Role of diffusion tensor imaging in diagnosis of patients with carpal tunnel syndrome

BackgroundCarpal tunnel syndrome is the commonest upper limb peripheral neuropathy. Diffusion tensor imaging evaluates the tissue microarchitecture and measures the movement of water protons. It is non-time-consuming, not invasive and not operator dependent. The aim of our study was to evaluate whether diffusion tensor imaging can diagnose carpal tunnel syndrome and whether DTI parameters can correlate with severity of carpal tunnel syndrome.ResultsSeventy-two wrists were assessed, 36 diagnosed with carpal tunnel syndrome and 36 age and sex matched controls. FA & ADC were measured at four locations (distal radioulnar joint, proximal, middle and distal carpal tunnel), and the mean for the whole median nerve was calculated. FA & ADC showed statistically significant difference between cases and control at each of the measured four locations and the mean of the whole median nerve. FA & ADC at the hook of hamate (distal CT) showed the most significant difference between cases and control. For FA, the cut-off point at the hook of hamate was 0.5 (sensitivity 94.4%, specificity of 88.9%, positive predictive value 89.5% and negative predictive value 94.1%) and the cut-off point for the mean of the whole nerve was 0.545 (sensitivity 97.22%, specificity 77.78%, positive predictive value 81.4% and negative predictive value 96.6%). For ADC, the cut-off point at the hook of hamate was 1.44 (sensitivity 97.22%, specificity 86.11%, positive predictive value 87.5% and negative predictive value 96.9%) and the cut-off point for the mean of the whole nerve was 1.415 (sensitivity 86.11%, specificity, 83.33%, positive predictive value 83.8% and negative predictive value 85.7%).ConclusionDiffusion tensor imaging can diagnose carpal tunnel syndrome with accuracy compared to the gold standard nerve conduction studies. Both FA and ADC showed statistically significant differences between cases & controls with FA measurements found to be more significant.