Exploring Deep Cervical Compartments in Head and Neck Surgical Oncology through Augmented Reality Vision: A Proof of Concept

Background: Virtual surgical planning allows surgeons to meticulously define surgical procedures by creating a digital replica of patients’ anatomy. This enables precise preoperative assessment, facilitating the selection of optimal surgical approaches and the customization of treatment plans. In neck surgery, virtual planning has been significantly underreported compared to craniofacial surgery, due to a multitude of factors, including the predominance of soft tissues, the unavailability of intraoperative navigation and the complexity of segmenting such areas. Augmented reality represents the most innovative approach to translate virtual planning for real patients, as it merges the digital world with the surgical field in real time. Surgeons can access patient-specific data directly within their field of view, through dedicated visors. In head and neck surgical oncology, augmented reality systems overlay critical anatomical information onto the surgeon’s visual field. This aids in locating and preserving vital structures, such as nerves and blood vessels, during complex procedures. In this paper, the authors examine a series of patients undergoing complex neck surgical oncology procedures with prior virtual surgical planning analysis. For each patient, the surgical plan was imported in Hololens headset to allow for intraoperative augmented reality visualization. The authors discuss the results of this preliminary investigation, tracing the conceptual framework for an increasing AR implementation in complex head and neck surgical oncology procedures

Detecting Mandible Fractures in CBCT Scans Using a 3-Stage Neural Network

After nasal bone fractures, fractures of the mandible are the most frequently encountered injuries of the facial skeleton. Accurate identification of fracture locations is critical for effectively managing these injuries. To address this need, JawFracNet, an innovative artificial intelligence method, has been developed to enable automated detection of mandibular fractures in cone-beam computed tomography (CBCT) scans. JawFracNet employs a 3-stage neural network model that processes 3-dimensional patches from a CBCT scan. Stage 1 predicts a segmentation mask of the mandible in a patch, which is subsequently used in stage 2 to predict a segmentation of the fractures and in stage 3 to classify whether the patch contains any fracture. The final output of JawFracNet is the fracture segmentation of the entire scan, obtained by aggregating and unifying voxel-level and patch-level predictions. A total of 164 CBCT scans without mandibular fractures and 171 CBCT scans with mandibular fractures were included in this study. Evaluation of JawFracNet demonstrated a precision of 0.978 and a sensitivity of 0.956 in detecting mandibular fractures. The current study proposes the first benchmark for mandibular fracture detection in CBCT scans. Straightforward replication is promoted by publicly sharing the code and providing access to JawFracNet on grand-challenge.org

Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps

This paper introduces panoptica, a versatile and performance-optimized package designed for computing instance-wise segmentation quality metrics from 2D and 3D segmentation maps. panoptica addresses the limitations of existing metrics and provides a modular framework that complements the original intersection over union-based panoptic quality with other metrics, such as the distance metric Average Symmetric Surface Distance. The package is open-source, implemented in Python, and accompanied by comprehensive documentation and tutorials. panoptica employs a three-step metrics computation process to cover diverse use cases. The efficacy of panoptica is demonstrated on various real-world biomedical datasets, where an instance-wise evaluation is instrumental for an accurate representation of the underlying clinical task. Overall, we envision panoptica as a valuable tool facilitating in-depth evaluation of segmentation methods.Comment: 15 pages, 6 figures, 3 table

Digital Implant Planning in Patients with Ectodermal Dysplasia: Clinical Report

Ectodermal dysplasia may severely affect the development of jaw growth and facial appearance. This case report describes the treatment of two patients suffering from ectodermal dysplasia, both treated with dental implant-fixed restorations by means of computer-guided surgery. Two patients presented to our clinic with congenital malformation of the jaw as a manifestation of ectodermal dysplasia, showing oligodontia and alveolar ridge deficit. Clinical examination revealed multiple unattached teeth and a need for prosthetic therapy. For both cases, dental implants were placed based on a computer-guided planning. A surgical guide was used to determine the positioning of the dental implants according to the prosthetic planning, which allowed for a satisfactory aesthetic and functional outcome. Computer-guided implant placement allowed predictable treatment of complex cases with satisfactory aesthetic and functional results. Adequate surgical and prosthetic planning is considered critical for treatment success

