Radiographic Images Research Articles

Evaluation of Intervertebral Disc Space Width Between 10th and 11th Thoracic Vertebrae in Cats Using Radiography and Magnetic Resonance Imaging.

It is well known that the T10-T11 intervertebral disc space is usually narrower than the adjacent intervertebral disc spaces in most dogs. However, whether the T10-T11 disc space is narrower than the adjacent disc spaces is not well-established in cats. To measure the intervertebral disc space width of the T10-T11 disc space and to compare it with that of the adjacent disc spaces using radiography and magnetic resonance imaging (MRI). In Groups 1 (101 clinically normal cats) and 2 (32 cats without spinal diseases from T8 to T13), dorsal width (DW), central width (CW) and ventral width (VW) of the T8-T13 disc spaces were measured by radiography or MRI. Significant differences of the DW, CW and VW among disc spaces measured by radiography and MRI were evaluated. Intra- and interobserver reliabilities were measured by intraclass correlation coefficient. In Groups 1 and 2 using radiography, the DW and CW of the T10-T11 disc space were significantly narrower than those of adjacent disc spaces (p<0.05). The DW of the T8-T12 disc spaces was significantly narrower than that of the T12-T13 disc space in Group 1 using radiography. In Groups 1 and 2 using radiography, the CW and VW of the T8-T11 disc spaces were significantly narrower than those of the T11-T13 disc spaces. In Group 2 using MRI, the DW of the T10-T11 disc space was significantly narrower than that of the T11-T13 disc spaces. The VW of the T8-T11 disc spaces was significantly narrower than that of the T11-T13 disc spaces. The T10-T11 intervertebral disc space on radiography is statistically narrower than the adjacent intervertebral disc spaces in normal cats. The cranial thoracic intervertebral disc spaces (T8-T11) are usually narrower than the caudal thoracic intervertebral disc spaces (T11-T13) on radiography and MRI.

Establishment of a Digital Laminography facility at the Malaysian Nuclear Agency

Digital Laminography (DL) is a technique that enables the estimation of indication depth from a set of digital projection radiographs. It allows the engineers or researchers to visualize and measure the depth from the object’s surface. The technique applies to welded components and non-metal applications such as composite materials. The technique also allows users to understand engineering problems and further analyze the cause of failures. Malaysian Nuclear Agency is pursuing the building and establishment the DL system at its facility. A gantry is designed to hold a 225kVp X-ray tube that is mechanically moved slowly. A 100 µm pixel size Digital Detector Array (DDA) is used to capture the images. This paper highlights simulation and a preliminary assessment to understand the physics and appropriate steps to build a DL system. It discusses the simulation and experimental study of exposure parameters and setup by digital radiographic testing (RT-D) of known imperfections of a welded steel plate before performing the DL measurement. The radiographic images and their achieved contrast sensitivity and image quality are analyzed according to ISO 17636-2. The results of simulations and experiments demonstrate a good and consistent ability to measure the depth and extension of the reconstructed imperfections within ± 1 mm regarding the actual size and position.

AI and radiologist assessments on the prevalence of TMJ osteoarthritis using radiographic images: A comparative study

Objectives: This study aims to address the significant discomfort and functional impairment associated with temporomandibular joint osteoarthritis (TMJ OA), which negatively impacts the quality of life. It emphasizes the importance of prompt diagnosis and explores the potential of an Artificial Intelligence (AI) system to enhance TMJ OA diagnosis. Methods: The prevalence of TMJ OA was evaluated using 3 diagnostic tools: the gold standard, the AI model, and an examiner. In total, 132 patients who performed 190 cone-beam computed tomography (CBCT) images were included. Results: The prevalence of TMJ OA was 62.11% using the gold standard, 63.68% using the AI model, and 58.42% when assessed by the examiner. No gender variation in TMJ OA diagnosis was reported (p-value&gt;0.05). Age variations were reported with the gold standard and the examiner diagnosis. When compared to the gold standard, the AI model had remarkable sensitivity (97.46%) and specificity (91.67%). Conclusions: The AI model shows promise in enhancing the accuracy of TMJ OA diagnosis, offering potential benefits for early detection and improved patient outcomes.

