Reconstruction of myocardial architecture at high resolution using diffusion tensor MRI

D. F. Scollan, A. Alexander Holmes, Jianyang Zhang, Raimond L. Winslow

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Diffusion tensor MRI (DTMRI) is a possible new means of elucidating the anatomic structure of the myocardium. It enjoys several advantages over traditional histological methods, including its ability to rapidly and nondestructively measure fiber architecture at very high resolution. However, quantitative validation of this MRI method has been lacking. Here, fiber orientations are estimated at the same locations using both DTMRI and histology in one formalin-fixed rabbit heart. Fiber orientations were statistically similar, differing on average by 5.3° (RMS) at any one location. The ventricular myofiber architecture of a number of normal rabbit hearts was then reconstructed using DTMRI into 3-D computer models for visualization. Myofiber organization appeared qualitatively similar to a previous high-resolution reconstruction using traditional histology.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Number of pages1
ISBN (Print)0780356756
StatePublished - Dec 1 1999
EventProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS) - Atlanta, GA, USA
Duration: Oct 13 1999Oct 16 1999

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
ISSN (Print)0589-1019

Other

OtherProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
CityAtlanta, GA, USA
Period10/13/9910/16/99

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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