1.Image repeat analysis in conventional radiography in mobile clinics: A retrospective observational study.
Mark M. Alpio ; Grace Meroflor A. Lantajo ; Joseph Dave M. Pregoner
Acta Medica Philippina 2025;59(Early Access 2025):1-5
BACKGROUND
Mobile clinics offer crucial healthcare services, including X-ray examinations, to underserved communities. Minimizing image repeats in this setting is vital due to radiation exposure, patient inconvenience, and cost implications.
OBJECTIVESThis study investigated the prevalence and causes of image repeat in conventional radiography performed within mobile clinics in the Philippines.
METHODSA retrospective review analyzed data from five mobile clinics located in two highly urbanized cities in the Philippines from July to December 2023). Radiology staff assessed image quality, with suboptimal images requiring retakes. Reasons for rejection were categorized.
RESULTSOut of 871 radiographs taken, 118 (13.55%) were repeated. Vertebrae and pelvic girdle images had the highest repeat rates (33.33%). Positioning errors were the most common cause (44.07%), followed by underexposure and overexposure.
CONCLUSIONThis study identified a concerning repeat rate (13.55%) for mobile X-rays, primarily due to improper patient positioning, particularly for specific body parts. Targeted training programs and stricter protocols for mobile clinic staff are needed. Radiography education should also emphasize these skills, potentially through collaboration with mobile clinic operators to ensure graduates are prepared for the unique challenges of this environment.
Mobile Health Units ; Patient Positioning ; Radiography ; X-rays ; X-ray Film
2.Image repeat analysis in conventional radiography in mobile clinics: A retrospective observational study.
Mark M. ALIPIO ; Grace Meroflor A. LANTAJO ; Joseph Dave M. PREGONER
Acta Medica Philippina 2025;59(18):56-60
BACKGROUND
Mobile clinics offer crucial healthcare services, including X-ray examinations, to underserved communities. Minimizing image repeats in this setting is vital due to radiation exposure, patient inconvenience, and cost implications.
OBJECTIVESThis study investigated the prevalence and causes of image repeat in conventional radiography performed within mobile clinics in the Philippines.
METHODSA retrospective review analyzed data from five mobile clinics located in two highly urbanized cities in the Philippines from July to December 2023). Radiology staff assessed image quality, with suboptimal images requiring retakes. Reasons for rejection were categorized.
RESULTSOut of 871 radiographs taken, 118 (13.55%) were repeated. Vertebrae and pelvic girdle images had the highest repeat rates (33.33%). Positioning errors were the most common cause (44.07%), followed by underexposure and overexposure.
CONCLUSIONThis study identified a concerning repeat rate (13.55%) for mobile X-rays, primarily due to improper patient positioning, particularly for specific body parts. Targeted training programs and stricter protocols for mobile clinic staff are needed. Radiography education should also emphasize these skills, potentially through collaboration with mobile clinic operators to ensure graduates are prepared for the unique challenges of this environment.
Mobile Health Units ; Patient Positioning ; Radiography ; X-rays ; X-ray Film
3.Clinical manifestation analysis of the eruption failure of deciduous molars.
Manting WANG ; Dingzhou JIANG ; Xiao ZHU ; Linna QIAN ; Junzhuo GOU ; Wenxiang JIANG ; Zhifang WU
West China Journal of Stomatology 2025;43(4):513-517
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
4.Clinical efficacy of demineralized dentin matrix particles in immediate implantation for bone defects in posterior region: a 1 to 5-year follow-up study.
Hao WU ; Ning CAO ; Liangwei CAO ; Fei YU ; Xu ZHANG ; Shibo WEI ; Hongwu WEI ; Shuigen GUO
West China Journal of Stomatology 2025;43(4):570-583
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
5.Application of Multi-Model Adaptive Statistical Iterative Reconstruction-Veo in Ultra-Low Dose Chest CT Examination of Children in Plateau Area.
