Imaging Science in Dentistry最新文献

Purpose: This study evaluated the impact of artifacts generated by metal crowns on the detection of proximal caries lesions in teeth at various distances using cone-beam computed tomography (CBCT). Additionally, the diagnostic impacts of tube current and metal artifact reduction (MAR) were investigated.

Materials and methods: Thirty teeth were arranged within 10 phantoms, each containing 1 first premolar, 1 second premolar, and 1 second molar. A sound first molar (for the control group) or a tooth with a metal crown was placed. Of the 60 proximal surfaces evaluated, 15 were sound and 45 exhibited enamel caries. CBCT scans were acquired using an OP300 Maxio unit (Instrumentarium, Tuusula, Finland), while varying the tube current (4, 8, or 12.5 mA) and enabling or disabling MAR. Five observers assessed mesial and distal surfaces using a 5-point scale. Multi-way analysis of variance was employed for data comparison, with P<0.05 indicating statistical significance.

Results: The area under the curve (AUC) varied from 0.40 to 0.60 (sensitivity: 0.28-0.45, specificity: 0.44-0.80). The diagnostic accuracy was not significantly affected by the presence of a metal crown, milliamperage, or MAR (P>0.05). However, the overall AUC and specificity were significantly lower for surfaces near a crown (P<0.05).

Conclusion: CBCT-based caries detection was not influenced by the presence of a metal crown, variations in milliamperage, or MAR activation. However, the diagnostic accuracy was low and was further diminished for surfaces near a crown. Consequently, CBCT is not recommended for the detection of incipient caries lesions.

Purpose: Pycnodysostosis (PYCD), an autosomal recessive syndrome, is characterized by an imbalance in bone remodeling that produces various clinical and radiographic craniofacial manifestations. This review represents a systematic examination of these manifestations, as well as oral features associated with PYCD.

Materials and methods: A systematic review was conducted across 8 databases from February to March 2023. The search strategy focused on studies reporting cases of PYCD that examined the clinical and radiographic craniofacial and oral characteristics associated with this syndrome.

Results: The review included 84 studies, encompassing a total of 179 cases of PYCD. More than half of the patients were female (55.3%), and the mean age was 14.7 years. Parental consanguinity was reported in 51.4% of the cases. The most common craniofacial clinical manifestation was a prominent nose, observed in 57.5% of cases. Radiographically, the most frequently reported craniofacial characteristics included the presence of an obtuse mandibular angle (84.3%) and frontal cranial bosses (82.1%). Clinical and radiographic examinations revealed oral alterations, with micrognathia present in 62.6% of patients and malocclusion in 59.2%. Among dental anomalies, tooth agenesis was the most commonly reported, affecting 15.6% of patients.

Conclusion: Understanding the clinical and radiographic craniofacial features of PYCD is crucial for dental professionals. This knowledge enables these clinicians to devise effective treatment plans and improve patient quality of life.

Purpose: The aims of this study were to create a deep learning model to distinguish between nasopalatine duct cysts (NDCs), radicular cysts, and no-lesions (normal) in the midline region of the anterior maxilla on panoramic radiographs and to compare its performance with that of dental residents.

Materials and methods: One hundred patients with a confirmed diagnosis of NDC (53 men, 47 women; average age, 44.6±16.5 years), 100 with radicular cysts (49 men, 51 women; average age, 47.5±16.4 years), and 100 with normal groups (56 men, 44 women; average age, 34.4±14.6 years) were enrolled in this study. Cases were randomly assigned to the training datasets (80%) and the test dataset (20%). Then, 20% of the training data were randomly assigned as validation data. A learning model was created using a customized DetectNet built in Digits version 5.0 (NVIDIA, Santa Clara, USA). The performance of the deep learning system was assessed and compared with that of two dental residents.

Results: The performance of the deep learning system was superior to that of the dental residents except for the recall of radicular cysts. The areas under the curve (AUCs) for NDCs and radicular cysts in the deep learning system were significantly higher than those of the dental residents. The results for the dental residents revealed a significant difference in AUC between NDCs and normal groups.

Conclusion: This study showed superior performance in detecting NDCs and radicular cysts and in distinguishing between these lesions and normal groups.

Chronic nonbacterial osteomyelitis (CNO) is histologically characterized by nonspecific osteitis. This inflammatory disorder, which lacks an infectious origin, typically presents with chronic pain and swelling at the affected site that can persist for months or even years. However, it is rare for CNO to affect the mandible. A 10-year-old girl presented with a primary complaint of pain in her left mandible. She had no significant medical or dental history. On examination, swelling was visible on the left buccal side, and imaging revealed radiolucent bone deterioration within the left mandible. This case report presents the radiological changes observed over a 12-year follow-up period. Variations in radiopacity, radiolucency, and periosteal reactions were noted periodically. This case highlights the radiological characteristics and findings that are crucial for the diagnosis of CNO, a condition for which no clear diagnostic criteria are currently available.

