Comparison between Glioblastoma and Primary Central Nervous System Lymphoma Using MR Image-based Texture Analysis

• DOI: 10.2463/mrms.mp.2017-0044
• Publication Date: 2017-06-21T22:10:01Z
• Authors: Akira Kunimatsu; Natsuko Kunimatsu; Kouhei Kamiya; Takeyuki Watadani; Harushi Mori; Osamu Abe
• Keywords: Gray level

To elucidate differences between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) with MR image-based texture features.This was an Institutional Review Board (IRB)-approved retrospective study. Consecutive, pathologically proven, initially treated 44 patients GBM 16 PCNSL were enrolled. We calculated a total of 67 image features on the largest contrast-enhancing lesion in each patient post-contrast T1-weighted images. Texture analyses included first-order (histogram) second-order gray level co-occurrence matrix, run length matrix (GLRLM), size zone multiple matrix. All measured by two neuroradiologists independently intraclass correlation coefficients calculated. Reproducible greater than 0.7 used for hierarchical clustering cases along unpaired t statistics-based comparisons under control false discovery rate (FDR) < 0.05. Principal component analysis (PCA) performed to find predominant evaluating PCNSL.Twenty-one out satisfied acceptable coefficient FDR constraints. PCA suggested entropy, median, GLRLM-based non-uniformity, percentage as distinguished features. Compared PCNSL, median significantly lower, entropy non-uniformity higher GBM.Among textures, are considered enhance PCNSL.