Computed Tomography Scan Data Research Articles

Determination of Mouth Width for Facial Reconstruction Based on Statistical Regression Model.

It is important to generate predictable statistical models by increasing the number of variables on the human skeletal and soft tissue structures on the face to increase the accuracy of human facial reconstructions. The purpose of this study was to determine mouth width 3-dimensionally based on statistical regression model. Cone-beam computed tomography scan data from 130 individuals were used to measure the horizontal and vertical dimensions of orbital and nasal structures and intercanine width. The correlation between these hard tissue variables and the mouth width was evaluated using the statistical regression model. Orbital width, nasal width, and intercanine width were found to be strong predictors of the mouth width determination and were used to generate the regression formulae to find the most approximate position of the mouth. These specific variables may contribute to improving the accuracy of mouth width determination for oral and maxillofacial reconstructions.

Characteristics of Lung Cancer Patients with Brain Metastases based on Baseline Head Computerized Tomography (CT)-scan in Arifin Achmad Hospital October 2022 - June 2023

Background: The majority of lung cancer cases are often discovered at a late stage because it frequently develops without symptoms in the early stages. Many lung cancer deaths are caused by metastases to other organs. The purpose of this study was to examine the features of lung cancer patients with brain metastases using baseline CT scan data. Method: Between October 2022 and June 2023, a cross-sectional study was conducted at the Arifin Achmad Hospital in Pekanbaru on all newly diagnosed lung cancer patients with brain metastases who also met the inclusion and exclusion criteria. Results: Eight subjects of lung cancer with brain metastasis were found from 49 patients. All subjects were male with age mostly in between 40 and 60 years. Three subjects (37.5%) were Squamous Cell Carcinoma (SCC), four subject (50%) were adenocarcinoma and 1 (12.5%) were SCLC. Conclusion: This study discovered that 16.3% of patients who met the inclusion criteria had lung cancer with brain metastases. Further research should be done on a cohort study and a preventive strategy for lung cancer with brain metastases.

Our 7-year experience supporting the Ross autograft with the novel technique of Personalized External Aortic Root Support

ObjectiveThe Ross operation is a widely accepted option for aortic valve replacement in children, and evidence shows its excellent results in terms of hemodynamics and durability. However, indications are still limited due to the fact that it is a technically demanding procedure, only performed by specialized surgeons. On top of that, and despite numerous techniques being applied, autograft dilatation remains a key disadvantage, which can lead to graft failure. In recent years, the ExoVasc Personalized External Aortic Root Support (PEARS) has proven to be a safe and effective option to prevent aortic root dilatation in various aortopathies and is a technique that lends itself to support the pulmonary autograft in the Ross operation. MethodsDuring the past 7 years, we have used the ExoVasc PEARS graft, manufactured from the patients' pulmonary artery measurements from computed tomography scan data, to support the pulmonary autograft in the Ross operation. This graft (manufactured by Exstent Ltd, UK) is implanted at the same time as the autograft. We have reviewed all the patients who underwent this surgery, including demographic data, aorta measurements, operative data, and follow-up assessment consisting of periodic echocardiograms and magnetic resonance imaging scans. ResultsFifty patients were included in the study. Mean age at the time of the operation was 29.84 years, the youngest patient was 9 years-old. Nineteen patients (38%) had previous sternotomies; 11 of them having had a previous aortic valve replacement. Seventy-two percent of patients had initially a bicuspid aortic valve. Mean diameter of the ascending aorta was 3.83 cm. Forty-four percent of patients required a concomitant reduction aortoplasty due to mismatch sizes between the ascending aorta and the autograft. Mean bypass and crossclamp times were 200.66 and 151.14 minutes, respectively. Median length of stay was 6 days. Mean follow-up was 16.88 months. Two patients required subsequent aortic valve replacement (1 had rheumatic valve disease and the other had iatrogenic damage in his autograft valve leaflet). Ascending aorta dimensions remain stable when compared with immediate postoperative studies. There were no deaths. ConclusionsThe ExoVasc PEARS graft has proven to be an excellent support in the Ross operation to prevent the autograft failure related to autograft dilatation that can offer several advantages compared with other existing techniques. With this type of support, we believe the Ross indications can be expanded to multiple clinical scenarios, given the good long-term results this operation offers in terms of durability, life expectancy, and hemodynamics.

