Automatic detection of posterior superior alveolar artery in dental cone-beam CT images using a deeply supervised multi-scale 3D network.

OBJECTIVES: This study aimed to develop a robust and accurate deep learning network for detecting the posterior superior alveolar artery (PSAA) in dental cone-beam CT (CBCT) images, focusing on the precise localization of the centre pixel as a critical centreline pixel. METHODS: PSAA locations were manually labelled on dental CBCT data from 150 subjects. The left maxillary sinus images were horizontally flipped. In total, 300 datasets were created. Six different deep learning networks were trained, including 3D U-Net, deeply supervised 3D U-Net (3D U-Net DS), multi-scale deeply supervised 3D U-Net (3D U-Net MSDS), 3D Attention U-Net, 3D V-Net, and 3D Dense U-Net. The performance evaluation involved predicting the centre pixel of the PSAA. This was assessed using mean absolute error (MAE), mean radial error (MRE), and successful detection rate (SDR). RESULTS: The 3D U-Net MSDS achieved the best prediction performance among the tested networks, with an MAE measurement of 0.696 ± 1.552 mm and MRE of 1.101 ± 2.270 mm. In comparison, the 3D U-Net showed the lowest performance. The 3D U-Net MSDS demonstrated a SDR of 95% within a 2 mm MAE. This was a significantly higher result than other networks that achieved a detection rate of over 80%. CONCLUSIONS: This study presents a robust deep learning network for accurate PSAA detection in dental CBCT images, emphasizing precise centre pixel localization. The method achieves high accuracy in locating small vessels, such as the PSAA, and has the potential to enhance detection accuracy and efficiency, thus impacting oral and maxillofacial surgery planning and decision-making.

Post-traumatic bifid mandibular condyle: A case report and literature review.

Bifid mandibular condyle (BMC) is an uncommon morphological variant of the mandibular condyle. Although authors have proposed various etiologies for BMC, no consensus has emerged. In addition, varying findings have been reported regarding the epidemiological parameters of BMC (e.g., prevalence, gender ratio, and age), possibly due to its low incidence. BMC is occasionally associated with symptoms of the temporomandibular joint, such as ankylosis, pain, and trismus; however, it is difficult to detect this condition on conventional radiographs. This study reports a case of BMC with radiographic findings, and reviews the literature on the epidemiology of BMC.

Wernicke's encephalopathy in a patient with masticator and parapharyngeal space abscess: a case report.

Wernicke's encephalopathy is a fatal neurological disease caused by thiamine deficiency. Many reports indicate that Wernicke's encephalopathy is caused by malnutrition. We report the case of a 79-year-old female patient who had a left masticator space and parapharyngeal space abscess who was diagnosed with Wernicke's encephalopathy. She reported problems while eating due to the presence of the abscess, but the true quantities of food she was ingesting were never assessed. Clinicians have a responsibility to provide adequate nutritional support by ensuring that patients receive adequate nutrition. Clinicians should also keep in mind that Wernicke's encephalopathy may occur in patients who experienced prolonged periods of malnutrition.