Application of a Generalized Scan Statistic Model to Evaluate TOF PET Images

Noise equivalent counts (NEC) have been used as a measure or proxy of PET image quality for many years. It has been shown to be a useful metric, for example to determine clinical patient dosage. However, NEC should be used cautiously in evaluating image quality since it is a global data quality measure that does not take into account localized effects due to spatial resolution and image reconstruction, as well as the effect of time-of-flight (TOF) imaging on resultant images. In this work, we study the use of a numerical observer that uses a generalized scan-statistic model to estimate lesion detectability with localization in a uniform background phantom, for varying activity levels and scan times. Data were acquired on a clinical whole-body TOF PET scanner. Data show that ALROC increases as a function of NEC but at high activity levels it approaches a peak value earlier than the NEC peak. Also, the ALROC for images acquired with the same NEC, but at two different activity levels and scan times, is similar. Our results show that with TOF information we can either achieve improved clinical performance for heavy patients, or reduce the scan time or injected activity while maintaining similar ALROC value as in a Non-TOF image.