Pancreas adenocarcinoma CT texture analysis: comparison of 3D and 2D tumor segmentation techniques

• Published in: Abdominal imaging 2021-03, Vol.46 (3), p.1027-1033
• Main Authors: Kulkarni, Ameya, Carrion-Martinez, Ivan, Dhindsa, Kiret, Alaref, Amer A., Rozenberg, Radu, van der Pol, Christian B.
• Format: Article
• Language: English
• Subjects: Adenocarcinoma; Attenuation; Contouring; Correlation coefficient; Correlation coefficients; Entropy; Feature extraction; Gastroenterology; Hepatology; Homogeneity; Image processing; Image segmentation; Imaging; Kurtosis; Mean; Median (statistics); Medicine; Medicine & Public Health; Pancreas; Pancreatic cancer; Radiology; Research ethics; Skewness; Standard deviation; Tumors; Two dimensional analysis
• ISSN: 2366-004X; 2366-0058
• DOI: 10.1007/s00261-020-02759-1

Purpose To determine equivalency of multi-slice 3D CTTA and single slice 2D CTTA of pancreas adenocarcinoma. Methods This retrospective study was research ethics board approved. Untreated pancreas adenocarcinomas were segmented on CT in 128 consecutive patients. Tumor segmentation was compared using two techniques: 3D segmentation by contouring all visible tumor in a 3D volume, and 2D segmentation using only a single axial image. First-order CTTA features including mean, minimum, maximum Hounsfield units (HU), standard deviation, skewness, kurtosis, entropy, and second-order gray-level co-occurrence matrix (GLCM) features homogeneity, contrast, correlation, entropy and dissimilarity were extracted. Median values were compared using the Mann–Whitney U test with Holm–Bonferroni correction. Kendall’s Rank Correlation Tau assessed for correlation, and agreement was calculated using intraclass correlation coefficients (ICC) using a two-way model with single rating and absolute agreement. Statistical significance defined as P