Comparison of Glenoid Dimensions Between 3D Computed Tomography and 3D Printing.

Glenoid dimensions can be measured in vivo with various imaging methods including two-dimensional (2D) and three-dimensional computed tomography (CT) and magnetic resonance imaging scans. Printing of three-dimensional (3D) models of the glenoid using imaging data is feasible and can be used to better understand skeletal trauma and complex skeletal deformations such as glenoid bone loss in patients with shoulder instability. The purpose of this study was to compare measurements of glenoid dimensions on 3D CT scan reconstructed models and 3D printed models of the glenoid. CT scans from 62 young, male adults acquired for non-trauma-related causes were evaluated. Following volume rendering, a stereolithography model of each scapula was constructed and a 3D model was printed. Additionally, 3D CT models of each glenoid were reconstructed using dedicated software. Measurements of the maximum glenoid height and width were performed on both the 3D printed and the 3D reconstructed models. To assess intra- and interrater reliability, measurements of 15 glenoids were repeated by two observers after three weeks. The measurements of the 3D printed and 3D reconstructed models were compared. Inter- and intra-rater reliability was excellent or perfect. Analysis of height and width values demonstrated a strong correlation of 0.91 and 0.89 respectively (p<0.001) for both the 3D printed models and the 3D reconstructed models. There was a strong correlation between the height and width, but no significant difference between the glenoid width and height in both models. There was no statistical significance between height and width when measurements on the two models were examined (p=0.12 and 0.23 respectively). 3D printed glenoid models can be used to evaluate the glenoid dimensions, width, and height, as they provide similar accuracy with 3D reconstructed models as provided from CT scan data.

Assessment of resectability of pancreatic cancer using novel immersive high-performance virtual reality rendering of abdominal computed tomography and magnetic resonance imaging.

Virtual reality (VR) allows for an immersive and interactive analysis of imaging data such as computed tomography (CT) and magnetic resonance imaging (MRI). The aim of this study is to assess the comprehensibility of VR anatomy and its value in assessing resectability of pancreatic ductal adenocarcinoma (PDAC). This study assesses exposure to VR anatomy and evaluates the potential role of VR in assessing resectability of PDAC. Firstly, volumetric abdominal CT and MRI data were displayed in an immersive VR environment. Volunteering physicians were asked to identify anatomical landmarks in VR. In the second stage, experienced clinicians were asked to identify vascular involvement in a total of 12 CT and MRI scans displaying PDAC (2 resectable, 2 borderline resectable, and 2 locally advanced tumours per modality). Results were compared to 2D standard PACS viewing. In VR visualisation of CT and MRI, the abdominal anatomical landmarks were recognised by all participants except the pancreas (30/34) in VR CT and the splenic (31/34) and common hepatic artery (18/34) in VR MRI, respectively. In VR CT, resectable, borderline resectable, and locally advanced PDAC were correctly identified in 22/24, 20/24 and 19/24 scans, respectively. Whereas, in VR MRI, resectable, borderline resectable, and locally advanced PDAC were correctly identified in 19/24, 19/24 and 21/24 scans, respectively. Interobserver agreement as measured by Fleiss κ was 0.7 for CT and 0.4 for MRI, respectively (p < 0.001). Scans were significantly assessed more accurately in VR CT than standard 2D PACS CT, with a median of 5.5 (IQR 4.75-6) and a median of 3 (IQR 2-3) correctly assessed out of 6 scans (p < 0.001). VR enhanced visualisation of abdominal CT and MRI scan data provides intuitive handling and understanding of anatomy and might allow for more accurate staging of PDAC and could thus become a valuable adjunct in PDAC resectability assessment in the future.

Computer Tomography (CT)-Based Study to Investigate Feasibility and Efficacy of Thoracoscopic Surgery in the Treatment of Penetrating Chest Wall Tuberculosis.

