Neurosensory Deficits of the Mandibular Nerve Following Extraction of Impacted Lower Third Molars-A Retrospective Study.

BACKGROUND: Neurosensory deficits are one of the major complications after impacted lower third molar extraction leading to an impaired patient's quality of life. This study aimed to evaluate the incidence of neurosensory deficits after lower third molar extraction and compare it radiologically to the corresponding position of the inferior alveolar nerve. METHODS: In a retrospective study, all patients who underwent impacted lower third molar extraction between January and December 2019 were compiled. Therefore, clinical data as well as preoperative radiological imaging were assessed. RESULTS: In total, 418 patients who underwent lower third molar extractions (n = 555) were included in this study. Of these, 33 (5.9%) had short-term (i.e., within the initial 7 postoperative days) and 12 (1.3%) long-term (i.e., persisting after 12 months) neurosensory deficits documented. The inferior alveolar nerve position in relation to the tooth roots showed apical position in 27%, buccal position in 30.8%, lingual position in 35.4%, and interradicular position in 6.9%. CONCLUSIONS: A statistically significant increased incidence of neurosensory deficits occurs when the inferior alveolar nerve is directly positioned lingually to the tooth roots (p = 0.01).

Evaluating a Periapical Lesion Detection CNN on a Clinically Representative CBCT Dataset-A Validation Study.

The aim of this validation study was to comprehensively evaluate the performance and generalization capability of a deep learning-based periapical lesion detection algorithm on a clinically representative cone-beam computed tomography (CBCT) dataset and test for non-inferiority. The evaluation involved 195 CBCT images of adult upper and lower jaws, where sensitivity and specificity metrics were calculated for all teeth, stratified by jaw, and stratified by tooth type. Furthermore, each lesion was assigned a periapical index score based on its size to enable a score-based evaluation. Non-inferiority tests were conducted with proportions of 90% for sensitivity and 82% for specificity. The algorithm achieved an overall sensitivity of 86.7% and a specificity of 84.3%. The non-inferiority test indicated the rejection of the null hypothesis for specificity but not for sensitivity. However, when excluding lesions with a periapical index score of one (i.e., very small lesions), the sensitivity improved to 90.4%. Despite the challenges posed by the dataset, the algorithm demonstrated promising results. Nevertheless, further improvements are needed to enhance the algorithm's robustness, particularly in detecting very small lesions and the handling of artifacts and outliers commonly encountered in real-world clinical scenarios.