The deformity angular ratio: can three-dimensional computed tomography improve prediction of intraoperative neuromonitoring events? Academic Article uri icon

Overview

abstract

  • PURPOSE: Assess whether a novel deformity angular ratio (DAR) calculated using preoperative three-dimensional computed tomography (3D CT) is more accurate than total DAR (T-DAR) radiographic measurements at predicting intraoperative neuromonitoring (IONM) events during vertebral column resection (VCR). METHODS: Consecutive, unique patients undergoing thoracic VCR by a single surgeon from 2015 to 2021 were identified. The T-DAR was calculated by dividing the total radiographic Cobb angle by the number of vertebral segments the angle subtends. 3D CT DAR was calculated for each patient from a preoperative CT scan by finding the maximum angle subtended by three contiguous vertebral segments. All patients were assessed for IONM events. A binary threshold of 25 was used for T-DAR and 3D CT DAR measurements for predictive analysis. p < 0.05 indicated significance. RESULTS: In total, 68 patients were identified. Mean age was 28 years. Mean levels fused was 15. Twenty-one patients (31%) had IONM events. In patients, with and without an IONM event, mean T-DAR was 26.6 ± 9.8 and 21.5 ± 8.8 (p = 0.04), respectively. 3D CT DAR mean values were 26.4 ± 10.8 and 18.4 ± 5.6, respectively (p < 0.001). 3D CT DAR accurately classified 81% of patients with a positive predictive value (PPV) of 75%. In comparison, T-DAR accurately classified 60% of patients with a PPV of 39%. CONCLUSION: 3D CT substantially improves preoperative IONM event prediction when compared to traditional radiographic measurements. A 3D CT DAR of 25 or greater was correlated with an increased rate of IONM events. 3D CT reconstructions are a useful adjunct for planning prior to a VCR.

publication date

  • June 1, 2022

Research

keywords

  • Kyphosis
  • Scoliosis

Identity

Scopus Document Identifier

  • 85131399751

Digital Object Identifier (DOI)

  • 10.1007/s43390-022-00518-4

PubMed ID

  • 35648363

Additional Document Info

volume

  • 10

issue

  • 5