Chest wall tuberculosis may develop if tuberculous (TB) lesions spread through the chest wall and invade the thoracic cavity. The presence of a mass on the patient's chest wall may be the first indication of TB, and a chest CT scan can help diagnose external penetrating chest wall TB, the incursion of tuberculosis from the lungs into the chest wall. This study examines the safety and efficacy of thoracoscopic-assisted surgery for the treatment of penetrating chest wall tuberculosis as a means of exploring novel concepts of minimally invasive surgery. Our hospital conducted a retrospective study of 25 patients with penetrating chest wall TB who underwent thoracoscopic surgery between January 2020 and June 2021. General demographics, CT scan data linked to surgery, and postoperative patient outcomes were compared between the two groups. The data was also evaluated to determine the range of operation time and the volume of bleeding from different foci in the thoracic cavity. All procedures went well after patients took conventional antituberculosis medication for at least two weeks prior to surgery. CT scans showed that thoracoscopic surgery needed a smaller incision than traditional chest wall TB surgery, with no discernible increase in surgical time. Postoperative tube use, length of hospital stay, and blood loss were all significantly lower than they would have been with conventional surgery. In addition, thoracoscopy was associated with a significantly reduced rate of subsequent treatment. Fibrous plate development and calcification caused the longest operation times in the thoracoscopic surgery group, whereas multiple pleural tuberculomas generated the most hemorrhage. Thoracoscopic surgery usually reveals tuberculous foci hiding in the thoracic cavity. Thethoracic surgery can eliminate the TB focus in the chest wall and intrathoracic while treating penetrating chest wall tuberculosis. The CT scan is a crucial part of the diagnostic process for these patients. Minor surgical trauma, low complication and recurrence rates, and good results. There is a greater distinction between the two surgical approaches for patients with penetrating chest wall TB as opposed to those with basic chest wall tuberculosis.

Baseplate inferior offset affects shoulder range of motion in reverse shoulder arthroplasty in Asian population

BackgroundImpingement is a common complication of reverse shoulder arthroplasty. Placement of the baseplate with a wide impingement-free angle is ideal; however, there are few studies on Asian populations, which have smaller height and physique, and there is a lack of guidance on achieving optimal outcomes. The purpose of the present study was to explore the impingement-free range of motion reverse shoulder arthroplasty and analyze the suitable baseplate position or tilt for the Asian population using simulation software.MethodsWe uploaded computed tomography scan data from 20 Asian patients to three-dimensional (3D) simulation software. The implantation of the reverse shoulder arthroplasty component was performed on the 3D humerus and scapula using software, and range of motion was assessed until impingement occurred.ResultsThe range of motion in flexion significantly improved when the baseplate was lowered up to 3 mm inferiorly. Range of motion in abduction and internal and external rotation significantly improved as the baseplate was lowered up to 4 mm. There was no significant difference in range of motion in any motion after changing the inferior tilt, except in internal and external rotation.ConclusionsThe range of motion in abduction, flexion, and internal and external rotations significantly improved with increased inferior offset. These results may prove valuable in determining the optimal baseplate position for RSA, particularly in Asian populations.

Finite element analysis of vertebroplasty in the osteoporotic T11-L1 vertebral body: Effects of bone cement formulation.

Vertebral compression fractures are one of the most severe clinical consequences of osteoporosis and the most common fragility fracture afflicting 570 and 1070 out of 100,000 men and women worldwide, respectively. Vertebroplasty (VP), a minimally invasive surgical procedure that involves the percutaneous injection of bone cement, is one of the most efficacious methods to stabilise osteoporotic vertebral compression fractures. However, postoperative fracture has been observed in up to 30% of patients following VP. Therefore, this study aims to investigate the effect of different injectable bone cement formulations on the stress distribution within the vertebrae and intervertebral discs due to VP and consequently recommend the optimal cement formulation. To achieve this, a 3D finite element (FE) model of the T11-L1 vertebral body was developed from computed tomography scan data of the spine. Osteoporotic bone was modeled by reducing the Young's modulus by 20% in the cortical bone and 74% in cancellous bone. The FE model was subjected to different physiological movements, such as extension, flexion, bending, and compression. The osteoporotic model caused a reduction in the average von Mises stress compared with the normal model in the T12 cancellous bone and an increment in the average von Mises stress value at the T12 cortical bone. The effects of VP using different formulations of a novel injectable bone cement were modeled by replacing a region of T12 cancellous bone with the materials. Due to the injection of the bone cement at the T12 vertebra, the average von Mises stresses on cancellous bone increased and slightly decreased on the cortical bone under all loading conditions. The novel class of bone cements investigated herein demonstrated an effective restoration of stress distribution to physiological levels within treated vertebrae, which could offer a potential superior alternative for VP surgery as their anti-osteoclastogenic properties could further enhance the appeal of their fracture treatment and may contribute to improved patient recovery and long-term well-being.

