Search Results (409)

Background and Objectives: Spinopelvic alignment may affect the outcomes of total hip arthroplasty (THA), with pelvic version influencing the risk of mechanical complications occurring after surgery. On the other hand, THA surgery itself may contribute to the modification of pelvis version. The sacro-femoro-pubic (SFP) angle is measured on anteroposterior (AP) radiographs of the pelvis in a supine position, and is used to estimate pelvic tilt (PT), representative of pelvic version, which requires lateral views of the sacrum for its calculation; however, these X rays are not routinely performed in the preoperative setting of hip surgery. This study aims to analyze how THA determines changes in the pelvic version of operated patients; the SFP angle will be used to assess pelvic version on standard AP radiographs. Materials and Methods: This retrospective study included 182 consecutive patients undergoing THA for unilateral primary degenerative hip osteoarthritis (HOA-study group, n = 104) or femoral neck fracture (FNF-control group, n = 78) at the author’s institution. The SFP angle was measured on AP pelvic radiographs of the non-replaced hip preoperatively, postoperatively, and at the last follow-up. PT values were derived from SFP angles. Pre- and postoperative PT and its variations ΔPT were assessed. Study groups were compared in terms of native and postoperative variations of pelvic version. Results: The average absolute value of ΔPT was 2.99° ± 3.07° in the HOA group and 3.57° ± 2.92° in FNF group. There was no significant overall difference in preoperative or postoperative PT values between groups. In both groups, THA surgery led to a certain improvement, still not significant, in pelvic orientation, with FNF patients presenting a greater tendency toward retroversion. No significant differences in complication rates were found comparing patients with different pelvic orientations. Conclusions: THA can lead to a “normalization” of pelvic version in a certain number of patients with preoperative anteversion or retroversion. Although statistically non-significant, this observation may have clinical implications for spinopelvic balance and could support prioritizing THA in patients with concurrent spinal disease. Further research is needed to confirm these findings and to evaluate the long-term impact of THA on spinopelvic alignment. Full article

Medical image registration is an indispensable preprocessing step to align medical images to a common coordinate system before in-depth analysis. The registration precision is critical to the following analysis. In addition to representative image features, the initial pose settings and multiple poses in images will significantly affect the registration precision, which is largely neglected in state-of-the-art works. To address this, the paper proposes a dual-pose medical image registration algorithm based on improved differential evolution. More specifically, the proposed algorithm defines a composite similarity measurement based on contour points and utilizes this measurement to calculate the similarity between frontal–lateral positional DRR (Digitally Reconstructed Radiograph) images and X-ray images. In order to ensure the accuracy of the registration algorithm in particular dimensions, the algorithm implements a dual-pose registration strategy. A PDE (Phased Differential Evolution) algorithm is proposed for iterative optimization, enhancing the optimization algorithm’s ability to globally search in low-dimensional space, aiding in the discovery of global optimal solutions. Extensive experimental results demonstrate that the proposed algorithm provides more accurate similarity metrics compared to conventional registration algorithms; the dual-pose registration strategy largely reduces errors in specific dimensions, resulting in reductions of 67.04% and 71.84%, respectively, in rotation and translation errors. Additionally, the algorithm is more suitable for clinical applications due to its lower complexity. Full article

This update is aimed at various specialists who deal with fractures, such as emergency physicians, general practitioners, orthopedists, and sports medicine physicians. The Global Burden of Disease 2019 Fracture Collaborators estimated the worldwide incidence to be at 178 million, i.e., 2.2 fractures per 1000 people per year. Traditionally, X-rays are the first choice for suspected fractures. However, many fractures can also be detected or excluded with ultrasound. This option is especially attractive when available at the “point of care,”, i.e., at the patient’s bedside in the ambulatory or emergency setting. Point-of-care ultrasound provides clinicians with a simple, cost-effective imaging tool without radiation and complex infrastructure. The evidence suggests that ultrasound has high diagnostic sensitivity and can reliably rule out many fractures with a high degree of certainty. When applied correctly, it could potentially save millions of radiographs and, in some cases, even compete with the accuracy of X-rays and CT scans. These findings suggest a potential paradigm shift. This update discusses the advantages of ultrasound, its examination technique, sonoanatomy of fractures, and relevant indication groups, including its application for analgesia through nerve, fascia, and fascial plane blocks. Ultrasound’s diagnostic value supports its integration into routine fracture assessment, particularly in emergency and ambulatory care settings Full article

