Validation of the SSTR-RADS 1.0 for the structured interpretation of SSTR-PET/CT and treatment planning in neuroendocrine tumor (NET) patients.

ABSTRACT

OBJECTIVES: The recently proposed standardized reporting and data system for somatostatin receptor (SSTR)-targeted PET/CT SSTR-RADS 1.0 showed promising first results in the assessment of diagnosis and treatment planning with peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET). This study aimed to determine the intra- and interreader agreement of SSTR-RADS 1.0. METHODS: SSTR-PET/CT scans of 100 patients were independently evaluated by 4 readers with different levels of expertise according to the SSTR-RADS 1.0 criteria at 2 time points within 6 weeks. For each scan, a maximum of five target lesions were freely chosen by each reader (not more than three lesions per organ) and stratified according to the SSTR-RADS 1.0 criteria. Overall scan score and binary decision on PRRT were assessed. Intra- and interreader agreement was determined using the intraclass correlation coefficient (ICC). RESULTS: Interreader agreement using SSTR-RADS 1.0 for identical target lesions (ICC ≥ 0.91) and overall scan score (ICC ≥ 0.93) was excellent. The decision to state "functional imaging fulfills requirements for PRRT and qualifies patient as potential candidate for PRRT" also demonstrated excellent agreement among all readers (ICC ≥ 0.86). Intrareader agreement was excellent even among different experience levels when comparing target lesion-based scores (ICC ≥ 0.98), overall scan score (ICC ≥ 0.93), and decision for PRRT (ICC ≥ 0.88). CONCLUSION: SSTR-RADS 1.0 represents a highly reproducible and accurate system for stratifying SSTR-targeted PET/CT scans with high intra- and interreader agreement. The system is a promising approach to standardize the diagnosis and treatment planning in NET patients. KEY POINTS • SSTR-RADS 1.0 offers high reproducibility and accuracy. • SSTR-RADS 1.0 is a promising method to standardize diagnosis and treatment planning for patients with NET.