Objective To evaluated the application effect of reverse digital modeling combined with three-dimensional (3D)-printed disease models in the standardized training of orthopedic residents focusing on pelvic tumors. Methods From August 2022 to August 2023, 60 orthopedic residents from West China Hospital, Sichuan University were randomly assigned to a trial group (n=30) and a control group (n=30). The trial group received instruction using reverse digital modeling and 3D-printed pelvic tumor models, while the control group underwent traditional teaching methods. Teaching outcomes were evaluated and compared between groups through knowledge tests, practical skill assessments, and satisfaction surveys. Results Before training, there was no statistically significant difference in knowledge tests or practical skill assessments between the two groups (P>0.05). After training, the trial group showed significantly better performance than the control group in knowledge tests (90.5±5.2 vs. 78.4±6.8, P<0.05), skill assessments (92.7±4.9 vs. 81.3±6.2, P<0.05), and satisfaction surveys (9.40±1.10 vs. 7.60±1.20, P<0.05). One month after training, the trial group still showed significantly better performance than the control group in knowledge tests (88.1±6.4 vs. 72.3±7.1, P<0.05) and skill assessments (90.3±5.8 vs. 75.6±6.9, P<0.05). Conclusions Reverse digital modeling combined with 3D printing offers an intuitive and effective teaching approach that improves comprehension of pelvic tumor anatomy and strengthens clinical and technical competencies. This method significantly enhances learning outcomes in standardized residency training and holds promise for broader integration into medical education.
Integration of heterogeneous systems is the key to hospital information construction due to complexity of the healthcare environment. Currently, during the process of healthcare information system integration, people participating in integration project usually communicate by free-format document, which impairs the efficiency and adaptability of integration. A method utilizing business process model and notation (BPMN) to model integration requirement and automatically transforming it to executable integration configuration was proposed in this paper. Based on the method, a tool was developed to model integration requirement and transform it to integration configuration. In addition, an integration case in radiology scenario was used to verify the method.
The human skeletal muscle drives skeletal movement through contraction. Embedding its functional information into the human morphological framework and constructing a digital twin of skeletal muscle for simulating physical and physiological functions of skeletal muscle are of great significance for the study of "virtual physiological humans". Based on relevant literature both domestically and internationally, this paper firstly summarizes the technical framework for constructing skeletal muscle digital twins, and then provides a review from five aspects including skeletal muscle digital twins modeling technology, skeletal muscle data collection technology, simulation analysis technology, simulation platform and human medical image database. On this basis, it is pointed out that further research is needed in areas such as skeletal muscle model generalization, accuracy improvement, and model coupling. The methods and means of constructing skeletal muscle digital twins summarized in the paper are expected to provide reference for researchers in this field, and the development direction pointed out can serve as the next focus of research.
Population pharmacokinetics is a research technique based on computer simulation and data analysis, and it has been employed to investigate the dynamic behavior of drug metabolism in different populations. This approach could address practical challenges such as prolonged clinical trial durations, high costs, and increased difficulty in traditional clinical trials. By comprehensively analyzing differences in the internal drug metabolism processes across populations with varying physiological and pathological conditions, population pharmacokinetics has emerged as an effective method to optimize drug development and clinical applications. This article provides a preliminary overview of the essence of population pharmacokinetics, its application in clinical trials, and potential future trends. We hope to serve as a reference and guidance for the application of new technologies and methods in clinical trials.
Virtual clinical trials are clinical trials conducted through computer simulation technology, which breaks through the limitations of traditional clinical trials and has the advantages of saving time, reducing costs, and reducing the risk of human trials. With the application of new computer technologies such as population pharmacokinetics, physiologically-based pharmacokinetics, quantitative systems pharmacology, and artificial intelligence, the field of virtual clinical trials in healthcare has become an important development direction. This article will give a preliminary review of the connotation, methods and future development trends of virtual clinical trials, aiming to provide reference for the application of new technologies and methods in clinical trials.
Objective To investigate effectiveness of applying the Bone Morphingbased image-free computer-assisted system for the ligament balancing managementin the total knee arthroplasty (TKA). Methods Between November 2002 and June 2003, twenty-one posterior stabilized total knee prostheses (Ceraver, France) were implanted in 21 patients using the Bone Morphing based image-free Ceravision system.This cohort included 5 men and 16 women with an average age of 72.4 years, two undergoing high tibial osteotomy and 1 undergoing distal femoral osteotomy before. The preoperative deviation was measured by the full-length AP X-rays. The knees were in varus deviation in 14 patients and in valgus deviation in 7 patients, with an average of 2.36°(varus 13°-valgus 13°). The frontal X-rays ofthe knee were assessed, the mean value of the varus force-stress test was 8.47°(varus 2°-varus 20°), and the mean value of the valgus forcestress test was 3.63°(varus 7°-valgus 12°). Results With the Ceravisionrecorded data, the intraoperative alignment was assessed, the mean lower limb axis was 3.33°(varus 12°-valgus 10°),and compared with the preoperative data, the difference was significant (Plt;0.05); the mean value of the varus force-stress test was 6.47°(varus 0°-varus 24°), the mean value of the valgus force-stress test was 4.32°(varus 8°- valgus 15°), and compared with the preoperative data, the difference was significant (Plt;0.05). The post-prosthetic alignment on Ceravision with a deviation of 0.175°(varus 2°- valgus 3°) was compared with the postoperative alignment by the full-length AP X-rays, with a deviation of 0.3°(varus 3.5°-valgus 1.5°), the difference wasn’t significant(Pgt;0.05).The clinical check-up performed 3 months after operation showed that the average range of movement (ROM) was 115°(105-130°), the mean frontal laxity was 0.27 mm(0.2-0.5 mm). The femoral and tibial components were implanted in the satisfactory 3 dimensional position without ligament imbalance in all the patients, andthere were no instability or patella complications.Conclusion Utilization of the Bone Morphing based image-free computer-assisted system can achieve an accurate component 3 dimensional alignment, optimal bone resection, optimal control of surgical decision in releasing the soft tissues, rotating the femoral component to gain an extension/flexion rectangular gap, and managing theligament balancing so as to achieve a satisfactory initial clinical outcome. This system can be routinely used in the TKA.
