Objective. Generalisation of synthetic CT (sCT) generation to diagnostic MRI data in the spine faces many challenges, particularly when aiming at accurate visualisation of pathologies for orthopaedic treatment management. In this study we assessed the effect of potential confounding factors on the performance of sCT generation from diagnostic MR images.Approach. Paired spinal diagnostic MR and CT scans from two centres (51 patients) were collected retrospectively, spanning multiple spinal pathologies and regions. Each patient's dataset contained 3D T1-/T2-weighted and 2D T1- and T2-weighted scans. 3D U-Nets were trained per centre on the 3D MR data and CT using a mean absolute error (MAE) loss. The performance was assessed on sCTs derived from original 2D and 3D data and from simulated 2D data with varying orientation (axial/coronal/sagittal) and slice spacing (1.1-6.6 mm). The sCTs were compared to the CTs using MAE, peak signal-to-noise ratio, and dice similarity coefficient.Main results. We identified MR resolution, orientation and contrast as confounding factors for sCT generation from diagnostic MR. Additionally, CT noise and CT-to-MR registration were identified to influence the performance evaluation. Performance degraded with larger slice spacings and significant differences between orientations occurred more often at larger slice spacings. The effect of slice spacing and orientation was stronger inside the vertebrae than outside. While the networks performed better overall on contrasts more similar to the training contrasts, they demonstrated promising performance when trained on 3D T2w images and tested on 2D T1w images. Finally, higher CT noise levels resulted in worse sCT performance metrics, reflected in a significant correlation between noise and MAE.Significance. This work demonstrates that generalisation of sCT generation to diagnostic spine MRI data is hampered primarily by MRI acquisition related aspects including MR resolution, orientation and contrast, which provides guidance for future work on generalisable sCT from diagnostic MR.

3D cerebral angiographic imaging offers superior spatial resolution and flexible acquisition compared with CTA, enabling selective injections and dynamic phase selection1-4. Its application in gamma knife radiosurgery has been increasingly recognized, particularly for arteriovenous shunts, where precise visualization of angioarchitecture is essential.5-12 We describe strategies for incorporating 3D rotational angiography and conebeam CT into treatment planning, highlighting their respective strengths and limitations.7,8,12,13-16 Imaging can be performed either before or after frame fixation, each approach carrying unique advantages and constraints.19,20 Postprocessing-targeted reconstruction, MIP/MPR, subtraction imaging, and metal-artifact reduction-further refines visualization, highlighting the complementary value of each technique.17,18 These tools enhance confidence in nidus delineation and planning accuracy. Collaboration with endovascular specialists is critical for optimal acquisition and data sharing. This video presents technical considerations and practical tips to optimize the clinical use of 3D angiographic imaging in gamma knife radiosurgery for arteriovenous shunt management.

Biomechanics of the tooth cervical region investigated using 3D digital image correlation, micro CT, and finite element analysis.

Spatial characteristics of metacarpal fractures: A quantitative 3D CT study of fall-related versus nonfall-related injuries.

The incidence of acetabular fractures has increased, and classification according to Judet and Letournel remains challenging. While 3D CT improves accuracy, virtual reality (VR) may enhance training. This study assessed whether aVR simulator improves classification accuracy and understanding in inexperienced users. An HTC VIVE Pro headset and an Alienware m15 R4 computer were utilized. Programming was done in Unity (2021.3.4f1 LTS), and segmentation in Slicer3D. In total, 83ninth-semester medical students, divided into aVR group (n = 44) and a3D control group (n = 39), took part. Participants had to classify 11acetabular fractures, supported by pictograms if needed, followed by auser survey. Accuracy was compared. All participants completed the study. Overall, 68% had no prior knowledge of the classification. The control group achieved amedian of 27% (interquartile range [IQR]: 14-36%) correct classifications, while the VR group reached 45% (IQR: 36-64%), showing higher accuracy (p < 0.001). In general, essential fractures were classified significantly more accurately than associated fractures (p < 0.001). The VR system was rated as more intuitive than the 3D software (p = 0.025). The VR simulator significantly improved acetabular fracture classification among inexperienced users. It is intuitive, easy to use, and offers strong potential for future surgical training.

Multi-head Self-Attention and Window-Attention Transformer Model for Multi-label Abdominal Trauma Classification Using 3D CT Scans

ABSTRACT T‐spherical fuzzy sets (TSFSs) provide a robust and flexible framework for modeling uncertainty by aggregating membership, nonmembership, and neutrality degrees using t‐norms. This study introduces a new family of set‐theoretic weighted similarity and distance measures specifically designed for TSFSs, which should pique curiosity about their innovative approach. This study demonstrates that numerous traditional measurements fail to satisfy fundamental axiomatic properties. Conversely, our suggested measurements demonstrate unwavering reliability and efficacy over a wide range of scenarios. To validate the practical utility of these measures, we integrate them into a deep learning classification framework. Finally, we apply the proposed similarity measurement to deep learning classification of 3D CT scans. It can improve classification accuracy by effectively handling uncertain features in medical imaging data.