Discussion on effect of observation circumstances for image in digital radiography

The discriminability of the IQI in the film radiography is affected by the observation circumstance and the luminance of film viewer. ISO17636-2 states that the images of digital radiograph shall be examined in a dimmed room. However, it does not describe requirements for the observation environment in digital radiography, despite the fact that the environment is similar to that of a normal professional PC and the display of the images can be easily adjusted. In this report, the influence of the observation environment in digital radiography was compared as the parameters the wire diameter and the WL value of a display adjustment value when the minimum wire diameter of the image quality indicator (IQI) was percepted, using images of welded steel at t25mm and t50mm. For welded steel of t25mm, differences due to SNRN values and differences due to the observation environment of light and dark room were compared. For t50mm, differences due to the presence or absence of the observation mask for the single wire of wire IQI which is places in front of the display, differences due to the resolution and brightness of the PC monitor, and differences when the WL was adjusted arbitrarily or fixed were compared. For the Digital Radiographic testing (RT-D), the basic spatial resolutions (SRb) were obtained by measuring the profile and applying of visual observation with the duplex wire type IQI. On the other hand, when observing the image of wire type IQI, the observation ways that one was obtain the perceptible image for all wires and another was to get the perceptible single wire image by using the observation mask for watching each wire were applied. Moreover, the influence of window width (WW) and window level (WL) adjustment on the discrimination of wire-type IQI was examined by quantifying it as WW/WL. As a result, it was confirmed that the discriminality in the dimmed room and the adjustment of WW and WL were effective. In addition, using the observation a mask showed that the perception of the adjacent wire image affected observer cognition in IQI discrimination during image observation. When using viewer software profiling, SRb measurements were not affected by the observation environment, but the visual observation was affected by the environment, and when observing images in the dimmed room with RT-D, it was found that adjusting WW and WL had a greater effect on discrimination for images with low SNRN and low contrast.

Evaluation of cfDNA fragmentation characteristics in plasma for the diagnosis of lung cancer: A prospective cohort study.

Lung cancer is one of the most prevalent cancers worldwide, yet only approximately 16% of patients are diagnosed in early stage, highlighting the urgent need for novel, highly accurate detection models. In our study, patients with suspected lung cancer or lung disease, as identified through radiographic imaging, along with healthy individuals, were consecutively recruited from Beijing Chest Hospital. Circulating free DNA (cfDNA) was extracted from plasma samples, and low-depth whole-genome sequencing was performed to identify fragmentomic features for model construction. A total of 265 participants were prospectively enrolled, comprising 124 lung cancer patients and 141 noncancer individuals. The model we developed was based on four cfDNA fragmentation characteristics, including 20-bp breakpoint nucleotides motif, fragmentation size coverage, fragmentation size distribution, and copy number variation. In an independent test cohort, the model achieved an area under the curve (AUC) of 0.861 (95% CI: 0.781-0.942) and demonstrated a sensitivity of 70% (95% CI: 53.5%-83.4%) at a specificity of 89.4% (95% CI: 76.9%-96.5%). Notably, the model was also effective in detecting early-stage cancer, with an AUC of 0.808 (95% CI: 0.69-0.925). In summary, our lung cancer detection model shows strong screening capabilities by leveraging four cfDNA fragmentation characteristics, exhibiting robust performance in early cancer diagnosis.

