Automatic segmentation and classification of frontal sinuses for sex determination from CBCT scans using a two-stage anatomy-guided attention network

Sex determination is essential for identifying unidentified individuals, particularly in forensic contexts. Traditional methods for sex determination involve manual measurements of skeletal features on CBCT scans. However, these manual measurements are labor-intensive, time-consuming, and error-prone. The purpose of this study was to automatically and accurately determine sex on a CBCT scan using a two-stage anatomy-guided attention network (SDetNet). SDetNet consisted of a 2D frontal sinus segmentation network (FSNet) and a 3D anatomy-guided attention network (SDNet). FSNet segmented frontal sinus regions in the CBCT images and extracted regions of interest (ROIs) near them. Then, the ROIs were fed into SDNet to predict sex accurately. To improve sex determination performance, we proposed multi-channel inputs (MSIs) and an anatomy-guided attention module (AGAM), which encouraged SDetNet to learn differences in the anatomical context of the frontal sinus between males and females. SDetNet showed superior sex determination performance in the area under the receiver operating characteristic curve, accuracy, Brier score, and specificity compared with the other 3D CNNs. Moreover, the results of ablation studies showed a notable improvement in sex determination with the embedding of both MSI and AGAM. Consequently, SDetNet demonstrated automatic and accurate sex determination by learning the anatomical context information of the frontal sinus on CBCT scans.

Radiological manifestations and clinical findings of patients with oncologic and osteoporotic medication-related osteonecrosis of the jaw

Medication-related osteonecrosis of the jaw (MRONJ) poses a challenging form of osteomyelitis in patients undergoing antiresorptive therapies in contrast to conventional osteomyelitis. This study aimed to compare the clinical and radiological features of MRONJ between patients receiving low-dose medications for osteoporosis and those receiving high-dose medications for oncologic purposes. The clinical, panoramic radiographic, and computed tomography data of 159 patients with MRONJ (osteoporotic group, n = 120; oncologic group, n = 39) who developed the condition after using antiresorptive medications for the management of osteoporosis or bone malignancy were analyzed. The osteoporotic group was older (75.8 vs. 60.4 years, p < 0.01) and had a longer duration of medication usage than the oncologic group (58.1 vs. 28.0 months, p < 0.01). Pus discharge and swelling were more common in the osteoporotic group (p < 0.05), whereas bone exposure was more frequent in the oncologic group (p < 0.01). The mandibular cortical index (MCI) in panoramic radiographs was higher in the osteoporotic group (p < 0.01). The mean sequestra size was larger in the oncologic group than in the osteoporotic group (15.3 vs. 10.6 mm, p < 0.05). The cured rate was significantly higher in the osteoporotic group (66.3% vs. 33.3%, p < 0.01). Oncologic MRONJ exhibited distinct clinical findings including rapid disease onset, fewer purulent signs, and lower cure rates than osteoporotic MRONJ. Radiological features such as sequestrum size on CT scan, and MCI values on panoramic radiographs, may aid in differentiating MRONJ in osteoporotic and oncologic patients.

Clinical and radiological features of malformed mesiodens in the nasopalatine canal: an observational study

OBJECTIVES

The purpose of this study is to investigate the morphological changes that occur when mesiodens is located within the nasopalatine canal, as well as clinical characteristics.

METHODS

Clinical records and CT images of patients who had mesiodens in the nasopalatine canal were retrospectively analysed. In addition to demographic information, clinical symptoms and complications associated with extraction of mesiodens were recorded. Using CT images, number, location, size, and tooth morphology were evaluated.

RESULTS

This study included 32 patients and 38 mesiodens within the nasopalatine canal. Supernumerary teeth exhibited a characteristic feature of thin and elongated shape in the canal (narrow width and elongation were observed in 96.6% and 53.3% of the patients, respectively). Fusion was found in 4 patients and dilaceration in 12. A complication occurred in 2 patients, which was tooth remnant, not a neurologic complication. Only 5 mesiodens could be detected in the nasopalatine canal on panoramic images.

CONCLUSIONS

Morphological abnormalities in mesiodens within the nasopalatine canal were frequently detected, and these could be effectively diagnosed through 3D imaging analysis.

Automatic and robust estimation of sex and chronological age from panoramic radiographs using a multi-task deep learning network: a study on a South Korean population

Sex and chronological age estimation are crucial in forensic investigations and research on individual identification. Although manual methods for sex and age estimation have been proposed, these processes are labor-intensive, time-consuming, and error-prone. The purpose of this study was to estimate sex and chronological age from panoramic radiographs automatically and robustly using a multi-task deep learning network (ForensicNet). ForensicNet consists of a backbone and both sex and age attention branches to learn anatomical context features of sex and chronological age from panoramic radiographs and enables the multi-task estimation of sex and chronological age in an end-to-end manner. To mitigate bias in the data distribution, our dataset was built using 13,200 images with 100 images for each sex and age range of 15-80 years. The ForensicNet with EfficientNet-B3 exhibited superior estimation performance with mean absolute errors of 2.93 ± 2.61 years and a coefficient of determination of 0.957 for chronological age, and achieved accuracy, specificity, and sensitivity values of 0.992, 0.993, and 0.990, respectively, for sex prediction. The network demonstrated that the proposed sex and age attention branches with a convolutional block attention module significantly improved the estimation performance for both sex and chronological age from panoramic radiographs of elderly patients. Consequently, we expect that ForensicNet will contribute to the automatic and accurate estimation of both sex and chronological age from panoramic radiographs.

Multislice computed tomography demonstrating mental nerve paresthesia caused by periapical infection: A case report

Components derived from an infected lesion within the bone can spread through various passages in the mandible, particularly via the mental foramen. Radiologically, the spread of infection is typically nonspecific and challenging to characterize; however, multislice computed tomography (MSCT) can effectively detect pathological changes in soft tissues and the bone marrow space. This report describes the case of a 55-year-old woman who experienced mental nerve paresthesia due to a periapical infection of the right mandibular second premolar. MSCT imaging revealed increased attenuation around the periapical lesion extending into the mandibular canal and loss of the juxtamental foraminal fat pad. Following endodontic treatment of the tooth suspected to be the source of the infection, the patient's symptoms resolved, and the previous MSCT imaging findings were no longer present. Increased bone marrow attenuation and obliteration of the fat plane in the buccal aspect of the mental foramen may serve as radiologic indicators of inflammation spreading from the bone marrow space.

Deep learning-based automatic segmentation of the mandibular canal on panoramic radiographs: A multi-device study

Purpose

The objective of this study was to propose a deep-learning model for the detection of the mandibular canal on dental panoramic radiographs.

Materials and Methods

A total of 2,100 panoramic radiographs (PANs) were collected from 3 different machines: RAYSCAN Alpha (n=700, PAN A), OP-100 (n=700, PAN B), and CS8100 (n=700, PAN C). Initially, an oral and maxillofacial radiologist coarsely annotated the mandibular canals. For deep learning analysis, convolutional neural networks (CNNs) utilizing U-Net architecture were employed for automated canal segmentation. Seven independent networks were trained using training sets representing all possible combinations of the 3 groups. These networks were then assessed using a hold-out test dataset.

Results

Among the 7 networks evaluated, the network trained with all 3 available groups achieved an average precision of 90.6%, a recall of 87.4%, and a Dice similarity coefficient (DSC) of 88.9%. The 3 networks trained using each of the 3 possible 2-group combinations also demonstrated reliable performance for mandibular canal segmentation, as follows: 1) PAN A and B exhibited a mean DSC of 87.9%, 2) PAN A and C displayed a mean DSC of 87.8%, and 3) PAN B and C demonstrated a mean DSC of 88.4%.

Conclusion

This multi-device study indicated that the examined CNN-based deep learning approach can achieve excellent canal segmentation performance, with a DSC exceeding 88%. Furthermore, the study highlighted the importance of considering the characteristics of panoramic radiographs when developing a robust deep-learning network, rather than depending solely on the size of the dataset.

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.

Development and validation of a clinical phantom reproducing various lesions for oral and maxillofacial radiology research

Purpose

The objective of this study was to propose a method for developing a clinical phantom to reproduce various diseases that are clinically prevalent in the field of dentistry. This could facilitate diverse clinical research without unnecessarily exposing patients to radiation.

Material and Methods

This study utilized a single dry skull, which was visually and radiographically examined to evaluate its condition. Existing lesions on the dry skull were preserved, and other relevant lesions were artificially created as necessary. These lesions were then documented using intraoral radiography and cone-beam computed tomography. Once all pre-existing and reproduced lesions were confirmed by the consensus of 2 oral and maxillofacial radiologists, the skull was embedded in a soft tissue substitute. To validate the process, cone-beam computed tomography scans and panoramic radiographs were obtained of the fabricated phantom. All acquired images were subsequently evaluated.

Results

Most lesions could be identified on panoramic radiographs, although some sialoliths and cracked teeth were confirmed only through cone-beam computed tomographic images. A small gap was observed between the epoxy resin and the bone structures. However, 2 oral and maxillofacial radiologists agreed that this space did not meaningfully impact the interpretation process.

Conclusion

The newly developed phantom has potential for use as a standardized phantom within the dental field. It may be utilized for a variety of imaging studies, not only for optimization purposes, but also for addressing other experimental issues related to both 2- and 3-dimensional diagnostic radiography.

Comparison of 2D, 2.5D, and 3D segmentation networks for maxillary sinuses and lesions in CBCT images

BACKGROUND

The purpose of this study was to compare the segmentation performances of the 2D, 2.5D, and 3D networks for maxillary sinuses (MSs) and lesions inside the maxillary sinus (MSL) with variations in sizes, shapes, and locations in cone beam CT (CBCT) images under the same constraint of memory capacity.

METHODS

The 2D, 2.5D, and 3D networks were compared comprehensively for the segmentation of the MS and MSL in CBCT images under the same constraint of memory capacity. MSLs were obtained by subtracting the prediction of the air region of the maxillary sinus (MSA) from that of the MS.

RESULTS

The 2.5D network showed the highest segmentation performances for the MS and MSA compared to the 2D and 3D networks. The performances of the Jaccard coefficient, Dice similarity coefficient, precision, and recall by the 2.5D network of U-net +  + reached 0.947, 0.973, 0.974, and 0.971 for the MS, respectively, and 0.787, 0.875, 0.897, and 0.858 for the MSL, respectively.

CONCLUSIONS

The 2.5D segmentation network demonstrated superior segmentation performance for various MSLs with an ensemble learning approach of combining the predictions from three orthogonal planes.

Automatic classification of 3D positional relationship between mandibular third molar and inferior alveolar canal using a distance-aware network

The purpose of this study was to automatically classify the three-dimensional (3D) positional relationship between an impacted mandibular third molar (M3) and the inferior alveolar canal (MC) using a distance-aware network in cone-beam CT (CBCT) images. We developed a network consisting of cascaded stages of segmentation and classification for the buccal-lingual relationship between the M3 and the MC. The M3 and the MC were simultaneously segmented using Dense121 U-Net in the segmentation stage, and their buccal-lingual relationship was automatically classified using a 3D distance-aware network with the multichannel inputs of the original CBCT image and the signed distance map (SDM) generated from the segmentation in the classification stage. The Dense121 U-Net achieved the highest average precision of 0.87, 0.96, and 0.94 in the segmentation of the M3, the MC, and both together, respectively. The 3D distance-aware classification network of the Dense121 U-Net with the input of both the CBCT image and the SDM showed the highest performance of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve, each of which had a value of 1.00. The SDM generated from the segmentation mask significantly contributed to increasing the accuracy of the classification network. The proposed distance-aware network demonstrated high accuracy in the automatic classification of the 3D positional relationship between the M3 and the MC by learning anatomical and geometrical information from the CBCT images.

Automatic detection and classification of nasopalatine duct cyst and periapical cyst on panoramic radiographs using deep convolutional neural networks

OBJECTIVE

The aim of this study is to evaluate a deep convolutional neural network (DCNN) method for the detection and classification of nasopalatine duct cysts (NPDC) and periapical cysts (PAC) on panoramic radiographs.

STUDY DESIGN

A total of 1,209 panoramic radiographs with 606 NPDC and 603 PAC were labeled with a bounding box and divided into training, validation, and test sets with an 8:1:1 ratio. The networks used were EfficientDet-D3, Faster R-CNN, YOLO v5, RetinaNet, and SSD. Mean average precision (mAP) was used to assess performance. Sixty images with no lesion in the anterior maxilla were added to the previous test set and were tested on 2 dentists with no training in radiology (GP) and on EfficientDet-D3. The performances were comparatively examined.

RESULTS

The mAP for each DCNN was EfficientDet-D3 93.8%, Faster R-CNN 90.8%, YOLO v5 89.5%, RetinaNet 79.4%, and SSD 60.9%. The classification performance of EfficientDet-D3 was higher than that of the GPs' with accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 94.4%, 94.4%, 97.2%, 94.6%, and 97.2%, respectively.

CONCLUSIONS

The proposed method achieved high performance for the detection and classification of NPDC and PAC compared with the GPs and presented promising prospects for clinical application.

Differentiation between Chondrosarcoma and Synovial Chondromatosis of the Temporomandibular Joint Using CT and MR Imaging

BACKGROUND AND PURPOSE

Chondrosarcoma and synovial chondromatosis of the temporomandibular joint share overlapping clinical and histopathologic features. We aimed to identify CT and MR imaging features to differentiate chondrosarcoma from synovial chondromatosis of the temporomandibular joint.

MATERIALS AND METHODS

The CT and MR images of 12 and 35 patients with histopathologically confirmed chondrosarcoma and synovial chondromatosis of the temporomandibular joint, respectively, were retrospectively reviewed. Imaging features including lesion size, center, enhancement, destruction/sclerosis of surrounding bone, infiltration into the tendon of the lateral pterygoid muscle, calcification, periosteal reaction, and osteophyte formation were assessed. A comparison between chondrosarcoma and synovial chondromatosis was performed with a Student t test for quantitative variables and the Fisher exact test or linear-by-linear association test for qualitative variables. Receiver operating characteristic analysis was performed to determine the diagnostic performance for differentiation of chondrosarcoma and synovial chondromatosis based on a composite score obtained by assigning 1 point for each of 9 imaging features.

RESULTS

High-risk imaging features for chondrosarcoma were the following: lesion centered on the mandibular condyle, destruction of the mandibular condyle, no destruction/sclerosis of the articular eminence/glenoid fossa, infiltration into the tendon of the lateral pterygoid muscle, absent or stippled calcification, periosteal reaction, internal enhancement, and size of ≥30.5 mm. The best cutoff value to discriminate chondrosarcoma from synovial chondromatosis was the presence of any 4 of these high-risk imaging features, with an area under the curve of 0.986 and an accuracy of 95.8%.

CONCLUSIONS

CT and MR imaging features can distinguish chondrosarcoma from synovial chondromatosis of the temporomandibular joint with improved diagnostic performance when a subcombination of 9 imaging features is used.

Head and neck manifestations of fibrodysplasia ossificans progressiva: Clinical and imaging findings in 2 cases

Fibrodysplasia ossificans progressiva is a rare hereditary disorder characterized by progressive heterotopic ossification in muscle and connective tissue, with few reported cases affecting the head and neck region. Although plain radiographic findings and computed tomography features have been well documented, limited reports exist on magnetic resonance findings. This report presents 2 cases of fibrodysplasia ossificans progressiva, one with limited mouth opening due to heterotopic ossification of the lateral pterygoid muscle and the other with restricted neck movement due to heterotopic ossification of the platysma muscle. Clinical findings of restricted mouth opening or limited neck movement, along with radiological findings of associated heterotopic ossification, should prompt consideration of fibrodysplasia ossificans progressiva in the differential diagnosis. Dentists should be particularly vigilant with patients diagnosed with fibrodysplasia ossificans progressiva to avoid exposure to diagnostic biopsy and invasive dental procedures.

Nasal cavity perforation by implant fixtures: case series with emphasis on panoramic imaging of nasal cavity extending posteriorly

The nasal cavity is an important landmark when considering implant insertion into the anterior region of the maxillary arch. The perforation of implants into the nasal cavity may cause complications, such as implant migration, inflammation, or changes in nasal airflow; thus, precise assessment of the nasal cavity is mandatory.Three cases of nasal cavity perforation by dental implants are presented, including one case of implant fixture migration into the nasal cavity. On panoramic radiographs of the patients, the following common features were observed: the horizontal radiopaque line of the hard palate was observed to be inferior to or similar to that of the antral floor and the bone between the lateral wall of the nasal cavity and the medial wall of the maxillary sinus was emphasized in a triangular shape.When the maxillary sinus is small and alveolar bone resorption is severe, panoramic evaluation may cause overestimation of the available residual bone, particularly in the maxillary canine/premolar region. Therefore, the residual bone should be reevaluated three-dimensionally to measure the exact bony shape and volume.

Validation of bone mineral density measurement using quantitative CBCT image based on deep learning

The bone mineral density (BMD) measurement is a direct method of estimating human bone mass for diagnosing osteoporosis, and performed to objectively evaluate bone quality before implant surgery in dental clinics. The objective of this study was to validate the accuracy and reliability of BMD measurements made using quantitative cone-beam CT (CBCT) image based on deep learning by applying the method to clinical data from actual patients. Datasets containing 7500 pairs of CT and CBCT axial slice images from 30 patients were used to train a previously developed deep-learning model (QCBCT-NET). We selected 36 volumes of interest in the CBCT images for each patient in the bone regions of potential implants sites on the maxilla and mandible. We compared the BMDs shown in the quantitative CBCT (QCBCT) images with those in the conventional CBCT (CAL_CBCT) images at the various bone sites of interest across the entire field of view (FOV) using the performance metrics of the MAE, RMSE, MAPE (mean absolute percentage error), R² (coefficient of determination), and SEE (standard error of estimation). Compared with the ground truth (QCT) images, the accuracy of the BMD measurements from the QCBCT images showed an RMSE of 83.41 mg/cm³, MAE of 67.94 mg/cm³, and MAPE of 8.32% across all the bone sites of interest, whereas for the CAL_CBCT images, those values were 491.15 mg/cm³, 460.52 mg/cm³, and 54.29%, respectively. The linear regression between the QCBCT and QCT images showed a slope of 1.00 and a R² of 0.85, whereas for the CAL_CBCT images, those values were 0.32 and 0.24, respectively. The overall SEE between the QCBCT images and QCT images was 81.06 mg/cm³, whereas the SEE for the CAL_CBCT images was 109.32 mg/cm³. The QCBCT images thus showed better accuracy, linearity, and uniformity than the CAL_CBCT images across the entire FOV. The BMD measurements from the quantitative CBCT images showed high accuracy, linearity, and uniformity regardless of the relative geometric positions of the bone in the potential implant site. When applied to actual patient CBCT images, the CBCT-based quantitative BMD measurement based on deep learning demonstrated high accuracy and reliability across the entire FOV.

SinusC-Net for automatic classification of surgical plans for maxillary sinus augmentation using a 3D distance-guided network

The objective of this study was to automatically classify surgical plans for maxillary sinus floor augmentation in implant placement at the maxillary posterior edentulous region using a 3D distance-guided network on CBCT images. We applied a modified ABC classification method consisting of five surgical approaches for the deep learning model. The proposed deep learning model (SinusC-Net) consisted of two stages of detection and classification according to the modified classification method. In detection, five landmarks on CBCT images were automatically detected using a volumetric regression network; in classification, the CBCT images were automatically classified as to the five surgical approaches using a 3D distance-guided network. The mean MRE for landmark detection was 0.87 mm, and SDR for 2 mm or lower, 95.47%. The mean accuracy, sensitivity, specificity, and AUC for classification by the SinusC-Net were 0.97, 0.92, 0.98, and 0.95, respectively. The deep learning model using 3D distance-guidance demonstrated accurate detection of 3D anatomical landmarks, and automatic and accurate classification of surgical approaches for sinus floor augmentation in implant placement at the maxillary posterior edentulous region.

V2-Net: An Attention-guided Volumetric Regression Network for Tooth Landmark Localization on CT Images with Metal Artifacts

For virtual surgical planning in orthognathic surgery, marking tooth landmarks on CT images is an important procedure. However, the manual localization procedure of tooth landmarks is time-consuming, labor-intensive, and requires expert knowledge. Also, direct and automatic tooth landmark localization on CT images is difficult because of the lower resolution and metal artifacts of dental images. The purpose of this study was to propose an attention-guided volumetric regression network (V2-Net) for accurate tooth landmark localization on CT images with metal artifacts and lower resolution. V2-Net has an attention-guided network architecture using a coarse-to-fine-attention mechanism that guided the 3D probability distribution of tooth landmark locations within anatomical structures from the coarse V-Net to the fine V-Net for more focus on tooth landmarks. In addition, we combined attention-guided learning and a 3D attention module with optimal Pseudo Huber loss to improve the localization accuracy. Our results show that the proposed method achieves state-of-the-art accuracy of 0.85 ± 0.40 mm in terms of mean radial error, outperforming previous studies. In ablation studies, we observed that the proposed attention-guided learning and a 3D attention module improved the accuracy of tooth landmark localization in CT images of lower resolution and metal artifacts. Furthermore, our method achieved 97.92% in terms of the success detection rate within the clinically accepted accuracy range of 2.0 mm.

Safety and efficacy of trastuzumab biosimilar plus irinotecan or gemcitabine in patients with previously treated HER2 (ERBB2)-positive non-breast/non-gastric solid tumors: a phase II basket trial with circulating tumor DNA analysis

BACKGROUND

Human epidermal growth factor receptor 2 (HER2) (ERBB2)-directed agents are standard treatments for patients with HER2-positive breast and gastric cancer. Herein, we report the results of an open-label, single-center, phase II basket trial to investigate the efficacy and safety of trastuzumab biosimilar (Samfenet®) plus treatment of physician's choice for patients with previously treated HER2-positive advanced solid tumors, along with biomarker analysis employing circulating tumor DNA (ctDNA) sequencing.

METHODS

Patients with HER2-positive unresectable or metastatic non-breast, non-gastric solid tumors who failed at least one prior treatment were included in this study conducted at Asan Medical Center, Seoul, Korea. Patients received trastuzumab combined with irinotecan or gemcitabine at the treating physicians' discretion. The primary endpoint was the objective response rate as per RECIST version 1.1. Plasma samples were collected at baseline and at the time of disease progression for ctDNA analysis.

RESULTS

Twenty-three patients were screened from 31 December 2019 to 17 September 2021, and 20 were enrolled in this study. Their median age was 64 years (30-84 years), and 13 patients (65.0%) were male. The most common primary tumor was hepatobiliary cancer (seven patients, 35.0%), followed by colorectal cancer (six patients, 30.0%). Among 18 patients with an available response evaluation, the objective response rate was 11.1% (95% confidence interval 3.1% to 32.8%). ERBB2 amplification was detected from ctDNA analysis of baseline plasma samples in 85% of patients (n = 17), and the ERBB2 copy number from ctDNA analysis showed a significant correlation with the results from tissue sequencing. Among 16 patients with post-progression ctDNA analysis, 7 (43.8%) developed new alterations. None of the patients discontinued the study due to adverse events.

CONCLUSIONS

Trastuzumab plus irinotecan or gemcitabine was safe and feasible for patients with previously treated HER2-positive advanced solid tumors with modest efficacy outcomes, and ctDNA analysis was useful for detecting HER2 amplification.

Structure-preserving quality improvement of cone beam CT images using contrastive learning

Cone-beam CT (CBCT) is widely used in dental clinics but exhibits limitations in assessing soft tissue pathology because of its lack of contrast resolution and low Hounsfield Units (HU) quantification accuracy. We aimed to increase the image quality and HU accuracy of CBCTs while preserving anatomical structures. We generated CT-like images from CBCT images using a patchwise contrastive learning-based GAN model. Our model was trained on unpaired CT and CBCT datasets with the novel combination of losses and the feature extractor pretrained on our training dataset. We evaluated the quality of the images generated by our model in terms of Fréchet inception distance (FID), peak signal-to-noise ratio (PSNR), mean absolute error (MAE), and root mean square error (RMSE). Additionally, the structure preservation performance was assessed by the structure score. As a result, the generated CT-like images by our model were significantly superior to those generated by various baseline models in terms of FID, PSNR, MAE, RMSE, and structure score. Therefore, we demonstrated that our model provided the complementary benefits of preserving the anatomical structures of the input CBCT images and improving the image quality to be similar to those of CT images.

Preoperative Chemoradiotherapy With Capecitabine With or Without Temozolomide in Patients With Locally Advanced Rectal Cancer: A Prospective, Randomised Phase II Study Stratified by O6-Methylguanine DNA Methyltransferase Status: KCSG-CO17-02

AIMS

To evaluate the clinical efficacy of adding temozolomide (TMZ) to preoperative capecitabine (CAP)-based chemoradiotherapy in patients with locally advanced rectal cancer (LARC) and validate O⁶-methylguanine DNA methyltransferase (MGMT) methylation status as a predictive marker for TMZ combined regimens.

MATERIALS AND METHODS

LARC patients with clinical stage II (cT3-4N0) or III (cT_anyN+) disease were enrolled. They were stratified into unmethylated MGMT (uMGMT) and methylated MGMT (mMGMT) groups by methylation-specific polymerase chain reaction before randomisation and were then randomly assigned (1:1) to one of four treatment arms: uMGMT/CAP (arm A), uMGMT/TMZ + CAP (arm B), mMGMT/CAP (arm C) and mMGMT/TMZ + CAP (arm D). The primary end point was the pathological complete response (pCR) rate.

RESULTS

Between November 2017 and July 2020, 64 patients were randomised. Slow accrual caused early study termination. After excluding four ineligible patients, 60 were included in the full analysis set. The pCR rate was 15.0% (9/60), 0%, 14.3%, 18.8% and 26.7% for the entire cohort, arms A, B, C and D, respectively (P = 0.0498 between arms A and D). The pCR rate was 9.7% in the CAP group (arms A + C), 20.7% in the TMZ + CAP group (arms B + D), 6.9% in the uMGMT group (arms A + B) and 22.6% in the mMGMT group (arms C + D). Grade 1-2 nausea or vomiting was significantly more frequent in the TMZ + CAP treatment groups (arms B + D) than in the CAP treatment groups (arms A + C, P < 0.001) with no difference in grade 3 adverse events. There were no grade 4 or 5 adverse events.

CONCLUSION

The addition of TMZ to CAP-based chemoradiotherapy tended to improve pCR rates, particularly in those with mMGMT LARC. MGMT status may warrant further investigation as a predictive biomarker for chemotherapeutic agents and radiotherapy.

A case report of an unusual temporomandibular joint mass: Nodular fasciitis

Nodular fasciitis (NF) is a benign myofibroblastic proliferation that grows very rapidly, mimicking a sarcoma on imaging. It is treated by local excision, and recurrence has been reported in only a few cases, even when excised incompletely. The most prevalent diagnoses of temporomandibular joint (TMJ) masses include synovial chondromatosis, pigmented villonodular synovitis, and sarcomas. Cases of NF in the TMJ are extremely rare, and only 3 cases have been reported to date. Due to its destructive features and rarity, NF has often been misdiagnosed as a more aggressive lesion, which could expose patients to unnecessary and invasive treatment approaches beyond repair. This report presents a case of NF in the TMJ, focusing on various imaging features, along with a literature review aiming to determine the hallmark features of NF in the TMJ and highlight the diagnostic challenges.

Effects of household water-repellent agents and number of coating layers on the physical properties of cotton woven fabrics

The increased interest in outdoor activities has prompted the demand for water-repellent fabrics that can withstand various environmental factors. In this study, the water repellency and physical properties, namely thickness, weight, tensile strength, elongation, and stiffness, of cotton woven fabrics were analyzed according to various treatments with different types of household water-repellent agents and number of coating layers. Fluorine-, silicone-, and wax-based water-repellent agents were coated on cotton woven fabrics once, thrice, and five times. Thickness, weight, and stiffness increased with the number of coating layers, which may reduce comfort. These properties increased minimally for the fluorine- and silicone-based water-repellent agents, whereas they considerably increased for the wax-based water-repellent agent. The fluorine-based water-repellent agent had a low water repellency rating of 2.2 even after five coating layers, and the silicone-based water-repellent agent had a higher rating of 3.4 with the same five coating layers. Meanwhile, the wax-based water-repellent agent had the highest water repellency rating of 5 even with only one coating layer, which was maintained with repeated coatings. Therefore, fluorine- and silicone-based water-repellent agents minimally altered the fabric properties even with repeated coatings; multiple coating layers, especially five or more layers for the fluorine-based water-repellent agent, are recommended to attain excellent water repellency. Conversely, one coating layer of the wax-based water-repellent agent is recommended to retain the comfort of the wearer.

Deep learning-based apical lesion segmentation from panoramic radiographs

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-related osteomyelitis of the maxilla in a post-COVID-19 patient

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.

High-precision measurement of the W boson mass with the CDF II detector

The mass of the W boson, a mediator of the weak force between elementary particles, is tightly constrained by the symmetries of the standard model of particle physics. The Higgs boson was the last missing component of the model. After observation of the Higgs boson, a measurement of the W boson mass provides a stringent test of the model. We measure the W boson mass, M_W, using data corresponding to 8.8 inverse femtobarns of integrated luminosity collected in proton-antiproton collisions at a 1.96 tera-electron volt center-of-mass energy with the CDF II detector at the Fermilab Tevatron collider. A sample of approximately 4 million W boson candidates is used to obtain [Formula: see text], the precision of which exceeds that of all previous measurements combined (stat, statistical uncertainty; syst, systematic uncertainty; MeV, mega-electron volts; c, speed of light in a vacuum). This measurement is in significant tension with the standard model expectation.

Automatic detection of teeth and dental treatment patterns on dental panoramic radiographs using deep neural networks

Disaster victim identification issues are especially critical and urgent after a large-scale disaster. The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on dental panoramic radiographs (DPRs) using deep learning to promote its applicability as human identifiers. A total of 1 638 DPRs, of which the chronological age ranged from 20 to 49 years old, were collected from January 2000 to November 2020. This dataset consisted of natural teeth, prostheses, teeth with root canal treatment, and implants. The detection of natural teeth and dental treatment patterns including the identification of teeth number was done with a pre-trained object detection network which was a convolutional neural network modified by EfficientDet-D3. The objective metrics for the average precision were 99.1% for natural teeth, 80.6% for prostheses, 81.2% for treated root canals, and 96.8% for implants, respectively. The values for the average recall were 99.6%, 84.3%, 89.2%, and 98.1%, in the same order, respectively. This study showed outstanding performance of convolutional neural network using dental panoramic radiographs in automatically identifying teeth number and detecting natural teeth, prostheses, treated root canals, and implants.

It is useful to use dental panoramic radiographs to perform the disaster victim identification (DVI).

Correlation analysis between radiation exposure and the image quality of cone-beam computed tomography in the dental clinical environment

Purpose

This study was conducted to measure the radiation exposure and image quality of various cone-beam computed tomography (CBCT) machines under common clinical conditions and to analyze the correlation between them.

Materials and Methods

Seven CBCT machines used frequently in clinical practice were selected. Because each machine has various sizes of fields of view (FOVs), 1 large FOV and 1 small FOV were selected for each machine. Radiation exposure was measured using a dose-area product (DAP) meter. The quality of the CBCT images was analyzed using 8 image quality parameters obtained using a dental volume tomography phantom. For statistical analysis, regression analysis using a generalized linear model was used.

Results

Polymethyl-methacrylate (PMMA) noise and modulation transfer function (MTF) 10% showed statistically significant correlations with DAP values, presenting positive and negative correlations, respectively (P<0.05). Image quality parameters other than PMMA noise and MTF 10% did not demonstrate statistically significant correlations with DAP values.

Conclusion

As radiation exposure and image quality are not proportionally related in clinically used equipment, it is necessary to evaluate and monitor radiation exposure and image quality separately.

Radiographic features of cleidocranial dysplasia on panoramic radiographs

Purpose

This study aimed to investigate the panoramic imaging features of cleidocranial dysplasia (CCD) with a relatively large sample.

Materials and Methods

The panoramic radiographs of 40 CCD patients who visited Seoul National University Dental Hospital between 2004 and 2018 were analyzed. Imaging features were recorded based on the consensus of 2 radiologists according to the following criteria: the number of supernumerary teeth and impacted teeth; the shape of the ascending ramus, condyle, coronoid process, sigmoid notch, antegonial notch, and hard palate; the mandibular midline suture; and the gonial angle.

Results

The mean number of supernumerary teeth and impacted teeth were 6.1 and 8.3, respectively, and the supernumerary teeth and impacted teeth were concentrated in the anterior and premolar regions. Ramus parallelism was dominant (32 patients, 80.0%) and 5 patients (12.5%) showed a mandibular midline suture. The majority of mandibular condyles showed a rounded shape (61.2%), and most coronoid processes were triangular (43.8%) or round (37.5%). The mean gonial angle measured on panoramic radiographs was 122.6°.

Conclusion

Panoramic radiographs were valuable for identifying the features of CCD and confirming the diagnosis. The presence of numerous supernumerary teeth and impacted teeth, especially in the anterior and premolar regions, and the characteristic shapes of the ramus, condyle, and coronoid process on panoramic radiographs may help to diagnose CCD.

Pemetrexed plus cisplatin in patients with previously treated advanced sarcoma: a multicenter, single-arm, phase II trial

Background

Patients with advanced sarcomas have a poor prognosis and few treatment options that improve overall survival. We assessed the efficacy and tolerability of pemetrexed and cisplatin combination therapy in patients with refractory bone and soft tissue sarcoma (STS).

Patients and Methods

Patients were included in this multicenter, phase II study (ClinicalTrials.gov identifier NCT03809637) if they progressed after receiving one or more chemotherapy regimens containing an anthracycline and/or ifosfamide. Pemetrexed was first administered intravenously, followed by cisplatin, over a cycle of 21 days, for a maximum of six cycles. The primary endpoint was a progression-free rate (PFR) at 3 months (3-month PFR).

Results

From January 2017 to September 2019, we enrolled 37 patients; of these, 73% had previously undergone three or more rounds of chemotherapy. Five patients (13.5%) exhibited objective responses, including two patients (2/6, 33.3%) with malignant peripheral nerve sheath tumors, one patient (1/4, 25%) with synovial sarcoma, one patient (1/4, 25%) with undifferentiated pleomorphic sarcoma, and one patient (1/4, 25%) with angiosarcoma. The median progression-free survival was 2.6 months, and the 3-month PFR was 45.9% (n = 17). None of the four patients with osteosarcoma exhibited objective responses or were progression free at 3 months. The most frequent treatment-related grade 3-4 toxicities included neutropenia (16.2%), anemia (13.5%), thrombocytopenia (13.5%), and fatigue (8.1%). Among 26 patients (70.3%) available for immunohistochemical assessments, patients in the low-excision repair cross-complementation group 1 (ERCC1) and low-thymidylate synthase expression groups showed a tendency for longer overall survival.

Conclusions

Combination therapy with pemetrexed and cisplatin was associated with clinically meaningful and sustained responses among patients with advanced and refractory STS. The combination therapy met its predefined primary study endpoint.

•

Pemetrexed and cisplatin show promising efficacy for advanced sarcoma treatment, particularly as a salvage therapy option.

•

The combination therapy met its predefined primary endpoint, with a 3-month PFR of 45.9%.

•

Pemetrexed and cisplatin showed acceptable toxicity in heavily treated sarcoma patients.

QCBCT-NET for direct measurement of bone mineral density from quantitative cone-beam CT: a human skull phantom study

The purpose of this study was to directly and quantitatively measure BMD from Cone-beam CT (CBCT) images by enhancing the linearity and uniformity of the bone intensities based on a hybrid deep-learning model (QCBCT-NET) of combining the generative adversarial network (Cycle-GAN) and U-Net, and to compare the bone images enhanced by the QCBCT-NET with those by Cycle-GAN and U-Net. We used two phantoms of human skulls encased in acrylic, one for the training and validation datasets, and the other for the test dataset. We proposed the QCBCT-NET consisting of Cycle-GAN with residual blocks and a multi-channel U-Net using paired training data of quantitative CT (QCT) and CBCT images. The BMD images produced by QCBCT-NET significantly outperformed the images produced by the Cycle-GAN or the U-Net in mean absolute difference (MAD), peak signal to noise ratio (PSNR), normalized cross-correlation (NCC), structural similarity (SSIM), and linearity when compared to the original QCT image. The QCBCT-NET improved the contrast of the bone images by reflecting the original BMD distribution of the QCT image locally using the Cycle-GAN, and also spatial uniformity of the bone images by globally suppressing image artifacts and noise using the two-channel U-Net. The QCBCT-NET substantially enhanced the linearity, uniformity, and contrast as well as the anatomical and quantitative accuracy of the bone images, and demonstrated more accuracy than the Cycle-GAN and the U-Net for quantitatively measuring BMD in CBCT.

