PURPOSE - The objective of this study was to prospectively evaluate various quantitative metrics on FDG PET/CT for monitoring sunitinib therapy and predicting prognosis in patients with metastatic renal cell cancer (mRCC).
METHODS - Seventeen patients (mean age: 59.0 ± 11.6) prospectively underwent a baseline FDG PET/CT and interim PET/CT after 2 cycles (12 weeks) of sunitinib therapy. We measured the highest maximum standardized uptake value (SUVmax) of all identified lesions (highest SUVmax), sum of SUVmax with maximum six lesions (sum of SUVmax), total lesion glycolysis (TLG) and metabolic tumor volume (MTV) from baseline PET/CT and interim PET/CT, and the % decrease in highest SUVmax of lesion (%Δ highest SUVmax), the % decrease in sum of SUVmax, the % decrease in TLG (%ΔTLG) and the % decrease in MTV (%ΔMTV) between baseline and interim PET/CT, and the imaging results were validated by clinical follow-up at 12 months after completion of therapy for progression free survival (PFS).
RESULTS - At 12 month follow-up, 6/17 (35.3%) patients achieved PFS, while 11/17 (64.7%) patients were deemed to have progression of disease or recurrence within the previous 12 months. At baseline, PET/CT demonstrated metabolically active cancer in all cases. Using baseline PET/CT alone, all of the quantitative imaging metrics were predictive of PFS. Using interim PET/CT, the %Δ highest SUVmax, %Δ sum of SUVmax, and %ΔTLG were also predictive of PFS. Otherwise, interim PET/CT showed no significant difference between the two survival groups regardless of the quantitative metric utilized including MTV and TLG.
CONCLUSIONS - Quantitative metabolic measurements on baseline PET/CT appears to be predictive of PFS at 12 months post-therapy in patients scheduled to undergo sunitinib therapy for mRCC. Change between baseline and interim PET/CT also appeared to have prognostic value but otherwise interim PET/CT after 12 weeks of sunitinib did not appear to be predictive of PFS.
PloS one. 2016 Apr 28*** epublish ***
Ryogo Minamimoto, Amir Barkhodari, Lauren Harshman, Sandy Srinivas, Andrew Quon
Department of Radiology, Division of Nuclear Medicine, Stanford University School of Medicine, Stanford, CA, United States of America., Department of Radiology, Division of Nuclear Medicine, Stanford University School of Medicine, Stanford, CA, United States of America., Department of Internal Medicine, Division of Medical Oncology, Harvard Medical School, Boston, MA, United States of America., Department of Internal Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA, United States of America., Department of Radiology, Division of Nuclear Medicine, Stanford University School of Medicine, Stanford, CA, United States of America.