In order to quantitatively analyze the morphology and period of pulse signals, a time-space analytical modeling and quantitative analysis method for pulse signals were proposed. Firstly, according to the production mechanism of the pulse signal, the pulse space-time analytical model was built after integrating the period and baseline of pulse signal into the analytical model, and the model mathematical expression and its 12 parameters were obtained for pulse wave quantification. Then, the model parameters estimation process based on the actual pulse signal was presented, and the optimization method, constraints and boundary conditions in parameter estimation were given. The spatial-temporal analytical modeling method was applied to the pulse waves of healthy subjects from the international standard physiological signal sub-database Fantasia of the PhysioNet in open-source, and we derived some changes in heartbeat rhythm and hemodynamic generated by aging and gender difference from the analytical models. The model parameters were employed as the input of some machine learning methods, e.g. random forest and probabilistic neural network, to classify the pulse waves by age and gender, and the results showed that random forest has the best classification performance with Kappa coefficients over 98%. Therefore, the space-time analytical modeling method proposed in this study can effectively quantify and analyze the pulse signal, which provides a theoretical basis and technical framework for some related applications based on pulse signals.
ObjectiveSystemic lupus erythematosus (SLE) patients from a SLE family with homogeneity can provide experimental basis for individualized diagnosis and treatment by studying the characteristics of laboratory tests and symptoms. MethodsLaboratory tests were analyzed for three SLE patients in the family, and set up the screen model by three laboratory tests (anitnuclear antibody positive, rheumatoid factor positive and IgE positive, ANA+RF+IgE+). All SLE cases were screened from latest four years as SLE subtype patients (named "similar family SLE patients"), then the family laboratory tests and clinical characteristics were analyzed. ResultsA total of 55 patients (6.27%) were screened as similar family SLE patients from individual SLE patients according to model from 877 cases. The laboratory tests of similar family SLE patients including creatinine, WBC, CRP were significant lower than other SLE patients (P < 0.05), but significant higher for the IgG, positive rate of anti-SSA and anti-SSB (P < 0.05), and the alopecia and skin rashes were more common in similar family SLE patients than other SLE patients. ConclusionsThe ANA+RF+IgE+ SLE patients are of lower inflammatory state and kidney involvement; Clinical symptom is priority to alopecia and skin rashes.
The geometric bone model of patients is an important basis for individualized biomechanical modeling and analysis, formulation of surgical planning, design of surgical guide plate, and customization of artificial joint. In this study, a rapid three-dimensional (3D) reconstruction method based on statistical shape model was proposed for femur. Combined with the patient plain X-ray film data, rapid 3D modeling of individualized patient femur geometry was realized. The average error of 3D reconstruction was 1.597–1.842 mm, and the root mean square error was 1.453–2.341 mm. The average errors of femoral head diameter, cervical shaft angle, offset distance and anteversion angle of the reconstructed model were 0.597 mm, 1.163°, 1.389 mm and 1.354°, respectively. Compared with traditional modeling methods, the new method could achieve rapid 3D reconstruction of femur more accurately in a shorter time. This paper provides a new technology for rapid 3D modeling of bone geometry, which is helpful to promote rapid biomechanical analysis for patients, and provides a new idea for the selection of orthopedic implants and the rapid research and development of customized implants.
Magnetic resonance imaging (MRI)-based electroencephalography (EEG) forward modeling method has become prevalent in the field of EEG. However, due to the inability to obtain clear images of an infant’s fontanel through MRI, the fontanelle information is often lacking in the EEG forward model, which affects accuracy of modeling in infants. To address this issue, we propose a novel method to achieve fontanel compensation for infant EEG forward modeling method. First, we employed imaging segmentation and meshing to the head MRIs, creating a fontanel-free model. Second, a projection-based surface reconstruction method was proposed, which utilized priori information on fontanel morphology and the fontanel-free head model to reconstruct the two-dimensional measured fontanel into a three-dimensional fontanel model to achieve fontanel-compensation modeling. Finally, we calculated a fontanel compensation-based EEG forward model for infants based on this model. Simulation results, based on a real head model, demonstrated that the compensation of fontanel had a potential to improve EEG forward modeling accuracy, particularly for the sources beneath the fontanel (relative difference measure larger than 0.05). Additional experimental results revealed that the uncertainty of the infant’s skull conductivity had the widest impact range on the neural sources, and the absence of fontanel had the strongest impact on the neural sources below the fontanel. Overall, the proposed fontanel-compensated method showcases the potential to improve the modeling accuracy of EEG forward problem without relying on computed tomography (CT) acquisition, which is more in line with the requirements of practical application scenarios.