An investigation of the trade-off between the count level and image quality in myocardial perfusion SPECT using simulated images: the effects of statistical noise and object variability on defect detectability.

Quantum noise as well as anatomic and uptake variability in patient populations limits observer performance on a defect detection task in myocardial perfusion SPECT (MPS). The goal of this study was to investigate the relative importance of these two effects by varying acquisition time, which determines the count level, and assessing the change in performance on a myocardial perfusion (MP) defect detection task using both mathematical and human observers. We generated ten sets of projections of a simulated patient population with count levels ranging from 1/128 to around 15 times a typical clinical count level to simulate different levels of quantum noise. For the simulated population we modeled variations in patient, heart and defect size, heart orientation and shape, defect location, organ uptake ratio, etc. The projection data were reconstructed using the OS-EM algorithm with no compensation or with attenuation, detector response and scatter compensation (ADS). The images were then post-filtered and reoriented to generate short-axis slices. A channelized Hotelling observer (CHO) was applied to the short-axis images, and the area under the receiver operating characteristics (ROC) curve (AUC) was computed. For each noise level and reconstruction method, we optimized the number of iterations and cutoff frequencies of the Butterworth filter to maximize the AUC. Using the images obtained with the optimal iteration and cutoff frequency and ADS compensation, we performed human observer studies for four count levels to validate the CHO results. Both CHO and human observer studies demonstrated that observer performance was dependent on the relative magnitude of the quantum noise and the patient variation. When the count level was high, the patient variation dominated, and the AUC increased very slowly with changes in the count level for the same level of anatomic variability. When the count level was low, however, quantum noise dominated, and changes in the count level resulted in large changes in the AUC. This behavior agreed with a theoretical expression for the AUC as a function of quantum and anatomical noise levels. The results of this study demonstrate the importance of the tradeoff between anatomical and quantum noise in determining observer performance. For myocardial perfusion imaging, it indicates that, at current clinical count levels, there is some room to reduce acquisition time or injected activity without substantially degrading performance on myocardial perfusion defect detection.