OBJECTIVES

To present a rare case of a 17-year-old girl with multiple odontogenic keratocysts, skeletal abnormalities, central nervous system and cutaneous anomalies.

METHODS

Design:Case Report

Setting:Tertiary Government Training Hospital

Patient: One

RESULTS

A 17-year-old Filipino girl presented with a one-year history of progressive left mandibular swelling. Orthopantomography revealed multiple cysts involving the mandible and maxillae. Histopathologic examination of incision biopsy specimens confirmed odontogenic keratocysts. Other physical examination findings included coarse face and multiple palmar and plantar pits. Radiologic investigations demonstrated calcification of the falx cerebri and tentorium cerebelli, bifid rib and cervicothoracic scoliosis. Based on clinical, radiological, and histopathological findings, a diagnosis of Gorlin-Goltz syndrome was established. The patient underwent enucleation and curettage of the cysts with peripheral ostectomy, and there was no recurrence on repeat orthopantomography at six months and two years post-operatively. However, on the fourth year, the patient claimed there was a mandibular cyst which was not verified as she was lost to follow-up.

CONCLUSION

This case highlights the importance of recognizing multiple odontogenic keratocysts as a potential manifestation of Gorlin-Goltz Syndrome. Early diagnosis enables appropriate management and long term surveillance to monitor for other manifestations of this syndrome that may occur later in life.

Human ; Female ; Adolescent: 13-18 Yrs Old ; Basal Cell Nevus Syndrome ; Mandible ; Radiography, Panoramic ; Focal Dermal Hypoplasia ; Ribs ; Scoliosis ; Spinal Cord ; Women ; History ; Lost To Follow-up ; Diagnosis

OBJECTIVES: We propose a YOLOv11-TDSP model for improving the accuracy of dental abnormality detection on panoramic oral X-ray images. METHODS: The SHSA single-head attention mechanism was integrated with C2PSA in the backbone layer to construct a new C2PSA_SHSA attention mechanism. The computational redundancy was reduced by applying single-head attention to some input channels to enhance the efficiency and detection accuracy of the model. A small object detection layer was then introduced into the head layer to correct the easily missed and false detections of small objects. Two rounds of structured pruning were implemented to reduce the number of model parameters, avoid overfitting, and improve the average precision. Before training, data augmentation techniques such as brightness enhancement and gamma contrast adjustment were employed to enhance the generalization ability of the model. RESULTS: The experiment results showed that the optimized YOLOv11-TDSP model achieved an accuracy of 94.5%, a recall rate of 92.3%, and an average precision of 95.8% for detecting dental abnormalities. Compared with the baseline model YOLOv11n, these metrics were improved by 6.9%, 7.4%, and 5.6%, respectively. The number of parameters and computational cost of the YOLOv11-TDSP model were only 12% and 13% of those of the high-precision YOLOv11x model, respectively. CONCLUSIONS The lightweight YOLOv11-TDSP model is capable of highly accurate identification of various dental diseases on panoramic oral X-ray images.
Radiography, Panoramic/methods* ; Humans ; Algorithms ; Tooth Abnormalities/diagnostic imaging*

