Background: There is no accepted methodology for CT-based vasodilator stress myocardial perfusion imaging and analysis. We developed a technique for quantitative 3D analysis of CT images, which provides several indices of myocardial perfusion. We sought to determine the ability of these indices during vasodilator stress to identify segments supplied by coronary arteries with obstructive disease and to test the accuracy of the detection of perfusion abnormalities against SPECT. Methods: We studied 93 patients referred for CT coronary angiography (CTCA) who underwent regadenoson stress. 3D analysis of stress CT images yielded segmental perfusion indices: mean X-ray attenuation, severity of defect and relative defect volume. Each index was averaged for myocardial segments, grouped by severity of stenosis: 0%, <50%, 50-70%, and >70%. Objective detection of perfusion abnormalities was optimized in 47 patients and then independently tested in the remaining 46 patients. Results: CTCA depicted normal coronary arteries or non-obstructive disease in 62 patients and stenosis of >50% in 31. With increasing stenosis, segmental attenuation showed a 7% decrease, defect severity increased 11%, but relative defect volume was 7-fold higher in segments with obstructive disease (p<0.001). In the test group, detection of perfusion abnormalities associated with stenosis >50% showed sensitivity 0.78, specificity 0.54, accuracy 0.59. When compared to SPECT in a subset of 21 patients (14 with abnormal SPECT), stress CT perfusion analysis showed sensitivity 0.79, specificity 0.71, accuracy 0.76. Conclusions: 3D analysis of vasodilator stress CT images provides quantitative indices of myocardial perfusion, of which relative defect volume was most robust in identifying segments supplied by arteries with obstructive disease. This study may have implications on how CT stress perfusion imaging is performed and analyzed.