Search Results (7,827)

Background/Objectives: Hip displacement is a common problem in children with cerebral palsy (CP). Typically, the recommended hip surveillance imaging for these children consists of an anteroposterior pelvic radiograph, from which we calculate the migration percentage (MP) to determine treatment plans (conservative/preventive therapy, femoral osteotomy, femoral and pelvic osteotomies, and salvage surgery). However, little is known about the accuracy of MP for treatment planning. We aim to compare treatment plans based on MP thresholds with plans determined by an orthopedic surgeon following review of the hip CTs. Methods: We retrospectively identified hip CTs performed in children who were ≤18 years old with CP (11/2018—07/2024). The inclusion criteria were: (1) a pelvic radiograph performed 6 months prior to the hip CT; and (2) no surgeries between the pelvic radiograph and the hip CT. These hip CTs were randomized and blindly reviewed by an orthopedic surgeon to determine each child’s treatment plan (CT-treatment). Separately, a pediatric radiologist blindly reviewed the randomized pelvic radiographs and measured each hip’s MP to determine each child’s treatment plan (XR-treatment). We used kappa-agreement and Bland–Altman analyses to compare XR- and CT-treatments. Results: Our study cohort consisted of 139 children (mean age = 9.3 ± 3.8 years; male = 90) with 278 hips. The proportion of agreement and unweighted kappa between XR- and CT-treatment were both low: 0.532 (148/278) and 0.339, respectively. Bland–Altman analyses showed that XR-treatment and CT-treatment were exchangeable when MP ≤ 10% but were not exchangeable otherwise. Conclusions: We should be cautious about relying exclusively on pelvic radiographs and subsequent MP calculation in making treatment decisions for hip displacement in children with CP since many anatomic details become evident on 3D imaging. Full article

During the COVID-19 pandemic, researchers have made efforts to detect COVID-19 through various methods. In the dataset used for this study, COVID-19 patients were identified using chest computed tomography (CT) images. High dimensionality is frequently an issue in machine learning image classification. Accordingly, this study implemented three dimensionality reduction methods in combination with various machine learning algorithms for improved classification. Principal component analysis (PCA), uniform manifold approximation and projection (UMAP), and diffusion maps were applied to the dataset to extract the most important features of the chest CT images. The extracted features were given as input either to logistic regression or the extreme gradient boosting (XGBoost) algorithm to perform classification. The strongest model identified from this study was diffusion maps in combination with logistic regression. This model, evaluated against existing models from similar studies in recent years, yielded strong performance for detecting COVID-19 cases using chest CT images. Our proposed model achieved 97.35% accuracy, 92.16% sensitivity, and 98.59% specificity on the held-out test set in differentiating between COVID-19-positive cases and healthy, non-COVID-19 cases. This study aimed to detect COVID-19 without the use of viral testing. Importantly, this method could assist clinicians in making an initial diagnosis, especially when viral testing is not available or timely enough for the patient’s case. This study also provides deeper insight into various dimensionality reduction methods and how compatible they are with biomedical imaging data. Models were trained using stratified cross-validation on the training set, with final performance evaluated on a held-out test set at the patient level to prevent data leakage. Additional imbalance-aware metrics were used to assess robustness given class distribution differences. Full article

Background: Although magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for most spinal evaluations, computed tomography (CT) is still always required for preoperative planning to assess osseous anatomy and determine surgical device size, increasing the radiation exposure and workflow complexity. CT-like images enable visualization of precise bone morphology without ionizing radiation. In addition, these images often provide CT myelography-like contrasts, allowing the simultaneous depiction of the spinal canal area (SCA). This study aimed to evaluate whether CT-like images provide measurement accuracy equivalent to conventional CT and MRI for pedicle screw planning and spinal canal area assessment. Methods: We retrospectively analyzed paired lumbar CT and MRI datasets obtained within ≤1 month in 51 patients. Pedicle width and length were measured on CT and CT-like images, whereas SCA was measured on T2 weighed-images and CT-like images. A total of 224 vertebrae were analyzed. Annotated images were independently evaluated by two readers in a randomized order. Inter-modality agreement was assessed using intraclass correlation coefficients (ICCs) and a Bland–Altman analysis. Results: CT-like images demonstrated an excellent agreement with CT for pedicle measurements (ICCs: 0.968–0.985 for width; 0.922–0.966 for length). Mean differences were ≤0.1 mm for pedicle width and approximately 1 mm for pedicle length, which are unlikely to affect screw selection. The agreement with T2WI for SCA was good to excellent (ICCs: 0.766–0.945). Conclusions: CT-like images provide comparable performance for quantitative pedicle assessment and show high agreement for SCA evaluation, supporting comprehensive preoperative assessment with a single MRI examination. Full article

