Stroke infarct volume estimation in fixed tissue: Comparison of diffusion kurtosis imaging to diffusion weighted imaging and histology in a rodent MCAO model

PLoS One. 2018 Apr 26;13(4):e0196161. doi: 10.1371/journal.pone.0196161. eCollection 2018.

Abstract

Diffusion kurtosis imaging (DKI) is a new promising MRI technique with microstructural sensitivity superior to conventional diffusion tensor (DTI) based methods. In stroke, considerable mismatch exists between the infarct lesion outline obtained from the two methods, kurtosis and diffusion tensor derived metrics. We aim to investigate if this mismatch can be examined in fixed tissue. Our investigation is based on estimates of mean diffusivity (MD) and mean (of the) kurtosis tensor (MKT) obtained using recent fast DKI methods requiring only 19 images. At 24 hours post stroke, rat brains were fixed and prepared. The infarct was clearly visible in both MD and MKT maps. The MKT lesion volume was roughly 31% larger than the MD lesion volume. Subsequent histological analysis (hematoxylin) revealed similar lesion volumes to MD. Our study shows that structural components underlying the MD/MKT mismatch can be investigated in fixed tissue and therefore allows a more direct comparison between lesion volumes from MRI and histology. Additionally, the larger MKT infarct lesion indicates that MKT do provide increased sensitivity to microstructural changes in the lesion area compared to MD.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Brain / diagnostic imaging*
  • Brain / pathology
  • Brain / physiology
  • Diffusion Magnetic Resonance Imaging*
  • Diffusion Tensor Imaging*
  • Disease Models, Animal
  • Infarction, Middle Cerebral Artery / diagnostic imaging*
  • Infarction, Middle Cerebral Artery / pathology
  • Male
  • Rats
  • Rats, Sprague-Dawley

Grants and funding

This work was supported by the Danish Heart Association, the Velux Foundation (ARCADIA), Cabinetmaker Sophus Jacobsen & wife Astrid Jacobsens Foundation and Aarhus University. The 9.4-T scanner system was funded by the Danish Research Council's Infrastructure program, the Velux Foundation and the Department of Clinical Medicine, Aarhus University. The Villum Foundation supported the Centre for Stochastic Geometry and Advanced Bioimaging. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.