A Virtual Clinical Trial to Detect Changes in Tumor Uptake with PET using Lesion Embedding

We conducted a virtual clinical trial (VCT) using patient data from the PennPET Explorer scanner and embedded lesions to model tumor response to therapy as measured by a change in the standardized uptake value (SUV). Two patient data sets (high and low BMI) were bootstrapped prior to embedding data from separately acquired sphere-in-air data sets. In each bootstrapped dataset, 20 small lesions (1 cm diameter) were embedded, 10 each in lung and liver organs. Multiple scans were reconstructed using list-mode time of flight-ordered subset expectation maximization (TOF-OSEM) for varying scan durations and pre-defined lesion uptake values. The resulting SUV measurements were utilized to construct receiver operating characteristic (ROC) curves to evaluate the system's ability to discriminate between different values of lesion uptake corresponding to therapy-induced changes. The area under the ROC curve (AUC) was used as a summary metric of this discrimination performance. Our results demonstrate that long axial field of view (LAFOV) PET scanners with high sensitivity may effectively detect early tumor response to therapy, even with brief scan durations (1 minute scan) or, equivalently, with reduced activity. The AUC values change very slowly with increasing scan duration, suggesting that performance is not primarily limited by count statistics within the studied range. The AUC values are also not very sensitive to the patient BMI or the type of SUV metrics (i.e. SUV_mean and SUV_max), and are relatively independent of the local background (organ) uptake. The primary factor determining the AUC values seems to be the absolute change in lesion uptake that will be sensitive to partial volume effects as determined by the scanner spatial resolution. Hence, a standard axial field-of-view scanner with similar spatial resolution will likely perform as well as a LAFOV scanner after appropriate compensation for the sensitivity differences.