Soft-tissue sarcomas (STSs) comprise a rare, heterogeneous group of mesenchymal malignancies in which histologic grade remains the strongest determinant of outcome, metastatic risk, and therapeutic strategy. Intermediate/high-grade STSs exhibit a pronounced propensity for early distant relapse, yet growing evidence indicates that metastatic behaviour is not uniform. Within this spectrum, an oligometastatic phenotype, characterised by a limited number of metastases, often confined to the lung, has emerged as a clinically and biologically distinct state associated with more indolent metastatic kinetics and improved survival when treated with aggressive local interventions. However, the criteria that define true oligometastatic STSs remain unsettled, and prospective evidence is lacking. Emerging molecular and immunological correlates provide a potential framework for biological triage. Low genomic complexity (low-risk CINSARC), a B-cell/TLS-rich tumour microenvironment, high immune-cytotoxic signatures, and persistently low or undetectable circulating tumour DNA (ctDNA) are each linked to reduced metastatic competence and may underpin oligometastatic trajectories. Conversely, high chromosomal instability, immunosuppressive microenvironments, and elevated ctDNA levels align with covertly polymetastatic biology despite limited radiographic disease. In this context, artificial intelligence and machinelearning approaches applied to computational genomics, immune profiling, imaging, and liquid-biopsy data offer a powerful strategy to integrate these multi-dimensional features and refine predictions of metastatic behaviour in STS. Oligometastatic STS therefore represents a biologically definable subset amenable to multimodal management integrating local ablative therapies, systemic agents, and immune-based strategies. Prospective, biomarker-stratified trials are needed to validate selection frameworks and optimise treatment sequencing in this evolving therapeutic space. Full article

Background/Objectives: Virtual surgical planning (VSP) and CAD/CAM technologies have revolutionized complex maxillofacial reconstruction. While high-resolution imaging is critical for these workflows, the specific clinical impact of photon-counting computed tomography (PCCT) remains to be fully established. This prospective pilot study evaluates the feasibility and clinical utility of integrating PCCT into the preoperative planning and surgical workflow of complex maxillofacial reconstructive cases. Methods: This feasibility study included ten patients requiring complex maxillofacial reconstruction with microvascular free flaps. All underwent preoperative imaging with photon-counting CT. Primary endpoints included clinical assessment of osseous invasion, reliability of donor-site vascular mapping from a single acquisition, and compatibility of PCCT datasets with VSP/CAD-CAM platforms. Secondary endpoints included resection margin status, flap survival, and short-term oncologic outcomes. Results: PCCT provided high-resolution visualization of cortical and medullary bone, enabling detailed assessment of tumor-related osseous involvement. In selected cases, findings supported refinement of resection planning when prior imaging had been inconclusive. Spectral reconstructions reduced metal artifacts and facilitated precise segmentation for multi-segment osteotomies. Donor-site vascular anatomy was successfully evaluated within the same scan, supporting operative planning without additional imaging. PCCT datasets were fully compatible with the virtual surgical planning (VSP) software used in this study (CMX Portal, version 2.6.1158, Medartis AG, Basel, Switzerland; or ProPlan CMF, version 5.7.8.025, Materialise NV, Leuven, Belgium) in all cases (100%). Reconstruction was completed successfully in all patients, with 100% flap survival and R0 margins in all malignant cases. No technical failures occurred during imaging transfer or CAD/CAM fabrication. Conclusions: The integration of PCCT into the surgical workflow proved technically feasible and clinically impactful. This pilot data supports its potential to enhance surgical precision and preoperative planning in complex jaw reconstruction. Full article

