Imaging Science in Dentistry最新文献

Purpose: The aim of this study was to develop and evaluate a carrier device for dental-dedicated magnetic resonance imaging (ddMRI).

Materials and methods: The carrier device comprised 5 glass test tubes, which were vertically positioned within a glass beaker and filled with air, distilled water, 1.5% agar, nickel nitrate [Ni(NO₃)₂] in 1.5% agar, or 1000 g·L^-1 dipotassium phosphate (K₂HPO₄). The beaker was filled with distilled water, a 0.3 g·L^-1 Ni(NO₃)₂ aqueous solution, or a 1000 g·L^-1 K₂HPO₄ aqueous solution. The device was scanned using a proton density turbo-spin-echo pulse sequence on a ddMRI system equipped with a dental-dedicated radiofrequency surface coil. Triplicate scans were performed for each combination of tube fillings and beaker solutions, yielding a total of 45 image volumes. Quantitative image metrics were then assessed.

Results: The developed carrier device, composed of carrier vials filled with 1.5% agar surrounded by a 1000 g·L^-1 K₂HPO₄ aqueous solution, was identified as the best option for ddMRI quality assessments.

Conclusion: The proposed carrier device represents a promising method for embedding dental materials and other specimens, thereby facilitating the evaluation of their behaviour in ddMRI.

Purpose: Diffusion-weighted magnetic resonance imaging (DW-MRI) facilitates the differentiation of unicystic ameloblastoma (UAM), odontogenic keratocyst (OKC), and dentigerous cyst (DC) by depicting detailed internal lesion structures based on water molecule movement. This study aimed to evaluate the efficacy of DW-MRI in distinguishing UAM, OKC, and DC.

Materials and methods: This systematic review included studies from 2008 to 2022 that evaluated the diagnostic accuracy of DW-MRI through apparent diffusion coefficient (ADC) values in UAM, OKC, and DC. Six studies were qualitatively appraised using the QUADAS-2 tool, and 4 studies were subsequently included in a network meta-analysis for quantitative assessment of mean ADC values. The protocol was registered with PROSPERO (registration number: CRD42024502152).

Results: Six studies encompassing 230 patients employed DW-MRI with an echo planar imaging sequence, yielding images with either hyperintense or hypointense lesion enhancements. The studies demonstrated that the mean ADC value for UAM was >2.0×10^-3 mm²/s, for DC was >1.0×10^-3 mm²/s, and for OKC was <1.0×10^-3 mm²/s (P<0.05).

Conclusion: This systematic review shows that DW-MRI, when used in conjunction with ADC measurements, effectively differentiates among UAM, OKC, and DC. The statistically significant ADC cut-off values support the use of DW-MRI as an adjunctive imaging modality to improve diagnostic accuracy in clinical practice.

Purpose: This study aimed to evaluate whether the position and number of high-density objects within the field of view (FOV) affect the volumetric alteration (VA) artifact in cone-beam computed tomography (CBCT) images.

Materials and methods: Four cylinders, each made of either cobalt-chromium, titanium, or zirconium, were placed in a phantom for acquisitions using the OP300 Maxio (Instrumentarium Dental, Tuusula, Finland) and Eagle (Dabi Atlante S/A Indústrias Médico Odontológicas, Ribeirão Preto, Brazil) CBCT systems. The cylinders were arranged in 7 different combinations based on their position and number within the FOV. Two oral radiologists segmented the volumes of the cylinders, and VA was calculated as the difference between the tomographic and physical volumes. Statistical analyses included the intraclass correlation coefficient (ICC) and multiway analysis of variance with Tukey's post-hoc test (α=5%).

Results: VA was observed under all experimental conditions. The factors region (anterior/posterior), combination (1 to 7), and material (cobalt-chromium, titanium, or zirconium) significantly influenced VA (P<0.05). In general, the presence of 3 cylinders within the FOV reduced VA (P<0.05). Although the effect of a cylinder's position varied with the CBCT system, VA typically increased in the posterior region (P<0.05). Additionally, titanium exhibited the lowest VA for both CBCT systems (P<0.05).

Conclusion: The presence of 3 high-density objects within the FOV reduced VA in CBCT images, whereas positioning an object in the posterior region generally increased its measured volume.

Purpose: The aim of this research was to develop a prediction model for diagnosis of Sjögren's syndrome using radiomics and machine learning techniques applied to computed tomography images of the parotid glands and to assess its efficacy by temporal validation.