Surgical Significance of Variant Anatomy of Inferior Mesenteric Artery and Left Colic Artery: A Computed Tomography Angiographic Study

Introduction: A variation in vessel morphology determines flow dynamics and vascular disease pathogenesis. Definite information on the distinctive anatomical variations of the mesenteric vessels is extremely important for laparoscopic surgical procedures and interventional radiological procedures in the abdominal region. Three-dimensional-computed tomography angiography (3D-CTA) is a less invasive method to evaluate vascular anatomy using a visual tracking method on high-definition images, contrast-enhanced inferior mesenteric artery (IMA) can be traced to its terminal branches beside the colon wall. Subjects and Methods: Abdominal contrast-enhanced computed tomography scan data from 180 patients was retrospectively collected, reconstructed, and analyzed. The origin, length of IMA from origin to the first branch, branching patterns of IMA, and tracking patterns of the ascending branch of left colic artery (LCA), were examined, and their associations with clinical features were analyzed. Results: IMA displayed variations in the level of origin ranging from upper 1/3 of L3 to upper 1/3 of L4, mean length from origin to the first branch was 27.4 ± 7.8 mm. Observed branching patterns of IMA were grouped according to Yada classification: Type 1 (52.2%), Type 2 (15.5%), Type 3 (14.4%), and Type 4 (17.7%). Tracking of the ascending branch of LCA before anastomosis with marginal artery revealed four patterns: Type A LCA pattern in 43.9%; Type B LCA anatomy pattern was (19.4%); Type C LCA anatomy pattern was (20.0%); and Type D LCA anatomy pattern was observed (16.7%). Conclusion: Preoperative understanding of the vascular variations of IMA and LCA can be obtained by 3D-CTA. This may be helpful to surgeons in planning preoperative strategies to prevent iatrogenic injuries.

Development of patient-specific 3D printed implants for total knee arthroplasty

Aim: Arthritis is a degenerative condition characterized by the progressive deterioration of the knee joint, leading to aches, rigidity, and decreased mobility. Total knee arthroplasty (TKA) surgery is performed to alleviate pain for restoring activity in these patients. TKA is carried out due to natural wear of the cartilage and meniscus or by sudden impact at the knee joint area. The surgical procedure involves careful planning, precise bone cuts, and insertion of artificial components made of metal alloys and high-density polyethylene. However, conventional manufacturing of customized knee implants involves time and cost. This work aims to present the application of three-dimensional (3D) printing for developing individualized knee implants for TKA and the challenges faced during it. Methods: Morphometry of the knee joint varies among different populations, including Indian and Western, which pose challenges during the surgery as accurate alignment and implant sizing are crucial for optimal outcomes. A female patient’s pre-surgery computed tomography (CT) scan is considered to identify the disease and to find region of interest (ROI) such as knee joint. Process involves converting scanned data to a file format for 3D printing via computer-aided design (CAD). Results: The patient’s CT scan data is processed to obtain the CAD models of knee joint and standard triangulation language (STL) file. Additional geometries and noise present near the region are removed to get ROI. Open loops and overlapping triangles are rectified in the STL file. Based on the morphometry of the bone, resection is done to obtain the CAD models of knee implants. 3D printing of the knee joint and implant prototypes is then obtained using fused deposition modelling (FDM). Line layers on the printed implant prototype are seen. Conclusions: Patient-specific 3D printed knee joint implant prototypes are successfully obtained using FDM. Challenges faced during the work are successfully worked out.

Detecting meso-damage and subsurface cracks in a hard rock using frequency-modulated thermal wave imaging (FMTWI)

Mines, tunnels, and hillside roadways that are subjected to high levels of stress are prone to massive and violent occurrences of rock failures. It results in a multitude of irreversible consequences, including the loss of human lives. Nevertheless, preceding rock failures, the development of micro and macrocracks, which are sometimes not discernible on the surface, takes place. Subsurface cracks indicate the degradation of rock and can be employed as a means to anticipate occurrences of rock failures and bursts. Therefore, the utilization of subsurface imaging techniques for rocks facilitates the estimation of the true strength of the rock mass. Nevertheless, in many instances, rock masses are not easily reachable, posing difficulties for standard techniques such as ground-penetrating radar or computed tomography (CT) scan imaging, to identify the cracks. Hence, this research endeavours to explore the feasibility of employing frequency-modulated thermal wave imaging (FMTWI) for identifying subsurface cracks and their coalescence in hard rocks through the utilization of numerical simulation and experimental methods. A model was constructed using the finite element method wherein artificial cracks were intentionally introduced into a cylindrical granite specimen based on the CT scan data acquired during the meso-damage analysis. The thermograms obtained were subjected to pre-processing and post-processing techniques, and afterwards compared with the CT scan images. The FMTWI tests were conducted in the laboratory to calibrate and validate the simulation results. The findings derived from the analyses of temperature profiles and thermograms indicate that this particular technology is a promising one and offers several advantages in comparison to alternative methods for detecting micro- or macrocracks in deep mines and tunnels.