Background: The generation of synthetic CT images from MRI scans represents a crucial step toward enabling MRI-only clinical workflows and supporting multi-modal integration in medical imaging, particularly in radiotherapy planning. Despite significant advancements in deep learning models, many current methods still struggle to reconstruct high-density structures, especially bone, and exhibit limited accuracy in density values. This shortcoming is largely attributed to the passage of excessive or noisy features through skip connections in the traditional U-Net architecture, which degrade the quality of information transmitted to the decoder, negatively impacting the clarity of anatomical boundaries and the pixel-wise accuracy of the resulting synthetic image. Methods: In this work, we propose an enhanced 3D U-Net architecture in which the Convolutional Block Attention Module (CBAM) is systematically integrated within each skip connection. The CBAM sequentially applies channel and spatial attention to adaptively reweight encoder feature maps before fusion with the decoder, thereby emphasizing anatomically relevant structures while suppressing irrelevant feature propagation. The model was trained and evaluated on the SynthRAD2023 (Task 1—Brain) MRI–CT dataset. To rigorously assess the contribution of the attention mechanism, a dedicated ablation study was conducted comparing three variants: 3D U-Net with Squeeze-and-Excitation (SE), Coordinate Attention (CA), and the proposed CBAM module. Performance was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Normalized Cross-Correlation (NCC). Results: The ablation study demonstrated that the CBAM-enhanced model consistently outperformed both SE- and CA-based variants across all quantitative metrics. Specifically, the proposed method achieved an MAE of $38.2\pm 5.4$ HU and an RMSE of $51.0\pm 12.0$ HU, representing the lowest reconstruction errors among the evaluated models. In addition, it obtained a PSNR of $29.45\pm 2.10$ dB, SSIM of $0.940\pm 0.031$, and NCC of $0.967\pm 0.015$, indicating superior structural preservation and strong voxel-wise correspondence between synthesized and reference CT volumes. These results confirm that the sequential integration of channel and spatial attention provides a statistically and practically meaningful improvement for high-fidelity MRI-to-CT synthesis. Discussion and Conclusions: Generating high-resolution brain CT images from brain MRI scans using a 3D U-Net network enhanced with a CBAM module can contribute to supporting the clinical workflow by providing additional diagnostic data without the need for extra radiological examinations, thereby enhancing diagnostic efficiency and reducing radiation exposure. This technique helps reduce patient exposure to radiation and improves accessibility in resource-limited settings. Furthermore, this method is valuable for retrospective studies, surgical planning, and image-guided therapy, where complete multi-modal data may not always be available. Full article

Objectives: The patient presented various neurological symptoms in her 50s, such as memory issues, insomnia, depression, and motor impairment. Diverse investigations were performed to identify the underlying causes on her neurological symptoms and understand her neuro- deteriorations. Methods: Clinical neurological and brain imaging analyses: CT, MRI and PET were performed on the patient. Blood was drawn for the whole-exome sequencing and functional studies with biomarker for amyloid-beta oligomers and SLC20A2 protein in plasma. Results: Brain imaging revealed calcifications in multiple regions, including the subcortical white matter, basal ganglia, thalami, and dentate nuclei. Genetic analysis revealed a c.1152_1153delCA, p.Asn384Lysfs*30 variant in SLC20A2 gene. The decreased SLC20A2 protein levels in plasma in comparison to healthy controls suggested a loss-of-function mechanism from the mutation. The patient had a positive AlzOn result, indicating an increased tendency for amyloid oligomerization and suggesting a potential indirect link between SLC20A2 and amyloid-beta pathways. Conclusions: A novel frameshift mutation, Asn384Lysfs*30, in the SLC20A2 gene was identified in a patient with Primary Brain Calcification (PBC). This mutation was located in a critical large loop region of the protein, where other similar mutations (e.g., Gly366fs89, Ser385Ilefs*70) were previously reported. These findings indicated that mutations in SLC20A2 caused the reduced protein expressions, potentially resulting PBC through haploinsufficiency. Full article

