Neuropathy Score Reporting and Data System: A Reporting Guideline for MRI of Peripheral Neuropathy With a Multicenter Validation Study.
Academic Article
Overview
abstract
BACKGROUND. A standardized guideline and scoring system would improve evaluation and reporting of peripheral neuropathy (PN) on MRI. OBJECTIVE. The objective of this study was to create and validate a neuropathy classification and grading system, which we named the Neuropathy Score Reporting and Data System (NS-RADS). METHODS. This retrospective study included 100 patients with nerve imaging studies and known clinical diagnoses. Experts crafted NS-RADS using mutually agreed-on qualitative criteria for the classification and grading of PN. Different classes were created to account for the spectrum of underlying pathologies: unremarkable (U), injury (I), neoplasia (N), entrapment (E), diffuse neuropathy (D), not otherwise specified (NOS), and postintervention state (PI). Subclasses were established to describe the severity or extent of the lesions. Validation testing was performed by 11 readers from 10 institutions with experience levels ranging from 3 to 18 years after residency. After initial reader training, cases were presented to readers who were blinded to the final clinical diagnoses. Interobserver agreement was assessed using correlation coefficients and the Conger kappa, and accuracy testing was performed. RESULTS. Final clinical diagnoses included normal (n = 5), nerve injury (n = 25), entrapment (n = 15), neoplasia (n = 33), diffuse neuropathy (n = 18), and persistent neuropathy after intervention (n = 4). The miscategorization rate for NS-RADS classes was 1.8%. Final diagnoses were correctly identified by readers in 71-88% of cases. Excellent inter-reader agreement was found on the NS-RADS pathology categorization (κ = 0.96; 95% CI, 0.93-0.98) as well as muscle pathology categorization (κ = 0.76; 95% CI, 0.68-0.82). The accuracy for determining milder versus more severe categories per radiologist ranged from 88% to 97% for nerve lesions and from 86% to 94% for muscle abnormalities. CONCLUSION. The proposed NS-RADS classification is accurate and reliable across different reader experience levels and a spectrum of PN conditions. CLINICAL IMPACT. NS-RADS can be used as a standardized guideline for reporting PN and improved multidisciplinary communications.