Perioperative changes in radiographic density in erector spinae muscle and mortality after lung transplantation

RationaleThe radiographic density of the erector spinae muscle (ESM) is often decreased early after lung transplantation (LTx). The prognostic impact of this change has not been elucidated. ObjectiveTo investigate whether the decrease in the radiographic density of ESMs early after LTx is associated with a poor prognosis. MethodsThis study is a single center retrospective cohort study. Routine follow-up chest computed tomography scan data just before and 12 weeks after LTx were retrospectively retrieved for adult patients who underwent primary LTx at Kyoto University Hospital. The radiographic density of ESM was quantitatively evaluated as the mean attenuation of the ESM (ESMct), and the impact of the decreased ESMct during the 12 weeks after LTx on overall survival (OS) was examined by Cox proportional hazard regression. ResultsA total of 151 recipients (94 cadaveric LTx, 57 living-donor lobar LTx) were included in this study. The median duration of postoperative observation was 4.4 years, during which time 39 recipients (26%) died. Decreased postoperative ESMct was significantly associated with poor OS (HR, 1.64; 95% CI, 1.14–2.35, P = 0.008 per 1 Z score decrease) in the multivariate model adjusted for age, sex, episodes of acute rejection, and preoperative ESMct. Similar results were obtained when the subjects were limited to those with cadaveric LTx. ConclusionA decreased perioperative ESMct was strongly associated with a poor prognosis after LTx in addition to low preoperative ESMct. Maintaining postoperative muscle radiographic density, which reflects muscle quality, may be important for a better prognosis after LTx.

SCAM-GAN: Generating brain MR images from CT scan data based on CycleGAN combined with attention module

The diagnosis of epilepsy often depends heavily on Magnetic Resonance Imaging (MRI). Unfortunately, the utilization of MRI is constrained, due to its expensive price and lengthy operating times. More significantly, certain people with claustrophobia or cardiac pacemakers are not candidates for MRI owing to the risk of harm. Computed tomography (CT) images, in comparison, are considerably faster, cheaper, and free from the same restrictions. As opposed to conventional medical imaging synthetic techniques, which rely on abundant unpaired data or a minimum number of paired data, the proposed method in this study utilizes unpaired training data to predict an MR picture from a CT scan. This method overcomes tight registration problem in paired training and reduces the challenge of context mismatch in unpaired training. It is possible to convert 2D brain MR pictures from CT scans using the Spatial & Channel Attention Mechanism-Generative Adversarial Network (SCAM-GAN) that includes cycle-consistent and adversarial losses. The superiority of the proposed strategy was established by quantitative comparisons versus separate training approaches which are paired and unpaired.

An Approach to Recognise Lung Diseases Using Segmentation and Classification

Abstract Lung cancer is one of the most common causes of death in people worldwide. One of the key procedures for early detection of cancer is segmentation or analysis and classification or assessment of lung images. Radiotherapists have to invest a lot of effort into the manual segmentation of medical images. To solve this issue, early-stage lung cancer is detected using Computed Tomography (CT) scan images. The proposed system for diagnosing lung cancer is divided into two main components: the first part is an analyser component built on the upper layer of the U-shaped Network Transformer (UNT), and the second component is an assessment component built on the upper layer of the self-supervised network, which is used to categorise the output segmentation component as benign or cancerous. The proposed method provides a powerful tool for the early detection and treatment of lung cancer by combining CT scan data with 2D input. Numerous experiments are conducted to improve the analysis and evaluation of the findings. Using the public dataset, both test and training experiments were conducted. New state-of-the-art performances were achieved with experimental results: an analyser accuracy of 96.9% and an assessment accuracy of 96.98%. The proposed approach provides a new powerful tool for leveraging 2D-input CT scan data for early detection and treatment of lung cancer using a variety of methods.

