Abstract #4324

Data and cluster-extent based thresholding to analyze statistical parametric maps in the study of knee articular cartilage biochemical composition.

Allison B Randolph V¹, Valentina Pedoia¹, Lorenzo Nardo¹, and Sharmila Majumdar¹

¹Radiology & Biomedical Imaging, UCSF, San Francisco, CA, United States

Voxel-based relaxometry (VBR) allows for MR relaxtion time analysis without the sometimes deletorious assumtions of traditional ROIs. However, VBR introduces potentially new analysis issues, such as noise and map heterogeneity. In this study we propose to use VBR significance thresholding in conjunction with cluster-extent based thresholding to define data-driven regions of interest (ROIs) that include the most critical information in Statistical Parametric Maps (SPM), controlling the aforesaid issues. The results suggests that the data driven voxel cluster ROIs and predefined traditional ROIs have unique, separate anatomical locations, and that the data-driven clusters perform better when correlated to osteoarthritis (OA) disease markers.

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