Imaging Science in Dentistry最新文献

Purpose: Convolutional neural networks (CNNs) have rapidly emerged as one of the most promising artificial intelligence methods in the field of medical and dental research. CNNs can provide an effective diagnostic methodology allowing for the detection of early-staged diseases. Therefore, this study aimed to evaluate the performance of a deep CNN algorithm for apical lesion segmentation from panoramic radiographs.

Materials and methods: A total of 1000 panoramic images showing apical lesions were separated into training (n=800, 80%), validation (n=100, 10%), and test (n=100, 10%) datasets. The performance of identifying apical lesions was evaluated by calculating the precision, recall, and F1-score.

Results: In the test group of 180 apical lesions, 147 lesions were segmented from panoramic radiographs with an intersection over union (IoU) threshold of 0.3. The F1-score values, as a measure of performance, were 0.828, 0.815, and 0.742, respectively, with IoU thresholds of 0.3, 0.4, and 0.5.

Conclusion: This study showed the potential utility of a deep learning-guided approach for the segmentation of apical lesions. The deep CNN algorithm using U-Net demonstrated considerably high performance in detecting apical lesions.

Mucormycosis is a rare, invasive fungal infection that progresses aggressively and requires prompt surgery and appropriate treatment. The number of cases of mucormycosis in coronavirus disease 2019 (COVID-19) patients has recently increased, and patients with uncontrolled diabetes mellitus are particularly at an elevated risk of infection. This report presents a case of mucormycosis-related osteomyelitis of the maxilla in a 37-year-old man with diabetes mellitus. The patient complained of severe and persistent pain in the right maxilla, accompanied by increased tooth mobility and headache. On contrast-enhanced computed tomographic images, gas-forming osteomyelitis of the right maxilla was observed. Destruction of the maxilla and palatine bone then proceeded aggressively. Sequestrectomy was performed on the right maxilla, and the histopathological diagnosis was mucormycosis. Further investigation after the first operation revealed the patient's history of COVID-19 infection.

Supernumerary teeth that are present in the molar region may be evident based on crowding and impaction, but most cases are asymptomatic and discovered as incidental findings during routine radiological examinations. This article reports the case of a 29-year-old woman who presented with a severe feeling of pressure in the region of the maxillary third molars that had been increasing in intensity for weeks. A clinical examination revealed crowding of the maxillary anterior teeth despite the completion of orthodontic treatment and an erupted third molar with localized gingivitis in the second quadrant. A radiographic examination revealed bilateral supernumerary maxillary fourth and fifth molars, so cone-beam computed tomography was performed to locate the supernumerary teeth precisely for a preoperative diagnosis and comprehensive treatment planning. This report presents the radiological and surgical case management of a rare case of bilateral supernumerary molars and reviews the literature regarding epidemiology and treatment options.

Purpose: This study investigated whether the relationship between the maxillary sinus and the root of the maxillary premolar is correlated with the root position and whether there is a difference in the long axis angle of premolars and the buccal bone thickness according to the sinus-root relationship and root position.

Materials and methods: Cone-beam computed tomographic images of 587 maxillary first premolars and 580 second premolars from 303 patients were retrospectively reviewed. The maxillary sinus floor-root relationship was classified into 4 types, and the root position in the alveolar bone was evaluated as buccal, middle, or palatal. The long axis angle of the maxillary premolars in the alveolar bone and the buccal bone thickness were measured. The correlation between these parameters was analyzed.

Results: The maxillary sinus floor-root relationship showed a statistically significant correlation with the root position in the alveolar bone. Most maxillary first premolars were buccally located, and more than half of the second premolars had their roots in the middle. The long axis angle of the premolars was significantly larger in buccal-positioned teeth than in middle-positioned teeth, and the buccal bone was thinner.

Conclusion: When the root of the maxillary premolar was separated from the sinus floor, the premolar was often located on the buccal side. Most of the maxillary first premolars had a thinner buccal bone and larger inclination than the second premolars. It is recommended to evaluate the root position, sagittal angle and buccal bone thickness using CBCT for implant treatment planning.

Purpose: The goal of this systematic review was to compare the use of cone-beam computed tomography (CBCT) with that of computed tomography (CT) for volumetric evaluations of the tongue and oral cavity.

Materials and methods: A search for articles was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-analyses guidelines. The PubMed, Scopus, ScienceDirect, and SAGE Journals databases were searched for articles published between 2011 and 2021. Articles were screened and assessed for eligibility. Screening involved checking for duplication, reading the title and abstract, and reading the full text.

Results: The initial search retrieved 25,780 articles. Application of the eligibility criteria yielded 16 articles for qualitative analysis. Multiple uses of CBCT were identified. In several studies, researchers assessed the volumetric correlation between tongue and oral cavity volumes, as well as other parameters. Post-treatment volumetric evaluations of the oral cavity were also reported, and the reliability of CBCT was assessed. The use of CT resembled that of CBCT.

Conclusion: CBCT has been used in the evaluation of tongue and oral cavity volumes to assess correlations between those volumes and with the upper airway. It has also been used for volumetric evaluation after surgical and non-surgical procedures and to assess the relationships between tongue volume, tooth position, occlusion, and body mass index. Participants with obstructive sleep apnea and malocclusion have been evaluated, and the reliability of CBCT has been assessed. In the included studies, CT was utilized for similar purposes as CBCT, but its reliability was not assessed.