OBJECTIVES: This study aimed to investigate the clinical characteristics of deciduous fused teeth and their inherited permanent-tooth performance type by using panoramic radiographs. METHODS: A total of 14 404 panoramic radiographs of 3- to 6-year-old children with deciduous dentition were collected from January 2023 to July 2024. The incidence of deciduous fused teeth was observed, and the abnormality of permanent teeth was recorded. SPSS 24.0 software was used for statistical analysis. RESULTS: The incidence of deciduous fused teeth was 3.06% (441/14 404). The order of dental position was as follows: mandibular deciduous incisors and cusp teeth fused (58.18%) > mandibular deciduous central and lateral incisors fused (30.91%) > maxillary deciduous central and lateral incisors fused (8.89%) > deciduous incisors and supernumerary teeth fused (2.02%). Deciduous fused teeth were found in 226 boys and 215 girls, with no significant difference between the sexes (P>0.05). We observed one pair (87.76%, 387/441) and two pairs (12.24%, 54/441) of fused teeth (54/441), respectively. A total of 287 pairs of fusion teeth on the right side more than 208 pairs on the left side, and the difference between them was statistically significant (P<0.01). More fusion teeth existed in mandibular deciduous teeth (443 pairs) than in maxillary ones (54 pairs), and the difference between them was statistically significant (P<0.01). More unilateral deciduous teeth (387 subjects) were found than bilateral ones (54 subjects), and the difference between them was statistically significant (P<0.01). Three types of deciduous fused teeth with inherited permanent teeth were observed as follows: 1) 49.49% (245/495) of inherited permanent teeth was absent, 2) 46.67% (231/495) of inherited permanent teeth was not absent, and 3) the number of fused permanent teeth accounted for 3.84% (19/495). CONCLUSIONS The incidence of deciduous fused teeth was 3.06%, mostly occurring in the lower anterior teeth region, with no gender difference. One pair of fused teeth is commonly observed, more often on the right than the left. These fusions occur more frequently in the mandible than the maxillary, and unilateral cases are more common than bilateral ones. Deciduous fused teeth had a certain impact on inherited permanent teeth. Pediatric dentists should pay attention to and closely observe whether any abnormality exists in the permanent dentition for early detection to prevent the harm caused by deciduous fused teeth.
Humans ; Tooth, Deciduous/abnormalities* ; Male ; Child ; Female ; Child, Preschool ; Dentition, Permanent ; Radiography, Panoramic ; Fused Teeth/diagnostic imaging* ; Incisor/diagnostic imaging* ; Tooth, Supernumerary/diagnostic imaging* ; Incidence ; Mandible

OBJECTIVES: This study aimed to investigate the incidence, imaging characteristics, and clinical manifestations of the eruption failure of deciduous molars using panoramic radiographs to provide a foundation for diagnosis and treatment in this population. METHODS: This study retrospectively reviewed panoramic radiographs of children aged 4-8 years obtained from Stomatology Hospital, Zhejiang University School of Medicine between January 2021 and December 2023. A total of 31 331 subjects were included for the radiographic assessment of the tooth eruption failure of deciduous molars. Incidence, radiographic characteristics, and associated complications were documented. Statistical analysis was performed using SPSS 26.0. RESULTS: The incidence of the eruption failure of deciduous molars among children aged 4-8 years was 0.94% (296/31 331). The rate was 1.55 times higher in females than in males, demonstrating a significant gender difference (P<0.001). Among the affected deciduous molars, mandibular first deciduous molars accounted for 76.4%, followed by the mandibular second deciduous molars (13.8%), and the maxillary deciduous molars collectively comprised 9.8%. The severity of eruption disorders was significantly associated with the mesial and distal tilting of adjacent teeth and elongation of the antagonist (P<0.001). CONCLUSIONS The incidence of the eruption failure of deciduous molars in children aged 4-8 years was 0.94%, with a high prevalence in females and a predilection for the mandible, particularly the mandibular first deciduous molar. For deciduous molars with severe eruption failure, early intervention is crucial to mitigate complications such as malocclusion and space loss.
Humans ; Child ; Child, Preschool ; Tooth, Deciduous/diagnostic imaging* ; Female ; Molar/physiopathology* ; Male ; Retrospective Studies ; Tooth Eruption ; Radiography, Panoramic ; Incidence

