DECT-ECV fraction demonstrated significant inverse correlations with tumor cell density (ρ = - 0.434, p = 0.0065) and Ki-67 index (ρ = - 0.440, p = 0.0025).
conclusionAmong the CT imaging findings, only DECT-ECV fraction showed a significant difference between G1 and G2 tumors. DECT-ECV fraction appears to be a useful imaging biomarker for differentiating G1 from G2 tumors in pNENs.
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