BackgroundSuprascapular nerve entrapment is a medical condition characterized by clinical symptoms such as neck and shoulder pain, discomfort, upper limb weakness, and heaviness. These symptoms are caused by the compression of the suprascapular nerve at the suprascapular notch. The treatment of this nerve entrapment has been a long-standing challenge. Intelligent-assisted radiofrequency neurolysis is a novel and promising non-pharmacological treatment. Herein, we presented the therapeutic efficacy of this technique in 40 patients.ObjectiveThis study was designed to evaluate the feasibility of three-dimensional (3D) CT imaging integrated with intraoperative intelligence-assisted calibration for radiofrequency ablation of the suprascapular nerve.MethodsA total of 40 patients were enrolled. The control group received the conventional surgery, while the treatment group was given 3D CT imaging plus the intraoperative intelligence-assisted calibration. Intelligence-assisted refers to the use of a smartphone app based on gravity calibration to realize the precise measurement and correction of the puncture needle angle during the operation, combined with 3D CT imaging to achieve the accurate positioning of the suprascapular nerve entrapment site. Data was analyzed on the two groups, including the time taken from starting positioning to successful puncture, Visual Analogue Scale (VAS) scores and ROWE scores before and after treatment, the therapeutic effect, complications, and number of cases with abnormal electromyography (EMG) items before and after treatment.ResultsTime of puncture completion in the treatment group was significantly shorter than that in the control group (8.06 vs 15.98 min, p < 0.05). Postoperative therapeutic effect in the treatment group was also superior to that in the control group. The treatment group had significant differences between pre- and post-treatment VAS scores and had superior ROWE scores compared to the control group.ConclusionThe application of 3D CT imaging combined with intraoperative intelligence-assisted calibration for suprascapular nerve radiofrequency ablation can effectively shorten the operation time, improve the procedural efficiency and therapeutic effect and significantly reduce patients’ clinical symptoms.

To evaluate the accuracy of arthroscopic glenoid bone loss (GBL) assessment and its influencing factors, and to compare the consistency of three-dimensional computed tomography (3D CT) and 3D printed measurements. 3D printed models were created from the 3D CT images. Experts reviewed arthroscopic images to assess GBL, and a questionnaire was used to correlate assessment accuracy with surgeon age, experience, and annual surgical volume. Separately, ten residents measured each model three times using three methods: the linear method and best-fit circle method on 3D CT, and a manual method with vernier calipers on the physical models. Agreement was calculated using intra-group correlation coefficients (ICC). A statistically significant difference in assessment accuracy was found among surgeons with different annual surgical volumes (p = 0.029). Comparisons between the three measurement methods showed that the best-fit circle method yielded significantly higher values than both the linear and manual methods (p < 0.001). The manual method demonstrated the highest consistency across different times and observers (ICC 0.998 and 0.995, respectively), suggesting it is the most stable technique. The accuracy of arthroscopic GBL judgment varies with the surgeon’s annual surgical volume. While all three measurement methods show excellent agreement, the best-fit circle method provides significantly larger GBL measurements compared to the linear and manual methods. Level II, Cross-Sectional Study.

The optimal treatment for cerebral vasospasm (CV) following traumatic brain injury (TBI) has not been established, and management generally follows strategies developed for aneurysmal subarachnoid hemorrhage. The authors report a case of a patient with traumatic subarachnoid hemorrhage and cerebral contusion who presented with worsening consciousness and disorientation and subsequently developed symptomatic CV on day 6 of hospitalization. MRI and 3D CT demonstrated narrowing of the left internal carotid artery and middle cerebral artery (MCA) with reduced cerebral perfusion. Intra-arterial administration of fasudil hydrochloride yielded a temporary improvement. However, MCA stenosis recurred the next day, requiring percutaneous transluminal balloon angioplasty. Subsequent imaging showed improved cerebral perfusion, and the patient was discharged without delayed cerebral ischemia. Fluctuations in consciousness or neuropsychological symptoms after TBI should prompt evaluation for CV using perfusion imaging, even in the absence of focal neurological deficits. When a high risk of severe vasospasm accompanied by perfusion reduction is identified, prompt, stepwise therapeutic intervention should be implemented, beginning with the least invasive treatment option to optimize clinical outcomes. https://thejns.org/doi/abs/10.3171/CASE25943.