OBJECTIVES: This study aims to evaluate the short- to medium-term clinical efficacy of demineralized dentin matrix (DDM) particles applied during the immediate implantation of alveolar bone defects in the posterior region. METHODS: A total of 76 patients with 110 simple taper retentive implants were included in the conducted study and divided into Groups A and B in accordance with the bone grafting materials. Cone beam computed tomography and panoramic radiographs were taken immediately after implant surgery, immediate crown repair, and final follow-up time. The average follow-up time for Groups A and B was recorded. The primary observed clinical indicators were overall survival rate of the implant, bone resorption of the mesial and distal margins of the implant, buccal bone width resorption at the platform level and 1 mm below the platform, and bone height of the implant. Implant complication was a secondary observed clinical indicator. RESULTS: During the 1-to-5-year follow-up observation period, the mean follow-up of Group A was 38.2 months while that of Group B was 39.9 months. In Group A, two implants failed, one of which fractured, and implant overall survival rate was 96.4%. Four implants failed in Group B due to peri-implantitis, and implant overall survival rate was 92.6%. No statistically significant difference in implant overall survival rate was found between the two groups (P>0.05). In Group A, the average bone resorption in the mesial and distal margins of the implants was (1.011±2.047) mm and (0.841±2.183) mm, respectively. In Group B, the average bone resorption of the mesial and distal margins of the implants was (1.546±1.778) mm and (1.431±1.909) mm, respectively. No statistically significant difference was noted between the two groups (P>0.05). In Group A, buccal bone width resorption at the platform level and 1 mm below the platform of the implant was (0.782±2.084) mm and (0.681±2.307) mm, respectively. In Group B, buccal bone width resorption at the platform level and 1 mm below the platform of implant was (1.071±1.474) mm and (0.949±1.909) mm, respectively. No statistically significant difference was found between the two groups (P>0.05). In Group A, the buccal bone height of resorption of the implant was (1.044±2.214) mm. In Group B, the buccal bone height of resorption of the implant was (1.075±1.456) mm. No statistically significant difference in bone height was observed between the two groups (P>0.05). CONCLUSIONS During the 1-to-5-year follow-up observation period, DDM particles can effectively increase the height and width of alveolar bone, and they can achieve the same effect of maintaining alveolar bone contour and bone augmentation compared with deproteinized inorganic calf bone. DDM particles can be used as a potential new bone grafting material for the treatment of bone defects in clinical practice.
Humans ; Follow-Up Studies ; Dentin ; Cone-Beam Computed Tomography ; Dental Implants ; Male ; Female ; Adult ; Alveolar Bone Loss/surgery* ; Middle Aged ; Bone Transplantation ; Radiography, Panoramic ; Dental Implantation, Endosseous/methods* ; Immediate Dental Implant Loading

INTRODUCTION: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations may miss diagnoses, which later require the callback of patients for further management. Artificial intelligence (AI) has been viewed as a potential solution to augment the shortage of radiologists after hours. We explored the efficacy of an AI solution in the detection of appendicular and pelvic fractures for adult radiographs performed after hours at a general hospital ED in Singapore, and estimated the potential monetary and non-monetary benefits. METHODS: One hundred and fifty anonymised abnormal radiographs were retrospectively collected and fed through an AI fracture detection solution. The radiographs were re-read by two radiologist reviewers and their consensus was established as the reference standard. Cases were stratified based on the concordance between the AI solution and the reviewers' findings. Discordant cases were further analysed based on the nature of the discrepancy into overcall and undercall subgroups. Statistical analysis was performed to evaluate the accuracy, sensitivity and inter-rater reliability of the AI solution. RESULTS: Ninety-two examinations were included in the final study radiograph set. The AI solution had a sensitivity of 98.9%, an accuracy of 85.9% and an almost perfect agreement with the reference standard. CONCLUSION An AI fracture detection solution has similar sensitivity to human radiologists in the detection of fractures on ED appendicular and pelvic radiographs. Its implementation offers significant potential measurable cost, manpower and time savings.
Humans ; Singapore ; Emergency Service, Hospital ; Fractures, Bone/diagnostic imaging* ; Artificial Intelligence ; Retrospective Studies ; Adult ; Male ; Female ; Cost Savings ; Middle Aged ; Pelvic Bones/diagnostic imaging* ; Reproducibility of Results ; Aged ; Sensitivity and Specificity ; Radiography

INTRODUCTION: In this study, we aimed to compare the performance of a convolutional neural network (CNN)-based deep learning model that was trained on a dataset of normal and abnormal paediatric elbow radiographs with that of paediatric emergency department (ED) physicians on a binomial classification task. METHODS: A total of 1,314 paediatric elbow lateral radiographs (patient mean age 8.2 years) were retrospectively retrieved and classified based on annotation as normal or abnormal (with pathology). They were then randomly partitioned to a development set (993 images); first and second tuning (validation) sets (109 and 100 images, respectively); and a test set (112 images). An artificial intelligence (AI) model was trained on the development set using the EfficientNet B1 network architecture. Its performance on the test set was compared to that of five physicians (inter-rater agreement: fair). Performance of the AI model and the physician group was tested using McNemar test. RESULTS: The accuracy of the AI model on the test set was 80.4% (95% confidence interval [CI] 71.8%-87.3%), and the area under the receiver operating characteristic curve (AUROC) was 0.872 (95% CI 0.831-0.947). The performance of the AI model vs. the physician group on the test set was: sensitivity 79.0% (95% CI: 68.4%-89.5%) vs. 64.9% (95% CI: 52.5%-77.3%; P = 0.088); and specificity 81.8% (95% CI: 71.6%-92.0%) vs. 87.3% (95% CI: 78.5%-96.1%; P = 0.439). CONCLUSION The AI model showed good AUROC values and higher sensitivity, with the P-value at nominal significance when compared to the clinician group.
Humans ; Deep Learning ; Child ; Retrospective Studies ; Male ; Female ; Radiography/methods* ; ROC Curve ; Elbow/diagnostic imaging* ; Neural Networks, Computer ; Child, Preschool ; Elbow Joint/diagnostic imaging* ; Emergency Service, Hospital ; Adolescent ; Infant ; Artificial Intelligence

BACKGROUND: The correlation between the morphological structure of the patellofemoral joint (PFJ) and the severity of knee joint osteoarthritis (KOA) remains uncertain. This study aims to investigate the correlation between the severity of knee joint osteoarthritis and the alignment of patellofemoral and patellar height on radiographs. METHODS: This multi-center, retrospective study analyzed the magnetic resonance imaging (MRI) scans and anteroposterior radiographs of 534 adult outpatients with KOA. To evaluate the radiographic severity of KOA, anteroposterior radiographs of the knee and the Kellgren-Lawrence (K-L) grade were used. Knee MRI scans were used to measure the patellar length ratio (PLR), sulcus angle (SA), lateral patellar tilt angle (LPTA), and the distance between tibial tuberosity and trochlear groove (TT-TG). We examined the association between the configuration of the PFJ, arrangement, and harshness of the KOA. Information on participants' demographics, such as age, sex, side, height, and weight, was collected. A chi-squared test was used for the correlation of radiographic severity of KOA with sex and the affected side. Spearman correlation was used for patellofemoral alignment or morphology and the radiographic severity of lateral KOA. Multiple linear regression models were used for the association between LPTA, SA, TT-TG, and severity of KOA after accounting for demographic variables. RESULTS: The study comprised of 534 patients; of these, 339 (63%) were female. A total of 586 knees were evaluated in this study. Age showed a strong positive correlation with KOA severity ( r  = 0.516, P <0.01), whereas LPTA showed a strong negative correlation ( r  = -0.662, P <0.01). Additionally, SA ( r  = 0.616, P <0.05), and TT-TG showed a strong positive correlation ( r  = 0.770, P <0.01) with tibiofemoral osteoarthritis (TFOA) severity. Multiple linear regression analysis indicated that knee osteoarthritis severity (β = -2.946, P <0.001) and side (β = -0.839, P  = 0.001) was associated with LPTA; knee osteoarthritis severity (β = 5.032, P <0.001) and age (β = -0.095, P <0.001) was associated with SA; knee osteoarthritis severity (β = 2.445, P <0.001), sex (β = -0.326, P  = 0.041), body mass index (β = -0.061, P  = 0.017) and age (β = -0.025, P <0.001) was associated with TT-TG. CONCLUSION Radiographic severity of KOA was positively associated with age, SA, and TT-TG but negatively associated with LPTA.
Humans ; Female ; Male ; Osteoarthritis, Knee/pathology* ; Middle Aged ; Retrospective Studies ; Aged ; Patellofemoral Joint/pathology* ; Magnetic Resonance Imaging ; Adult ; Patella/pathology* ; Radiography