Estimation of Height at Withers Based on Long Bone Measurements of Living Cats

In this study, coefficients enabling estimation of shoulder height were obtained by taking morphometric measurements from radiographic images of live cats using the radiogrammetric method. For this purpose, a total of 37 adult cats, including 17 females and 20 males, were involved. While the effect of sexual dimorphism was observed on the morphometric data, the presence of sexual dimorphism was only evident in the coefficients (factors) of the humerus and talus. No significant effect of gender was found on the shoulder height estimation coefficients (factors) for other thoracic and pelvic limb bones. Gender had an impact on the slenderness index in all thoracic limbs, but only on the tibia slenderness index among the pelvic limb bones. Generally, female individuals were found to have more slender limbs. It is believed that the obtained coefficients (factors) and index data will contribute significantly to the prediction of archaeological cat morphology.

Cephalometric landmark annotation using transfer learning: Detectron2 and YOLOv8 baselines on a diverse cephalometric image dataset

BackgroundCephalometric landmark annotation is a key challenge in radiographic analysis, requiring automation due to its time-consuming process and inherent subjectivity. This study investigates the application of advanced transfer learning techniques to enhance the accuracy of anatomical landmarks in cephalometric images, which is a vital aspect of orthodontic diagnosis and treatment planning. MethodsWe assess the suitability of transfer learning methods by employing state-of-the-art pose estimation models. The first framework is Detectron2, with two baselines featuring different ResNet backbone architectures: rcnn_R_50_FPN_3x and rcnn_R_101_FPN_3x. The second framework is YOLOv8, with three variants reflecting different network sizes: YOLOv8s-pose, YOLOv8m-pose, and YOLOv8l-pose. These pose estimation models are adopted for the landmark annotation task. The models are trained and evaluated on the DiverseCEPH19 dataset, comprising 1692 radiographic images with 19 landmarks, and their performance is analyzed across various images categories within the dataset. Additionally, the study is extended to a benchmark dataset of 400 images to investigate how dataset size impacts the performance of these frameworks. ResultsDespite variations in objectives and evaluation metrics between pose estimation and landmark localization tasks, the results are promising. Detectron2's variant outperforms others with an accuracy of 85.89%, compared to 72.92% achieved by YOLOv8's variant on the DiverseCEPH19 dataset. This superior performance is also observed in the smaller benchmark dataset, where Detectron2 consistently maintains higher accuracy than YOLOv8. ConclusionThe noted enhancements in annotation precision suggest the suitability of Detectron2 for deployment in applications that require high precision while taking into account factors such as model size, inference time, and resource utilization, the evidence favors YOLOv8 baselines.

Tooth numbering with polygonal segmentation on periapical radiographs: an artificial intelligence study.

Accurately identification and tooth numbering on radiographs is essential for any clinicians. The aim of the present study was to validate the hypothesis that Yolov5, a type of artificial intelligence model, can be trained to detect and number teeth in periapical radiographs. Six thousand four hundred forty six anonymized periapical radiographs without motion-related artifacts were randomly selected from the database. All periapical radiographs in which all boundaries of any tooth could be distinguished were included in the study. The radiographic images used were randomly divided into three groups: 80% training, 10% validation, and 10% testing. The confusion matrix was used to examine model success. During the test phase, 2578 labelings were performed on 644 periapical radiographs. The number of true positive was 2434 (94.4%), false positive was 115 (4.4%), and false negative was 29 (1.2%). The recall, precision, and F1 scores were 0.9882, 0.9548, and 0.9712, respectively. Moreover, the model yielded an area under curve (AUC) of 0.603 on the receiver operating characteristic curve (ROC). This study showed us that YOLOv5 is nearly perfect for numbering teeth on periapical radiography. Although high success rates were achieved as a result of the study, it should not be forgotten that artificial intelligence currently only can be guides dentists for accurate and rapid diagnosis. It is thought that dentists can accelerate the radiographic examination time and inexperienced dentists can reduce the error rate by using YOLOv5. Additionally, YOLOv5 can also be used in the education of dentistry students.

