http://www.nitrc.org/forum/forum.php?forum_id=6230 <table border="0" width="100%"><tr><td align="left"/></tr></table> <p><b>Radiomic Texture Analysis Mapping Predicts Areas of True Functional MRI Activity.</b></p> <p>Sci Rep. 2016;6:25295</p> <p>Authors: Hassan I, Kotrotsou A, Bakhtiari AS, Thomas GA, Weinberg JS, Kumar AJ, Sawaya R, Luedi MM, Zinn PO, Colen RR</p> <p>Abstract<br/> Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias. <br/> </p><p>PMID: 27151623 [PubMed - in process]</p> en-us Copyright 2000-2026 NITRC OSI Mon, 04 May 2026 23:04:31 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator