Development and accuracy validation of a fat fraction imaging biomarker for sialadenitis in the parotid gland.

BACKGROUND: The diagnosis of sialadenitis, the most frequent disease of the salivary glands, is challenging when the symptoms are mild. In such cases, biomarkers can be used as definitive diagnostic indicators. Recently, biomarkers have been developed by extracting and analyzing pathological and morphological features from medical imaging. This study aimed to establish a diagnostic reference for sialadenitis based on the quantitative magnetic resonance imaging (MRI) biomarker IDEAL-IQ and assess its accuracy. METHODS: Patients with sialadenitis (n = 46) and control subjects (n = 90) that underwent MRI were selected. Considering that the IDEAL-IQ value is a sensitive fat fractional marker to the body mass index (BMI), all subjects were also categorized as under-, normal-, and overweight. The fat fraction of parotid gland in the control and sialadenitis groups were obtained using IDEAL-IQ map. The values from the subjects in the control and sialadenitis groups were compared in each BMI category. For comparison, t-tests and receiver operating characteristic (ROC) curve analyses were performed. RESULTS: The IDEAL-IQ fat faction of the control and sialadenitis glands were 38.57% and 23.69%, respectively, and the differences were significant. The values were significantly lower in the sialadenitis group (P), regardless of the BMI types. The area under the ROC curve (AUC) was 0.83 (cut-off value: 28.72) in patients with sialadenitis. The AUC for under-, normal-, and overweight individuals were 0.78, 0.81, and 0.92, respectively. CONCLUSIONS: The fat fraction marker based on the IDEAL-IQ method was useful as an objective indicator for diagnosing sialadenitis. This marker would aid less-experienced clinicians in diagnosing sialadenitis.

Canal configuration and root morphology of mandibular premolars using cone-beam computed tomography in a Korean population.

OBJECTIVES: This study aimed to investigate the anatomy of mandibular premolars from two perspectives-the canal configuration and radicular grooves-using cone-beam computed tomography (CBCT) in a large Korean population. MATERIALS AND METHODS: CBCT images of mandibles acquired from March 2018 to December 2019 for dental treatment were randomly selected. In each image, the root canal of premolars was classified into 8 types according to the canal merging or diverging pattern and the number of apical foramens. The presence and the location of radicular grooves were also assessed. Statistical analysis was performed. RESULTS: A total of 1463 first and 1448 s premolars from 732 patients (390 males, 342 females, mean age of 36.1 years) were evaluated. A single canal with one foramen predominated in both first (85.7%) and second (99.5%) premolars, while complete or partial multi-canals accounted for 14.3% and 0.5% of first and second premolars, respectively. The prevalence of radicular grooves was significantly higher in first premolars (13.2%) than in second premolars (0.5%) and in males (4.3%, n = 119) than in females (2.5%, n = 73). CONCLUSIONS: Although most premolars were complete single canals, the first premolars showed a relatively higher number of complex canals compared to the second premolar. In addition, radicular grooves in mandibular premolars were significantly more common in male patients. CLINICAL RELEVANCE: When planning the endodontic treatment of mandibular premolars, clinicians should be aware of their morphologic complexity, especially in the first premolar of male patients.

Anatomical analysis of mandibular posterior teeth for endodontic microsurgery: a cone-beam computed tomographic evaluation.

OBJECTIVE: The purpose of this study was to analyze the anatomical structures relevant for endodontic microsurgery in the mandibular posterior teeth using a cone-beam computed tomography (CBCT). MATERIAL AND METHODS: A total of 963 mandibular posterior teeth were analyzed in CBCT scans from 133 patients. The buccolingual and mesiodistal dimensions of the root and the buccal bone thickness overlying the root were measured at the site of root resection (apical 3 mm). At this location, the relationship between the buccal cortical bone and root was classified into three types (separated, contact, and exposed), and the distance from the root apex to the mandibular canal was measured. RESULTS: The thickest buccolingual dimension of the roots was found in the mesial roots of first molars, at 5.59 ± 0.97 mm. The buccal bone thickness overlying the root became thicker in posterior tooth locations. In the first premolar and first molar mesial root, contact was the most common type of relationship between the buccal cortical bone and root. As the position of the teeth became more posterior, the distance from the apex to the mandibular canal became shorter. CONCLUSIONS: As the position of the teeth became more posterior, the buccal bone thickness increased and the distance to the mandibular canal became closer; therefore, particular attention is required for posterior teeth. The first premolar and the first molar mesial root are often in contact with the buccal cortical bone, which may allow infections to spread to the buccal structure more easily and negatively affect for post-surgical healing. CLINICAL RELEVANCE: When planning and performing endodontic microsurgery, understanding the anatomical structure of the surgical site will help minimize tissue damage and reduce complications.

Developing evidence-based clinical imaging guidelines of justification for radiographic examination after dental implant installation.

BACKGROUND: This study aimed to develop evidence-based clinical imaging guidelines to assess the proper implant location following implant surgery and identify potential complications during follow-up. METHODS: The guideline development process employed an adaptation methodology in accordance with the Korean clinical imaging guidelines (K-CIG). Core (Ovid-Medline, Ovid-Embase, National Guideline Clearinghouse, and Guideline International Network) and domestic databases (KoreaMed, KMbase, and KoMGI) were searched used to retrieve guidelines, and two reviewers analyzed the retrieved articles. The articles were included in this review using well-established inclusion criteria. RESULTS: Our online search identified 66 articles, of which 3 were selected for the development of the guidelines. Consequently, based on these three guidelines, we formulated distinct recommendations regarding the appropriate imaging modalities that should be used following implant placement. CONCLUSIONS: Conventional imaging (e.g., periapical or panoramic radiography) should be the first choice for assessing the implant following its placement and osseointegration. The metal artifacts in Cone Beam Computed Tomography (CBCT) should be considered. However, CBCT is recommended for patients with sensory abnormalities following dental implant surgery to evaluate and identify the underlying cause of implant complications and to determine the appropriate treatment.

Therapeutic effect of intraductal saline irrigation in chronic obstructive sialadenitis.

BACKGROUND: The aim of the present study was to evaluate the effectiveness of intraductal irrigation using normal saline in chronic obstructive sialadenitis. METHODS: Patients who had one of the following symptoms were recruited: pain, swelling, stiffness, and dry mouth. A total of 58 salivary glands in 33 patients were diagnosed as having sialadenitis using sialography and ultrasonography. The patients were divided into two groups (swelling group and dry mouth group), according to the major complaint. Repeated intraductal irrigation was performed on each gland. Difference of symptom severity evaluated using numerical rating scale (NRS), and ductal width measured using ultrasonography were compared between the two groups. RESULTS: The average NRS score was significantly decreased from 6.0 to 3.3 after 3-5 visits of intraductal irrigation (P < 0.05). The reduction in NRS was greater in the swelling group than in the dry mouth group, although the difference between the groups was not statistically significant. There was no change of ductal width before and after the irrigation. CONCLUSIONS: Intraductal irrigation according to this study method using normal saline is a simple treatment for the patients with chronic obstructive sialadenitis. It provides a conservative treatment option reducing the subjective symptoms.

Microarchitectural changes in the mandibles of ovariectomized rats: a systematic review and meta-analysis.

BACKGROUND: This study aimed to examine radiologic microarchitectural changes in the mandibles of ovariectomized (OVX) rats through a systematic review and meta-analysis and to identify factors of the OVX rat model that influence on the bone microstructure. METHODS: Eligible articles were identified by searching electronic databases, including Embase, Medline, Web of Science, and KoreaMed, for articles published from January 1966 to November 2017. Two reviewers independently performed study selection, data extraction, and quality assessment. The pooled standardized mean difference (SMD) with 95% confidence intervals was calculated using a random-effects model. Subgroup analysis and meta-regression were performed to explore the effect of potential sources on the outcomes. The reliability of the results was assessed by sensitivity analysis and publication bias. RESULTS: Of 1160 studies, 16 studies (120 OVX and 120 control rats) were included in the meta-analysis. Compared to the control group, the OVX rats' trabecular bone volume fraction (SMD = - 2.41, P < 0.01, I2 = 81%), trabecular thickness (SMD = - 1.73, P < 0.01, I2 = 73%) and bone mineral density (SMD = - 0.95, P = 0.01, I2 = 71%) displayed the bone loss consistent with osteoporosis. The trabecular separation (SMD = 1.66, P < 0.01, I2 = 51%) has widen in the OVX mandibular bone in comparison to the control group. However, the trabecular number showed no indication to detect the osteoporosis (SMD = - 0.45, P = 0.38, I2 = 76%). The meta-regression indicated that longer post-OVX periods led to greater changes in bone mineral density (ß = - 0.104, P = 0.017). However, the rats' age at OVX was not linked to bone microstructure change. CONCLUSIONS: Using meta-regression and sensitivity analysis techniques, heterogeneity across the micro CT studies of OVX-induced osteoporosis was found. The major factors of heterogeneity were the region of interest and post-OVX period. Our assessment can assist in designing experiments to maximize the usefulness of OVX rat model.

CT and MR imaging findings of head and neck chondrosarcoma.

OBJECTIVES: This study investigated the imaging features of head and neck chondrosarcoma (HNCS) according to its origin and pathologic subtype. METHODS: Patients who were pathologically diagnosed with HNCS between January 2000 and April 2022 were retrospectively reviewed. Lesions were classified based on their origin and pathologic subtype. The size and margin were evaluated on the image. Internal calcification and the effects on adjacent bone were assessed using computed tomography (CT) images, while signal intensity and contrast enhancement patterns were analyzed using magnetic resonance (MR) imaging. RESULTS: Thirteen HNCSs were included in this study: 8 bone tumors (61.5%) and 5 soft tissue tumors (38.5%). The bone tumors were pathologically diagnosed as conventional (n = 5) and mesenchymal type (n = 3). Soft tissue tumors were defined as myxoid type. The main symptoms were swelling (90.9%) and pain (72.7%). The lesions measured 4.5 cm on average. The margins showed benign and well-defined except for the mesenchymal type. On CT, most bone tumors (75%) showed internal calcification with remodeling or destruction of the adjacent bone. No soft tissue tumors, except one case, showed internal calcification or destruction of the adjacent bone. MR imaging features were non-specific (T2 high signal intensity and contrast enhancement). CONCLUSIONS: HCNS showed various imaging findings according to their origin and pathologic subtype. HNCS should be differentiated if a bone tumor shows internal calcification and affects the adjacent bone. When diagnosing slow-growing soft tissue tumors, even if low possibility, HNCS should be considered.

A rare case report of ameloblastic fibrodentinoma with imaging features in a pediatric patient.

Ameloblastic fibrodentinoma (AFD) is a rare benign odontogenic tumor that resembles an ameloblastic fibroma with dysplastic dentin. This report presents a rare case of mandibular AFD with imaging features in a young patient. Panoramic radiography and computed tomography revealed a well-defined lesion with internal septa and calcified foci, causing inferior displacement of the adjacent molars as well as buccolingual cortical thinning and expansion of the posterior mandible. The lesion was surgically removed via mass excision, and the involved tooth was extracted under general anesthesia. During the 5-year follow-up period, no evidence of recurrence was observed. Radiologic features of AFD typically reveal a moderately to well-defined mixed lesion with varying degrees of radiopacity, reflecting the extent of dentin formation. Radiologists should consider AFD in the differential diagnosis when encountering a multilocular lesion with little dense radiopacity, particularly if it is associated with delayed eruption, impaction, or absence of involved teeth, on radiographic images of young patients.

Evaluation of masticatory muscles in temporomandibular joint disorder patients using quantitative MRI fat fraction analysis-Could it be a biomarker?

Temporomandibular joint disorders (TMDs) are closely related to the masticatory muscles, but objective and quantitative methods to evaluate muscle are lacking. IDEAL-IQ, a type of chemical shift-encoded magnetic resonance imaging (CSE-MRI), can quantify the fat fraction (FF). The purpose of this study was to develop an MR IDEAL-IQ-based method for quantitative muscle diagnosis in TMD patients. A total of 65 patients who underwent 3 T MRI scans, including CSE-MRI sequences, were retrospectively included. MRI diagnoses and clinical data were reviewed. There were 19 patients in the normal group and 46 patients in the TMD group with unilateral disc displacement. The TMD group was subdivided into those with and without clenching. The right and left FF values of the masseter, medial, and lateral pterygoid muscles were measured twice by two oral radiologists on CSE-MRI, and the average value was used. FF measurements using CSE-MRI showed excellent intra- and inter-observer agreement (ICC > 0.889 for both). There were no statistically significant differences between the right and left FF values in the masseter, medial pterygoid, and lateral pterygoid of the normal group (p > 0.05). A statistically significant difference was found in the TMD group without clenching, in which the masseter muscle had a statistically significantly lower FF value on the disc displacement side (3.94 ± 1.61) than on the normal side (4.52 ± 2.24) (p < 0.05). CSE-MRI, which can reproducibly quantify muscle FF values, is expected to be a biomarker for objective muscle evaluation in TMD patients. The masseter muscle is expected to be particularly useful compared to other masticatory muscles, but further research is needed.

Attention-guided jaw bone lesion diagnosis in panoramic radiography using minimal labeling effort.

Developing a deep-learning-based diagnostic model demands extensive labor for medical image labeling. Attempts to reduce the labor often lead to incomplete or inaccurate labeling, limiting the diagnostic performance of models. This paper (i) constructs an attention-guiding framework that enhances the diagnostic performance of jaw bone pathology by utilizing attention information with partially labeled data; (ii) introduces an additional loss to minimize the discrepancy between network attention and its label; (iii) introduces a trapezoid augmentation method to maximize the utility of minimally labeled data. The dataset includes 716 panoramic radiograph data for jaw bone lesions and normal cases collected and labeled by two radiologists from January 2019 to February 2021. Experiments show that guiding network attention with even 5% of attention-labeled data can enhance the diagnostic accuracy for pathology from 92.41 to 96.57%. Furthermore, ablation studies reveal that the proposed augmentation methods outperform prior preprocessing and augmentation combinations, achieving an accuracy of 99.17%. The results affirm the capability of the proposed framework in fine-grained diagnosis using minimally labeled data, offering a practical solution to the challenges of medical image analysis.

Developing evidence-based clinical imaging guidelines for the diagnosis of vertically fractured teeth.

OBJECTIVES: This study aimed to develop an evidence-based clinical imaging guideline for teeth suspected with vertical root fractures. METHODS: An adaptation methodology based on the Korean Clinical Imaging Guidelines (K-CIG) was used in the guideline development process. After searching for guidelines using major databases such as Ovid-Medline, Elsevier-Embase, National Guideline Clearinghouse, and Guideline International Network, as well as domestic databases such as KoreaMed, KMbase, and KoMGI, two reviewers analyzed the retrieved articles. The retrieved articles were included in this review using well-established inclusion criteria. RESULTS: Twenty articles were identified through an online search, of which three were selected for guideline development. Based on these three guidelines, this study developed specific recommendations concerning the optimal imaging modality for diagnosing teeth suspected of vertical root fractures. CONCLUSIONS: Periapical radiography is the preferred method for assessing teeth with mastication-related pain and suspected vertical root fractures. However, if intraoral radiographs do not provide sufficient information about root fractures, a small FOV CBCT may be considered. However, the use of CBCT in endodontically treated teeth is significantly constrained by the presence of artificial shading.

Automatic diagnosis of true proximity between the mandibular canal and the third molar on panoramic radiographs using deep learning.

Evaluating the mandibular canal proximity is crucial for planning mandibular third molar extractions. Panoramic radiography is commonly used for radiological examinations before third molar extraction but has limitations in assessing the true contact relationship between the third molars and the mandibular canal. Therefore, the true relationship between the mandibular canal and molars can be determined only through additional cone-beam computed tomography (CBCT) imaging. In this study, we aimed to develop an automatic diagnosis method based on a deep learning model that can determine the true proximity between the mandibular canal and third molars using only panoramic radiographs. A total of 901 third molars shown on panoramic radiographs were examined with CBCT imaging to ascertain whether true proximity existed between the mandibular canal and the third molar by two radiologists (450 molars: true contact, 451 molars: true non-contact). Three deep learning models (RetinaNet, YOLOv3, and EfficientDet) were developed, with performance metrics of accuracy, sensitivity, and specificity. EfficientDet showed the highest performance, with an accuracy of 78.65%, sensitivity of 82.02%, and specificity of 75.28%. The proposed deep learning method can be helpful when clinicians must evaluate the proximity of the mandibular canal and a third molar using only panoramic radiographs without CBCT.

Automatic diagnosis of retention pseudocyst in the maxillary sinus on panoramic radiographs using a convolutional neural network algorithm.

The evaluation of the maxillary sinus is very important in dental practice such as tooth extraction and implantation because of its proximity to the teeth, but it is not easy to evaluate because of the overlapping structures such as the maxilla and the zygoma on panoramic radiographs. When doom-shaped retention pseudocysts are observed in sinus on panoramic radiographs, they are often misdiagnosed as cysts or tumors, and additional computed tomography is performed, resulting in unnecessary radiation exposure and cost. The purpose of this study was to develop a deep learning model that automatically classifies retention pseudocysts in the maxillary sinuses on panoramic radiographs. A total of 426 maxillary sinuses from panoramic radiographs of 213 patients were included in this study. These maxillary sinuses included 86 sinuses with retention pseudocysts, 261 healthy sinuses, and 79 sinuses with cysts or tumors. An EfficientDet model first introduced by Tan for detecting and classifying the maxillary sinuses was developed. The developed model was trained for 200 times on the training and validation datasets (342 sinuses), and the model performance was evaluated in terms of accuracy, sensitivity, and specificity on the test dataset (21 retention pseudocysts, 43 healthy sinuses, and 20 cysts or tumors). The accuracy of the model for classifying retention pseudocysts was 81%, and the model also showed higher accuracy for classifying healthy sinuses and cysts or tumors (98% and 90%, respectively). One of the 21 retention pseudocysts in the test dataset was misdiagnosed as a cyst or tumor. The proposed model for automatically classifying retention pseudocysts in the maxillary sinuses on panoramic radiographs showed excellent diagnostic performance. This model could help clinicians automatically diagnose the maxillary sinuses on panoramic radiographs.

Comparison of the clinical usefulness of structured and free-text reports for interpretation of jaw lesions on cone beam computed tomography images.

OBJECTIVE: This study compared the clinical usefulness of structured reports (SRs) and free-text reports (FTRs) of lesions depicted on cone beam computed tomography (CBCT) images from the perspectives of report providers and receivers. STUDY DESIGN: In total, 36 CBCT images of jaw lesions obtained between February 2020 and August 2020 were evaluated. A working group of 3 oral and maxillofacial radiologists (OMRs) established a reporting system and prepared reports. Evaluation group I (2 OMRs) wrote SRs and FTRs for each case and assessed the reporting process for the criteria of convenience and organization. Evaluation group II (3 general practitioners [GPs] and 3 oral and maxillofacial surgeons [OMSs]) assessed the reports for the criteria of productivity, consistency, and organization. A 5-point Likert scale was used to assess the usefulness of each report. Scores were statistically compared according to report type with the paired Wilcoxon signed-rank test. RESULTS: The SRs scored significantly higher for all criteria as assessed by evaluation group I and the GPs of group II (P < .001). The FTRs scored significantly higher for productivity and organization as assessed by the OMSs of group II (P = .005 for both criteria). CONCLUSIONS: The clinical usefulness of reports may differ according to roles of the report recipients in diagnosis and treatment.

Harmonization of robust radiomic features in the submandibular gland using multi-ultrasound systems: a preliminary study.

OBJECTIVE: This study aimed to identify robust radiomic features in multiultrasonography of the submandibular gland and normalize the interdevice discrepancies by applying a machine-learning-based harmonization method. METHODS: Ultrasonographic images of normal submandibular gland of young healthy adults, aged between 20 and 40 years, were selected from two different devices. In a total of 30 images, the region of interest was determined along the border of gland parenchyma, and 103 radiomic features were extracted using A-VIEW. The coefficient of variation (CV) was obtained for individual features, and the features showing CV less than 10% were selected. For the selected features, the interdevice discrepancy was normalized using machine-learning method, called the ComBat harmonization. Median differences of the features between the two scanners, before and after harmonization, were compared using Mann-Whitney U-test; confidence interval of 95%. RESULTS: Among total 103 radiomic features, 17 features were selected as robust, showing CV less than 10% in both scanners. All values of selected features, except two, showed a statistical difference between the two devices. After applying the ComBat harmonization method, the median and distribution of the 16 features were harmonized to show no significant difference between the two scanners (p > 0.05). One feature remained different (p ≤ 0.05). CONCLUSION: On ultrasonographic examination, robust radiomic features for normal submandibular gland were obtained and interdevice normalization was efficiently conducted using ComBat harmonization. Our findings would be useful for multidevices or multicenter studies based on clinical ultrasonographic imaging data to improve the accuracy of the overall diagnostic model.

Development of deep learning model and evaluation in real clinical practice of lingual mandibular bone depression (Stafne cyst) on panoramic radiographs.

OBJECTIVES: Lingual mandibular bone depression (LMBD) is a developmental bony defect in the lingual aspect of the mandible that does not require any surgical treatment. It is sometimes confused with a cyst or another radiolucent pathologic lesion on panoramic radiography. Thus, it is important to differentiate LMBD from true pathological radiolucent lesions requiring treatment. This study aimed to develop a deep learning model for the fully automatic differential diagnosis of LMBD from true pathological radiolucent cysts or tumors on panoramic radiographs without a manual process and evaluate the model's performance using a test dataset that reflected real clinical practice. METHODS: A deep learning model using the EfficientDet algorithm was developed with training and validation data sets (443 images) consisting of 83 LMBD patients and 360 patients with true pathological radiolucent lesions. The test data set (1500 images) consisted of 8 LMBD patients, 53 patients with pathological radiolucent lesions, and 1439 healthy patients based on the clinical prevalence of these conditions in order to simulate real-world conditions, and the model was evaluated in terms of accuracy, sensitivity, and specificity using this test data set. RESULTS: The model's accuracy, sensitivity, and specificity were more than 99.8%, and only 10 out of 1500 test images were erroneously predicted. CONCLUSION: Excellent performance was found for the proposed model, in which the number of patients in each group was composed to reflect the prevalence in real-world clinical practice. The model can help dental clinicians make accurate diagnoses and avoid unnecessary examinations in real clinical settings.

Impact of physiological parameters on the parotid gland fat fraction in a normal population.

Quantifying physiological fat tissue in the organs is important to further assess the organ's pathologic status. This study aimed to investigate the impact of body mass index (BMI), age, and sex on the fat fraction of normal parotid glands. Patients undergoing magnetic resonance imaging (MRI) of iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL-IQ) due to non-salivary gland-related disease were reviewed. Clinical information of individual patients was categorized into groups based on BMI (under/normal/overweight), age (age I/age II/age III), and sex (female/male) and an inter-group comparison of the fat fraction values of both parotid glands was conducted. Overall, in the 626 parotid glands analyzed, the fat fraction of the gland was 35.80%. The mean fat fraction value increased with BMI (30.23%, 35.74%, and 46.61% in the underweight, normal and overweight groups, respectively [p < 0.01]) and age (32.42%, 36.20%, and 41.94% in the age I, II, and III groups, respectively [p < 0.01]). The fat content of normal parotid glands varies significantly depending on the body mass and age regardless of sex. Therefore, the patient's age and body mass should be considered when evaluating fatty change in the parotid glands in imaging results.