MGScoliosis: Multi-grained scoliosis detection with joint ordinal regression from natural image

Scoliosis is among the most prevalent diseases affecting teenagers. However, traditional scoliosis screening methods often resort to physical examination or radiographic imaging. The two ways both rely on experts with high costs, which are not suitable for wide-range screening. Besides, estimating Cobb angle level only using natural images are challenging. To tackle these issues, we propose a multi-grained scoliosis detection framework by jointly estimating severity level and Cobb angle level of scoliosis from a natural image instead of a radiographic image, which has not been explored before. Specifically, we regard scoliosis estimation as an ordinal regression problem, and transform it into a series of binary classification sub-problems. Besides, we adopt the visual attention network with large kernel attention as the backbone for feature learning, which can model local and global correlations with efficient computations. The feature learning and the ordinal regression is put into an end-to-end framework, in which the two tasks of scoliosis severity level estimation and scoliosis angle level estimation are jointly learned and can contribute to each other. Extensive experiments demonstrate that our approach outperforms state-of-the-art methods as well as human performance, which provides a promising and economical solution to wide-range scoliosis screening. Particularly, our approach achieves accuracies of 94.90% and 79.62% in estimating severity level and Cobb angle level, improving large margins of 4.90% and 12.15% over existing natural image based scoliosis detection performance, respectively. The code is available at https://github.com/RuiChen-stack/MGScoliosis.

Osteochondral Autograft Transplantation for Symptomatic Full-thickness Patellar Cartilage Defects in Adolescents.

This study aimed to review the clinical, radiographic, and magnetic resonance imaging (MRI) outcomes of osteochondral autograft transplantation applied to patellar cartilage lesions of patients under 18 years of age. Data from nine consecutive patients were retrospectively analyzed for indications, preoperative complications, and clinical-radiographic outcomes. Patients were clinically evaluated using the Pedi-IKDC and Lysholm scores. In addition, return to sports and knee pain were assessed. MRI evaluation included an analysis of osteochondral graft integration using the magnetic resonance observation of cartilage repair tissue 2.0 score and radiographic classification of osteoarthritis using the Kellgren-Lawrence system. Nine patients (9 knees, 6 males) with a mean age of 14 years (SD: 1.7, range; 11 to 17y) were analyzed. Lesions were located on the medial facet (N=5), lateral facet (N=3), and central ridge of the patella (N=1). One or 2 cylindrical osteochondral grafts were transplanted, with a median diameter of 9mm (range: 8 to 10mm). The average lesion size was 102.9mm2. At a mean follow-up of 45.1 months (range: 23 to 117mo), the mean Pedi-IKDC score was 89.2 (SD: 9.8), and the Lysholm score was 94.4 (SD: 4.8). Patients returned to sports in an average of 7.3 months (SD: 2, range: 6 to 12mo). MRI of 8 patients showed osteochondral graft integration with a mean magnetic resonance observation of cartilage repair tissue 2.0 score of 86.9 (SD: 7, range: 80 to 100). Six knees showed Kellgren-Lawrence grade 0 joint space on radiographs, and 3 showed grade 1. Eight patients were asymptomatic at the last follow-up, and 1 reported occasional mild pain with intense physical activity. One patient developed arthrofibrosis, requiring arthroscopic lysis of adhesions and manipulation. Osteochondral autograft transplantation is a safe and effective technique for treating symptomatic patellar full-thickness chondral lesions in adolescents. Long-term follow-up studies will determine whether the affected area maintains structural and functional integrity over time. Level IV-therapeutic study.

Castellvi classification of lumbosacral transitional vertebrae: comparison between conventional radiography, CT, and MRI.

