Using an adaptive semiautomated self-evaluated registration technique to analyze MRI data for myocardial perfusion assessment

Abstract

Purpose: To validate the adaptive semiautomated self-evaluated registration technique (ASSERT) followed by factor analysis of medical image sequence (FAMIS) for analyzing myocardial perfusion using magnetic resonance imaging (MRI) images.

Materials and methods: Eleven patients having a significant stenosis of at least one coronary artery detected by coronarography were examined by thallium tomoscintigraphy and perfusion MRI (first-pass of Gd-DTPA-BMA) at rest and under pharmacologic stress. The MRI images were analyzed by ASSERT to correct for rigid motion in the acquisition plane and to reject those images that were severely deformed or acquired outside the slice plane. The images thus obtained were analyzed by FAMIS. The resulting factor images representing myocardial perfusion were read to identify the ischemic territories corresponding to left anterior descending coronary arteries and right coronary arteries.

Results: ASSERT allowed automatic correction for motion and the exclusion of images that could not be registered. The ischemic territories, identified from the factor images of the myocardium, agreed with those identified by coronarography and tomoscintigraphy for 20 of the 22 territories.

Conclusion: The results demonstrate the feasibility of analyzing myocardial perfusion using MRI acquisition and treating the resulting images by ASSERT and FAMIS. Extending this method to multislice examinations will enable evaluation of the perfusion of the whole myocardium.