Comprehensive review of the incisive branch of the inferior alveolar nerve

Identification of the Incisive Branch of the Inferior Alveolar Nerve of Edentulous Mandibles Using Cone-Beam Computerized Tomography

This study explored the average length of the incisive branch (IB) of the inferior alveolar nerve on cone-beam computerized tomography (CBCT) with regard to patient demographics in patients with edentulous mandibles. CBCT was used in a retrospective study of edentulous mandibles to assess the presence and anatomical variation for the IB. Three independent observers measured bilateral IB lengths. In addition to demographics, IB length and port of exit data were obtained. A 1-way analysis of variance was used to test whether IB length varied by sex or port of exit, and a standard Pearson correlation was used to test for IB length and age significance, with a significance level of P < .05. Intraclass correlation coefficients showed significant agreement in IB length across all observers. No significant difference was noted between the exit port and IB length. An important effect was reported for sex, indicating women have generally shorter IB lengths (9.43 ± 3.99 vs 10.55 ± 3.92). There was a significant correlation with age, but the relationship was weak. Edentulous mandibles have an altered anatomic landscape, and establishing predictive IB dimensions aids practitioners in surgical planning.

Two-stage extraction by partial grinding of impacted mandibular third molar in close proximity to the inferior alveolar nerve

BACKGROUND

Extraction of impacted third molars often leads to severe complications caused by damage to the inferior alveolar nerve (IAN).

AIM

To proposes a method for the partial grinding of an impacted mandibular third molar (IMM3) near the IAN to prevent IAN injury during IMM3 extraction.

METHODS

Between January 1996 and March 2022, 25 patients with IMM3 roots near the IAN were enrolled. The first stage of the operation consisted of grinding a major part of the IMM3 crown with a high-speed turbine dental drill to achieve sufficient space between the mandibular second molar and IMM3. After 6 months, when the root tips were observed to be away from the IAN on X-ray examination, the remaining part of the IMM3 was completely removed.

RESULTS

All IMM3s were extracted easily without symptoms of IAN injury after extraction.

CONCLUSION

Partial IMM3 grinding may be a good alternative treatment option to avoid IAN injury in high-risk cases.

A unique artificial intelligence-based tool for automated CBCT segmentation of mandibular incisive canal

OBJECTIVES

To develop and validate a novel artificial intelligence (AI) tool for automated segmentation of mandibular incisive canal on cone beam computed tomography (CBCT) scans.

METHODS

After ethical approval, a data set of 200 CBCT scans were selected and categorized into training (160), validation (20), and test (20) sets. CBCT scans were imported into Virtual Patient Creator and ground truth for training and validation were manually segmented by three oral radiologists in multiplanar reconstructions. Intra- and interobserver analysis for human segmentation variability was performed on 20% of the data set. Segmentations were imported into Mimics for standardization. Resulting files were imported to 3-Matic for analysis using surface- and voxel-based methods. Evaluation metrics involved time efficiency, analysis metrics including Dice Similarity Coefficient (DSC), Intersection over Union (IoU), Root mean square error (RMSE), precision, recall, accuracy, and consistency. These values were calculated considering AI-based segmentation and refined-AI segmentation compared to manual segmentation.

RESULTS

Average time for AI-based segmentation, refined-AI segmentation and manual segmentation was 00:10, 08:09, and 47:18 (284-fold time reduction). AI-based segmentation showed mean values of DSC 0.873, IoU 0.775, RMSE 0.256 mm, precision 0.837 and recall 0.890 while refined-AI segmentation provided DSC 0.876, IoU 0.781, RMSE 0.267 mm, precision 0. 852 and recall 0.902 with the accuracy of 0.998 for both methods. The consistency was one for AI-based segmentation and 0.910 for manual segmentation.

CONCLUSIONS

An innovative AI-tool for automated segmentation of mandibular incisive canal on CBCT scans was proofed to be accurate, time efficient, and highly consistent, serving pre-surgical planning.

Detection Rate and Variability in Measurement of Mandibular Incisive Canal on Cone-Beam Computed Tomography: A Study of 220 Dentate Hemi-Mandibles from Italy

The mandibular incisive canal (MIC) is a small bony channel located in the interforaminal region; it represents the anterior continuation of the mandibular canal. Cone-beam computed tomography (CBCT) is the most commonly utilized radiological technique for assessing the MIC. The main purpose of this study was to evaluate the detectability and variability in measurements of the MIC on CBCT. A total of 220 dentate hemi-mandibles were retrospectively selected for this study. For each hemi-mandible, the detectability, diameter, and distance of the MIC from anatomical landmarks (cortical plates and tooth apices) were evaluated in consensus by two observers. The analysis was performed at four different levels (first premolar, canine, lateral incisor, and central incisor) and was repeated after one month. The variability of MIC measurements was expressed as the coefficient of repeatability (CR), obtained from the Bland-Altman analysis. The MIC detection rate reduced from the first premolar to the central incisor (from 82.3% to 0.5%). The CR of MIC measurements (diameter and distances from anatomical landmarks) was ≤0.74 mm. Although the MIC is difficult to detect in a non-negligible percentage of cases, the limited variability in measurements confirms that CBCT is an effective technique for the assessment of the MIC.