Y Li1, C Yan2, S Weng3, Z Shi2, H Sun2, J Chen2, X Xu2, R Ye2, J Hong4. 1. Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350005, China. Electronic address: fjmulym@163.com. 2. Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350005, China. 3. Department of Radiology, Fujian Provincial Maternity and Child Health Hospital, Fuzhou, Fujian, China. 4. Department of Radiation Oncology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350005, China.
Abstract
AIM: To determine whether texture analysis of preoperative magnetic resonance imaging (MRI) images could be used to detect Ki67 expression, a widely used cell proliferation marker in hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In total, 83 patients were included, 25 with low Ki67 (Ki67 ≤10%) HCC expression and 58 with high Ki67 (Ki67 ≥10%) HCC expression as demonstrated by retrospective surgical evaluation. All patients were examined using a 3 T MRI unit with one standard protocol. The region of interest was drawn manually by one radiologist. Texture analysis included histogram, co-occurrence matrix, run-length matrix, gradient, auto-regressive model, and wavelet transform features as calculated by MaZda (version 4.6; quantitative texture analysis software). The features reduced by the Fisher, probability of classification error, and average correlation coefficient (POE+ACC), mutual information were used to select the features that predicted Ki67 proliferation status with highest accuracy and then using the B11 program for data analysis and classification. RESULTS: The misclassification rate of the principal component analysis (PCA) in the hepatobiliary phase (HBP), T2-weighted imaging (T2WI), arterial phase (AP), and portal vein phase (PVP) was 36/83 (43.37%), 35/82 (42.68%), 40/83 (48.19%), and 34/83 (40.96%), respectively. The misclassification of the linear discriminant analysis in HBP, T2WI, AP, and PVP phase was 13/83 (15.66%), 21/82 (25.61%), 9/83 (10.84%), and 8/83 (9.64%), respectively. The misclassification of the nonlinear discriminant analysis in HBP, T2WI, AP, and PVP phase was 7/83 (8.43%), 6/82 (7.32%), 5/83 (6.02%), and 7/83 (8.43%), respectively. CONCLUSIONS: Texture analysis of HBP, AP, and PVP were helpful for predicting Ki67 expression and may provide a less-invasive method to investigate critical histopathology markers for HCC.
AIM: To determine whether texture analysis of preoperative magnetic resonance imaging (MRI) images could be used to detect Ki67 expression, a widely used cell proliferation marker in hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In total, 83 patients were included, 25 with low Ki67 (Ki67 ≤10%) HCC expression and 58 with high Ki67 (Ki67 ≥10%) HCC expression as demonstrated by retrospective surgical evaluation. All patients were examined using a 3 T MRI unit with one standard protocol. The region of interest was drawn manually by one radiologist. Texture analysis included histogram, co-occurrence matrix, run-length matrix, gradient, auto-regressive model, and wavelet transform features as calculated by MaZda (version 4.6; quantitative texture analysis software). The features reduced by the Fisher, probability of classification error, and average correlation coefficient (POE+ACC), mutual information were used to select the features that predicted Ki67 proliferation status with highest accuracy and then using the B11 program for data analysis and classification. RESULTS: The misclassification rate of the principal component analysis (PCA) in the hepatobiliary phase (HBP), T2-weighted imaging (T2WI), arterial phase (AP), and portal vein phase (PVP) was 36/83 (43.37%), 35/82 (42.68%), 40/83 (48.19%), and 34/83 (40.96%), respectively. The misclassification of the linear discriminant analysis in HBP, T2WI, AP, and PVP phase was 13/83 (15.66%), 21/82 (25.61%), 9/83 (10.84%), and 8/83 (9.64%), respectively. The misclassification of the nonlinear discriminant analysis in HBP, T2WI, AP, and PVP phase was 7/83 (8.43%), 6/82 (7.32%), 5/83 (6.02%), and 7/83 (8.43%), respectively. CONCLUSIONS: Texture analysis of HBP, AP, and PVP were helpful for predicting Ki67 expression and may provide a less-invasive method to investigate critical histopathology markers for HCC.
Authors: Emily Harding-Theobald; Jeremy Louissaint; Bharat Maraj; Edward Cuaresma; Whitney Townsend; Mishal Mendiratta-Lala; Amit G Singal; Grace L Su; Anna S Lok; Neehar D Parikh Journal: Aliment Pharmacol Ther Date: 2021-08-12 Impact factor: 9.524