Orthokeratinized odontogenic cyst: A large series and comprehensive literature review with emphasis on synchronous multiple occurrence and neoplastic transformation

OBJECTIVES

The objective of this study was to demonstrate the clinical, radiologic, and histologic features of orthokeratinized odontogenic cyst (OOC); determine the characteristics of multiple OOCs; and present rare but significant manifestations of OOC.

STUDY DESIGN

A clinical, radiologic, and histopathologic study of 65 primary and 2 recurrent OOC cases was performed retrospectively along with a comprehensive literature review.

RESULTS

OOCs shared similar radiologic findings with odontogenic keratocyst, yet some showed features that have not been previously described: root resorption and radiopaque foci. Histologic review revealed a unique histiocytic lining and some findings suggestive of the multipotentiality of the odontogenic epithelium. The analysis of patients with multiple OOCs demonstrated that multiple OOCs occurred synchronously with a marked predilection for young male adults. Two unusual cases were also identified: an OOC combined with a BRAF^V600E ameloblastoma and a recurrent OOC with malignant transformation.

CONCLUSIONS

This largest series presents previously unreported radiographic and histopathologic features that can be seen in OOC. Multiple OOCs have clinical characteristics distinct from those of solitary cases. The first reported OOC associated with ameloblastoma suggests the involvement of oncogenic mutations in odontogenic tumorigenesis. Although OOC shows a low recurrence rate, the possibility of malignant transformation of recurrent OOCs should be emphasized.

Prenylflavonoids isolated from Macaranga tanarius stimulate odontoblast differentiation of human dental pulp stem cells and tooth root formation via the mitogen-activated protein kinase and protein kinase B pathways

AIM

To identify odontogenesis-promoting compounds and examine the molecular mechanism underlying enhanced odontoblast differentiation and tooth formation.

METHODOLOGY

Five different nymphaeols, nymphaeol B (NB), isonymphaeol B (INB), nymphaeol A (NA), 3'-geranyl-naringenin (GN) and nymphaeol C (NC) were isolated from the fruit of Macaranga tanarius. The cytotoxic effect of nymphaeols on human DPSCs was observed using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The effect of nymphaeols on odontoblast differentiation was analysed with Alizarin Red S staining and odontoblast marker expression was assessed using real-time polymerase chain reaction and Western blot analysis. The molecular mechanism was investigated with Western blot analysis. In order to examine the effect of INB on dentine formation in the developing tooth germ, INB-soaked beads were placed under the tooth bud explants in the collagen gel; thereafter, the tooth bud explant-bead complexes were implanted into the sub-renal capsules for 3 weeks. Tooth root formation was analysed using micro-computed tomography and histological analysis. Data are presented as mean ± standard error (SEM) values of three independent experiments, and results are compared using a two-tailed Student's t-test. The data were considered to have statistical significance when the P-value was less than 0.05.

RESULTS

Three of the compounds, NB, INB, and GN, did not exert a cytotoxic effect on human DPSCs. However, INB was most effective in promoting the deposition of calcium minerals in vitro (P < 0.001) and induced the expression of odontogenic marker genes (P < 0.05). Moreover, this compound strongly induced the phosphorylation of mitogen-activated protein (MAP) kinases and protein kinase B (AKT) (P < 0.05). The inhibition of p38 MAP, c-Jun N-terminal kinase (JNK), and AKT substantially suppressed the INB-induced odontoblast differentiation (P < 0.001). In addition, isonymphaeol B significantly induced the formation of dentine and elongation of the tooth root in vivo (P < 0.05).

CONCLUSIONS

Prenylflavonoids, including INB, exerted stimulatory effects on odontoblast differentiation and tooth root and dentine formation via the MAP kinase and AKT signalling pathways. These results suggest that nymphaeols could stimulate the repair processes for dentine defects or injuries.

Artificial intelligence in oral and maxillofacial radiology: what is currently possible?

Artificial intelligence, which has been actively applied in a broad range of industries in recent years, is an active area of interest for many researchers. Dentistry is no exception to this trend, and the applications of artificial intelligence are particularly promising in the field of oral and maxillofacial (OMF) radiology. Recent researches on artificial intelligence in OMF radiology have mainly used convolutional neural networks, which can perform image classification, detection, segmentation, registration, generation, and refinement. Artificial intelligence systems in this field have been developed for the purposes of radiographic diagnosis, image analysis, forensic dentistry, and image quality improvement. Tremendous amounts of data are needed to achieve good results, and involvement of OMF radiologist is essential for making accurate and consistent data sets, which is a time-consuming task. In order to widely use artificial intelligence in actual clinical practice in the future, there are lots of problems to be solved, such as building up a huge amount of fine-labeled open data set, understanding of the judgment criteria of artificial intelligence, and DICOM hacking threats using artificial intelligence. If solutions to these problems are presented with the development of artificial intelligence, artificial intelligence will develop further in the future and is expected to play an important role in the development of automatic diagnosis systems, the establishment of treatment plans, and the fabrication of treatment tools. OMF radiologists, as professionals who thoroughly understand the characteristics of radiographic images, will play a very important role in the development of artificial intelligence applications in this field.

Several issues regarding the diagnostic imaging of medication-related osteonecrosis of the jaw

This review presents an overview of some diagnostic imaging-related issues regarding medication-related osteonecrosis of the jaws (MRONJ), including imaging signs that can predict MRONJ in patients taking antiresorptive drugs, the early imaging features of MRONJ, the relationship between the presence or absence of bone exposure and imaging features, and differences in imaging features by stage, between advanced MRONJ and conventional osteomyelitis, between oncologic and osteoporotic patients with MRONJ, and depending on the type of medication, method of administration, and duration of medication. The early diagnosis of MRONJ can be made by the presence of subtle imaging changes such as thickening of the lamina dura or cortical bone, not by the presence of bone exposure. Most of the imaging features are relatively non-specific, and each patient's clinical findings and history should be referenced. Oral and maxillofacial radiologists and dentists should closely monitor plain radiographs of patients taking antiresorptive/antiangiogenic drugs.

Automatic diagnosis for cysts and tumors of both jaws on panoramic radiographs using a deep convolution neural network

OBJECTIVES

The purpose of this study was to automatically diagnose odontogenic cysts and tumors of both jaws on panoramic radiographs using deep learning. We proposed a novel framework of deep convolution neural network (CNN) with data augmentation for detection and classification of the multiple diseases.

METHODS

We developed a deep CNN modified from YOLOv3 for detecting and classifying odontogenic cysts and tumors of both jaws. Our data set of 1282 panoramic radiographs comprised 350 dentigerous cysts (DCs), 302 periapical cysts (PCs), 300 odontogenic keratocysts (OKCs), 230 ameloblastomas (ABs), and 100 normal jaws with no disease. In addition, the number of radiographs was augmented 12-fold by flip, rotation, and intensity changes. We evaluated the classification performance of the developed CNN by calculating sensitivity, specificity, accuracy, and area under the curve (AUC) for diseases of both jaws.

