Dento maxillo facial radiology最新文献

Objectives: To elucidate the relationships between the maximum standardized uptake value (SUVmax) of alveolar bone and those of lymph nodes (LNs) around the neck on 18F-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET).

Methods: The SUVmax values of alveolar bone and of level IA, level IB, and level IIA LNs of 174 patients, including those with and without active odontogenic inflammation, on PET/CT performed for a health check were retrospectively evaluated. The upper and lower jaws were divided into four blocks (right maxilla, left maxilla, right mandible, and left mandible). The SUVmax values of each block and of the LNs were calculated. The differences in the SUVmax of each LN level between patients with and without odontogenic inflammation, and the relationship between the SUVmax values of alveolar bone and of the LNs were analysed statistically.

Results: Significant differences in SUVmax values of bilateral level IB and IIA LNs were found between patients with and without odontogenic inflammation (Mann-Whitney U test: right level IB, P = .008; left level IB, P = .006; right level IIA, P < .001; left level IIA, P = .002), but not in bilateral level IA LNs (Mann-Whitney U test: right level IA, P = .432; left level IA, P = .549). The inflammatory site with the highest SUVmax in level IB LNs was the ipsilateral mandible (multivariate analysis: right, beta = 0.398, P < .001; left, beta = 0.472, P < .001), and the highest SUVmax in level IIA LNs was the ipsilateral maxilla (multivariate analysis: right, beta = 0.223, P = .002; left, beta = 0.391, P < .001).

Conclusions: The SUVmax values of level IB and IIA LNs were associated with a tendency towards a higher SUVmax value of alveolar bone on 18F-FDG-PET.

Objectives: To assess the performance of deep learning (DL) in the detection, classification, and segmentation of maxillary sinus diseases.

Methods: An electronic search was conducted by two reviewers on databases including PubMed, Scopus, Cochrane, and IEEE. All English papers published no later than February 7, 2024, were evaluated. Studies related to DL for diagnosing maxillary sinus diseases were also searched in journals manually.

Results: Fourteen of 1167 studies were eligible according to the inclusion criteria. All studies trained DL models based on radiographic images. Six studies applied to detection tasks, one focused on classification, two segmented lesions, and five studies made a combination of two types of DL models. The accuracy of the DL algorithms ranged from 75.7% to 99.7%, and the area under curves (AUC) varied between 0.7 and 0.997.

Conclusion: DL can accurately deal with the tasks of diagnosing maxillary sinus diseases. Students, residents, and dentists could be assisted by DL algorithms to diagnose and make rational decisions on implant treatment related to maxillary sinuses.

Objective: This study aims to develop a facial vascular enhancement imaging system and analyze vascular distribution in the facial region to assess its potential in preventing unintended intravascular injections during cosmetic facial filling procedures.

Methods: A facial vascular enhancement imaging system based on optical detection technology was designed, and volunteers were recruited. The system was utilized to detect and analyze vascular distribution in various anatomical regions of the faces. The vascular visualization-enhanced (VVE) images generated by the system were compared with visible light images to validate the vascular visualization capability of the system. Additionally, the reliability of vascular visualization was assessed by comparing the observed vascular patterns in the VVE images with those in near-infrared light images.

Results: Thirty volunteers were recruited. The VVE images produced by the system demonstrated a significant capacity to identify vascular morphology and yielded a higher vessel count compared to visible light images, particularly in the frontal, orbital, perioral, mental, temporal, cheek, and parotid masseter regions (P < .05). The temporal region exhibited the highest vascular density, followed by the cheek region and then the frontal region. Reliability analysis of vascular visualization enhancement indicated that the system's imaging of facial vasculature not only demonstrated reliability but also enhanced physicians' visual perception.

Conclusion: Blood vessel distribution varies across facial regions. The facial vascular enhancement imaging system facilitates real-time and clear visualization of facial vasculature, offering immediate visual feedback to surgeons. This innovation holds promise for enhancing the safety and effectiveness of facial filling procedures.

Objectives: The aim of this study was to identify cone-beam computed tomography (CBCT) protocols that offer an optimal balance between effective dose (ED) and 3D model for orthognathic virtual surgery planning, using CT as a reference, and to assess whether such protocols can be defined based on technical image quality metrics.

Methods: Eleven CBCT (VISO G7, Planmeca Oy, Helsinki, Finland) scan protocols were selected out of 32 candidate protocols, based on ED and technical image quality measurements. Next, an anthropomorphic RANDO SK150 phantom was scanned using these 11 CBCT protocols and 2 CT scanners for bone quantity assessments. The resulting DICOM (Digital Imaging and Communications in Medicine) files were converted into Standard Tessellation Language (STL) models that were used for bone volume and area measurements in the predefined orbital region to assess the validity of each CBCT protocol for virtual surgical planning.