This report presents a rare case where a displaced temporomandibular joint (TMJ) disc was reduced to its normal position after orthognathic surgery, and long-term magnetic resonance imaging (MRI) follow-up visualized these postoperative changes. A 22-year-old male patient presented for facial asymmetry. He also complained of pain in the right TMJ area, and MRI showed disc displacements in both TMJs. After orthognathic surgery for facial asymmetry correction, the TMJ was re-evaluated. The symptom had resolved and the disc was positioned within the normal range during mouth opening. However, 6 and a half years after surgery, he complained of recurrent pain in the right joint, and MRI revealed medial disc displacement in the right TMJ. In conclusion, the influence of orthognathic surgery on the disc position might continue for a long time until the TMJ adapts to the new position. Careful and long-term follow-up is suggested to assess the TMJ complex.

McCune-Albright syndrome (MAS) is a rare multisystem disorder characterized by a clinical triad of polyostotic fibrous dysplasia (FD), skin pigmentation, and hyperfunctioning endocrinopathies. A 42-year-old man visited our medical hospital for the treatment of intermittent headaches and was diagnosed with MAS with acromegaly. This patient showed various clinical features of MAS, including pituitary adenoma, polyostotic FD, and hypogonadotropic hypogonadism. The FD lesions showed characteristic radiographic features, such as widespread, sclerotic bony lesions in the cranial bones, mixed radiolucent-radiopaque multilocular lesions in the mandible, and radiolucent lesions in the axial and appendicular skeleton. Over the years, the patient had been hospitalized multiple times due to accidental bony fractures associated with the fragile bony state of FD. This report presents a retrospective description of a case of MAS, with a review of the relevant literature.

Purpose: The purpose of this study was to compare volume measurements obtained using 2 image software packages on Digital Imaging and Communications in Medicine (DICOM) images acquired from 1 multidetector computed tomography and 5 cone-beam computed tomography devices, using different protocols for physical volume measurements.

Materials and methods: Four pieces of bovine leg were prepared. Marrow was removed from 3 pieces, leaving cortical bone exposed. The resulting space of 1 piece was filled with water, another was filled with propylene glycol, and the third was left unfilled. The marrow in the fourth sample was left fully intact. Volume measurements were obtained after importing DICOM images into the Dolphin Imaging 11.95 and ITK-SNAP software programs. Data were analyzed using 3-way analysis of variance with a generalized linear model to determine the effects of voxel size, software, and content on percentage mean volume differences between tomographic protocols. A significance level of 0.05 was used.

Results: The intraclass correlation coefficients for intraobserver and interobserver reliability were, respectively, 0.915 and 0.764 for the Dolphin software and 0.894 and 0.766 for the ITK-SNAP software. Three sources of statistically significant variation were identified: the interaction between software and content (P=0.001), the main effect of content (P=0.014), and the main effect of software (P=0.001). Voxel size was not associated with statistically significant differences in volume measurements.

Conclusion: Both content and software influenced the accuracy of volume measurements, especially when the content had gray values similar to those of the adjacent tissues.

Purpose: This technical report aims to describe and detail the use of micro-computed tomography for a reliable evaluation of the bulk-fill composite/tooth interface.

Materials and methods: Bulk-fill composite restorations in tooth cavities were scanned using micro-computed tomography to obtain qualitatively and quantitatively valuable information. Two-dimensional information was processed using specific algorithms, and ultimately a 3-dimensional (3D) specimen reconstruction was generated. The 3D rendering allowed the visualization of voids inside bulk-fill composite materials and provided quantitative measurements. The 3D analysis software VG Studio MAX was used to perform image analysis and assess gap formation within the tooth-restoration interface. In particular, to evaluate internal adaptation, the Defect Analysis add-on module of VG Studio Max was used.

Results: The data, obtained with the processing software, highlighted the presence and the shape of gaps in different colours, representing the volume of porosity within a chromatic scale in which each colour quantitatively represents a well-defined volume.

Conclusion: Micro-computed tomography makes it possible to obtain several quantitative parameters, providing fundamental information on defect shape and complexity. However, this technique has the limit of not discriminating materials without radiopacity and with low or no filler content, such as dental adhesives, and hence, they are difficult to visualise through software reconstruction.

Purpose: Despite the proliferation of numerous morphometric and anthropometric methods for sex identification based on linear, angular, and regional measurements of various parts of the body, these methods are subject to error due to the observer's knowledge and expertise. This study aimed to explore the possibility of automated sex determination using convolutional neural networks (CNNs) based on lateral cephalometric radiographs.

Materials and methods: Lateral cephalometric radiographs of 1,476 Iranian subjects (794 women and 682 men) from 18 to 49 years of age were included. Lateral cephalometric radiographs were considered as a network input and output layer including 2 classes (male and female). Eighty percent of the data was used as a training set and the rest as a test set. Hyperparameter tuning of each network was done after preprocessing and data augmentation steps. The predictive performance of different architectures (DenseNet, ResNet, and VGG) was evaluated based on their accuracy in test sets.

Results: The CNN based on the DenseNet121 architecture, with an overall accuracy of 90%, had the best predictive power in sex determination. The prediction accuracy of this model was almost equal for men and women. Furthermore, with all architectures, the use of transfer learning improved predictive performance.

Conclusion: The results confirmed that a CNN could predict a person's sex with high accuracy. This prediction was independent of human bias because feature extraction was done automatically. However, for more accurate sex determination on a wider scale, further studies with larger sample sizes are desirable.