Application of texture analysis based on T2-weighted magnetic resonance images in discriminating Gleason scores of prostate cancer
Autor: | Gu Yifeng, Zhenyu Shu, Yuezhu Jia, Feng Jianju, Pan Ruigen, Xueli Yang, Lihua Weng |
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Rok vydání: | 2020 |
Předmět: |
Male
Spearman's rank correlation coefficient 030218 nuclear medicine & medical imaging Correlation 03 medical and health sciences Prostate cancer 0302 clinical medicine Image Interpretation Computer-Assisted medicine Entropy (information theory) Humans Radiology Nuclear Medicine and imaging Gleason scores Electrical and Electronic Engineering Instrumentation Mathematics Aged Radiation medicine.diagnostic_test Receiver operating characteristic business.industry Prostate Prostatic Neoplasms Magnetic resonance imaging Middle Aged Condensed Matter Physics medicine.disease Magnetic Resonance Imaging ROC Curve 030220 oncology & carcinogenesis Analysis of variance Neoplasm Grading Nuclear medicine business |
Zdroj: | Journal of X-ray science and technology. 28(6) |
ISSN: | 1095-9114 |
Popis: | OBJECTIVE: To investigate the value of texture analysis in magnetic resonance images for the evaluation of Gleason scores (GS) of prostate cancer. METHODS: Sixty-six prostate cancer patients are retrospective enrolled, which are divided into five groups namely, GS = 6, 3 + 4, 4 + 3, 8 and 9–10 according to postoperative pathological results. Extraction and analysis of texture features in T2-weighted MR imaging defined tumor region based on pathological specimen after operation are performed by texture software OmniKinetics. The values of texture are analyzed by single factor analysis of variance (ANOVA), and Spearman correlation analysis is used to study the correlation between the value of texture and Gleason classification. Receiver operating characteristic (ROC) curve is then used to assess the ability of applying texture parameters to predict Gleason score of prostate cancer. RESULTS: Entropy value increases and energy value decreases as the elevation of Gleason score, both with statistical difference among five groups (F = 10.826, F = 2.796, P |
Databáze: | OpenAIRE |
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