Xian-Tao WANG ; Rui-Ting BAI ; CIDANWANGJIU ; SUOLANGNIMA ; NIMAZHUOGA ; Bai-Yan SU
Acta Academiae Medicinae Sinicae 2025;47(1):29-34
Objective To explore the application value of multi-model adaptive statistical iterative reconstruction-Veo (ASiR-V) in ultra-low dose chest CT examination of children in the plateau area. Methods The children who underwent chest CT examination in Xizang Autonomous Region People's Hospital were enrolled in this study and assigned into two groups according to the scanning conditions.Group A underwent scanning at a tube voltage of 100 kV and ASiR-V 50% reconstruction,and group B underwent scanning at a tube voltage of 80 kV and ASiR-V 0 (Group B1) and ASiR-V 50% (Group B2) reconstruction.The image quality of each group was evaluated objectively and subjectively.The radiation dose and image quality were compared between groups. Results Groups A and B showed the volume CT dose indexes of (2.33±0.62) mGy and (0.86±0.01) mGy and the dose length products of (65.01±25.12) mGy·cm and (23.55±3.38) mGy·cm,respectively,which presented differences between groups (both P<0.001).The image noise in the bilateral upper and middle lung areas in group B2 was lower than that in group B1 but higher than that in group A (all P<0.001).There was no significant difference in image quality score of the lung window among groups (all P>0.05).Groups A,B1,and B2 had no significant differences in ascending aorta (P=0.538) or liver CT value (P=0.175) in the mediastinal window.The signal-to-noise ratios and contrast-to-noise ratios of ascending aorta and liver in group B2 were higher than those in group B1 (all P<0.001) and lower than those in group A (all P<0.05).The image quality score of the mediastinal window followed a descending order of group A>group B2>group B1 (all P<0.001)。Conclusion ASiR-V combined with low tube voltage can effectively reduce the radiation dose and guarantee the image quality of chest CT of children in the plateau area.
Humans
;
Radiation Dosage
;
Tomography, X-Ray Computed/methods*
;
Child
;
Male
;
Female
;
Child, Preschool
;
Radiography, Thoracic/methods*
;
Infant
;
Models, Statistical
;
Image Processing, Computer-Assisted/methods*
6.An lightweight algorithm for multi-dimensional optimization of intelligent detection of dental abnormalities on panoramic oral X-ray images.
Taotao ZHAO ; Ming NI ; Shunxing XIA ; Yuehao JIAO ; Yating HE
Journal of Southern Medical University 2025;45(8):1791-1799
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*
7.Clinical study on deciduous fused teeth and inherited permanent teeth.
Fenfang QIU ; Shan MENG ; Yangyang CHONG ; Xiaoli SONG
West China Journal of Stomatology 2025;43(1):92-97
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
8.Multiple odontogenic keratocysts as initial manifestation of gorlin-goltz syndrome: A case report
Geralen Befina L. Gernale-Songahid ; Marion A. Acuin ; Jenny Lyn Y. Uy-Chua
Philippine Journal of Otolaryngology Head and Neck Surgery 2025;40(Supplement):24-28
OBJECTIVES
To present a rare case of a 17-year-old girl with multiple odontogenic keratocysts, skeletal abnormalities, central nervous system and cutaneous anomalies.
METHODSDesign:Case Report
Setting:Tertiary Government Training Hospital
Patient: One
RESULTSA 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.
CONCLUSIONThis 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
9.Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits.
John Jian Xian QUEK ; Oliver James NICKALLS ; Bak Siew Steven WONG ; Min On TAN
Singapore medical journal 2025;66(4):202-207
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
10.Use of deep learning model for paediatric elbow radiograph binomial classification: initial experience, performance and lessons learnt.
Mark Bangwei TAN ; Yuezhi Russ CHUA ; Qiao FAN ; Marielle Valerie FORTIER ; Peiqi Pearlly CHANG
Singapore medical journal 2025;66(4):208-214
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


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