18 F sodium fluoride PET/CT in patients with prostate cancer: Quantification of normal tissues, benign degenerative lesions, and malignant lesions

Abstract

Understanding the range and variability of normal, benign degenerative, and malignant 18 F sodium fluoride ( 18 F NaF) positron emission tomography/computed tomography (PET/CT) uptake is important in influencing clinical interpretation. Further, it is essential for the development of realistic semiautomated quantification techniques and simulation models. The purpose of this study is to determine the range of these values in a clinically relevant patient population with prostate cancer. 18 F NaF PET/CT scans were analyzed in patients with prostate cancer (n = 47) referred for evaluation of bone metastases. Mean and maximum standardized uptake values [SUVs (SUV mean and SUV max )] were made in normal background regions (n = 470) including soft tissues (liver, aorta, bladder, adipose, brain, and paraspinal muscle) and osseous structures (T12 vertebral body, femoral diaphyseal cortex, femoral head medullary space, and ribs). Degenerative joint disease (DJD; n = 281) and bone metastases (n = 159) were identified and quantified by an experienced reader using all scan information including coregistered CT. For normal bone regions, the highest 18 F NaF PET SUV mean occurred in T12 (6.8 ± 1.4) and it also showed the lowest coefficient of variation (cv = 21%). For normal soft tissues, paraspinal muscles showed very low SUV mean (0.70 ± 0.11) and also showed the lowest variability (cv = 16%). Average SUV mean in metastatic lesions is higher than uptake in benign degenerative lesions but values showed a wide variance and overlapping values (16.3 ± 13 vs 11.1 ± 3.8; P < 0.00001). The normal 18 F NaF PET uptake values for prostate cancer patients in normal background, benign degenerative disease, and osseous metastases are comparable to those reported for a general population with a wide variety of diagnoses. These normal ranges, specifically for prostate cancer patients, will aid in clinical interpretation and also help to establish the basis of normal limits in a semiautomated data analysis algorithm.