Anatomical Characteristics of the Lateral Pterygoid Muscle in Mandibular Prognathism

Relationship between craniofacial skeletal patterns and anatomic characteristics of masticatory muscles: a systematic review and meta-analysis

BACKGROUND

The anatomic characteristics of the masticatory muscles differ across craniofacial skeletal patterns.

OBJECTIVE

To identify differences in the anatomic characteristics of masticatory muscles across different sagittal and vertical craniofacial skeletal patterns.

ELIGIBILITY CRITERIA

Studies measuring the thickness, width, cross-sectional area (CSA), volume and orientation of masticatory muscles in healthy patients of different sagittal (Class I, Class II, and Class III) and/or vertical (normodivergent, hypodivergent, and hyperdivergent) patterns.

INFORMATION SOURCES

Unrestricted literature searches in 8 electronic databases/registers until December 2023.

RISK OF BIAS AND SYNTHESIS OF RESULTS

Study selection, data extraction, and risk of bias assessment with a customised tool were performed independently in duplicate. Random-effects meta-analysis and assessment of the certainty of clinical recommendations with the GRADE approach were conducted.

RESULTS

34 studies (37 publications) were selected with a total of 2047 participants and data from 16 studies were pulled in the meta-analysis. Masseter muscle thickness in relaxation was significantly greater by 1.14 mm (95% CI 0.74-1.53 mm) in hypodivergent compared to normodivergent patients while it was significantly decreased in hyperdivergent patients by - 1.14 mm (95% CI - 1.56 to - 0.73 mm) and - 2.28 mm (95% CI - 2.71 to - 1.85 mm) compared to normodivergent and hypodivergent patients respectively. Similar significant differences were seen between these groups in masseter muscle thickness during contraction as well as masseter muscle CSA and volume. Meta-analyses could not be performed for sagittal categorizations due to insufficient number of studies.

CONCLUSIONS

Considerable differences in masseter muscle thickness, CSA and volume were found across vertical skeletal configurations being significantly reduced in hyperdivergent patients; however, results should be interpreted with caution due to the high risk of bias of the included studies. These variations in the anatomic characteristics of masticatory muscles among different craniofacial patterns could be part of the orthodontic diagnosis and treatment planning process.

REGISTRATION

PROSPERO CRD42022371187 .

Temporomandibular Joint Space in Mandibular Prognathism

This study compared the temporomandibular joint (TMJ) space between patients with normal and prognathic mandibles. The study included a total of 68 Korean individuals, and the TMJ space was measured using computed tomography. Patients with normal SNB values (normal mandible) were classified into Group 1. Patients with high SNB values (prognathic mandibles) were categorized into Group 2. The TMJ space was defined as the distance between the condylar process and the mandibular fossa, and it was significantly different between Groups 1 and 2 (1.94±0.07 mm versus 1.50±0.05 mm, P< 0.01). This study confirmed that the TMJ space in patients with prognathic mandibles is narrower than that in patients with normal mandibles.

Three-Dimensional Postoperative Results Prediction for Orthognathic Surgery through Deep Learning-Based Alignment Network

To date, for the diagnosis of dentofacial dysmorphosis, we have relied almost entirely on reference points, planes, and angles. This is time consuming, and it is also greatly influenced by the skill level of the practitioner. To solve this problem, we wanted to know if deep neural networks could predict postoperative results of orthognathic surgery without relying on reference points, planes, and angles. We use three-dimensional point cloud data of the skull of 269 patients. The proposed method has two main stages for prediction. In step 1, the skull is divided into six parts through the segmentation network. In step 2, three-dimensional transformation parameters are predicted through the alignment network. The ground truth values of transformation parameters are calculated through the iterative closest points (ICP), which align the preoperative part of skull to the corresponding postoperative part of skull. We compare pointnet, pointnet++ and pointconv for the feature extractor of the alignment network. Moreover, we design a new loss function, which considers the distance error of transformed points for a better accuracy. The accuracy, mean intersection over union (mIoU), and dice coefficient (DC) of the first segmentation network, which divides the upper and lower part of skull, are 0.9998, 0.9994, and 0.9998, respectively. For the second segmentation network, which divides the lower part of skull into 5 parts, they were 0.9949, 0.9900, 0.9949, respectively. The mean absolute error of transverse, anterior-posterior, and vertical distance of part 2 (maxilla) are 0.765 mm, 1.455 mm, and 1.392 mm, respectively. For part 3 (mandible), they were 1.069 mm, 1.831 mm, and 1.375 mm, respectively, and for part 4 (chin), they were 1.913 mm, 2.340 mm, and 1.257 mm, respectively. From this study, postoperative results can now be easily predicted by simply entering the point cloud data of computed tomography.

Volumetric Change in the Masseter and Lateral Pterygoid after Mandibular Setback

In this study, we evaluated changes in the masseter and lateral pterygoid muscles in the prognathic mandible group after a mandibular setback by comparing the volume-to-length ratios. Preoperative and postoperative 1-year computed tomography was used to calculate the volume-to-length ratio of the lateral pterygoid and masseter muscle in 60 Korean individuals. Three-dimensional images were reconstructed, the results of which showed no significant differences in the volume-to-length ratios of the masseter and lateral pterygoid muscles after a mandibular setback (p > 0.05). This result was found for both vertical ramus osteotomy and sagittal split ramus osteotomy, and for both males and females. No significant differences in the volume-to-length ratio of the masseter and lateral pterygoid muscles were found up to 1 year after a mandibular setback. Therefore, this study can contribute to the prediction of soft-tissue profiles after mandibular setback.