Background: Spring ligament (SL) injuries are primarily associated with progressive collapsing flatfoot deformity, but can also occur due to trauma. It remains unclear whether the morphological changes following trauma differ from those caused by chronic overload. The aim of this study was (1) to analyze whether a relationship exists between the injury pattern and foot deformity and (2) to evaluate whether there is a distinction between trauma-related and non-trauma-related injuries. Method: We prospectively enrolled 198 patients with a median age of 57 years (range, 13 to 86 years; female, 127 (64%); male, 71 (36%)) who had a clinically diagnosed, surgically confirmed, and classified SL injury. We used weight-bearing standard X-rays to assess foot deformity. The control group consisted of 30 patients (median age 51 years, range, 44–66; female, 21 (70.0%); male, 9 (30.0%)) with no foot deformities or prior foot surgeries. Results: A 41.9% incidence of trauma was identified as the cause of these injuries, accounting for 16 (20.8%) of isolated injuries to the SL, 30 (42.9%) of SL injury accompanied by a posterior tibial (PT) tendon avulsion, and 37 (72.5%) of SL injury alongside a bony avulsion at the navicular injuries. The odds of being post-traumatic decreased with each year of age by a factor of 0.97 (95% CI: 0.95–0.99). Conclusions: While all radiographic measurements for flatfoot deformity became pathological after an injury to the SL, they did not accurately predict the injury patterns of the SL and distal PT tendon. Generally, post-traumatic cases exhibited lower severity of foot deformity, suggesting that other structures beyond the SL may contribute to the development of flatfoot deformity. Full article

Radiography, favoured for its ability to provide a non-invasive insight into the contents of wrapped or coffined artefacts, has revolutionised the study of mummified human and animal remains. Despite this potential, the technology is limited by its capacity to realistically visualise the surface attributes of these often-complex artefacts. In this paper, photogrammetry—a technique widely used in archaeology and heritage applications—is applied to build upon the radiographic investigation of six ancient Egyptian votive artefacts from Manchester Museum; a study which combines the two techniques for the first time on votive material from the collection. The paper showcases the results gained through clinical radiography techniques (digital X-ray and computed tomography) on the internal contents of the artefacts, highlighting the problems encountered when viewing the outer surface. With a simple on-site photogrammetry protocol, improved visualisation was possible, providing photo-realistic renderings with important potential for both research, conservation and engagement. Full article

Purpose: This pilot study aimed to evaluate how deviations in X-ray tube head angulation and digital sensor alignment affect the radiographic measurement of the profile angle in CAD-CAM abutments. Materials and Methods: A mandibular model was used with five implant positions (central, buccal, and lingual offsets). Custom CAD-CAM abutments were designed with identical bucco-lingual direction contours and varying mesio-distal asymmetry for the corresponding implant positions. Periapical radiographs were acquired under controlled conditions by systematically varying vertical tube angulation, horizontal tube angulation, and horizontal sensor rotation from 0° to 20° in 5° increments for each parameter. Profile angles, interthread distances, and proximal overlaps were measured and compared with baseline STL data. Results: Profile angle measurements were significantly affected by both X-ray tube and sensor deviations. Horizontal tube angulation produced the greatest profile angle distortion, particularly in buccally positioned implants. Vertical x-ray tube angulations beyond 15° led to progressive underestimation of profile angles, while horizontal tube head rotation introduced asymmetric mesial–distal variation. Sensor rotation also caused marked interthread elongation, in some cases exceeding 100%, despite vertical projection being maintained. Profile angle deviations greater than 5° occurred in multiple conditions. Conclusions: X-ray tube angulation and sensor alignment influence the reliability of profile angle measurements. Radiographs with > 10% interthread elongation or crown overlap may be inaccurate and warrant re-acquisition. Special attention is needed when imaging buccally positioned implants. Full article