The reliability and diagnostic accuracy of commonly used diagnostic imaging modalities in the classification of lumbosacral transitional vertebrae (LSTV) are poorly known, and comparative studies are scarce. To compare the diagnostic performance of conventional radiography (CR), computed tomography (CT), and magnetic resonance imaging (MRI) in classifying LSTVs. In this retrospective cross-sectional study, a total of 852 patients undergoing lumbar imaging studies using all three modalities were initially assessed for the presence of LSTV using CT scans. In total, 100 patients with LSTV anatomy were identified. Four readers performed blinded and independent evaluations of these 100 patients on each modality, and an experienced fellowship-trained radiologist performed a gold standard read using all three modalities. Inter-reader reliability metrics were analyzed in comparison to the gold standard. Statistical software R (4.2.1) was used for the analyses. We found superior diagnostic efficacy for CT: the sensitivity, specificity, accuracy, and balanced accuracy were 76%, 93%, 77%, and 84%, respectively. For MRI, the metrics were 54%, 88%, 56%, and 68%, and for CR 32%, 85%, 42%, and 59%, respectively. Inter-reader reliability was found to be good for CT (κ = 0.63-0.71) and fair for both CR (κ = 0.16-0.32) and MRI (κ = 0.24-0.56). CT had the highest diagnostic performance in all measured metrics with good inter-reader reliability. MRI and CR showed fairly poor sensitivity and accuracy, and thus consideration should be used when classifying LSTVs with these two modalities.

Hybrid Deep Learning Based Model for Removing Grid-Line Artifacts from Radiographical Images

The digital imaging technique known as Computed Radiography (CR) has transformed the medical imaging industry by providing a number of advantages. It eliminates the need for traditional film-based methods, making it more efficient and convenient. A common issue faced with CR images is the presence of grid artifacts and other pattern artifacts, which can have a significant impact on the quality of the images when viewed on a computer screen, especially if a clinic-grade display is not accessible. This paper presents a novel framework for removing grid line artifacts from X-ray images, which is a critical challenge in medical imaging. The framework proposes a hybrid Deep Grid model that combines a Gaussian band-stop filter with ADAM optimization to produce high-quality, grid-line free X-ray images that are suitable for further analysis and diagnosis. Deep learning (DL) models for instance the Convolutional Neural Network (CNN), DenseNet, VGG-Net, and Fast R-CNN were utilized to classify images, and the grid-by-grid removal of grid lines in the image was performed. The proposed framework achieved a high accuracy rate of 98% in eliminating grid line artifacts from X-ray images, demonstrating its possibility for a big improvement the accuracy and reliability of diagnostics for medical based on X-ray images

Clinical and instrumental characteristics of osteoarthritis in hyperuricemia

Objective: to investigate in a multicentre single-stage study the relationships between hyperuricemia (HU) and clinical, instrumental and laboratory parameters of osteoarthritis (OA).Material and methods. The study included 200 patients aged 40 to 75 years with a definite diagnosis of knee (KN) OA that met ACR criteria, with stage I–III OA by Kellgren–Lawrence. The mean age of the patients was 55.9±10.3 years and the body mass index (BMI) was 29.4±6.2 kg/m2. An individual chart was completed for each patient, including anthropometric parameters, medical history and clinical examination data, visual analogue scale (VAS) assessment of KN pain, WOMAC, patient's general health assessment (GHA) and information on comorbidities. All patients underwent standard radiography and magnetic resonance imaging (MRI) of the KN (WORMS), dual-energy X-ray absorptiometry of the lumbar spine and femoral neck, and laboratory examination.Results and discussion. HU was diagnosed in 57 (28.5) patients when the serum uric acid (UA) level was above 360 μmol/L. Patients were divided into two groups according to the presence or absence of HU. The age of the patients in the two groups was comparable, but they differed significantly in terms of disease duration, BMI, waist and hip circumference, which were greater in the HU group (p &lt;0.05). Statistically significant differences were also found in the assessment of the severity of OA course: there were higher pain indices according to VAS, WOMAC total score and its components (pain and functional impairment, FI), GHA in the HU group. On MRI, osteitis was more common in the medial aspect of the tibia (odds ratio 5.75; 95% confidence interval 1.29–25.6; p=0.03). Patients with HU had higher concentrations of CRP, COMP, leptin, insulin, triglycerides and creatinine (p &lt;0.05 for all values).Spearman correlation analysis confirmed the association between HU and duration and radiological stage of OA, the presence of osteitis in the medial aspect of tibia detected by MRI, pain according to VAS and WOMAC, FI according to WOMAC and GHA (p&lt;0.05).Conclusion. At high UA levels, pain values according to VAS and WOMAC are higher, GHA is worse, and CRP and COMP levels are elevated. MRI shows more frequent osteitis in the medial aspect of the tibia in patients with HU. Deciphering the mechanisms that determine the relationship between HU and OA is important for the development of new methods for the prevention and treatment of these diseases.

Has the cat got your tongue, or is something obstructing your throat? A review of imaging of ingested and aspirated foreign bodies in the paediatric population.

Children frequently swallow or inhale foreign objects, a situation that can be life-threatening. Radiographic imaging plays a lead role in the early identification and location of inhaled or swallowed objects is essential. Promptly identifying and locating inhaled or swallowed objects are essential, as some items require immediate removal. For example, button batteries in the throat can cause grave harm; magnets can attract each other through the gut and cause perforations; and other objects can obstruct the airway or intestinal tract. Radiologists must understand how these objects appear in images to assist doctors in treating patients effectively. Recognising signs of inhaled objects on radiographs is also crucial, as symptoms may not always be clear, and many inhaled objects are not visible on radiographs. Radiographs are the primary means of checking for swallowed or inhaled objects, although other tests like fluoroscopy and computed tomography may be used in complex cases. Doctors working with children should be acquainted with the appearance of these common objects on images and their clinical importance.

Improving the industrial defect recognition in radiographic testing by pre-training on medical radiographs

Deep learning methodologies have gained substantial traction for defect recognition in industrial radiographic testing including welds, castings and other fields. Regardless of the deep learning utilized, it has emerged as a standard configuration to use a model pre-trained from ImageNet to accelerate convergence and enhance recognition accuracy. However, there is a significant gap between the domain of natural images and industrial radiographs, raising the question of whether there might be a superior pre-training method than relying on ImageNet pre-training. Fortunately, medical radiographs are more similar to industrial radiographs than natural images because of the same imaging method. In this paper, we initially utilize numerous medical radiographic images from CheXpert dataset to train a pre-trained CNN model. Then, we apply this model to four distinct tasks within two radiographic testing scenarios to validate its advantages and generalization capabilities. Finally, experiments on multiple datasets indicate that our method brings more benefits than ImageNet pre-training or training from scratch, with a F1 score improvement of 3.41 %–13.72 % for defect classification and a mIoU improvement of 1.05 %–6.58 % for defect segmentation. It demonstrates that pre-training from medical radiographs provides a cost-free improvement for all kinds of tasks in industrial defect recognition.

Dentin thickness model: A novel method for dental age estimation using panoramic radiography

The study aims to evaluate the reliability of the novel dentin thickness model based on root parameters when applied to panoramic radiography images of mandibular first molar in the southern Turkish subpopulation. A total of 946 panoramic images were analyzed for the study. The samples were allocated into four age groups: Group 1(between 10 and 18), Group 2(between 19 and 30), Group 3(between 31 and 50), Group 4(between 51 and 78). The dentin thickness model measurements consisted of root dentin thickness of the mesial aspect of the distal root and distal canal width. Regression, intraclass correlation coefficient, and Durbin-Watson analyses were used for statistics. A medium correlation was detected in the dentin thickness model (R = 0.398). Root dentin thickness and canal width had a significant effect (p < 0.05), but gender did not (p > 0.05). Group 3 showed the highest accuracy (p < 0.001). Group 4 presented the lowest correlation with chronological age compared to other age groups (p < 0.001). The dentin thickness model showed a promising result for the dental age estimation with a medium correlation. The dentin thickness model included root measurements of the mesial aspect of the mandibular first molar without any crown parameters in the southern Turkish subpopulation. Gender did not affect the dentin thickness model.

