Custom Focal Trough in Cone-Beam Computed Tomography Reformatted Panoramic Versus Digital Panoramic for Mental Foramen Position to Aid Implant Planning

A rare case of an anatomical variant of nonexistent mental foramen

The mental foramen (MF) is an important anatomical landmark in the jaw, where the sensory nerve (mental nerve) and blood vessels emerge. To avoid sensory impairment or paresthesia caused by mental nerve damage, the MF must be accurately identified and localized. The literature describes a variety of anatomical variants of the MF, such as changes in its position, emergence profile or the presence of extra foramina. This case report documents a rare case of nonexistent mental foramina on the left side of the jaw, which was detected incidentally using cone-beam computed tomography (CBCT) prior to implant surgery planning.

Anatomical variant of anteriorly extending mental foramen: A case report

Key Clinical Message

By sharing this case, we aim to enhance the understanding of the mental foramen's intricate morphology, ultimately promoting safer and more successful surgical practices in the field of oral and maxillofacial surgery.

Abstract

In surgical procedures near the mental foramen, preserving this vital structure and its contents is crucial. Surgical treatments, including procedures like implants, orthognathic surgery, and tooth extractions, can potentially lead to injuries of the mental nerve, resulting in sensory disturbances such as numbness or tingling in the lower lip and chin. This case report highlights an uncommon anterior extension of the mental foramen, posing a risk to the patient if unnoticed. Variations in this structure are possible, emphasizing the need for comprehensive three-dimensional radiographic analysis before surgery to ensure patient safety. This report sheds light on the significance of identifying and understanding such variations to enhance the safety and precision of oral and maxillofacial interventions.

Inferior alveolar canal segmentation based on cone-beam computed tomography

PURPOSE

The shape and position of the inferior alveolar canal (IAC) are analyzed to effectively reduce the risk of iatrogenic injury based on cone-beam computer tomography (CBCT). To assist dental clinicians to make better use of the IAC information, we propose an IAC segmentation method based on CBCT images.

METHODS

In this paper, CBCT images are first preprocessed by the Hounsfield unit values clipping and gray normalization. Secondly, based on the multi-plane reconstruction (MPR) and curved surface reconstruction, the curved MPR image sets are generated by the smooth dental arch curve with a sampling distance of 1.00 pixels. Then, the K-means clustering algorithm is used to cluster the texture parameters of the gray level-gradient co-occurrence matrix enhanced by the gradient directions to improve the image contrast of the IAC. Finally, the IAC edges are roughly segmented by the 2D line-tracking method, and smoothed by the fourth-order polynomial to obtain the final segmentation result.

RESULTS

Twenty-one real clinical dental CBCT datasets were used to test the proposed method. The manual segmentation results of two specialized dental clinicians were used as quantitative evaluation criteria. The dice similarity index (DSI), average symmetric surface distance (ASSD), and mean curve distance (MCD) of the left IAC are 0.93 (SD = 0.01), 0.16 mm (SD = 0.05 mm), and 1.59 mm (SD = 0.25 mm), respectively; the DSI, ASSD, and MCD of the right IAC are 0.93 (SD = 0.02), 0.16 mm (SD = 0.05 mm), and 1.60 mm (SD = 0.30 mm), respectively.

CONCLUSIONS

The proposed method provides an effective image enhancement and segmentation solution to analyze the shape and position of the IAC. Experimental results show that the relationships between the IAC and other structures can be accurately reflected in the panoramic images without superimposition and geometric distortion, and the smooth edges of the IAC can be segmented.