Polymyalgia rheumatica patients presenting with atypical clinical features still exhibit characteristic <sup>18</sup>F-FDG PET/CT findings.
Authors
Affiliations (6)
Affiliations (6)
- Department of Rheumatology, Austin Health, Heidelberg, VIC, Australia.
- Department of Medicine, University of Melbourne, Parkville, VIC, Australia.
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia.
- Olivia Newton-John Cancer Research Institute, and School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia.
- Department of Rheumatology, Austin Health, Heidelberg, VIC, Australia. [email protected].
- Department of Medicine, University of Melbourne, Parkville, VIC, Australia. [email protected].
Abstract
The utility of <sup>18</sup>F-fluorodeoxyglucose positron emission tomography with low-dose computed tomography (<sup>18</sup>F-FDG PET/CT) to diagnose patients with atypical features but clinically confirmed PMR is unknown. This study explored <sup>18</sup>F-FDG PET/CT findings among atypical PMR cases and contrasted results with a typical PMR population. The performance of an AI model for PMR diagnosis was also tested. Natural language processing searched the electronic data warehouse at our institution for <sup>18</sup>F-FDG PET/CT reports with PMR findings. Medical record review confirmed the clinical diagnosis for potential cases. Required entry Criteria of the 2012 EULAR/ACR Classification for PMR (age ≥50 years, bilateral shoulder aching and abnormal CRP and/or ESR) stratified patients as "typical" or"atypical". Qualitative and semi-quantitative (SUV<sub>max</sub>) scoring of <sup>18</sup>F-FDG uptake at characteristic musculoskeletal sites was undertaken for steroid-naïve, atypical PMR patients and compared with results for steroid-naïve, typical cases from an earlier study. A ResNet50 AI model was tested on the atypical cohort's images, with GradCam maps generated and cross-checked by an experienced clinician. 225 <sup>18</sup>F-FDG PET/CT reports were retrieved from >38,000 scans; 121 patients had a clinical PMR diagnosis. Seventeen steroid-naïve, atypical cases were compared with 35 steroid-naïve, typical patients. The frequency of abnormalities at key musculoskeletal sites was similar between groups, however mean SUV<sub>max</sub>was significantly higher in the typical cohort. The AI model identified a PMR diagnosis in 16/17 (94.1%) atypical patients. Characteristic findings of PMR are appreciated on <sup>18</sup>F-FDG PET/CT among atypical patients, but avidity is reduced. AI technology can reliably detect this imaging pattern. Words: 249 <sub>(max. 250)</sub>.