Pembrolizumab is a programmed cell death protein (PD-1) inhibitor, humanized antibody widely used in cancer immunotherapy. Choriocarcinoma is an aggressive type of gestational trophoblastic neoplasia. Its treatment is based on surgical removal of the tumorous tissue and systemic chemotherapy; however, in some chemoresistant cases, immunotherapy can also be a valid option. Here, we report the first successful programmed death inhibitor-based treatment of a patient diagnosed with stage IV, ultra-high-risk choriocarcinoma in Hungary. Full article

Background: Obstructive sleep apnea (OSA) is associated with increased cardiovascular morbidity; however, its relationship with subclinical coronary atherosclerosis detected incidentally on routine chest computed tomography (CT) remains incompletely defined. We aimed to evaluate the association between questionnaire-based OSA risk and moderate-to-severe coronary artery calcification (CAC) in patients without known cardiac disease undergoing non-contrast chest CT for non-cardiac indications. Methods: In this prospective cross-sectional study, 268 consecutive adults undergoing routine non-contrast chest CT were included. OSA risk was assessed using the Berlin Questionnaire (BQ) and a modified BQ (mBQ), excluding hypertension and obesity components. CAC was quantified using the Agatston method on non-gated CT images, and moderate-to-severe CAC was defined as a score > 100. Multivariable logistic regression models were adjusted for age, sex, smoking status, alcohol use, obesity, lung disease, diabetes mellitus and hypertension. Results: Moderate-to-severe CAC was substantially more prevalent among patients at high risk for OSA than among those at low risk (43.1% vs. 12.0%, p < 0.001). In unadjusted analyses, high-risk OSA was strongly associated with CAC > 100. After multivariable adjustment, BQ-defined high-risk OSA remained independently associated with moderate-to-severe CAC (adjusted odds ratio [OR] 2.74, 95% confidence interval [CI] 1.29–5.78, p = 0.008). Similar results were observed with the mBQ (adjusted OR 2.62, 95% CI 1.27–5.41, p = 0.009). Increased snoring intensity was also independently associated with CAC > 100 (adjusted OR 2.25, 95% CI 1.07–4.72, p = 0.032). Conclusions: Questionnaire-defined high-risk OSA is independently associated with moderate-to-severe incidental CAC detected on routine chest CT. These findings support the integration of sleep-related risk assessment into opportunistic cardiovascular imaging frameworks and highlight the potential role of thoracic CT in multidimensional cardiovascular risk stratification. Full article

“Beak larva” is a collective term for four fossil specimens from Kachin amber, which are holometabolan larvae with a forward-projecting beak. This arrangement is very unusual, and so far it has been unclear whether these specimens are larvae of beetles or of lacewings. We present here new details of the mouthparts of one of these larvae based on synchrotron radiation-based X-ray µ-CT (SRµCT) imaging. We can identify that the main part of the beak is formed by the labrum and the labium; the mandibles insert laterally into this beak. The beak has two distinct channels to which the mandibles seem to be connected. The maxillae are tightly connected to the labium and head capsule and have an endite each (unclear if lacinia, galea, or mala), also inserting into the beak. Overall, these details reveal a mouthpart arrangement incompatible with an interpretation as a lacewing. The arrangement is most similar to that in some beetle larvae, namely those of Elateroidea. It most closely resembles that of the larvae of the species-poor sister groups Cerophytidae and Jurasaidae. It seems likely that the beak larvae are closely related to Jurasaidae, possessing an intermediate morphology. The combined data allow us to reconstruct aspects of the entire group, including the beak larvae, Cerophytidae, and Jurasaidae, indicating that they undergo hypermetamorphosis. The latter is most expressed in Jurasaidae. Combined with the paedomorphic female, this group seems to have four rather distinct morphologies and ecologies: (1) early mobile larvae, (2) physogastric, strongly wormlike larvae, (3) “normal”-appearing adult males, and (4) females with another unique morphology. Full article