Results: The highest CBCT bone volume and area of the STL models were obtained using normal dose protocol (F2) and ultra-low dose protocol (J13), which resulted in 48% and 96% of the mean STL bone volume and 48% and 95% of the bone area measured on CT scanners, respectively.

Conclusions: The normal dose CBCT protocol "F2" offered optimal bone area and volume balance for STL. The optimal CBCT protocol can be defined using contrast-to-noise ratio and modulation transfer function values that were similar to those of the reference CT scanners'. CBCT scanners with selected protocols can offer a viable alternative to CT scanners for acquiring STL models for virtual surgical planning at a lower effective dose.

Objectives: To evaluate magnetic susceptibility artefacts produced by orthodontic wires on MRI and the influence of wire properties and MRI image sequences on the magnitude of the artefact.

Methods: Arch form orthodontic wires [four stainless steels (SS), one cobalt chromium (CC) alloy, 13 titanium (Ti) alloys] were embedded in a polyester phantom, and scanned using a 1.5-T superconducting magnet scanner with an eight-channel phased-array coil. All wires were scanned with T1-weighted spin echo (SE) and gradient echo (GRE) sequences according to the American Society for Testing and Materials (ASTM) F2119-07 standard. The phantom also scanned other eight sequences. Artefacts were measured using the ASTM F2119-07 definition and OsiriX software. Artefact volume was analysed according to metal composition, wire length, number of wires, wire thickness, and imaging sequence as factors.

Results: With SE/GRE, black/white artefacts volumes from all SS wires were significantly larger than those produced by CC and Ti wires (P < .01). With the GRE, the black artefacts volume was the highest with the SS wires. With the SE, the black artefacts volume was small, whereas white artefacts were noticeable. The cranio-caudal extent of the artefacts was significantly longer with SS wires (P < .01). Although a direct relationship of wire length, number of wires, and wire thickness with artefact volume was noted, these factors did not influence artefact extension in the cranio-caudal direction.

Conclusions: Ferromagnetic/paramagnetic orthodontic wires create artefacts due to local alteration of magnetic field homogeneity. The SS-type wires produced the largest artefacts followed by CC and Ti.

Objectives: To assess the influence of two conventional and one adapted cheek and lip retractors and three emissivity setting values on intraoral infrared thermography (IT) temperature values.

Methods: The sample was composed by 50 volunteers. Three cheek and lip retractors were tested: Group 1-flex retractor (FR); Group 2-FR adapted with Styrofoam; Group 3-U-type retractor (UR) for cheek and lip. All thermograms were acquired using FLIR T650 infrared camera. A set of three thermograms in frontal norm were acquired for each lip and cheek retractor at 0.91, 0.96, and 0.98ε, with an interval of 15 min between each set of images to avoid thermal interference. All images were assessed by two observers. The ROIs' mean temperature of the four upper incisors was recorded. Two-way ANOVA and Sidak post-test were used for data assessment with a significance level of 5%.

Results: Group 3 showed higher mean temperature than Groups 1 and 2 at all emissivity settings for all assessed teeth (P < .05). 0.91ε showed higher temperature than 0.96ε and 0.98ε for all assessed variables (P < .01). Contralateral teeth assessed using Group 3 at 0.91ε showed statistical differences between each other (P < .05). No statistical difference was observed between contralateral teeth assessed using Groups 1 and 2 at 0.96ε and 0.98ε (P > .05).

Conclusions: The choice of cheek and lip retractor and emissivity setting can interfere on intraoral IT temperature values. U-type cheek and lip retractor and 0.91ε setting should not be used for IT image acquisition when assessing dental tissues.

Objectives: This study evaluated the impact of variations in anteroposterior and lateral tilts of patients' head on radiation-weighted doses to organs/tissues and effective doses using three different cone beam computed tomography machines.

Methods: An anthropomorphic phantom was used to estimate radiation doses in three CBCT machines (OP300, Eagle X 3D, and Eagle Edge). Thermoluminescent dosimeters were placed in regions corresponding to pre-stablished organ/tissues. CBCT examinations from the posterior mandible and anterior maxilla regions were acquired, with three different anteroposterior angulations (0°, 30°, and 45°), and from the posterior mandible in three different lateral angulations (0°, 20° to the left, and 20° to the right side). Radiation-weighted doses for each organ/tissue and effective doses were calculated for each machine and angulation.

Results: For the posterior mandible acquisitions, anteroposterior angulations of the head at 30° and 45° yielded a reduction in effective doses in all three devices. A 20° tilt to the right side resulted in lower doses than to the left (same side as the FOV). For the anterior maxilla, increased anteroposterior angulation was associated with reduction in effective dose in two devices.