Objectives: This study aimed to implement a high-resolution Saudi voxel-based anthropomorphic phantom in the OpenMC Monte Carlo (MC) simulation framework. The objective was to evaluate its applicability in radiological simulations, including radiographic imaging and effective dose calculations, tailored to the Saudi population. Methods: A voxel phantom comprising 30 segmented organs/tissues and over 32 million voxels were constructed from full-body computed tomography data and integrated into OpenMC. The implementation involved detailed voxel mapping, material definition using ICRP/ICRU-116 recommendations, and lattice geometry construction. The simulations included X-ray radiography projections using mesh tallies and anterior–posterior effective dose calculations across 20 photon energies (10 keV–1 MeV). The absorbed dose was calculated using OpenMC’s heating tally and converted to an effective dose using tissue weighting factors. Results: The phantom was successfully modeled and visualized in OpenMC, demonstrating accurate anatomical representation. Radiographic projections showed optimal contrast at 70 keV. The effective dose values for 29 organs were calculated and compared with MCNPX, the ICRP-116 reference phantom, and XGBoost-based machine learning (ML) predictions. OpenMC results showed good agreement, with maximum deviations of −35.5% against ICRP-116 at 10 keV. Root mean square error (RMSE) comparisons confirmed reasonable alignment, with OpenMC displaying higher RMSEs relative to other methods due to expanded organ modeling and material definitions. Conclusions: The integration of the Saudi voxel phantom into OpenMC demonstrates its utility for high-resolution dosimetry and radiographic simulations. OpenMC’s Python (version 3.10.14) interface and open-source nature make it a promising tool for radiological research. Future work will focus on combining MC and ML approaches for enhanced predictive dosimetry. Full article

This study applies deep learning-based object detection technology to defect detection in weld radiographs, proposing a technical solution for accurately identifying the types and locations of defects in weld X-ray radiographs. The research encompasses the construction of a defect dataset, the design of a multi-model object detection network, and the development of an automated film evaluation algorithm. This technology significantly enhances the efficiency and accuracy of detecting and identifying harmful defects on weld radiographs, providing critical technical support for ensuring the safe operation and efficient maintenance of pipelines of pressure equipment. Full article

Background/Objectives: Aseptic loosening is a major challenge in hip and knee arthroplasty. While radiostereometric analysis (RSA) is the gold standard for detecting early migration, it is static, costly, and requires metal beads. Provocation CT-based analysis studies implants under physiological stresses and offers a marker-free alternative with comparable accuracy. This systematic review evaluates its effectiveness, cost, and role in orthopedic imaging. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Three databases were searched, with no date restrictions, using keywords related to the research area. The risk of bias was assessed using the RoB-1 tool. Results: The initial search identified 42 studies, with 6 ultimately included in the review. These studies involved 198 patients with an average age of 65.0 years. Provocation CT demonstrated higher sensitivity and specificity than standard radiographs, particularly in cases with inconclusive X-rays. Additionally, the radiation dose for CT scans varied across studies, with effective doses ranging from 0.2 mSv to 4.5 mSv per scan. Compared to X-ray, CT-based methods showed comparable or superior performance in motion detection, though direct clinical comparisons with RSA remain lacking. Conclusions: Provocation CT-based analysis is a valuable diagnostic tool for early detection of implant loosening, offering a potentially feasible, accurate, and cost-effective alternative to traditional methods. However, standardized protocols, broader economic evaluations, and prospective multicenter trials are needed to confirm its routine clinical applicability. Full article

