Predictive scoring model for inferior alveolar nerve injury after lower third molar removal based on features of cone-beam computed tomography image

Abstract

IntroductionThis study aimed to construct a predictive scoring system for inferior alveolar nerve injury (IANI) following lower third molar (LM3) surgery based on cone-beam computed tomography (CBCT) images. Material and MethodsOf the 1573 patients who underwent LM3 removal following the CBCT, 39 with IANI and 457 randomly selected patients without IANI were enrolled. We collected information regarding the demographic characteristics of the patients, surgical situations, and inferior alveolar canal (IAC)-related CBCT factors. The association with IANI-risk was evaluated with a backward stepwise logistic regression model as per the Akaike information criterion. Scoring models’ abilities of discrimination (area under the curve) and calibration (Hosmer–Lemeshow test and calibration plots) were assessed, followed by evaluation of the clinical usefulness using decision curve analysis. ResultsAs per the multivariate analysis, the coronal positioned IAC on the enlarged root (odds ratio [OR], 3.78; P = 0.001), the length of perforated IAC (>3.4 mm) (OR, 3.05; P = 0.012), lingual/inter-radicular position of the IAC (OR, 3.96; P = 0.001), multiple roots closed to the perforated IAC (OR, 2.78; P = 0.025), and age >30 y (OR, 2.31; P = 0.076) were identified in the extended scoring model ranging from 0 to 12. This model was compared with our previously constructed baseline model that involved the latter three variables mentioned above, resulting in superior performance than that of the baseline model. ConclusionThe extended model would be a useful tool for reliable determination of the preoperative probability of IANI.