Real-world outcomes in patients with brain metastases secondary to HR+/HER2- MBC treated with abemaciclib and local intracranial therapy.

Real-world data are limited for patients with brain metastases secondary to metastatic breast cancer (MBC) and treated with cyclin-dependent kinase 4/6 inhibitors (CDK4/6i). This study describes real-world outcomes in patients with hormone receptor-positive, human epidermal growth factor 2-negative (HR+/HER2-) MBC with brain metastases diagnosis before abemaciclib initiation. A nationwide electronic health record-derived de-identified MBC database (January 2011-December 2021) was assessed retrospectively. Patients with HR+/HER2- MBC who were treated with abemaciclib (monotherapy or in combination) following diagnosis of brain metastases were included. Real-world best response reflected clinician-documented response assessment of the brain imaging (intracranial) and change in disease burden following radiographic imaging (extracranial); these were reported descriptively. Time to treatment discontinuation (TTD), real-world progression-free survival (rwPFS), and overall survival (rwOS) were assessed using Kaplan-Meier methods from abemaciclib initiation (index date). Among 82 included patients (mean age 57.0 years; 98.8% female), 22.0% and 19.5% received CDK4/6i and chemotherapy before abemaciclib initiation, respectively, and the majority (80.5%) received radiation/local surgery to the brain before abemaciclib initiation. Patients mostly received abemaciclib as monotherapy (n = 6) or in combination with endocrine therapy (n = 68). Median TTD was 7.1 (95% CI 4.6-11.3) months, rwPFS was 9.2 (95% CI 6.0-11.6) months, and rwOS was 20.8 (95% CI 13.9-26.0) months. Intracranial and extracranial objective response rates, as determined by treating physicians, were 45.1% (n = 23/51) and 56.7% (n = 34/60), respectively. Intracranial and extracranial clinical benefit rates were 62.7% (n = 32/51) and 70.0% (n = 42/60), respectively. In this real-world study of patients diagnosed with brain metastases and initiating abemaciclib, most patients received radiation/local surgery to the brain before abemaciclib initiation. Although the outcomes in this real-world study are encouraging, it is unclear if the benefit was due to local therapy, abemaciclib, or the combination, and causality cannot be inferred. Further prospective clinical studies are needed to confirm the clinical benefit of this approach.

Does the utilization of fluoroscopy affect the accuracy of prosthesis position in patients undergoing hip replacement surgery via the direct anterior approach compared to the posterolateral approach for an experienced surgeon? A single-center retrospective study

BackgroundThe direct anterior approach (DAA) for total hip arthroplasty (THA) has gained popularity due to perceived advantages in achieving better early outcomes. However, the theoretical benefits such as precise implant positioning and accurate leg length restoration are still inconsistent. In this study, we compared implant position and leg length discrepancy (LLD) of the DAA and posterolateral approach (PLA) conducted by a single surgeon who had mastered both approaches.MethodsThis study retrospectively reviewed the medical records and radiographic images of 244 patients who underwent THA between 2012 and 2021 by a single experienced surgeon using either the DAA (n = 120) or PLA (n = 124). Postoperative pelvic anteroposterior radiographs at 6 months follow-up were used to assess acetabular component inclination and anteversion, as well as LLD. Mann-Whitney U tests and Chi-squared test were performed to compare outcomes between the two approaches.ResultsNo significant differences were observed in patient demographics between the two groups. The DAA group demonstrated significantly lower postoperative LLD (0.00 mm) compared to the PLA group (5.00 mm, p < 0.0001). No significant difference was observed in the Lewinnek zone for cup anteversion and inclination angles between the two groups.ConclusionsFor experienced surgeons in other approaches, our findings suggest transferring to the DAA may not substantially improve cup positioning, but it might slightly enhance limb length measurement. For surgeons already proficient in other approaches and deciding to maintain those approaches, their primary concern for optimal THA outcome should be striving for leg length equivalence.

