Abstract
Inflammation-mediated foot osteopenia may play a pivotal role in the etiogenesis, pathogenesis, and therapeutic outcomes in individuals with diabetes mellitus (DM), peripheral neuropathy (PN), and Charcot neuroarthropathy (CN). Our objective was to establish a volumetric quantitative computed tomography-derived foot bone measurement as a candidate prognostic imaging marker to identify individuals with DMPN who were at risk of developing CN. We studied 3 groups: 16 young controls (27 ± 5 years), 20 with DMPN (57 ± 11 years), and 20 with DMPN and CN (55 ± 9 years). Computed tomography image analysis was used to measure metatarsal and tarsal bone mineral density in both feet. The mean of 12 right (7 tarsals and 5 metatarsals) and 12 left foot bone mineral densities, maximum percent difference in bone mineral density between paired bones of the right and the left feet, and the mean difference of the 12 right and the 12 left bone mineral density measurements were used as input variables in different classification analysis methods to determine the best classifier. Classification tree analysis produced no misclassification of the young controls and individuals with DMPN and CN. The tree classifier found 7 of 20 (35%) individuals with DMPN to be classified as CN (1 participant developed CN during follow-up) and 13 (65%) to be classified as healthy. These results indicate that a decision tree employing 3 measurements derived from volumetric quantitative computed tomography foot bone mineral density defines a candidate prognostic imaging marker to identify individuals with diabetes and PN who are at risk of developing CN.