Purpose: To determine the effect of smooth filter and partial volume correction (PVC) method on measured prostate-specific membrane antigen (PSMA) activity in small metastatic lesions and to determine the impact of these changes on the molecular imaging (mi) PSMA scoring. Materials & Methods: Men with biochemical recurrence of prostate cancer with negative CT and bone scintigraphy were referred for 18F-DCFPyL PET/CT. Examinations were performed on one of 2 PET/CT scanners (GE Discovery 610 or Siemens mCT40). All suspected tumor sites were manually contoured on co-registered CT and PET images, and each was assigned a miPSMA score as per the PROMISE criteria. The PVC factors were calculated for every lesion using the anatomical CT and then applied to the unsmoothed PET images. The miPSMA scores, with and without the corrections, were compared, and a simplified "rule of thumb" (RoT) correction factor (CF) was derived for lesions at various sizes (<4mm, 4-7mm, 7-9mm, 9-12mm). This was then applied to the original dataset and miPSMA scores obtained using the RoT CF were compared to those found using the actual corrections. Results: There were 75 men (median age, 69 years; median serum PSA of 3.69 ug/L) with 232 metastatic nodes < 12 mm in diameter (mean lesion volume of 313.5 ± 309.6 mm3). Mean SUVmax before and after correction was 11.0 ± 9.3 and 28.5 ± 22.8, respectively (p<0.00001). The mean CF for lesions <4mm (n = 22), 4-7mm (n = 140), 7-9mm (n = 50), 9-12 mm (n = 20) was 4 (range: 2.5-6.4), 2.8 (range: 1.6-4.9), 2.3 (range: 1.6-3.3) and 1.8 (range 1.4-2.4), respectively. Overall miPSMA scores were concordant between the corrected dataset and RoT in 205/232 lesions (88.4%). Conclusion: There is a significant effect of smooth filter and partial volume correction on measured PSMA activity in small nodal metastases, impacting the miPSMA score.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 2020 Mar 20 [Epub ahead of print]
Claudia Ortega, Josh Schaefferkoetter, Patrick Veit-Haibach, Reut Anconina, Alejandro Berlin, Nathan Perlis, Ur Metser
University of Toronto, Canada., Siemens Healthcare Limited, Oakville, ON, Canada., University Health Network.