The risk of developing symptomatic knee osteoarthritis (KOA) during a lifetime, i.e., pain, aching, or stiffness in a joint associated with radiographic KOA, was estimated in 2008 to be around 40% in men and 47% in women. The clinical and scientific communities lack an efficient diagnostic method to effectively monitor, evaluate, and predict the evolution of KOA before and during the therapeutic protocol. In this review, we summarize the main methods that are used or seem promising for the diagnosis of osteoarthritis, with a specific focus on non- or low-invasive methods. As standard diagnostic tools, arthroscopy, magnetic resonance imaging (MRI), and X-ray radiography provide spatial and direct visualization of the joint. However, discrepancies between findings and patient feelings often occur, indicating a lack of correlation between current imaging methods and clinical symptoms. Alternative strategies are in development, including the analysis of biochemical markers or acoustic emission recordings. These methods have undergone deep development and propose, with non- or minimally invasive procedures, to obtain data on tissue condition. However, they present some drawbacks, such as possible interference or the lack of direct visualization of the tissue. Other original methods show strong potential in the field of KOA monitoring, such as electrical bioimpedance or near-infrared spectrometry. These methods could permit us to obtain cheap, portable, and non-invasive data on joint tissue health, while they still need strong implementation to be validated. Also, the use of Artificial Intelligence (AI) in the diagnosis seems essential to effectively develop and validate predictive models for KOA evolution, provided that a large and robust database is available. This would offer a powerful tool for researchers and clinicians to improve therapeutic strategies while permitting an anticipated adaptation of the clinical protocols, moving toward reliable and personalized medicine. Full article

This study tackles the challenge of automatically estimating age from pelvis radiographs. Furthermore, we aim to develop a methodology for applying artificial intelligence to classify or regress medical imagery data. Our dataset comprises 684 pelvis X-ray images of patients, each accompanied by annotations and masks for various regions of interest (e.g., the femur shaft). Radiomic features, e.g., the co-occurrence matrix, were computed to characterize the image content. We assessed statistical analysis, machine learning, and deep learning methods for their effectiveness in this task. Correlation analysis indicated that using certain features in specific regions of interest is promising for accurate age estimation. Machine learning models demonstrated that when using uncorrelated features, the optimal mean absolute error (MAE) for age estimation is 5.20, whereas when employing convolutional networks on the texture feature maps yields the best result of 9.56. Automatically selecting radiomic features for machine learning models achieves a MAE of 7.99, whereas utilizing well-known convolutional architectures on the original image results in a system efficacy of 7.96. The use of artificial intelligence in medical data analysis produces comparable outcomes; however, when dealing with a large number of descriptors, selecting the most optimal ones through statistical analysis enables the identification of the best solution quickly. Full article

Non-destructive testing (NDT) methods are critical for evaluating the structural integrity of and detecting defects in composite materials across industries such as aerospace and renewable energy. This review examines the recent trends and successful implementations of NDT approaches for composite materials, focusing on articles published between 2015 and 2025. A systematic literature review identified 120 relevant articles, highlighting techniques such as ultrasonic testing (UT), acoustic emission testing (AET), thermography (TR), radiographic testing (RT), eddy current testing (ECT), infrared thermography (IRT), X-ray computed tomography (XCT), and digital radiography testing (DRT). These methods effectively detect defects such as debonding, delamination, and voids in fiber-reinforced polymer (FRP) composites. The selection of NDT approaches depends on the material properties, defect types, and testing conditions. Although each technique has advantages and limitations, combining multiple NDT methods enhances the quality assessment of composite materials. This review provides insights into the capabilities and limitations of various NDT techniques and suggests future research directions for combining NDT methods to improve quality control in composite material manufacturing. Future trends include adopting multimodal NDT systems, integrating digital twin and Industry 4.0 technologies, utilizing embedded and wireless structural health monitoring, and applying artificial intelligence for automated defect interpretation. These advancements are promising for transforming NDT into an intelligent, predictive, and integrated quality assurance system. Full article