Lumbar oblique radiography plays a crucial role in diagnosing spinal disorders, particularly spondylolysis and spondylolisthesis. Achieving optimal projection angles remains challenging due to variability in positioning techniques and subjective quality assessment. This study presents a deep learning framework for automatic angle estimation in lumbar oblique X-ray images using a two-stage object detection approach. Training data consisted of synthetic X-ray images generated from CT datasets with known projection angles (20° to 60°), annotated with three classes: L2–L4 vertebral levels, vertebral bodies, and pedicles. Two detection models were compared: Model1, a three-class whole-image detector, and Model2, a single-class pedicle detector applied to vertebral body crops from Model1. The Vertebral–Pedicle Ratio (VPR) was used to estimate projection angle via separate linear regression for negative-angle (n-group) and positive-angle (p-group) projections. Five-fold cross-validation showed Model2 achieved higher detection performance (macro mean AP@0.5 = 0.913, mean DSC = 0.825) than Model1 (macro mean AP@0.5 = 0.762, mean DSC = 0.791). Pooled regression yielded R²_n = 0.832 and R²_p = 0.870. Angle estimation with Model2 achieved MAE = 5.42° (SD 1.08°), substantially lower than Model1 (MAE = 9.57°, SD 1.64°), while Model1 offered faster throughput (18.3 FPS vs. 2.9 FPS). Two-stage pedicle detection using VPR-based linear regression provides clinically acceptable angle estimation accuracy in lumbar oblique radiography. Automated angle verification enables real-time positioning feedback during imaging, post-imaging image quality documentation in PACS, and retrospective auditing of facility positioning protocols. These comprehensive implementations are expected to standardize lumbar oblique radiography. Full article

Mild traumatic brain injury (mTBI) in adults is extremely common worldwide, but only a small fraction of these patients harbor clinically significant intracranial injuries. Computed tomography (CT) of the head is the standard diagnostic tool to detect traumatic brain hemorrhages or lesions, yet indiscriminate CT scanning of all mTBI patients is inefficient, costly, and exposes patients to ionizing radiation. To optimize patient care, numerous clinical decision rules and guidelines have been developed internationally to identify which adult patients with mTBI should undergo head CT. This review provides a global perspective on the indications for head CT in adult mTBI, comparing key decision rules including the Canadian CT Head Rule, New Orleans Criteria, UK NICE Head Injury Guidelines, and others. Methods: We conducted a comprehensive analysis of major international guidelines and decision rules for head CT in adult mTBI, focusing on their inclusion criteria, risk factors, and diagnostic performance. Results: All the examined rules prioritize near-100% sensitivity for identifying patients who need neurosurgical intervention, but they differ greatly in specificity and recommended CT utilization rates. North American rules such as the New Orleans Criteria tend to favor higher sensitivity, scanning almost all patients with any symptom, whereas the Canadian CT Head Rule and certain European guidelines (NICE, Scandinavian) are more selective, significantly reducing CT usage while maintaining safety. Discussion: We discuss how these variations reflect different healthcare settings and risk tolerances, and we examine the implications for neurosurgical practice. We also highlight challenges in guideline implementation, the impact on global CT utilization, and emerging approaches (such as biomarker-assisted triage) that may further refine decision-making. In conclusion, appropriate use of clinical decision rules for head CT in mTBI can safely minimize unnecessary imaging, but local adaptation and clinician judgment remain crucial to ensure that no significant injuries are missed while avoiding over-scanning. Full article