Deep residual unfolding: A novel sparse computed tomography reconstruction method leveraging iterative learning and neural networks

Addressing the challenge of compromised imaging quality in sparse Computed Tomography (CT) reconstructions—a significant issue due to the inherent sparsity of CT scan data—we present a novel method grounded in both iterative unfolding and deep learning techniques. This sparse CT reconstruction method involves constructing and minimizing an energy model, which comprises both a data fidelity term and a regularization term. Unlike traditional methods that rely on sparse variation operators like Total Variation (TV), our approach employs a deep learning model instantiated as a Residual Convolutional Neural Network. Enhanced with Group Normalization and the Swish activation function, this network iteratively unfolds the energy model to improve reconstruction quality. Our method's efficacy is validated through metrics such as Peak Signal Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Root Mean Square Error (RMSE) on a specific CT dataset. Overall, this work contributes to the advancement of sparse CT reconstructions, with significant potential implications for medical imaging applications.

Pseudo CT Synthesis Using Cone-Beam CT of Cervical Cancer with GAN-Based Neural Network Model

Cervical cancer (CC) is a tumor disease that threatens the health of women. As an important treatment of CC, radiotherapy has been widely used in clinic. With the rapid development of radiotherapy technology, adaptive radiotherapy has received much attention. Adaptive radiotherapy means more accurate radiation dose and more accurate radiation area, which can effectively protect normal tissue. It is significant to improve the local control rate of tumor and the quality of life of patients. However, the Cone-Beam CT (CBCT) images collected during radiotherapy are of poor quality and cannot provide real-time radiation effect information, resulting in timely and effective adjustment of radiation dose and radiation area in the process of radiotherapy for cervical cancer. To alleviate this issue, this study will establish a model to leverage CC CBCT images to synthetize pseudo computed tomography (CT) images with high quality, so as to achieve the purpose of quality improvement. This study included the data of 20 patients with CC in ** hospital. The planning CT and CBCT scan data of each patient before radiotherapy were collected, and the interval between the two kinds of image data was required to be less than one week. After data preprocessing, a total of 1206 pairs of images were trained and tested. The generative adversarial network (GAN) is constructed. In order to ensure the similarity between the input image and the output image, the L1 loss function is leveraged. And the full supervision method is used to train the model to achieve a better effect of image synthesis and improve the quality of CBCT image. Peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) were used as evaluation indexes. Using five-fold cross-validation, the values of PSNR between the pseudo-CT (sCT) and the planning CT (pCT) image and between the CBCT and the pCT image are calculated. The results are 26.9 and 22.6, respectively. The sCT obtained from the GAN model increases the peak signal-to-noise ratio by 19% compared with the original CBCT, which means that the proposed model built in this study can improve the useful information of the CBCT image. The SSIM values between sCT and pCT and between CBCT and pCT are also calculated, and the average values of them are 0.89 and 0.63, respectively. Therefore, in this experiment, the structure of the sCT obtained by the proposed model is closer to pCT. And the SSIM increases by 41.2% compared with the original CBCT, which means that the sCT by the proposed model is more similar to the pCT in structure. These results could make a more accurate judgment on the effect of radiotherapy. In this study, the pseudo-CT synthesis method based on GAN can improve the quality of CC CBCT image. The results show this method makes the structure clearer and could assist doctors to adjust the radiation dose and radiation area in time. This study is able to facilitate the development of adaptive radiotherapy for CC.

Does previous arthroscopic Bankart repair influence coracoid graft osteolysis in Latarjet procedure? A case-control study with computed tomography scan data