Materials and methods: In total, 132 parotid glands from 66 subjects (33 patients with Sjögren's syndrome and 33 controls) were analyzed. Radiomics features were extracted from manually segmented parotid glands using 3D Slicer. The volume data for 108 parotid glands were chronologically assigned to the training dataset, and the features extracted were imported into Prediction One (Sony Network Communications Inc, Tokyo, Japan). A prediction model was automatically generated. The area under the curve (AUC), accuracy, precision, recall, and F-value were calculated for internal validation. Temporal validation was performed using 24 images of the parotid glands obtained later.

Results: A total of 129 radiomics features were extracted, including 18 first-order, 14 shape, and 75 texture features. The internal validation test showed high performance, with an AUC of 0.92, accuracy of 0.88, precision of 0.90, recall of 0.85, and an F-value of 0.88. Temporal validation testing also showed high performance, with an AUC of 0.96. accuracy of 0.88, precision of 0.85, recall of 0.92, and an F-value of 0.88.

Conclusion: The prediction model effectively differentiated Sjögren's syndrome using radiomics and machine learning. Use of Prediction One significantly streamlined the workflow, including analysis of radiomics, creation of the prediction model, and evaluation of performance, while substantially reducing the time required.

Purpose: This study demonstrated the feasibility of obtaining mandible bone mineral density (BMD) scores using spectral panoramic imaging.

Materials and methods: Areal BMD scores were measured from the body and angle of the mandible in 3 anthropomorphic head phantoms using a spectral panoramic system (Planmeca Promax Mid, Planmeca Oy, Helsinki, Finland) equipped with a DC-Vela detector (Varex Imaging Corporation, Salt Lake City, USA). These results were compared to synthetic panoramic images generated from dual-energy CT acquisitions. Reproducibility was evaluated by repeatedly scanning 1 phantom with minor patient positioning errors, and the linearity of the BMD scores was assessed using calcium inserts in a Gammex 472 phantom (Sun Nuclear, Melbourne, USA).

Results: The experimental and synthetic panoramic images appeared visually similar. The mean synthetic score was 0.640 g/cm², and the anthropomorphic phantoms produced a root mean squared error of 0.0292 g/cm² with a correlation coefficient of 0.969. Typical patient positioning errors did not substantially increase the error, which measured 0.0296 g/cm² and 0.0474 g/cm² for the left and right sides, respectively. Linearity tests using the Gammex phantom yielded a correlation coefficient of 0.998 for BMD scores ranging from 0.03 to 2.7 g/cm².

Conclusion: The BMD data obtained from spectral panoramic imaging are consistent with both dual-energy CT and Gammex phantom measurements. Consequently, spectral panoramic imaging shows potential as a method for osteoporosis screening, leveraging the widespread use of panoramic imaging.

Nasal myiasis is an infestation by dipterous larvae within the nasal cavity, where they feed on both living tissue and fluid. This condition predominantly occurs in rural areas of tropical countries, where inadequate sanitation and a hot, humid climate create an ideal environment for larvae development. A 57-year-old, otherwise healthy male rural worker presented with a toothache in the region of the maxillary incisors. Imaging studies identified a punctiform radiopaque/hyperdense area near the nasal septum in the left nasal fossa. The larva was surgically excised and sent for histopathological analysis. Histologic sections confirmed the clinical diagnosis, and the patient remained asymptomatic after a 2-month follow-up. Nasal myiasis can mimic the symptoms of a toothache in the anterior region of the maxilla. This condition can affect even immunocompetent patients, and complementary imaging studies may be decisive in diagnosing it.

Basal cell adenocarcinoma, considered to be the malignant counterpart of basal cell adenoma, is a rare, low-grade malignant tumor of the salivary glands, accounting for 1-2% of salivary gland malignancies. It predominantly affects the parotid gland, while involvement of the minor salivary glands is exceptionally rare. This report presented a case of basal cell adenocarcinoma involving the left retromolar trigone in a 54-year-old woman. The initial provisional diagnosis suggested a benign or low-grade malignant salivary tumor. Advanced magnetic resonance imaging techniques, including diffusion-weighted imaging and apparent diffusion coefficient analysis, aided in the preoperative prediction of malignancy, and an incisional biopsy confirmed the diagnosis of basal cell adenocarcinoma. This case underscored the challenge of distinguishing basal cell adenocarcinoma from benign salivary tumors, as clinical and imaging features often overlap. Surgical excision remains the primary treatment, yielding favorable outcomes; however, long-term follow-up is crucial due to the risk of recurrence.