RESULTS

The overall classification performance for the diseases improved from 78.2% sensitivity, 93.9% specificity,91.3% accuracy, and 0.86 AUC using the CNN with unaugmented data set to 88.9% sensitivity, 97.2% specificity, 95.6% accuracy, and 0.94 AUC using the CNN with augmented data set. CNN using augmented data set had the following sensitivities, specificities, accuracies, and AUCs: 91.4%, 99.2%, 97.8%, and 0.96 for DCs, 82.8%, 99.2%, 96.2%, and 0.92 for PCs, 98.4%,92.3%,94.0%, and 0.97 for OKCs, 71.7%, 100%, 94.3%, and 0.86 for ABs, and 100.0%, 95.1%, 96.0%, and 0.97 for normal jaws, respectively.

CONCLUSION

The CNN method we developed for automatically diagnosing odontogenic cysts and tumors of both jaws on panoramic radiographs using data augmentation showed high sensitivity, specificity, accuracy, and AUC despite the limited number of panoramic images involved.

Development of panorama resolution phantom for comprehensive evaluation of the horizontal and vertical resolution of panoramic radiography

Panoramic radiography is the most commonly used equipment in the dental field, but there is no comprehensive standard about how to evaluate the spatial resolution of panoramic radiography. In this study, panorama resolution phantoms were developed for evaluation of horizontal and vertical resolution reflecting unique characteristics of panoramic radiography. Four horizontal resolution phantoms of staircase shape were designed to obtain images of horizontal lead line pairs in a 52 mm width. Four vertical resolution phantoms with vertical lead line pairs placed at an oblique angle were also designed. A phantom stand was made. Three machines were evaluated twice by two oromaxillofacial radiologists. The horizontal lead line pairs were readable over the entire measured area at the values of 1.88, 2.32, and 2.58 lp/mm for all machines. A readable area of horizontal 3.19 lp/mm was observed in the lingual side. In the vertical resolution phantoms, it was possible to read a narrower range. By using the panorama resolution phantoms and phantom stand, it was possible to evaluate the resolution of a wide buccolingual width in four significant areas. By evaluating the resolution of the vertical and horizontal compartments separately, it was possible to gain a better understanding of the obtained images.

Acquired facial lipoatrophy: A report of 3 cases with imaging features

Acquired facial lipoatrophy is a rare disease with an unclear etiology and pathological pathway. The distinct causative factors of this disease have been not elucidated, but it is suspected to be associated with immune system-related diseases, most notably AIDS. Although the management of facial lipoatrophy is very important for patients' social life and mental health, no treatment framework has been developed due to the unknown nature of the disease manifestation. The present case report was designed to provide sequential imaging to visualize the disease progression. The clinical backgrounds of the patients are also introduced, helping characterize this disease entity more clearly for maxillofacial specialists.

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.

A rare acantholytic variant of squamous cell carcinoma of the maxilla: A case report and literature review

RATIONALE

Acantholytic squamous cell carcinoma (ASCC) is an uncommon histopathologic variant of squamous cell carcinoma (SCC), which is the most common malignancy of the oral cavity. Though ASCC showed poor prognosis, the exact diagnosis is challenging.

PATIENTS CONCERNS

A 59-year-old female patient with 1-month long symptoms of pain and burning sensation in the right maxilla.

DIAGNOSES

Incisional biopsy in the maxilla established the pathologic diagnosis of SCC.

INTERVENTION

The patient underwent mass resection with near total maxillectomy.

OUTCOMES

The final diagnosis through the microscopic examination was ASCC. Palliative chemotherapy was done to relive the symptoms after the recurrence, however, the patient died of the disease at 8 months after her initial presentation.

LESSONS

Special attention should be paid to this variant of SCC because most patients with ASCC have a very poor prognosis.

Correlation between spatial resolution and ball distortion rate of panoramic radiography

BACKGROUND

The purpose of this study was to analyze the correlation between spatial resolution and ball distortion rate of panoramic radiography and to elucidate the minimum criterion for ball distortion rate, which is very relevant to clinical readability.

METHODS

Horizontal and vertical spatial resolution and ball distortion rates were calculated in the same position, such as the incisor, premolar, molar, and temporomandibular joint area with various object depths corresponding to 48 mm. Three devices were evaluated. A region showing spatial resolution above the reference standard was selected, and the ball distortion rate corresponding to the same region was divided into horizontal and vertical phantom groups. The mean and standard deviation of the obtained ball distortion rates were calculated. Student's t-test was used to statistically analyze the mean difference in ball distortion rates between vertical and horizontal phantom groups.

RESULTS

In all devices, the horizontal line pair phantom, but not the vertical line pair phantom, was readable in all areas measured at the line pair value of at least 1.88 lp/mm. The line pair value tended to be higher toward the center and lower toward the outside. The ball distortion rate tended to decrease closer to the center and increased further away. In addition, ball distortion rates could not be measured at some areas as they were not recognized as balls due to the high degree of distortion at the outermost and innermost sides. The number of balls satisfying the reference value using the horizontal line pair phantom was 102 (mean of ball distortion rates, 20.98; standard deviation, 15.25). The number of balls satisfying the reference value using the vertical line pair phantom was 49 (mean of ball distortion rates, 16.33; standard deviation, 14.25). However, mean ball distortion rate was not significantly different between the two groups.

CONCLUSIONS

Image layer of panoramic radiography could be evaluated by the spatial resolution using horizontal and vertical line pair phantoms and by assessing ball distortion rates through a ball-type panorama phantom. A ball distortion rate of 20% could be used as a threshold to evaluate the image layer of panoramic radiography.

Deep Learning Hybrid Method to Automatically Diagnose Periodontal Bone Loss and Stage Periodontitis

We developed an automatic method for staging periodontitis on dental panoramic radiographs using the deep learning hybrid method. A novel hybrid framework was proposed to automatically detect and classify the periodontal bone loss of each individual tooth. The framework is a hybrid of deep learning architecture for detection and conventional CAD processing for classification. Deep learning was used to detect the radiographic bone level (or the CEJ level) as a simple structure for the whole jaw on panoramic radiographs. Next, the percentage rate analysis of the radiographic bone loss combined the tooth long-axis with the periodontal bone and CEJ levels. Using the percentage rate, we could automatically classify the periodontal bone loss. This classification was used for periodontitis staging according to the new criteria proposed at the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. The Pearson correlation coefficient of the automatic method with the diagnoses by radiologists was 0.73 overall for the whole jaw (p < 0.01), and the intraclass correlation value 0.91 overall for the whole jaw (p < 0.01). The novel hybrid framework that combined deep learning architecture and the conventional CAD approach demonstrated high accuracy and excellent reliability in the automatic diagnosis of periodontal bone loss and staging of periodontitis.

Suspected Metallic Embolization Distal to Coiled Intracranial Aneurysms Detectable by Susceptibility-Weighted MR Imaging

BACKGROUND AND PURPOSE

After endovascular coiling of intracranial aneurysms, round dark parenchymal lesions believed to be particulate metal are sometimes encountered in MR imaging studies of the brain. We used SWI to assess the frequency of such occurrences, in addition to exploring likely causes and clinical implications.