A Neglected Fracture: Treatment and Infection of Seymour Fractures of the Hallux in the Pediatric Population.

Seymour physeal fractures of the distal phalanx of the Hallux in children are common but rarely described in the literature. There is limited literature investigating how these fractures should be specifically treated. Generally, good results are reported when open fractures are treated with debridement and antibiotics. This large retrospective review evaluates incidence of infection and compares outcomes of various treatments for Seymour physeal fractures of the distal phalanx of the Hallux in children. This study included patients ≤18 years of age treated for Seymour fractures of the Hallux between January 1, 2007, and November 20, 2018, at a single tertiary-care urban children's hospital. Demographic, injury, and treatment data were obtained via a retrospective review of electronic medical records, including closed versus open fracture status, time to treatment, and whether antibiotics were prescribed and taken. Initial radiographic imaging was examined by a single attending surgeon for angulation (degrees) and widening (mm). Outcome variables included the development of infection and the rate and success of healing. One hundred thirty-eight patients were included in our analysis. Most (84/138, 61%) fractures were closed and treated successfully without antibiotics. Treatment for open fractures varied greatly, with many of these fractures undergoing an incision and drainage procedure (I&D) (33/54, 61%) and antibiotic prescription (43/54, 76%). Most (47/54, 87%) open fractures did not develop infection. However, 7/54 open fractures presented with an active infection. Four out of seven (29%) of these fractures did not receive any treatment before infection presentation. Two others who presented with infection both had delayed antibiotics and neither underwent I&D. Fractures that either presented with or developed an infection presented significantly later than those fractures that did not develop infection (P<0.001). Neither angulation nor displacement correlated to the time of healing or development of infection. In our large cohort, the majority of open Seymour fractures of the Hallux treated in a timely manner did not develop infection, regardless of treatment. However, open fractures that presented multiple days after injury had an increased incidence of infection. Thus, for open fractures, we recommend timely antibiotics and I&D. Closed fractures may be treated conservatively, with no indication for reduction or use of antibiotics.

Comparative evaulation of condylar guidance obtained by digital panoramic radiographic images with that of obtained during jaw relation and try-in using two different interocclusal record material in completely edentulous patients: an in vivo study

Background In completely edentulous patients, maintaining the patient’s temporomandibular joint (TMJ) health and intraoral components is very essential, which can be achieved by an accurate interocclusal record, which can be taken by various materials and also at various stages. Simulation of the temporomandibular joint anatomy and mandibular movements is possible on a semi-adjustable articulator, which is widely used in prosthodontics. Transferring the record on articulator is a critical step in the fabrication of complete dentures, so it should be done precisely to reduce chair side time and also to avoid complications for patients. This study examines which material is more accurate and records which stage gives more precision by comparing the Condylar guidance on radiographs. This is because it is a relatively consistent bony landmark and can be used to correlate with clinical methods in terms of verification. The objective is to determine the inter occlusal records created during the Jaw Relation stage and Try-in using reinforced wax and Polyvinyl siloxane and compare these values to the condylar guidance obtained by orthopantomogram (OPG). Methods Recording the Condylar Guidance value on OPG by tracing the Glenoid fossa, Articular eminence, and the Frankfurt Horizontal Plane. Followed by conventional steps in making complete dentures at jaw relation and try-in stage. We will record values of condylar guidance with the two different Interocclusal record materials. Expected result It will help the clinicians to gain knowledge about obtaining precise condylar inclination angle by using suitable interocclusal record materials. Conclusions This study will help us to obtain condylar inclination, which in turn helps the patient’s satisfaction as it preserves the intraoral components and health of TMJ.