Purpose: This study employed a convolutional neural network (CNN) algorithm to develop an automated dental age estimation method based on the London Atlas of Tooth Development and Eruption. The primary objectives were to create and validate CNN models trained on panoramic radiographs to achieve accurate dental age predictions using a standardized approach.

Material and methods: A dataset of 801 panoramic radiographs from outpatients aged 5 to 15 years was used. A CNN model for dental age estimation was developed using a 16-layer CNN architecture implemented in Python with TensorFlow and Scikit-learn, guided by the London Atlas of Tooth Development. The model included 6 convolutional layers for feature extraction, each followed by a pooling layer to reduce the spatial dimensions of the feature maps. A confusion matrix was used to evaluate key performance metrics, including accuracy, precision, recall, and F1 score.

Results: The proposed model achieved an overall accuracy, precision, recall, and F1 score of 74% on the validation set. The highest F1 scores were observed in the 10-year and 12-year age groups, indicating superior performance in these categories. In contrast, the 6-year age group demonstrated the highest misclassification rate, highlighting potential challenges in accurately estimating age in younger individuals.

Conclusion: Integrating a CNN algorithm for dental age estimation represents a significant advancement in forensic odontology. The application of AI improves both the precision and efficiency of age estimation processes, providing results that are more reliable and objective than those obtained via traditional methods.

Purpose: Bone grafts can be challenging to assess on cone-beam computed tomography (CBCT) examinations due to their discreet appearance and the potential introduction of metallic artifacts from implant screws. This study aimed to evaluate the effect of CBCT milliamperage (mA) on detecting bone graft dehiscence adjacent to titanium (Ti) and zirconia (Zr) implants.

Materials and methods: Twenty Ti and 20 Zr implants were installed in bovine rib blocks. Gaps of at least 2 mm were created between the implant and the bone and filled with particulate autogenous bone grafts. In half of the blocks, the gap was completely filled, while in the other half, the grafting material was removed up to the third implant thread. CBCT images were acquired at 4, 6.3, and 10 mA and evaluated by 5 observers to detect bone graft dehiscence. The area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were calculated. These values were then compared across various dental implant materials and mA levels using 2-way analysis of variance with a significance level of 5%.

Results: No statistically significant differences were observed in the diagnostic values for bone graft dehiscence between implant types (P>0.05) or mA settings (P>0.05).

Conclusion: Although a protocol with lower radiation exposure (that is, lower mA) could be employed, the use of CBCT for evaluating bone graft dehiscence adjacent to different types of dental implants should be approached with caution.

Purpose: X-ray scattering adversely affects cone-beam computed tomography (CBCT) image quality, generating image artifacts, causing inaccurate tissue density representation, and reducing contrast. This study evaluated the performance of a 2-dimensional antiscatter grid (2D grid) prototype in a dental CBCT system.

Materials and methods: A focused 2D grid prototype was fabricated from tungsten and integrated with the detector of a dental CBCT system. Residual scatter transmitted through the 2D grid was corrected using a measurement-based scatter correction method. Phantom imaging experiments were performed in anatomical regions relevant to dental and head imaging with and without this grid. Following image reconstruction via filtered back projection, attenuation coefficients were converted to Hounsfield units (HU). Subsequently, scatter suppression performance, HU consistency, image artifacts, and contrast resolution were evaluated.

Results: The 2D grid reduced scatter intensity by a factor of 10-20 in CBCT projections. Consequently, the grid substantially increased contrast, reduced image artifacts, and improved HU consistency. The contrast increased by 27% and 48% in bone- and soft tissue-equivalent regions, respectively. HU value deviations among teeth decreased from 510 to 146 HU. These results indicate improved visualization and tissue density representation fidelity in CBCT images acquired with the 2D grid.

Conclusion: Use of a 2D grid could substantially improve the accuracy of tissue density representation and the contrast of dental and head anatomy in 3-dimensional images obtained with dental CBCT. Such improvements may translate to better quantitative evaluation of bone quality, enhanced tissue visualization, and more accurate model generation for surgical planning and guidance.