Assessing the effects of body weight on subchondral bone formation with quantitative 18F-sodium fluoride PET.

Abstract

The aim of this study was to quantify subchondral bone remodeling in the elbows, hands, knees, and feet using volumetric and metabolic parameters derived from 18F-sodium fluoride positron emission tomography (NaF-PET) and to assess the convergent validity of these parameters as an index of joint degeneration and preclinical osteoarthritis. A retrospective analysis was conducted in 34 subjects (32 males, 2 females) with metastatic bone disease who underwent full-body NaF-PET/CT scans. An adaptive contrast-oriented thresholding algorithm was applied to segment NaF-avid regions in the bilateral elbows, hands, knees, and feet of each subject, and metabolically active volume (MAV), maximum standardized uptake value (SUVmax), mean metabolic volumetric product (MVPmean), and partial volume-corrected MVPmean (cMVPmean) of the segmented regions were calculated. Global parameters for MAV, SUVmax, MVPmean, and cMVPmean were defined as the sum of the corresponding values in all the joints of a subject. Inter-rater reliability was determined with Lin's concordance correlation, and associations of global values with subject body weight and age were assessed with Pearson correlation and Spearman correlation analyses. Inter-rater reliability was observed to be the highest in SUVmax (ρc = 0.99), followed by MVPmean (ρc = 0.96), cMVPmean (ρc = 0.93), and MAV (ρc = 0.93). MAV, MVPmean, and cMVPmean were observed to significantly increase with weight (all p < 0.0001) determined by Pearson correlation. In addition, Spearman rank-order analysis demonstrated a significant correlation between SUVmax and weight in addition to MAV, MVPmean, and cMVPmean and weight (all p < 0.01). No significant association between age and any PET parameter was observed. These preliminary data demonstrate the feasibility and reliability of assessing bone turnover at the joints using quantitative NaF-PET. Our findings corroborate the fact that biomechanical factors including mechanical loading and weight-bearing are contributors to osteoarthritis disease progression.