Direct quantification of left ventricular motion and thickening changes using rest-stress myocardial perfusion SPECT.

UNLABELLED: Changes in myocardial wall motion and thickening during myocardial perfusion SPECT are typically assessed separately from gated studies for the presence of stress-induced functional abnormalities. We sought to develop and validate a novel approach for automatic quantification of rest-stress myocardial motion and thickening changes (MTCs).
METHODS: Endocardial surfaces at the end-diastolic and end-systolic frames for rest-stress studies were registered automatically to each other by matching ventricular surfaces. Myocardial MTCs were computed, and normal limits of change were determined as the mean and SD for each polar sample. Normal limits were used to quantify the MTCs for each map, and the accumulated sample values were used for abnormality assessments in segmental regions. A hybrid method was devised by combining the total perfusion deficit (TPD) and MTC for each vessel territory. Normal limits were obtained from 100 subjects with low likelihood of coronary artery disease. For validation, 623 subjects with correlating invasive angiography were studied. All subjects underwent a rest-stress (99m)Tc-sestamibi exercise or adenosine test and coronary angiography within 3 months of myocardial perfusion SPECT. All MTC and TPD measurements were derived automatically. The diagnostic accuracy for detection of coronary artery disease for MTC plus TPD was compared with TPD alone.
RESULTS: Segmental normal values were between -1.3 and -4.1 mm for motion change and between -30.1% and -9.8% for thickening change. MTC combined with TPD achieved 61% sensitivity for 3-vessel-disease (3VD), 63% for 2-vessel-disease (2VD), and 90% for 1-vessel-disease (1VD) detection, compared with 32% for 3VD (P < 0.0001), 53% for 2VD (P < 0.001), and 90% for 1VD (P = 1.0) detection using the TPD-alone method. The specificity for the combined method was 71% for 3VD, 72% for 2VD, and 47% for 1VD detection versus 90% for 3VD (P < 0.0001), 80% for 2VD (P < 0.001), and 50% for 1VD detection (P = 0.0625) for the TPD-alone method. The accuracy of 3VD detection by MTC plus TPD was higher (69%) than the accuracy of TPD plus change in ejection fraction (63%) (P < 0.004).
CONCLUSION: We established normal limits and a novel method for computation of regional functional changes between the rest and poststress studies. Compared with TPD alone, the combination of TPD with MTC improved the sensitivity for the detection of 3VD and 2VD.