Background/Objectives: In dental medicine, the integration of various types of X-ray images, such as periapical (PA), bitewing (BW), and panoramic (PANO) radiographs, is crucial for comprehensive oral health assessment. These complementary imaging modalities provide diverse diagnostic perspectives and support the early detection of oral diseases, thereby enhancing treatment outcomes. However, there is currently no existing system that integrates multiple types of dental X-rays for both adults and children to perform tooth localization and numbering. Methods: Therefore, this study aimed to propose a system based on YOLOv8 that integrates multiple dental X-ray images and automatically detects and numbers both permanent and deciduous teeth. Through image preprocessing, various types of dental X-ray images were standardized and enhanced to improve the recognition accuracy of individual teeth. Results: With the implementation of a novel image preprocessing method, the system achieved a detection precision of 98.16% for permanent and deciduous teeth, representing a 3% improvement over models without image enhancement. In addition, the system attained an average tooth numbering accuracy of 98.5% for permanent teeth and 96.3% for deciduous teeth, surpassing existing methods by 5.6%. Conclusions: These results might highlight the innovation of the proposed image processing method and show its practical value in assisting clinicians with accurate diagnosis of tooth loss and the identification of missing teeth, ultimately contributing to improved diagnosis and treatment in dental care. Full article

Pneumothorax is a potentially life-threatening condition defined as the collapse of the lung due to air leakage into the chest cavity. Delays in the diagnosis of pneumothorax can lead to severe complications and even mortality. A significant challenge in pneumothorax diagnosis is the shortage of radiologists, resulting in the absence of written reports in plain X-rays and, consequently, impacting patient care. In this paper, we propose an automatic triage system for pneumothorax detection in X-ray images based on deep learning. We address this problem from the perspective of multi-source domain adaptation where different datasets available on the Internet are used for training and testing. In particular, we use datasets which contain chest X-ray images corresponding to different conditions (including pneumothorax). A convolutional neural network (CNN) with an EfficientNet architecture is trained and optimized to identify radiographic signs of pneumothorax using those public datasets. We present the results using cross-dataset validation, demonstrating the robustness and generalization capabilities of our multi-source solution across different datasets. The experimental results demonstrate the model’s potential to assist clinicians in prioritizing and correctly detecting urgent cases of pneumothorax using different integrated deployment strategies. Full article

Objective: To assess radiographic changes in the alveolar bone on the distal aspect of the second molars (2Ms) over time, while impacted third molars (ITMs) remain present across two timepoints. Methods: This retrospective observational study aimed to assess radiographic changes between two timepoints (T0 and T1). Both Orthopantomogram (OPG) and Periapical (PA) X-rays were utilized, with three measurements taken on the distal surface of 2Ms using EMAGO 6.1 software. Statistical significance was defined as a p-value < 0.05. Results: A total of 51 patients met the inclusion criteria, with a mean age of 45 years (SD ± 13). Sixty-eight second molars were assessed at baseline (T0) and follow-up (T1), with a mean interval of 20 months (SEM ± 62 days). No significant changes were found in vertical, oblique, or angular bone levels between T0 and T1. Gender significantly affected the cementoenamel junction (CEJ)–base of defect (BD) measurements (p = 0.022) and defect angles at T0 (p = 0.048), but not at the adjusted T1 (p = 0.292). Other variables, including medical history, smoking, and ITM angulation, showed no influence. Patient age was borderline significant in relation to intrabony defect angle (p = 0.047). Conclusions: Considering its limitations, this analysis does not provide evidence to support the hypothesis that prophylactic extraction of ITMs yields significant bone-sparing benefits. Furthermore, it does not establish that prolonged retention of ITMs consistently results in short-term bone alterations in adjacent 2Ms. Consequently, further research is warranted to more accurately assess the medium- to long-term implications of ITM retention on the bone levels of 2Ms. Full article