Latarjet procedure is commonly performed in treatment of recurrent shoulder instability and also indicated as a salvage procedure for recurrence after failed arthroscopic Bankart repair. While this procedure has shown success, there is an increased awareness of complications in recent studies, especially for graft osteolysis. Most relevant research have focused on pathophysiology, incidence, location or risk factors of graft osteolysis; however, the data is limited to primary Latarjet procedures. This study aims to investigate the effect of previous arthroscopic Bankart repair surgery on corocaid bone graft osteolysis in Latarjet procedure. This retrospective case-control study analyzed data from patients who underwent primary Latarjet procedure or revision Latarjet procedure following failed arthroscopic Bankart repair. Clinical outcome measures included range of motion (ROM), subjective shoulder value (SSV) and Rowe score. Volumetric analysis of each transferred coracoid graft were performed using early postoperative and late postoperative computed tomography (CT) scan data and amount of graft osteolysis was then calculated as percentage of volume reduction of each graft. 32 patients who met the inclusion criteria, with 24 patients in the primary Latarjet group (group I) and 8 patients in revision Latarjet group (group II), were included to study. Mean age of patients was 32.5±7.7 years and mean follow-up duration was 52.1±8.9 months. Both study groups showed significant improvement in SSV compared to baseline (p<0.05). Comparison of postoperative clinical outcome measures showed no significant difference between two study groups in any outcome parameter (p>0.05). No recurrence was observed during follow-up period. There were 6 patients (25%) with positive apprehension sign in group I and 4 patients (50%) in group II (p>0.05). Analysis of radiological data revealed that all patients underwent some degree of graft osteolysis with varying osteolysis ratios between 12% to 98%. Mean osteolysis ratio of the coracoid graft was 67.3±22.6% in group I and 69.4±25.6% in group II, without significant difference between two groups (p>0.05). Findings of this study suggest that both primary and revision Latarjet procedures following failed arthroscopic Bankart repair underwent considerable amount of coracoid graft osteolysis. Previous arthroscopic Bankart repair did not seem to have significant influence on the amount of graft osteolysis and both primary and revision Latarjet procedures showed satisfactory clinical outcomes.

A Scientific Proposal for Surgical Decision-Making in Occult Intertrochanteric Fractures Based on Finite Element Analysis.

Background In the treatment of femoral intertrochanteric fractures, there is still a lack of consensus on the optimal approach for isolated greater trochanteric fractures and insufficient intertrochanteric fractures. The limited number of patients and restricted access to accurate assessment of fracture extension using magnetic resonance imaging contribute to the unclear treatment strategy. This study aims to utilize finite element (FE) analysis to analyze stress values at the fracture line and investigate their influence on intertrochanteric fracture extension under different loading conditions. The hypothesis is that fracture extension occurs following certain conditions, supporting the need for surgery based on scientific evidence. Methodology Osseous data from a computed tomography (CT) scan was used to create a proximal femur FE model using FEA software. CT scan data were converted to Digital Imaging and Communications in Medicine format and used to generate the FE model. Trabecular bone and cortex were meshed into tetrahedral elements. The model consisted of 1,592,642 elements and 282,530 nodes. Two models were created, namely, healthy proximal femur (HF) and femoral insufficient intertrochanteric fracture (FIF). Material properties were assigned based on CT values and conversion equations. The distal end of the femur was constrained. Stress analysis using the dynamic explicit approach was performed. Von Mises stresses were calculated for the proximal femur. The number of elements exceeding yield stress was counted to predict fracture risk by focusing on fracture line spots. In this study, the distribution of von Mises stress was compared between the HF and the FIF models. Six loading combinations were considered, namely, two weight-bearing conditions (3 W loading simulating for walking and 1/3 W for touch-down standing) and three hip flexion angles (0°, 15°, and 23°). Results Under 3 W loading, no significant stress elevations were observed in the HF model at any flexion angles. However, the FIF model exhibited increased stress at the site of the posterior fracture line extension. This stress-induced element destruction was observed in both cortical and cancellous bone. For the 1/3 W loading condition, only minimal stress elevation was observed in both HF and FIF models. To assess the influence on fracture extension, the number of yielded elements was evaluated along the fracture line edges (greater trochanter and middle of the intertrochanteric ridge). Under 3 W loading, the HF model had only one yielded element, indicating minimal fracture risk. In contrast, the FIF model exhibited a notable presence of yield elements in various regions (total/greater trochanter/shaft) at different flexion angles: 0° (115/16/28), 15° (265/158/23), and 23° (446/233/34). Under the 1/3 W loading condition, neither the HF nor the FIF models showed any yielding elements, regardless of the direction of external force. Conclusions The results demonstrated elevated stress levels at the fracture line in the FIF model, particularly during walking, indicating a higher risk of fracture extension at the flex position. However, under reduced weight-bearing conditions, the stress at the fracture site remained within the yield stress range, suggesting a relatively low risk of fracture extension. These findings hold significant clinical implications for developing surgical protocols that consider patients' compliance with weight-bearing restrictions.

