An anatomically-unbiased approach for analysis of renal BOLD magnetic resonance images

Robert I Menzies, Andrew Zammit-Mangion, Lyam M Hollis, Ross J Lennen, Maurits A Jansen, David J Webb, John J Mullins, James W Dear, Guido Sanguinetti, Matthew A Bailey

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Oxygenation defects may contribute to renal disease progression but the chronology of events is difficult to define in vivo without recourse to invasive methodologies. BOLD MRI provides an attractive alternative but the R2* signal is physiologically complex. Post-acquisition data analysis often relies on manual selection of region(s) of interest. This approach excludes from analysis significant quantities of biological information and is subject to selection bias. We present a semi-automated, anatomically unbiased approach to compartmentalize voxels into two quantitatively related clusters. In control F344 rats, low R2* clustering was located predominantly within the cortex and higher R2* clustering within the medulla (70.96±1.48 versus 79.00±1.50; 3 scans per rat; n=6; P
Original languageEnglish
JournalAJP - Renal Physiology
DOIs
Publication statusPublished - 17 Jul 2013

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