Conclusion: Effective doses are lower when small FOV CBCT exams of the posterior mandible and anterior maxilla are acquired with increased anteroposterior head angulation at 30° and 45°. For FOV in the posterior mandible, a 20° lateral tilt towards the side opposite to the FOV also yields lower effective doses. The main contribution to these dose reductions is the decrease in dose to salivary glands.

Background: Sinusitis is a commonly encountered clinical condition that imposes a considerable burden on the healthcare systems. A significant number of maxillary sinus opacifications are diagnosed as sinusitis, often overlooking the precise differentiation between cystic formations and inflammatory sinusitis, resulting in inappropriate clinical treatment. This study aims to improve diagnostic accuracy by investigating the feasibility of differentiating maxillary sinusitis, retention cysts, and normal sinuses.

Methods: We developed a deep learning-based automatic detection model to diagnose maxillary sinusitis using ostiomeatal unit computed tomography images. Of the 1080 randomly selected coronal-view CT images, including 2158 maxillary sinuses, datasets of maxillary sinus lesions comprised 1138 normal sinuses, 366 cysts, and 654 sinusitis based on radiographic findings, and were divided into training (n = 648 CT images), validation (n = 216), and test (n = 216) sets. We utilized a You Only Look Once based model for object detection, enhanced by the transfer learning method. To address the insufficiency of training data, various data augmentation techniques were adopted, thereby improving the model's robustness.

Results: The trained You Only Look Once version 8 nano (YOLOv8n) model achieved an overall precision of 97.1%, with the following class precisions on the test set: normal = 96.9%, cyst = 95.2%, and sinusitis = 99.2%. With an average F1 score of 95.4%, the F1 score was the highest for normal, then sinusitis, and finally, cysts. Upon evaluating a performance on difficulty level, the precision decreased to 92.4% on challenging test dataset.

Conclusions: The developed model is feasible for assisting clinicians in screening maxillary sinusitis lesions.

Objectives: The aim of the present study was to assess the reproducibility of findings in cone beam computed tomography (CBCT) scout images. Furthermore, the study aimed to assess whether a scout image shows pathology not seen within the CBCT volume (ie, added diagnostic information) and therefore must be assessed on the same terms as the full volume.

Methods: Using a retrospective design, 233 CBCT reports and scout images were assessed. Kappa statistics and percentage of accordance were used to evaluate intra- and interobserver reproducibility as well as agreement between scout and CBCT report.

Results: Intra- and interobserver reproducibility were overall low (kappa ranging from -0.008 to 1.000). Agreement between findings reported in the CBCT and scout was also low. One-hundred-fourteen impacted teeth, one apical periodontitis, and two sinus conditions seen in the scout image were not registered in the full volume report due to the extended size of the scout image.

Conclusions: Reproducibility of findings in scout images compared to CBCT volumes was low, and the scout showed very little additional diagnostic information.

Advances in knowledge: This study shows that although the reproducibility of viewing scout images is low, rare findings can go undetected if the scout is not assessed. Legislation regarding interpretation of scout images needs to be discussed.

Objectives: To investigate the ultrasound (US) characteristics of metastatic malignancies (MM) in the major salivary glands and to assess the diagnostic value of the close relationship with the glandular capsule in identifying MM.

Methods: From January 2016 and April 2022, 122 patients with major salivary gland malignancies, including 20 patients with MM and 102 patients with primary malignancies (PM) confirmed by histopathological examination, were enrolled in this study. Their clinicopathologic and US data were recorded and analyzed. The diagnostic performance of the close relationship with the glandular capsule for differentiating MM from PM was analyzed.

Results: The mean age of MM were older than that of PM (59.50 ± 14.57 vs. 49.96 ± 15.73, p = 0.013). Compared with PM patients, MM were associated with a higher prevalence of local pain symptoms (p = 0.007) and abnormal facial nerve function (p < 0.001). MM were also more frequently characterized by unclear borders, rough margins, irregular shapes, heterogeneous internal echos, absence of cystic areas, presence of calcifications, close relationship with the glandular capsule, and US-reported positive cervical lymph nodes (all p < 0.05). The close relationship with the glandular capsule showed to be a good indicator in distinguishing between MM and PM, with an area under the receiver operating characteristic curve of 0.863, a sensitivity of 100%, a specificity of 72.5%, and an accuracy of 92.2%. Positive and negative predictive were calculated at 41.7% and 100%, respectively.

Conclusions: The US finding of a close relationship with the glandular capsule is a highly sensitive diagnostic indicator for MM. Following this finding, US-guided needle biopsy should be recommended to further confirm the diagnosis.