Background and Objective: Despite advances in operative techniques and perioperative care, complications following coronary artery bypass grafting (CABG) remain an important cause of postoperative morbidity and organ dysfunction. This study aimed to evaluate the association between preoperative epicardial adipose tissue (EAT) thickness measured using computed tomography and postoperative morbidity and mortality in patients undergoing isolated CABG, and to explore whether EAT thickness may serve as a potential imaging-based risk marker for postoperative complications. Materials and Methods: The study was a retrospective single-center observational cohort study. Patients who underwent isolated coronary artery bypass grafting between 1 January 2019 and 2 January 2023, and had available preoperative computed tomography (CT) imaging were retrospectively reviewed. Epicardial adipose tissue thickness was measured on CT images at three predefined anatomical regions, yielding two parameters: total EAT thickness and right ventricular EAT thickness. Postoperative complications were evaluated using established definitions, with atrial fibrillation (AF) assessed according to European Society of Cardiology (ESC) criteria and acute kidney injury defined based on Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. Results: Patients who developed postoperative complications after coronary artery bypass grafting tended to have thicker epicardial adipose tissue. Increased total epicardial adipose tissue thickness was associated with postoperative paroxysmal atrial fibrillation, whereas greater right ventricular epicardial adipose tissue thickness was associated with postoperative acute kidney injury. Multivariable analysis confirmed that both total and right ventricular epicardial adipose tissue thickness were independently associated with postoperative complications (total EAT: OR 1.74, 95% CI 1.10–2.76; right ventricular EAT: OR 2.03, 95% CI 1.31–3.15). ROC analysis showed modest discrimination for postoperative atrial fibrillation (AUC 0.69) and acceptable discrimination for acute kidney injury (AUC 0.79). No association was observed between epicardial adipose tissue measurements and postoperative mortality. Conclusions: Increased preoperative epicardial adipose tissue thickness was associated with several early postoperative complications following coronary artery bypass grafting, including atrial fibrillation, acute kidney injury, and in-hospital infection. Preoperative epicardial adipose tissue thickness measured by computed tomography may represent a potentially useful imaging-based risk marker for early postoperative complications following isolated CABG, although confirmation in larger prospective studies is required. Full article

Background and Objective: Positive surgical margins (PSMs) remain a major challenge during radical prostatectomy, particularly in patients with high-risk prostate cancer (HR-PCa), where extracapsular extension, multifocal disease, and aggressive tumor biology substantially increase the likelihood of incomplete resection. In this setting, PSMs are strongly associated with early biochemical recurrence and frequently prompt adjuvant or salvage treatments, potentially exposing patients to overtreatment and added morbidity. Materials and Methods: To review and critically appraise established and emerging intraoperative technologies for surgical margin assessment during radical prostatectomy, with a specific focus on their potential role and relevance in patients with HR-PCa. Evidence Acquisition: A non-systematic literature review was performed using Pubmed, MEDLINE, Web of Science, and Google Scholar, focusing on preoperative, intraoperative ex vivo, and intraoperative in vivo technologies for margin assessment. Emphasis was placed on techniques with potential applicability to HR-PCa, where real-time intraoperative decision-making is particularly consequential. Evidence Synthesis: Preoperative tools, including multiparametric MRI, PSMA-PET imaging, and predictive nomograms, aid surgical planning but show limited sensitivity for microscopic extracapsular extension, especially in high-risk disease. Intraoperative frozen section analysis reduces positive surgical margin rates while enabling selective nerve-sparing (defined as a side-specific, risk-adapted preservation strategy); however, its widespread adoption is constrained by substantial logistical and resource requirements, and robust oncological outcome data in high-risk populations remain limited. Novel ex vivo approaches, such as fluorescence confocal microscopy and specimen-based PSMA PET/CT imaging, offer rapid whole-gland or targeted margin assessment with reduced dependency on dedicated pathology workflows. In parallel, emerging in vivo technologies, particularly PSMA-targeted near-infrared-fluorescence-guided surgery, enable real-time detection of residual tumor and facilitate selective re-resection, representing a biology-driven approach that may be especially suited to HR-PCa. Conclusions: In high-risk prostate cancer, intraoperative margin assessment technologies may extend beyond functional preservation and play a central role in optimizing oncological radicality and multimodal treatment sequencing. While NeuroSAFE remains the reference standard, PSMA-based ex vivo and in vivo technologies are particularly promising in HR-PCa due to their ability to integrate tumor biology into surgical decision-making. Prospective studies focusing on high-risk-specific oncological and patient-reported outcomes are needed before widespread clinical implementation. Full article