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Application of computerized 3D-CT texture analysis of pancreas for the assessment of patients with diabetes

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  • Siwon Jang
  • Jung Hoon Kim
  • Seo-Youn Choi
  • Sang Joon Park
  • Joon Koo Han

Abstract

Objective: To evaluate the role of computerized 3D CT texture analysis of the pancreas as quantitative parameters for assessing diabetes. Methods: Among 2,493 patients with diabetes, 39 with type 2 diabetes (T2D) and 12 with type 1 diabetes (T1D) who underwent CT using two selected CT scanners, were enrolled. We compared these patients with age-, body mass index- (BMI), and CT scanner-matched normal subjects. Computerized texture analysis for entire pancreas was performed by extracting 17 variable features. A multivariate logistic regression analysis was performed to identify the predictive factors for diabetes. A receiver operator characteristic (ROC) curve was constructed to determine the optimal cut off values for statistically significant variables. Results: In diabetes, mean attenuation, standard deviation, variance, entropy, homogeneity, surface area, sphericity, discrete compactness, gray-level co-occurrence matrix (GLCM) contrast, and GLCM entropy showed significant differences (P

Suggested Citation

  • Siwon Jang & Jung Hoon Kim & Seo-Youn Choi & Sang Joon Park & Joon Koo Han, 2020. "Application of computerized 3D-CT texture analysis of pancreas for the assessment of patients with diabetes," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0227492
    DOI: 10.1371/journal.pone.0227492
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