Automated detection of third molars and mandibular nerve by deep learning

The approximity of the inferior alveolar nerve (IAN) to the roots of lower third molars (M3) is a risk factor for the occurrence of nerve damage and subsequent sensory disturbances of the lower lip and chin following the removal of third molars. To assess this risk, the identification of M3 and IAN on dental panoramic radiographs (OPG) is mandatory. In this study, we developed and validated an automated approach, based on deep-learning, to detect and segment the M3 and IAN on OPGs. As a reference, M3s and IAN were segmented manually on 81 OPGs. A deep-learning approach based on U-net was applied on the reference data to train the convolutional neural network (CNN) in the detection and segmentation of the M3 and IAN. Subsequently, the trained U-net was applied onto the original OPGs to detect and segment both structures. Dice-coefficients were calculated to quantify the degree of similarity between the manually and automatically segmented M3s and IAN. The mean dice-coefficients for M3s and IAN were 0.947 +/- 0.033 and 0.847 +/- 0.099, respectively. Deep-learning is an encouraging approach to segment anatomical structures and later on in clinical decision making, though further enhancement of the algorithm is advised to improve the accuracy

A Survey on the Use of Artificial Intelligence by Clinicians in Dentistry and Oral and Maxillofacial Surgery

Contains fulltext : 253616.pdf (Publisher’s version ) (Open Access

Is the pattern of mandibular asymmetry in mild craniofacial microsomia comparable to non-syndromic class II asymmetry?

OBJECTIVES: To compare the characteristics of mandibular asymmetry in patients with unilateral craniofacial microsomia (CFM) and class II asymmetry. MATERIALS AND METHODS: Pretreatment cone-beam computed tomography of consecutive adults with Pruzansky-Kaban type I and IIA CFM (CFM group) was analyzed by 3D cephalometry. Fourteen mandibular landmarks and two dental landmarks were identified. The mandibular size and positional asymmetry were calculated by using landmark-based linear and volumetric measurements, in terms of asymmetry ratios (affected/non-affected side) and absolute differences (affected - non-affected side). Results were compared with non-syndromic class II with matched severity of chin deviation (Class II group). Statistical analyses included independent t test, paired t test, chi-square test, and ANOVA. RESULTS: CFM group (n, 21; mean age, 20.4 ± 2.5 years) showed significantly larger size asymmetry in regions of mandibular body, ramus, and condyle compared to Class II group (n, 21; mean age, 27.8 ± 5.9 years) (p < 0.05). The curvature of mandibular body was asymmetric in CFM. Regarding the positional asymmetry of mandibular body, while a comparable transverse shift and a negligible yaw rotation were found among the two groups, the roll rotation in CFM was significantly greater as well as the occlusal (6.06° vs. 4.17°) and mandibular (7.84° vs. 2.80°) plane cants (p < 0.05). CONCLUSIONS: Mild CFM showed significantly more severe size asymmetry and roll rotation in mandible than non-CFM class II asymmetry. CLINICAL RELEVANCE: To improve the mandibular size and positional asymmetry in CFM, adjunct hard tissue augmentation or reduction in addition to OGS orthodontics with a meticulous roll and yaw planning is compulsory, which is expected to be distinct from treating non-CFM class II asymmetry

The role of muscular traction in the occurrence of skeletal relapse after advancement bilateral sagittal split osteotomy (BSSO): A systematic review

The aim of this systematic review was (i) to determine the role of muscular traction in the occurrence of skeletal relapse after advancement BSSO and (ii) to investigate the effect of advancement BSSO on the perimandibular muscles. This systematic review reports in accordance with the recommendations proposed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Electronic database searches were performed in the databases MEDLINE, Embase and Cochrane Library. Inclusion criteria were as follows: assessment of relapse after advancement BSSO; assessment of morphological and functional change of the muscles after advancement BSSO; and clinical studies on human subjects. Exclusion criteria were as follows: surgery other than advancement BSSO; studies in which muscle activity/traction was not investigated; and case reports with a sample of five cases or fewer, review articles, meta-analyses, letters, congress abstracts or commentaries. Of the initial 1006 unique articles, 11 studies were finally included. In four studies, an intervention involving the musculature was performed with subsequent assessment of skeletal relapse. The changes in the morphological and functional properties of the muscles after BSSO were studied in seven studies. The findings of this review demonstrate that the perimandibular musculature plays a role in skeletal relapse after advancement BSSO and may serve as a target for preventive strategies to reduce this complication. However, further research is necessary to (i) develop a better understanding of the role of each muscle group, (ii) to develop new therapeutic strategies and (iii) to define criteria that allow identification of patients at risk

Reliability and Agreement of 3D Anthropometric Measurements in Facial Palsy Patients Using a Low-Cost 4D Imaging System

Contains fulltext : 221692.pdf (Publisher’s version ) (Closed access