Quantification of aging effects upon knee joint global joint inflammation (GJI) by FDG-PET

Objectives The goal of this study was to quantify aging effects upon knee joint Global Joint Inflammation (GJI) by FDG-PET.

Methods This prospective study included 64 subjects who underwent FDG-PET for hip joint prosthesis evaluation where the knees were imaged as well. Mean subject age was 53 (range 33-84). A fixed size 3D ROI was placed around each knee joint while excluding the popliteal vessels. FDG-avid regions in each knee joint were segmented using an adaptive thresholding method, and metabolically active volume (MAV), SUVmean, partial-volume corrected SUVmean (cSUVmean), and partial-volume corrected mean metabolic-volumetric-product (cMVPmean=cSUVmean × MAV) of segmented regions were calculated (ROVER software, ABX GmbH, Germany). GJI for each knee joint was then calculated as the sum of cMVPmean over all segmented regions. Association of GJI with age was assessed by Pearson correlation and linear regression methods, and knee joint GJI was compared between subjects age ≤55 vs. >55 using unpaired t testing.

Results The correlation coefficient of knee joint GJI with advancing age was 0.57 (p=0.02). In the linear regression model, with GJI as the dependent variable and age and gender as independent covariates, the beta coefficient of age was 2.1 (95%CI 1.1-3.2). For subjects age ≤55 vs. >55, mean GJI was 125cc and 211cc, respectively (p=0.03).

Conclusions Using novel software analysis methodology with FDG-PET, we were able to calculate knee joint GJI and to show increasing GJI with advancing age. Since degenerative disease is age-related and inflammation is implicated in its pathogenesis, our findings further confirm this association. These preliminary data suggest that this approach can potentially provide a means to objectively quantify the degree of inflammation in various other joint disorders as well