Optimized Xception Learning Model and XgBoost Classifier for Detection of Multiclass Chest Disease from X-ray Images.

Computed tomography (CT) scans, or radiographic images, were used to aid in the early diagnosis of patients and detect normal and abnormal lung function in the human chest. However, the diagnosis of lungs infected with coronavirus disease 2019 (COVID-19) was made more accurately from CT scan data than from a swab test. This study uses human chest radiography pictures to identify and categorize normal lungs, lung opacities, COVID-19-infected lungs, and viral pneumonia (often called pneumonia). In the past, several CAD systems using image processing, ML/DL, and other forms of machine learning have been developed. However, those CAD systems did not provide a general solution, required huge hyper-parameters, and were computationally inefficient to process huge datasets. Moreover, the DL models required high computational complexity, which requires a huge memory cost, and the complexity of the experimental materials' backgrounds, which makes it difficult to train an efficient model. To address these issues, we developed the Inception module, which was improved to recognize and detect four classes of Chest X-ray in this research by substituting the original convolutions with an architecture based on modified-Xception (m-Xception). In addition, the model incorporates depth-separable convolution layers within the convolution layer, interlinked by linear residuals. The model's training utilized a two-stage transfer learning process to produce an effective model. Finally, we used the XgBoost classifier to recognize multiple classes of chest X-rays. To evaluate the m-Xception model, the 1095 dataset was converted using a data augmentation technique into 48,000 X-ray images, including 12,000 normal, 12,000 pneumonia, 12,000 COVID-19 images, and 12,000 lung opacity images. To balance these classes, we used a data augmentation technique. Using public datasets with three distinct train-test divisions (80-20%, 70-30%, and 60-40%) to evaluate our work, we attained an average of 96.5% accuracy, 96% F1 score, 96% recall, and 96% precision. A comparative analysis demonstrates that the m-Xception method outperforms comparable existing methods. The results of the experiments indicate that the proposed approach is intended to assist radiologists in better diagnosing different lung diseases.

X-ray Computed Tomography (CT) to Scan the Structure and Characterize the Mud Cake Incorporated with Various Magnetic NPs Concentration: An Application to Evaluate the Wellbore Stability and Formation Damage

The X-ray computed tomography method has provided unrivalled data about the characterization and evolution of the internal/external structure of materials by analyzing CTN and non-destructive imaging approach. Applying this method on the appropriate drilling-fluid ingredients plays a significant role in generating proper mud cake quality to stabilize wellbore, and avoid formation damage and filtration loss by preventing drilling fluid invasion into the formation. In this study, smart-water drilling mud containing different concentrations of magnetite nanoparticles (MNPs) was used to assess the filtration loss properties and formation impairment. Conventional static filter press, non-destructive X-ray computed tomography (CT) scan images and high-resolution quantitative measurement of CT number method were used to estimate the filtrate volume and characterize the filter cake layers, hence evaluating the reservoir damage through hundreds of merged images. The CT scan data were combined with the HIPAX and Radiant viewer digital image processing. The variation in CT number of mud cake samples under different concentrations of MNPs and without MNPs concentration were analyzed, and hundreds of 3D images as a cross-sectional profile were used. This paper highlights the importance of MNPs property in terms of minimizing filtration volume and improving mud cake quality and thickness, and hence improving the wellbore stability. From the results, a notable reduction of filtrate drilling mud volume and mud cake thickness to 40.9% and 46.6%, respectively, were recorded for drilling fluids incorporated with 0.92 wt.% of MNPs. However, this study asserts that optimal MNPs should be implemented to guarantee the best filtration property. As confirmed from the results, increasing the MNPs concentration beyond the optimal value (up to 2 wt.%) increased the filtrate volume and mud cake thickness by 3.23 and 33.3%, respectively. CT scan profile images show two layers of mud cake produced from water-based drilling fluids possessing 0.92 wt.% MNPs. The latter concentration was found to be the optimal additive of MNPs as it caused a decrease in filtration volume, mud cake thickness, and pore spaces within the structure of the mud cake. Using the optimum MNPs, the CT number (CTN) shows a high CTN and density material, and uniform compacted thin mud cake structure (0.75 mm). The produced thin mud cake layer reveals the precipitation or exchange of elemental/mineral composition during fluid-solid interaction. These results confirm that MNPs could help in avoiding or reducing the formation damage, driving away drilling fluid from the formation, and improving borehole stability.