Objective: To investigate the application effectiveness of the artificial intelligence(AI) based Generative Pre-treatment tool of Skeletal Pathology (GPTSP) in measuring functional lumbar radiographic examinations. Methods: This is a retrospective case series study,reviewing the clinical and imaging data of 34 patients who underwent lumbar dynamic X-ray radiography at Department of Orthopedics, the Second Hospital of Shandong University from September 2021 to June 2023. Among the patients, 13 were male and 21 were female, with an age of (68.0±8.0) years (range:55 to 88 years). The AI model of the GPTSP system was built upon a multi-dimensional constrained loss function constructed based on the YOLOv8 model, incorporating Kullback-Leibler divergence to quantify the anatomical distribution deviation of lumbar intervertebral space detection boxes, along with the introduction of a global dynamic attention mechanism. It can identify lumbar vertebral body edge points and measure lumbar intervertebral space. Furthermore, spondylolisthesis index, lumbar index, and lumbar intervertebral angles were measured using three methods: manual measurement by doctors, predefined annotated measurement, and AI-assisted measurement. The consistency between the doctors and the AI model was analyzed through intra-class correlation coefficient (ICC) and Kappa coefficient. Results: AI-assisted physician measurement time was (1.5±0.1) seconds (range: 1.3 to 1.7 seconds), which was shorter than the manual measurement time ((2 064.4±108.2) seconds,range: 1 768.3 to 2 217.6 seconds) and the pre-defined annotation measurement time ((602.0±48.9) seconds,range: 503.9 to 694.4 seconds). Kappa values between physicians' diagnoses and AI model's diagnoses (based on GPTSP platform) for the lumbar slip index, lumbar index, and intervertebral angles measured by three methods were 0.95, 0.92, and 0.82 (all P<0.01), with ICC values consistently exceeding 0.90, indicating high consistency. Based on the doctor's manual measurement, compared with the predefined label measurement, altering AI assistance, doctors measurement with average annotation errors reduced from 2.52 mm (range: 0.01 to 6.78 mm) to 1.47 mm(range: 0 to 5.03 mm). Conclusions: The GPTSP system enhanced efficiency in functional lumbar analysis. AI model demonstrated high consistency in annotation and measurement results, showing strong potential to serve as a reliable clinical auxiliary tool.
Humans ; Female ; Retrospective Studies ; Male ; Lumbar Vertebrae/diagnostic imaging* ; Middle Aged ; Aged ; Aged, 80 and over ; Artificial Intelligence ; Radiography ; Spondylolisthesis/diagnostic imaging*

The orientation of the acetabular cup in hip joint anteroposterior radiograph is a key factor in evaluating the postoperative outcomes of total hip arthroplasty (THA). Currently, measurement of the acetabular cup anteversion angle primarily relies on manual drawing of auxiliary lines by orthopedic surgeons and calculations using scientific calculators. This study proposes an automated computer-aided measurement method for the acetabular cup anteversion angle based on hip joint anteroposterior radiograph. The proposed method segments hip prosthesis images using an improved Otsu algorithm, identifies feature points at the acetabular cup opening by combining circle-fitting theory and the cup's geometric characteristics, and fits an ellipse to the cup opening to calculate the anteversion angle. A total of 104 hip joint anteroposterior radiographs, including 71 right-sided and 81 left-sided prostheses, were analyzed. Two orthopedic surgeons independently measured the postoperative anteversion angles, and the results were compared with computer-generated measurements for correlation analysis. Spearman and Pearson correlation analyses demonstrated significant correlations between the proposed method and manual measurements for both the right group ( r = 0.795, P < 0.01) and the left group ( r = 0.859, P < 0.01). This method provides a reliable reference for orthopedic surgeons to assess postoperative prognosis.
Humans ; Acetabulum/anatomy & histology* ; Arthroplasty, Replacement, Hip/methods* ; Algorithms ; Hip Prosthesis ; Hip Joint/diagnostic imaging* ; Radiography ; Image Processing, Computer-Assisted/methods*