Comparison of fully automated computer analysis and visual scoring for detection of coronary artery disease from myocardial perfusion SPECT in a large population.

Journal of Nuclear Medicine

PubMedID: 23315665

Arsanjani R, Xu Y, Hayes SW, Fish M, Lemley M, Gerlach J, Dorbala S, Berman DS, Germano G, Slomka P. Comparison of fully automated computer analysis and visual scoring for detection of coronary artery disease from myocardial perfusion SPECT in a large population. J Nucl Med. 2013;54(2):221-8.
UNLABELLED
We compared the performance of fully automated quantification of attenuation-corrected (AC) and noncorrected (NC) myocardial perfusion SPECT (MPS) with the corresponding performance of experienced readers for detection of coronary artery disease (CAD).

METHODS
Rest-stress (99m)Tc-sestamibi MPS studies (n = 995; 650 consecutive cases with coronary angiography and 345 with likelihood of CAD < 5%) were obtained by MPS with AC. The total perfusion deficit (TPD) for AC and NC data was compared with the visual summed stress and rest scores of 2 experienced readers. Visual reads were performed in 4 consecutive steps with the following information progressively revealed: NC data, AC + NC data, computer results, and all clinical information.

RESULTS
The diagnostic accuracy of TPD for detection of CAD was similar to both readers (NC: 82% vs. 84%; AC: 86% vs. 85%-87%; P = not significant) with the exception of the second reader when clinical information was used (89%, P < 0.05). The receiver-operating-characteristic area under the curve (ROC AUC) for TPD was significantly better than visual reads for NC (0.91 vs. 0.87 and 0.89, P < 0.01) and AC (0.92 vs. 0.90, P < 0.01), and it was comparable to visual reads incorporating all clinical information. The per-vessel accuracy of TPD was superior to one reader for NC (81% vs. 77%, P < 0.05) and AC (83% vs. 78%, P < 0.05) and equivalent to the second reader (NC, 79%; and AC, 81%). The per-vessel ROC AUC for NC (0.83) and AC (0.84) for TPD was better than that for the first reader (0.78-0.80, P < 0.01) and comparable to that of the second reader (0.82-0.84, P = not significant) for all steps.

CONCLUSION
For detection of =70% stenoses based on angiographic criteria, a fully automated computer analysis of NC and AC MPS data is equivalent for per-patient and can be superior for per-vessel analysis, when compared with expert analysis.