Purpose: The purpose of this study was to clarify the panoramic image differences of cleft alveolus patients with or without a cleft palate, with emphases on the visibility of the line formed by the junction between the nasal septum and nasal floor (the upper line) and the appearances of the maxillary lateral incisor.

Materials and methods: Panoramic radiographs of 238 patients with cleft alveolus were analyzed for the visibility of the upper line, including clear, obscure or invisible, and the appearances of the maxillary lateral incisor, regarding congenital absence, incomplete growth, delayed eruption and medial inclination. Differences in the distribution ratio of these visibility and appearances were verified between the patients with and without a cleft palate using the chi-square test.

Results: There was a significant difference in the visibility distribution of the upper line between the patients with and without a cleft palate (p<0.05). In most of the patients with a cleft palate, the upper line was not observed. In the unilateral cleft alveolus patients, the medial inclination of the maxillary lateral incisor was more frequently observed in patients with a cleft palate than in patients without a cleft palate.

Conclusion: Two differences were identified in panoramic appearances. The first was the disappearance (invisible appearance) of the upper line in patients with a cleft palate, and the second was a change in the medial inclination on the affected side maxillary lateral incisor in unilateral cleft alveolus patients with a cleft palate.

Purpose: Oral hygiene, maintained through plaque control, helps prevent periodontal disease and dental caries. This study was conducted to examine the accuracy of plaque detection with an intraoral scanner (IOS) compared to images captured with an optical camera.

Materials and methods: To examine the effect of color tone, artificial tooth resin samples were stained red, blue, and green, after which images were acquired with a digital single-lens reflex (DSLR) camera and an IOS device. Stained surface ratios were then determined and compared. Additionally, the deviation rate of the IOS relative to the DSLR camera was computed for each color. In the clinical study, following plaque staining with red disclosing solution, the staining was captured by the DSLR and IOS devices, and the stained area on each image was measured.

Results: The stained surface ratios did not differ significantly between DSLR and IOS images for any color group. Additionally, the deviation rate did not vary significantly across colors. In the clinical test, the stained plaque appeared slightly lighter in color, and the delineation of the stained areas less distinct, on the IOS compared to the DSLR images. However, the stained surface ratio was significantly higher in the IOS than in the DSLR group.

Conclusion: When employing IOS with dental plaque staining, the impact of color was minimal, suggesting that the traditional red stain remains suitable for plaque detection. IOS images appeared relatively blurred and enlarged relative to the true state of the teeth, due to inferior sharpness compared to camera images.

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.

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.

The author herein presents an unusual case of eustachian tube calcification masquerading as loose radiopacities in the temporomandibular joints on a panoramic image, creating a diagnostic challenge. The patient, a 72-year-old woman, presented to the dental service for implant treatment to improve her masticatory function. A cone-beam computed tomography scan was performed and reviewed by a board-certified oral and maxillofacial radiologist. The scan showed no evidence of calcifications in the temporomandibular joints; however, it revealed nodular calcifications within the cartilaginous portion of the eustachian tube bilaterally. Additionally, this report briefly reviews the differential diagnosis of calcified loose bodies in the temporomandibular joint and provides information that needs to be reinforced periodically.

Purpose: This study aimed to evaluate age-stratified radiographic features in temporomandibular joint osteoarthritis using cone-beam computed tomography.

Materials and methods: In total, 210 joints from 183 patients (144 females, 39 males, ranging from 12 to 88 years old with a mean age of 44.75±19.97 years) diagnosed with temporomandibular joint osteoarthritis were stratified by age. Mandibular condyle position and bony changes (flattening, erosion, osteophytes, subchondral sclerosis, and subchondral pseudocysts in both the condyle and articular eminence, thickening of the glenoid fossa, joint space narrowing, and joint loose bodies) were evaluated through cone-beam computed tomography. After adjusting for sex, the association between age groups and radiographic findings was analyzed using both a multiple regression model and a multinomial logistic regression model (α=0.05).

Results: The prevalence of joint space narrowing and protruded condyle position in the glenoid fossa significantly increased with age (P<0.05). The risks of bony changes, including osteophytes and subchondral pseudocysts in the condyle; flattening, erosion, osteophyte, and subchondral sclerosis in the articular eminence; joint loose bodies; and thickening of the glenoid fossa, also significantly rose with increasing age (P<0.05). The number of radiographic findings increased with age; in particular, the increase was more pronounced in the temporal bone than in the mandibular condyle (P<0.05).

Conclusion: Increasing age was associated with a higher frequency and greater diversity of bony changes in the temporal bone, as well as a protruded condyle position in the glenoid fossa, resulting in noticeable joint space narrowing in temporomandibular joint osteoarthritis.