Quantification of SPECT myocardial perfusion images: Methodology and validation of the Yale-CQ method

Background. Quantification of single photon emission computed tomography (S PECT) images is important for reproducible and accurate image interpretatio n. In addition, SPECT quantification provides important prognostic informat ion. The purpose of this study was to validate the Yale circumferential qua ntification (Yale-CQ) method in phantom studies. Methods. Myocardial perfusion defects of varying extent and severities were simulated in a cardiac phantom with fillable defect inserts. Forty-five di fferent phantom configurations simulated 45 different myocardial perfusion defect sizes, ranging from 1.6% to 32% of the cardiac phantom volume, Autom atic processing was compared with manual processing In the phantom SPECT st udies. Results. The automatic Yale-CQ algorithm performed well in all phantom stud ies. Compared with manual processing, the mean absolute error for automatic ally determined center of short axis slices a as 0.27 pixel in the x direct ion, 0.45 pixel in the y direction, and 0.15 pixel in radius. Quantificatio n of phantom defects with the Yale-CQ method correlated well with actual de fect sizes (R = 0.99), but there was a systematic underestimation (mean en or = -7.9 %). With derived correction factors the overall correlation betwe en 45 phantom defects and actual defect sizes was excellent, and the estima tion error was significantly improved (R = 0.98, mean error = -0.82 % for m anual method and -0.95 do for automatic method). Conclusion. The automatic processing algorithm performs well for the phanto m studies. Myocardial perfusion abnormalities can he quantified accurately by use of the Yale-CQ method. Quantified SPECT defect size can be expressed as a percentage of the left ventricle.