Parotid gland evaluation of menopausal women with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method of MRI: a pilot study.

OBJECTIVES: This study aimed to analyze the quantitative fat fraction (FF) of the parotid gland in menopausal females with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method. METHODS: A total 138 parotid glands of 69 menopausal females were enrolled in our study and participants were divided into normal group and xerostomia group. The xerostomia group was divided into those with or without Sjögren's syndrome. Participants underwent IDEAL-IQ sequences of MRI and the stimulated salivary flow test (s-SFR). The unpaired t-test was used to compare the FFs between the normal and xerostomia groups and between the subgroups with and without Sjögren's syndrome. The correlation between FF and s-SFR was analyzed by Pearson's correlation. RESULTS: Excellent intra- and interobserver agreement during the measurement of FFs by IDEAL-IQ method (ICC>0.99, respectively). FF value in the xerostomia group was statistically significantly higher than the value in the normal group (p < 0.05). Within the xerostomia group, the average FF value of females with Sjögren's syndrome was higher than that of females without Sjögren's syndrome. However, the difference was not statistically significant (p > 0.05). Within the xerostomia group, FF value correlated negatively with s-SFR (p < 0.05). CONCLUSIONS: The FF of the parotid gland was higher in the xerostomia group than in the normal group and FF value and s-SFR showed a negative correlation. Analyses of the FF using IDEAL-IQ in menopausal females can be helpful for the quantitative diagnosis of xerostomia.

Deep learning synthesis of cone-beam computed tomography from zero echo time magnetic resonance imaging.

Cone-beam computed tomography (CBCT) produces high-resolution of hard tissue even in small voxel size, but the process is associated with radiation exposure and poor soft tissue imaging. Thus, we synthesized a CBCT image from the magnetic resonance imaging (MRI), using deep learning and to assess its clinical accuracy. We collected patients who underwent both CBCT and MRI simultaneously in our institution (Seoul). MRI data were registered with CBCT data, and both data were prepared into 512 slices of axial, sagittal, and coronal sections. A deep learning-based synthesis model was trained and the output data were evaluated by comparing the original and synthetic CBCT (syCBCT). According to expert evaluation, syCBCT images showed better performance in terms of artifacts and noise criteria but had poor resolution compared to the original CBCT images. In syCBCT, hard tissue showed better clarity with significantly different MAE and SSIM. This study result would be a basis for replacing CBCT with non-radiation imaging that would be helpful for patients planning to undergo both MRI and CBCT.

Radiomics-based sialadenitis staging in contrast-enhanced computed tomography and ultrasonography: a preliminary rat model study.

OBJECTIVE: The aim of this study was to measure the ability of radiomics analysis to diagnose different stages of sialadenitis, compare the diagnostic accuracy of computed tomography (CT) and ultrasonography (US), and suggest radiomics features selected through 3 machine learning algorithms that would be helpful in discriminating between stages of sialadenitis with both imaging systems. STUDY DESIGN: Wistar rats were treated to induce acute and chronic sialadenitis in the left and right submandibular glands, respectively. Contrast-enhanced CT and US of the glands were performed, followed by extirpation and histopathologic confirmation. Radiomics feature values of the glands were obtained from all images. Based on 3 feature selection methods, an optimal feature set was defined after a comparison of the receiver operating characteristic area under the curve (AUC) of each combination of 3 deep learning algorithms and 3 classification models. RESULTS: The attribute features for the CT model were 2 gray-level run length matrices and 2 gray-level zone length matrices. In the US model, there were 2 gray-level co-occurrence matrices and 2 gray-level zone length matrices. The most accurate diagnostic models of CT and US yielded outstanding (AUC = 1.000) and excellent (AUC = 0.879) discrimination, respectively. CONCLUSIONS: The radiomics diagnostic model using gray-level zone length matrices-based features conferred clinically outstanding discriminating ability among stages of sialadenitis using CT and excellent discrimination with US in almost all combinations of machine learning feature selections and classification models.