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PURPOSE: This study aims to evaluate the anatomy and anatomical variations of the anterior belly of the digastric muscle. METHODS: Hundred and fifty one ultrasonographic images of the digastric muscle pairs were evaluated in Near East University Faculty of Dentistry Department of Dentomaxillofacial Radiology. Morphological variations were recorded using the classification of the digastric muscle into 12 types by Kim et al. For the analysis, the Mann-Whitney U test and Chi-square test were used, and for the correlational analysis, Spearman's rho test was applied. P < 0.05 was considered statistically significant in all tests. RESULTS: Seventy female and 81 male patients aged 19-60 years were evaluated. Type 1 digastric muscle was observed in 145 of 151 patients, Type 2 in 3 patients, and Type 7 in 3 patients. The thicknesses of the right and left digastric muscles were measured, and a statistically significant difference was observed between the groups when the genders were compared. It was observed that both right and left digastric muscle thicknesses were higher in males than females. There was a statistically significant positive high correlation between right and left digastric muscle thicknesses (p = 0.000; r = 0.736). No statistically significant difference was found between genders (p = 0.596) in terms of anatomical variations. CONCLUSION: Considering that the variations of the digastric muscle may have a clinical significance role, the normal anatomy and variations of this muscle should be well known by maxillofacial surgeons and radiologists.
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Idioma , Músculos do Pescoço , Humanos , Masculino , Feminino , Músculos do Pescoço/diagnóstico por imagem , Estatísticas não Paramétricas , Distribuição de Qui-Quadrado , Correlação de DadosRESUMO
PURPOSE: The purpose of this cadaver study was to examine the surface morphology of the osteochondral grafts harvested from the femoral condyles using the free-hand graft harvesting technique. MATERIALS AND METHODS: One hundred osteochondral grafts were harvested with 6.5 mm chisels at ten different donor sites using the free-hand technique in five paired knee specimens (Mean age: 56.4 years). The cartilage and subchondral bone surface angles were measured through multiplanar reconstruction computerized tomography examination. The cartilage thickness was measured with a MicroScribe G2X digitizer with an accuracy of 0.02 mm. An acceptable congruity could be obtained when these plugs were transferred to a perpendicular socket (articular step-off of less than 1 mm and 0.5 mm) was evaluated. RESULTS: Four plugs were damaged or broken during harvesting due to technical difficulties; thus remaining 96 plugs were analyzed. The cartilage thickness varied between 1.36 mm and 3.26 mm across the donor sites. The cartilage was the thinnest in the medial intercondylar notch and thickest in the lateral supracondylar notch. Twenty of ninety-six plugs (20.8%) had unacceptable cartilage surface inclination according to the > 0.5 mm protrusion criteria. Of these plugs, 14 were harvested from the lateral intercondylar notch, whereas five of 96 plugs (5.2%) had unacceptable cartilage surface inclination according to the > 1 mm protrusion criteria. Of these plugs, all were harvested from the lateral intercondylar notch. CONCLUSIONS: High rates of unacceptable plugs (up to 100%) might be harvested from the lateral intercondylar notch. In large chondral lesions that require multiple plugs, lateral and medial supracondylar ridges were the best donor sites for perpendicular plug harvesting, whereas lateral intercondylar notch should be avoided.
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Cartilagem Articular , Humanos , Pessoa de Meia-Idade , Cartilagem Articular/diagnóstico por imagem , Cartilagem Articular/cirurgia , Transplante Ósseo/métodos , Transplante Autólogo , Articulação do Joelho/diagnóstico por imagem , Articulação do Joelho/cirurgia , Articulação do Joelho/patologia , Fêmur/diagnóstico por imagem , Fêmur/cirurgia , Fêmur/anatomia & histologia , CadáverRESUMO
AIMS AND OBJECTIVES: This study is a cross-sectional study aiming to determine the suicide literacy level of nurses and to examine the relationship between nurses' suicide literacy and certain variables. BACKGROUND: Suicide literacy in nurses is a factor which affects knowledge levels. The level of suicide literacy in nurses may affect the care given to patients and the behaviour of obtaining help in relation to themselves. METHODS: The study was conducted with 348 nurses between January and March 2020 at a hospital in the city of Antalya in Turkey. A personal information form and the Literacy of Suicide Scale (LOSS) were used to collect data. Descriptive statistical methods were used in data analysis. Stepwise multiple linear regression analysis was performed to determine the predictors of suicide literacy. The STROBE checklist was followed for this cross-sectional study. RESULTS: The nurses' mean score on LOSS was 11.08 ± 3.92. Significant predictors of suicide literacy in nurses were being single, working in the emergency department, having previous experience in the psychiatry clinic, not having a mental illness, having suicide attempts in the family, having previously obtained information on intervention on individuals at risk of suicide and stating that their sources of information on this topic were nursing education and the Internet. These variables explained 19.8% of the variance in suicide literacy. CONCLUSIONS: The nurses' suicide literacy was at a low level. It is recommended that education programs on the care of patients at risk of suicide be set up for all nurses working in general clinics. RELEVANCE TO CLINICAL PRACTICE: It is important to raise the levels of suicide literacy in nurses in order to provide better quality care to patients who are at risk of suicide. Also, raising levels of suicide literacy may strengthen nurses' behaviours in seeking help for themselves.
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Educação em Enfermagem , Enfermeiras e Enfermeiros , Humanos , Estudos Transversais , Conhecimentos, Atitudes e Prática em Saúde , Qualidade da Assistência à Saúde , Conhecimento , Inquéritos e QuestionáriosRESUMO
BACKGROUND AND OBJECTIVES: We aimed to develop a predictive model for the outcome of bruxism treatments using ultrasonography (USG)-based machine learning (ML) techniques. This study is a quantitative research study (predictive modeling study) in which different treatment methods applied to bruxism patients are evaluated through artificial intelligence. MATERIALS AND METHODS: The study population comprised 102 participants with bruxism in three treatment groups: Manual therapy, Manual therapy and Kinesio Tape or Botulinum Toxin-A injection. USG imaging was performed on the masseter muscle to calculate muscle thickness, and pain thresholds were evaluated using an algometer. A radiomics platform was utilized to handle imaging and clinical data, as well as to perform a subsequent radiomics statistical analysis. RESULTS: The area under the curve (AUC) values of all machine learning methods ranged from 0.772 to 0.986 for the training data and from 0.394 to 0.848 for the test data. The Support Vector Machine (SVM) led to excellent discrimination between bruxism and normal patients from USG images. Radiomics characteristics in pre-treatment ultrasound scans of patients, showing coarse and nonuniform muscles, were associated with a greater chance of less effective pain reduction outcomes. CONCLUSIONS: This study has introduced a machine learning model using SVM analysis on ultrasound (USG) images for bruxism patients, which can detect masseter muscle changes on USG. Support Vector Machine regression analysis showed the combined ML models can also predict the outcome of the pain reduction.
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OBJECTIVES: This study aims to examine the reliability of the old and new parameters in determining the axillary nerve safe area for surgical interventions in the proximal humerus by measuring the distances between the top of the humeral head, the top of the greater tuberosity, the base of the greater tuberosity, and the acromion and axillary nerve. PATIENTS AND METHODS: Between 2020 and 2022, a total of 52 shoulders of 26 fresh frozen male human cadavers (mean age: 46±25.5 years; range, 28 to 64 years), 26 right and 26 left were included. The deltopectoral approach was used. The intersection distances of the anterolateral end of the acromion, the top of the humeral head, the top of the tuberculum majus, and the base of the tuberculum majus with the N. axillaries were determined. All measurements were performed using the Microscribe® G2X. RESULTS: The mean distance from the top of the tuberculum majus to the axillary nerve (shown as "A") was measured as 4.36±0.17 cm and 4±0.21 cm on the right and left, respectively. The mean distance from the center of the base of the tuberculum majus to the axillary nerve (shown as "B") was measured as 1.27±0.18 cm and 1.24±0.11 cm on the right and left, respectively. The mean distance from the apex of the humeral head to the axillary nerve (shown as "C") was measured as 6.15±0.39 cm and 5.89±0.34 cm on the right and left, respectively. The mean distance between the anterolateral end of the acromion (shown as "D") was measured as 6.15±0.39 cm and 5.89±0.34 cm on the right and left, respectively. There was a moderate positive correlation between distances A and B measured on the right and left side, respectively (r=0.484; p=0.012) (r=0.454; p=0.020). CONCLUSION: A strong positive correlation was found between the distances A and B. The A, B, and C parameters had a weak correlation with parameter D. The anatomical parameters A and B was found to be less variable and more reliable than parameter D.
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Plexo Braquial , Úmero , Masculino , Humanos , Adulto Jovem , Adulto , Pessoa de Meia-Idade , Idoso , Reprodutibilidade dos Testes , Úmero/cirurgia , CadáverRESUMO
The aim of this study is to evaluate the relationship between orthodontic malocclusion, paranasal sinus (PS) variations, and adenoid vegetation in a group of pediatric patients with chronic rhinosinusitis. Clinical and radiographical data were retrospectively evaluated and 58 patients were diagnosed as having chronic sinus disease. Cone-beam computed tomography (CBCT) images were acquired with Newtom-3G. Anatomical variations of the PS were assessed on every section. Additionally, for cephalometric analysis, the images were imported into the InVivoDental software program. A total of 252 anatomical variations, which encompassed 19 different types, were detected in the current study. Concha bullosa was the most common anatomical variation, at 72.4%. Septum deviation was the second most common one, at 67.2%. The Class III group exhibited a significantly higher prevalence of concha bullosa and secondary middle turbinate than the other groups. While adenoid vegetation was most common in the Class III group, sinusitis and antral disease were most common in the Class II group. Overall, Class III subjects exhibited fewer PS variations. In conclusion, concha bullosa emerged as the most prevalent anatomical variation, with distinctive patterns observed across different malocclusion groups. Therefore, CBCT is useful, especially in pediatric patients, due to its low dose advantage.
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This study aims to develop an algorithm for the automatic segmentation of the parotid gland on CT images of the head and neck using U-Net architecture and to evaluate the model's performance. In this retrospective study, a total of 30 anonymized CT volumes of the head and neck were sliced into 931 axial images of the parotid glands. Ground truth labeling was performed with the CranioCatch Annotation Tool (CranioCatch, Eskisehir, Turkey) by two oral and maxillofacial radiologists. The images were resized to 512 × 512 and split into training (80%), validation (10%), and testing (10%) subgroups. A deep convolutional neural network model was developed using U-net architecture. The automatic segmentation performance was evaluated in terms of the F1-score, precision, sensitivity, and the Area Under Curve (AUC) statistics. The threshold for a successful segmentation was determined by the intersection of over 50% of the pixels with the ground truth. The F1-score, precision, and sensitivity of the AI model in segmenting the parotid glands in the axial CT slices were found to be 1. The AUC value was 0.96. This study has shown that it is possible to use AI models based on deep learning to automatically segment the parotid gland on axial CT images.
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Purpose: The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs (PRs), as well as to assess the appropriateness of its treatment recommendations. Material and Methods: PRs from 100 patients (representing 4497 teeth) with known clinical examination findings were randomly selected from a university database. Three dentomaxillofacial radiologists and the Diagnocat AI software evaluated these PRs. The evaluations were focused on various dental conditions and treatments, including canal filling, caries, cast post and core, dental calculus, fillings, furcation lesions, implants, lack of interproximal tooth contact, open margins, overhangs, periapical lesions, periodontal bone loss, short fillings, voids in root fillings, overfillings, pontics, root fragments, impacted teeth, artificial crowns, missing teeth, and healthy teeth. Results: The AI demonstrated almost perfect agreement (exceeding 0.81) in most of the assessments when compared to the ground truth. The sensitivity was very high (above 0.8) for the evaluation of healthy teeth, artificial crowns, dental calculus, missing teeth, fillings, lack of interproximal contact, periodontal bone loss, and implants. However, the sensitivity was low for the assessment of caries, periapical lesions, pontic voids in the root canal, and overhangs. Conclusion: Despite the limitations of this study, the synthesized data suggest that AI-based decision support systems can serve as a valuable tool in detecting dental conditions, when used with PR for clinical dental applications.
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OBJECTIVES: This study aims to evaluate the reliability of AI-generated STL files in diagnosing osseous changes of the mandibular condyle and compare them to a ground truth (GT) diagnosis made by six radiologists. METHODS: A total of 432 retrospective CBCT images from four universities were evaluated by six dentomaxillofacial radiologists who identified osseous changes such as flattening, erosion, osteophyte formation, bifid condyle formation, and osteosclerosis. All images were evaluated by each radiologist blindly and recorded on a spreadsheet. All evaluations were compared and for the disagreements, a consensus meeting was held online to create a uniform GT diagnosis spreadsheet. A web-based dental AI software was used to generate STL files of the CBCT images, which were then evaluated by two dentomaxillofacial radiologists. The new observer, GT, was compared to this new STL file evaluation, and the interclass correlation (ICC) value was calculated for each pathology. RESULTS: Out of the 864 condyles assessed, the ground truth diagnosis identified 372 cases of flattening, 185 cases of erosion, 70 cases of osteophyte formation, 117 cases of osteosclerosis, and 15 cases of bifid condyle formation. The ICC values for flattening, erosion, osteophyte formation, osteosclerosis, and bifid condyle formation were 1.000, 0.782, 1.000, 0.000, and 1.000, respectively, when comparing diagnoses made using STL files with the ground truth. CONCLUSIONS: AI-generated STL files are reliable in diagnosing bifid condyle formation, osteophyte formation, and flattening of the condyle. However, the diagnosis of osteosclerosis using AI-generated STL files is not reliable, and the accuracy of diagnosis is affected by the erosion grade.
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Osteófito , Osteosclerose , Tomografia Computadorizada de Feixe Cônico Espiral , Humanos , Côndilo Mandibular/diagnóstico por imagem , Osteófito/diagnóstico por imagem , Osteófito/patologia , Estudos Retrospectivos , Reprodutibilidade dos Testes , Tomografia Computadorizada de Feixe Cônico/métodos , Osteosclerose/diagnóstico por imagem , Articulação TemporomandibularRESUMO
This study aims to investigate the effect of using an artificial intelligence (AI) system (Diagnocat, Inc., San Francisco, CA, USA) for caries detection by comparing cone-beam computed tomography (CBCT) evaluation results with and without the software. 500 CBCT volumes are scored by three dentomaxillofacial radiologists for the presence of caries separately on a five-point confidence scale without and with the aid of the AI system. After visual evaluation, the deep convolutional neural network (CNN) model generated a radiological report and observers scored again using AI interface. The ground truth was determined by a hybrid approach. Intra- and inter-observer agreements are evaluated with sensitivity, specificity, accuracy, and kappa statistics. A total of 6008 surfaces are determined as 'presence of caries' and 13,928 surfaces are determined as 'absence of caries' for ground truth. The area under the ROC curve of observer 1, 2, and 3 are found to be 0.855/0.920, 0.863/0.917, and 0.747/0.903, respectively (unaided/aided). Fleiss Kappa coefficients are changed from 0.325 to 0.468, and the best accuracy (0.939) is achieved with the aided results. The radiographic evaluations performed with aid of the AI system are found to be more compatible and accurate than unaided evaluations in the detection of dental caries with CBCT images.
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Aim: The term "branchial cleft cyst" refers to the lesions that can be considered synonymous with cervical lymphoepithelial cysts. Although relatively rare, they constitute the second major cause of head and neck pathologies in childhood. This study aimed to report the clinical presentations, diagnosis, and management of pediatric patients with the pathological diagnosis of branchial cleft cyst. Material and methods: This study was a retrospective analysis of the records of 33 patients with the diagnosis of branchial cyst, in two different university hospitals, in two different populations. Results: Thirty-three cases of branchial cleft cysts were seen in 33 patients: 17 females and 16 males. The majority (16 patients) were 2nd branchial cleft cysts. Accurate diagnosis of branchial cleft malformation was made via imaging in 20 of the 21 (95%) patients that underwent preoperative surgical ultrasonographic imaging. Conclusion: Branchial cleft cysts are frequently incorrectly diagnosed and ignored in the differential diagnosis. Thus, the diagnosis is often delayed, resulting in the mismanagement of affected patients. A branchial cyst should be suspected in any patient with a swelling in the lateral aspect of the neck, regardless of whether the swelling is solid or cystic, painful or painless. The use of ultrasonography can dramatically help clinicians with distinguishing branchial cleft cysts from other similar lesions of the head and neck.
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OBJECTIVE: Penetration of intervertebral disc joint during lumbar puncture might be unnoticed during procedure. However, accelerated degeneration of the disc joint is a long-term consequence of inadvertent penetration. In this paper, we aimed to demonstrate and evaluate the risk of disc puncture during standard lumbar puncture. PATIENTS AND METHODS: 50 human cadavers were used in this study. Disc puncture risk was assessed by using worst case scenario model. Lumbar puncture was performed in a standard fashion using midline route at L3-4, L4-5 and L5-S1 levels. The needle was advanced until it hit resistance from the bone. Lateral X-ray was used to visualize the needle position. Needle ended up in two possible locations - posterior vertebral body wall and intervertebral disc space. RESULTS: The probability of puncturing the joint was 20 % for L3-4, 38 % for L4-5, 16 % for L5-S1. Total probability of disc penetration was 25 %. Statistical analysis revealed significantly increased risk for performing LP at L4-5 level in comparison with L5-S1 (pâ¯=â¯0.023). CONCLUSION: Lumbar puncture carries significant risk of intervertebral disc penetration. This complication is not realized during the procedure and lead to accelerated joint degeneration.
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Disco Intervertebral/diagnóstico por imagem , Disco Intervertebral/lesões , Vértebras Lombares/diagnóstico por imagem , Vértebras Lombares/lesões , Punção Espinal/efeitos adversos , Cadáver , Humanos , Degeneração do Disco Intervertebral/diagnóstico por imagem , Degeneração do Disco Intervertebral/etiologia , Fatores de Risco , Sacro/diagnóstico por imagem , Sacro/lesões , Punção Espinal/instrumentaçãoRESUMO
OBJECTIVES: This study aims to investigate the depth, transverse and sagittal diameters of lunate fossa which is a significant structure of the wrist in terms of reducing the risk for volar plate screws, which are administered in distal radius fractures, from penetrating into the joint. MATERIALS AND METHODS: Depth, transverse and sagittal diameters of lunate fossa in 50 right and 50 left adult dried radius bones without distal tip damage were measured by using MicroscribeG2X from the MicroScribe G series. RESULTS: Mean lunate fossa depth: left 2.419886±0.51 mm/right 2.543052±0.78 mm, mean lunate fossa sagittal diameter: left 19.656±1.57 mm/right 18.796±1.53 mm, mean lunate fossa transverse diameter: left 11.382±0.65 mm/right 11.106±0.91 mm. There was no statistically significant difference between right and left depth values of lunate fossa (p=0.320), whereas there was statistically significant difference between right and left transverse and sagittal diameters (p=0.006, p=0.048). CONCLUSION: Measurements involving depth of lunate fossa may guide the development of new anatomic plates and decrease complications like the penetration of screw into joint whilst volar plate administrations.