This study presents a deep convolutional neural network (DeepCNN) based framework for the automatic estimation of porosity in concrete materials from two-dimensional computed tomography (2D CT) scan images. Addressing the limitations of manual and time-consuming traditional porosity measurement methods, the proposed approach integrates advanced image processing techniques to improve robustness under low resolution and noisy imaging conditions. The DeepCNN architecture comprises a multi stage feature extractor with 21 convolutional layers and an SPP based neck, trained on 20,520 annotated CT images after data augmentation. Preprocessing steps include automated region of interest detection, intensity normalization, and class specific filtering prior to porosity estimation. The framework performs material classification and porosity estimation across multiple concrete classes, including cement-based mortars (CM0, CM5, CM10, CM20), geopolymer based mortar (GM), and ultra-high performance concrete (UHPC), using a rule based adaptive thresholding (RBAT) strategy incorporating clustering, filtering, and thresholding operations. Porosity is quantified by computing the ratio of pore area to the total image area. Across all material classes, the estimated porosity values showed close agreement with vacuum pycnometer measurements, with deviations within 2-3%, including deviations of 1.5% for UHPC and 1.3% for CM10. The DeepCNN classifier achieved a precision recall AUC of 1.0 during testing. These results demonstrate that the proposed hybrid framework provides an accurate, automated, and computationally efficient solution for porosity assessment, suitable for practical and industrial CT based material characterization workflows.

For orthopedic diagnostics, both 2D X-ray and 3D CT imaging play essential roles. X-ray imaging is widely accessible, clinically effective, easy to operate, and has lower radiation exposure than CT. However, its inherent 2D nature limits comprehensive visualization of skeletal structures, which 3D CT provides. To bridge this gap, we propose SkeDiff, an algorithm for reconstructing 3D CT images of the skeleton from orthogonal 2D X-ray projections. To fully leverage the information in X-ray images for guiding the diffusion process, we design a cross-dimensional conditional encoder, $E\_{Cond}$, to extract 2D priors for the 3D diffusion model, $DM\_{3DL}$. This encoder integrates a CNN-Mamba hybrid architecture to enhance feature extraction and nonlinear mapping. Additionally, we introduce a 3D UKAN diffusion backbone, which employs Kolmogorov-Arnold network (KAN) to improve feature representation through learnable nonlinear activations. Furthermore, we propose a diffusion-based scoliosis classifier, $D\_{SC}$, enabling scoliosis classification during the 3D CT reconstruction process. Experiments show that SkeDiff outperforms recent algorithms on spine, hip, and knee datasets.

The production of thin-walled products from thermoplastics by rotational molding (RM) has increasingly turned into polymer composites. Rotational molding (RM) is a technology that enables the manufacturing of ready-to-use products using a single-step processing method. The development of measurement technology leads to a deeper understanding of the process control-to-structure relationship. This study aims to correlate the process analysis based on the internal mold air temperature (IAT) with the structural, thermal, and mechanical properties of high-density polyethylene (HDPE) composites reinforced with two inorganic particle-shaped fillers, basalt powder (BP) and talc (T). Differential scanning calorimetry (DSC) confirmed the nucleating effect of the fillers, especially T, on the HDPE matrix, which correlates with the changes in the course of the IAT curves. Despite introducing fillers with small particle size (<100 μm), the obtained porosity of the products determined by 3D computed tomography (3D CT) was maximally 0.33%. The low porosity of RM products allowed the suppression of excessive, unfavorable effects of limiting mechanical performance (minimum tensile strength of 19.4 MPa). The composites showed up to 1450 MPa (BP) and 1300 (T) MPa young modulus compared to 1150 MPa (HDPE), respectively. The obtained research results confirm the validity of introducing particle-shaped inorganic fillers not only as modifiers of physical and mechanical properties, but also of processing properties. The study supplements the current state of knowledge with information on the manufacturing of composites using specific technology RM, which utilizes low-cost inorganic fillers with high potential for industrial implementation.