MATERIALS AND METHODS

We reviewed 700 MR imaging studies performed between September 2018 and March 2019 at our institution as follow-up monitoring of coiled intracranial aneurysms. Any sizeable (>5 mm) rounded dark-signal lesions encountered were presumed to be metallic. The magnitudes and locations of such lesions were recorded. In patients with these lesions, pertinent procedural documentation was screened for devices used, including coils, microcatheters, microguidewires, and stents. Medical records were also examined to determine whether any related symptoms ensued.

RESULTS

Twenty patients (2.8%) exhibited a total of 25 lesions on SWI. Diameters ranged from 5 to 11 mm (median, 8 mm). All except 2 lesions were located in brain regions downstream from aneurysms, but all lesions occupied vascular territories of vessels used to place guiding catheters. Other than the Synchro 14, which was routinely deployed, no device was regularly used in patients with SWI-detectable lesions; and none of the affected patients developed focal neurologic symptoms as a consequence.

CONCLUSIONS

Although the origins remain unclear, distal embolization of particulate metal distal to coiled cerebral aneurysms is occasionally observed on follow-up MR imaging studies. Such lesions, however, seem to have no apparent clinical impact.

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.

Development of an evidence-based clinical imaging diagnostic guideline for implant planning: Joint recommendations of the Korean Academy of Oral and Maxillofacial Radiology and National Evidence-based Healthcare Collaborating Agency

Purpose

This study was conducted to develop an evidence-based clinical imaging diagnostic guideline for implant planning, taking into account efficacy, benefits, and risks.

Materials and Methods

The guideline development process employed the adaptation methodology used for Korean clinical imaging guidelines(K-CIG). Core databases(Ovid-Medline, Ovid-Embase, National Guideline Clearinghouse, Guideline International Network) and domestic databases (KoreaMed, KMbase, and KoMGI) were searched for guidelines. The retrieved articles were analyzed by 2 reviewers, and articles were selected using well-established inclusion criteria.

Results

The search identified 294 articles, of which 3 were selected as relevant guidelines. Based on those 3 guidelines, 3 recommendations for implant planning were derived.

Conclusion

We recommend radiography or cone-beam computed tomography (CBCT) scanning for individual patients judged to require a cross-sectional image after reading of a panoramic X-ray image and a conventional intraoral radiological image. Various steps should be taken to raise awareness of these recommendations among clinicians and the public, and K-CIG should be regularly reviewed and revised.

Transplant outcomes in kidney recipients with lupus nephritis, and systematic review

Background

Despite improved survival of patients with lupus nephritis (LN), some require kidney transplantation because of progression to end-stage renal disease (ESRD). However, the transplant outcomes of these patients and other recipients have not been thoroughly compared.

Methods

In total, 1848 Korean kidney recipients who underwent transplantation from 1998 to 2017 at two tertiary referral centers were evaluated retrospectively. Among them, 28 recipients with LN, and 50 control recipients matched by age, sex, and donor type, were compared with respect to graft and patient survival. We pooled our data with 17 previous cohort studies in which the graft survival of recipients with LN was described in detail.

Results

During the median follow-up period of 9.5 years (maximum 21 years), graft failure (GF) occurred in 10.7% and 16.0% of LN and control recipients, respectively. No differences were found in the rates of GF and death-censored graft failure or patient survival between the two groups. The risks of acute T cell-mediated and antibody-mediated rejection were also similar between the two groups. The pooled analysis showed similar 1- and 5-year graft survival rates between LN and control recipients.

Conclusions

Kidney transplantation is an acceptable option in patients with concurrent LN and ESRD.

Steatocystoma multiplex: A case report of a rare entity

Steatocystoma multiplex is an uncommon benign skin disease, which typically manifests as numerous intradermal cysts that can be scattered anywhere on the body. Although usually asymptomatic, it can be significantly disfiguring. One type of steatocystoma multiplex is known to be associated with the autosomal dominant inheritance of a mutation in the gene coding for keratin 17 (KRT17). In such cases, it is often concurrent with other developmental abnormalities of the ectoderm-derived tissues, such as the nails, hair, and teeth. To the best of our knowledge, few cases have been reported of steatocystoma multiplex of the oral and maxillofacial region. This report describes a case of steatocystoma multiplex of both sides of the neck and multiple dental anomalies, with a focus on its clinical, radiological, and histopathological characteristics, as well as the possibility that the patient exhibited the familial type of this condition.

Effects of energy level, reconstruction kernel, and tube rotation time on Hounsfield units of hydroxyapatite in virtual monochromatic images obtained with dual-energy CT

Purpose

This study was performed to investigate the effects of energy level, reconstruction kernel, and tube rotation time on Hounsfield unit (HU) values of hydroxyapatite (HA) in virtual monochromatic images (VMIs) obtained with dual-energy computed tomography (DECT) (Siemens Healthineers, Erlangen, Germany).

Materials and Methods

A bone density calibration phantom with 3 HA inserts of different densities (CTWATER®; 0, 100, and 200 mg of HA/cm³) was scanned using a twin-beam DECT scanner at 120 kVp with tube rotation times of 0.5 and 1.0 seconds. The VMIs were reconstructed by changing the energy level (with options of 40 keV, 70 keV, and 140 keV). In order to investigate the impact of the reconstruction kernel, virtual monochromatic images were reconstructed after changing the kernel from body regular 40 (Br40) to head regular 40 (Hr40) in the reconstruction phase. The mean HU value was measured by placing a circular region of interests (ROIs) in the middle of each insert obtained from the VMIs. The HU values were compared with regard to energy level, reconstruction kernel, and tube rotation time.

Results

Hydroxyapatite density was strongly correlated with HU values (correlation coefficient=0.678, P<0.05). For the HA 100 and 200 inserts, HU decreased significantly at increased energy levels (correlation coefficient= −0.538, P<0.05) but increased by 70 HU when using Hr40 rather than Br40 (correlation coefficient=0.158, P<0.05). The tube rotation time did not significantly affect the HU (P>0.05).

Conclusion

The HU values of hydroxyapatite were strongly correlated with hydroxyapatite density and energy level in VMIs obtained with DECT.

Clinical and panoramic radiographic features of osteomyelitis of the jaw: A comparison between antiresorptive medication-related and medication-unrelated conditions

Purpose

This study was performed to analyze the clinical and imaging features of contemporary osteomyelitis (OM) and to investigate differences in these features on panoramic radiography according to patients' history of use of medication affecting bone metabolism.

Materials and Methods

The records of 364 patients (241 female and 123 male, average age 66.8±14.9 years) with OM were retrospectively reviewed. Panoramic imaging features were analyzed and compared between patients with medication-related OM (m-OM) and those with conventional, medication-unrelated OM (c-OM).

Results

The age of onset of OM tended to be high, with the largest number of patients experiencing onset in their 70s. The 2 most frequent presumed causes were antiresorptive medication use (44.2%) and odontogenic origin (34.6%). On panoramic radiographs, a mix of osteolysis and sclerosis was the most common lesion pattern observed (68.6%). Sequestrum, extraction socket, and periosteal new bone formation were found in 143 (42.1%), 79 (23.2%), and 24 (7.1%) cases, respectively. The m-OM group exhibited sequestrum and extraction socket more frequently and displayed significantly higher mandibular cortical index values than the c-OM group.

Conclusion

We observed some differences in imaging features as shown on panoramic radiography according to the history of antiresorptive medication use. This study may help elucidate the predictive imaging features of medication-related osteonecrosis of the jaw.