Journal of Nuclear Cardiology, Malek et al 2 review some of the important elements of QA procedures required to produce reliable computations of left ventricular (LV) perfusion and function parameters from gated SPECT myocardial perfusion imaging (MPI) data for the Cedars-Sinai QGS program, 3 which is a commonly used commercially available MPI analysis software package. While other algorithms operate on somewhat different principles and LV modeling assumptions, 4,5 all MPI software packages have in common the automated identification of the LV outflow tract valve plane, endocardial and epicardial borders. As the authors remind us, failure to ensure the appropriate locations of LV limits can compromise the validity of summed stress scores, summed rest scores, ejection fractions, LV volumes, LV mass, lung:heart count ratios, and transient ischemic dilatation, among other parameters.Additional parameters that can be compromised by sub-optimal LV valve plane placement include phase maps and the computed phase parameters derived from them, including phase histogram bandwidth (BW), phase standard deviation (SD), skewness, and kurtosis metrics. 6 If the LV valve plane is placed too far out beyond the end of the basal myocardium, the algorithms will misinterpret random variations of background counts as contributing to the number of pixels with contractions far from the actual phase at which the majority of regional LV contractions occurred, thereby leading to the false impression of asynchronous LAD and/or RCA territories, and an inaccurate broadening of the phase histogram curve with subsequent incorrectly large values of phase BW and SD. As phase measurements are a relatively recent extension of MPI study computations, establishing reliable values of these is important to enable capitalizing on the added dimension this has provided when evaluating patients with CAD. 7 When first presented with a newly acquired MPI dataset to be processed, users of analysis software packages frequently will first be presented with screens displaying the automated attempts to localize the LV centers and boundaries. As Malek et al 2 point out, it is important to verify that these initial automated definitions are correct, or to modify them to best conform to the visual impression of optimally appropriate choices.