Abstract
Abstract
Background
Prostate-specific membrane antigen (PSMA) PET/CT is a highly regarded radionuclide imaging modality for prostate cancer (PCa). This study aimed to evaluate the diagnostic performance of 18F-PSMA-1007 PET/CT in detecting intraprostatic lesions of PCa using radical prostatectomy (RP) specimens as a reference standard and to establish an optimal maximum standardized uptake value (SUVmax) cutoff for distinguishing between PCa and non-PCa lesions.
Methods
We retrospectively collected 117 patients who underwent 18F-PSMA-1007 PET/CT before RP. The uptake of the index tumor and contralateral non-PCa lesion was assessed. Histopathology of RP specimens was used as the gold standard. Kappa test was used to evaluate the consistency of preoperative PSMA PET/CT staging and postoperative pathological staging. Finally, an SUVmax cutoff value was identified by receiver operating characteristic (ROC) curve analysis to distinguish PCa lesions from non-PCa lesions. A prospective cohort including 76 patients was used to validate the results.
Results
The detection rate of 18F-PSMA-1007 PET/CT for prostate cancer was 96.6% (113/117). 18F-PSMA-1007 had a sensitivity of 91.2% and a positive predictive value (PPV) of 89.8% for the identification of intraprostatic lesions. The consistency test (Kappa = 0.305) indicated poor agreement between the pathologic T-stage and PSMA PET/CT T-stage. Based on ROC curve analysis, the appropriate SUVmax to diagnose PCa lesions was 8.3 (sensitivity of 71.3% and specificity 96.8%) with an area under the curve (AUC) of 0.93 (P < 0.001). This SUVmax cutoff discriminated PCa lesions from non-PCa lesions with a sensitivity of 74.4%, a specificity of 95.8% in the prospective validation group.
Conclusions
18F-PSMA-1007 PET/CT demonstrated excellent performance in detecting PCa. An optimal SUVmax threshold (8.3) could be utilized to identify lesions of PCa by 18F-PSMA-1007 PET/CT.
Trial registration
ClinicalTrials.gov Identifier: NCT04521894, Registered: August 17, 2020.
Funder
Natural Science Foundation of Shaanxi Province
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,Oncology,General Medicine,Radiological and Ultrasound Technology
Cited by
1 articles.
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