Study on seepage characteristics of concrete cracks based on CT 3D reconstruction and fractal theory

Magnetic resonance imaging (MRI) was used to evaluate paraspinal muscle damage after classic open surgery (OPEN) and minimally invasive spine surgery (MISS) after injury. In a randomised prospective study, we evaluated our hypothesis that MISS would result in a lower extent of atrophy and fibrosis as detected by MRI. MRI was performed after the injury and not earlier than 3 months after the removal of implants. 16 OPEN and 16 MISS patients underwent the final follow-up. Both atrophy and muscle fibrosis were assessed based on the progression of the condition after the surgery from the pre-operative state. Atrophy was assessed using T2-weighted axial scans based on the progression of fat tissue growth in the muscle and muscle tissue regression, while muscle fibrosis was assessed using T1-weighted scans before and after the administration of a contrast agent. Mean fibrotic changes were found to be higher in the OPEN group than in the MISS group, but insignificantly (p = 0.1100). Muscular atrophy was higher in the MISS group (p = 0.2099). Occurrence of fibrosis correlated positively with muscular atrophy only in the MISS group (R = 0.617 (0.174-0.852), p = 0.0094). Minimally invasive percutaneous methods of spinal stabilization and other types of less invasive spinal surgeries are more gentle to the paraspinal muscles than standard OPEN approaches. Their importance is clear despite certain disadvantages such as longer duration of surgery and higher radiation exposure (in case of insertion without robotic assistance or 3D CT guidance). The condition of the paraspinal muscles is more suitable for the follow-up physiotherapy, enabling easier and quicker recovery. In the long term, the muscles are more capable of maintaining spinal balance and allowing for a wider range of movement, despite in this study is a mild controversy in the higher percentage of muscle atrophy in MISS procedures. MISS procedures are more gentle to the paraspinal muscles than OPEN procedures. The condition of muscles is better for physiotherapy, enabling easier and quicker recovery.

DVAP-Reg: Dual-view anatomical prior-driven cross-dimensional registration for spinal surgery navigation.

Distribution and evolution mechanisms of deep sandstone pore-fracture system by using 3D CT reconstruction

Application value of a novel tappable bone grafting tool with variable angle lateral window in short-segment fixation via intermuscular approach for thoracolumbar fractures.

Robotic systems are transforming image-guided interventions by enhancing accuracy and minimizing radiation exposure. A significant challenge in robotic assistance lies in surgical path planning, which often relies on the registration of intraoperative 2D images with preoperative 3D CT scans. This requirement can be burdensome and costly, particularly in procedures like vertebroplasty, where preoperative CT scans are not routinely performed. To address this issue, we introduce a differentiable rendering-based framework for 3D transpedicular path planning utilizing bi-planar 2D X-rays. Our method integrates differentiable rendering with a vertebral atlas generated through a Statistical Shape Model (SSM) and employs a learned similarity loss to refine the SSM shape and pose dynamically, independent of fixed imaging geometries. We evaluated our framework in two stages: first, through vertebral reconstruction from orthogonal X-rays for benchmarking, and second, via clinician-in-the-loop path planning using arbitrary-view X-rays. Our results indicate that our method outperformed a normalized cross-correlation baseline in reconstruction metrics (DICE: 0.75 vs. 0.65) and achieved comparable performance to the state-of-the-art model ReVerteR (DICE: 0.77), while maintaining generalization to arbitrary views. Success rates for bipedicular planning reached 82% with synthetic data and 75% with cadaver data, exceeding the 66% and 31% rates of a 2D-to-3D baseline, respectively. In conclusion, our framework demonstrates the feasibility of versatile, CT-free 3D path planning for robot-assisted vertebroplasty, accommodating diverse intraoperative imaging conditions without requiring preoperative CT scans.

Introduction: Gnatoschizis (alveolar cleft), is a developmental defect of the maxillary alveolar bone, occurring in up to 75% of patients with cleft lip and palate. This condition may impair mastication and cause persistent oronasal fistulas if it is left untreated. Gnatoplasty with bone grafting is a reliable procedure to restore alveolar continuity and oral function. This report describes the management of bilateral gnatoschizis with bilateral gnatoplasty and bone graft reconstruction. Case Report: A 25-year-old female presented with nasal fluid leakage during meals. Two small openings were foung in the upper labial mucosa, forming oronasal communications. OPG and 3D CT scan confirmed anterior maxillary defects directly communicating with the nasal cavity. The patient treated by bilateral gnatoplasty under general anesthesia. Closure of nasal and oral mucosa were performed to seal the fistulas. Bone grafting followed without membrane coverage using AmGraft® (freeze-dried dentin matrix, allograft) and Bonefill Ortho® (bovine hydroxyapatite, xenograft). Postoperative CBCT demonstrated well-positioned grafts completely filling the defects and patient reported no nasal leakage and regained normal mastication. Discussion: This case highlights the effectiveness of gnatoplasty with bone grafting performed without membranes. This approach simplifies the procedure while still achieving both anatomical repair and functional rehabilitation. Conclusion: Bilateral gnatoplasty with bone graft reconstruction is effective for closing oronasal communication and restoring oral function, without using membranes, making this approach practical for patients with residual cleft defects.