Identifying in vivo DCE MRI Parameters Correlated with ex vivo Quantitative Microvessel Architecture: A

We introduce a novel radiohistomorphometric method for quantitative correlation and subsequent discovery of imaging markers for aggressive prostate cancer (CaP). While this approach can be employed in the context any imaging modality and disease domain, we seek to identify quantitative dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) attributes that are highly correlated with density and architecture of tumor microvessels, surrogate markers of CaP aggressiveness. This retrospective study consisted of five Gleason score matched patients who underwent 3 Tesla multiparametric MRI prior to radical prostatectomy (RP). The excised gland was sectioned and quartered with a rotary knife. For each serial section, digitized images of individual quadrants were reconstructed into pseudo whole mount sections via previously developed stitching program. The individual quadrants were stained with vascular marker CD31 and annotated for CaP by an expert pathologist. The stained microvessel regions were quantitatively characterized in terms of density and architectural arrange-ment via graph algorithms, yielding a series of quantitative histomorphometric features. The reconstructed pseudo whole mount histologic sections were non-linearly co-registered with DCE MRI to identify tumor extent on MRI on a voxel-by-voxel basis. Pairwise correlations between kinetic and microvessel features within CaP annotated regions on the two modalities were computed to identify highly correlated attributes. Preliminar