International Journal of Computer Assisted Radiology and Surgery最新文献

{"title":"Synchronising a stereoscopic surgical video stream using specular reflection.","authors":"Kilian Chandelon, Adrien Bartoli","doi":"10.1007/s11548-024-03232-w","DOIUrl":"10.1007/s11548-024-03232-w","url":null,"abstract":"<p><strong>Purpose: </strong>A stereoscopic surgical video stream consists of left-right image pairs provided by a stereo endoscope. While the surgical display shows these image pairs synchronised, most capture cards cause de-synchronisation. This means that the paired left and right images may not correspond once used in downstream tasks such as stereo depth computation. The stereo synchronisation problem is to recover the corresponding left-right images. This is particularly challenging in the surgical setting, owing to the moist tissues, rapid camera motion, quasi-staticity and real-time processing requirement. Existing methods exploit image cues from the diffuse reflection component and are defeated by the above challenges.</p><p><strong>Methods: </strong>We propose to exploit the specular reflection. Specifically, we propose a powerful left-right comparison score (LRCS) using the specular highlights commonly occurring on moist tissues. We detect the highlights using a neural network, characterise them with invariant descriptors, match them, and use the number of matches to form the proposed LRCS. We perform evaluation against 147 existing LRCS in 44 challenging robotic partial nephrectomy and robotic-assisted hepatic resection video sequences with simulated and real de-synchronisation.</p><p><strong>Results: </strong>The proposed LRCS outperforms, with an average and maximum offsets of 0.055 and 1 frames and 94.1±3.6% successfully synchronised frames. In contrast, the best existing LRCS achieves an average and maximum offsets of 0.3 and 3 frames and 81.2±6.4% successfully synchronised frames.</p><p><strong>Conclusion: </strong>The use of specular reflection brings a tremendous boost to the real-time surgical stereo synchronisation problem.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"289-299"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141762451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging domain knowledge for synthetic ultrasound image generation: a novel approach to rare disease AI detection.","authors":"M Mendez, F Castillo, L Probyn, S Kras, P N Tyrrell","doi":"10.1007/s11548-024-03309-6","DOIUrl":"10.1007/s11548-024-03309-6","url":null,"abstract":"<p><strong>Purpose: </strong>This study explores the use of deep generative models to create synthetic ultrasound images for the detection of hemarthrosis in hemophilia patients. Addressing the challenge of sparse datasets in rare disease diagnostics, the study aims to enhance AI model robustness and accuracy through the integration of domain knowledge into the synthetic image generation process.</p><p><strong>Methods: </strong>The study employed two ultrasound datasets: a base dataset (Db) of knee recess distension images from non-hemophiliac patients and a target dataset (Dt) of hemarthrosis images from hemophiliac patients. The synthetic generation framework included a content generator (Gc) trained on Db and a context generator (Gs) to adapt these images to match Dt's context. This approach generated a synthetic target dataset (Ds), primed for AI training in rare disease research. The assessment of synthetic image generation involved expert evaluations, statistical analysis, and the use of domain-invariant perceptual distance and Fréchet inception distance for quality measurement.</p><p><strong>Results: </strong>Expert evaluation revealed that images produced by our synthetic generation framework were comparable to real ones, with no significant difference in overall quality or anatomical accuracy. Additionally, the use of synthetic data in training convolutional neural networks demonstrated robustness in detecting hemarthrosis, especially with limited sample sizes.</p><p><strong>Conclusion: </strong>This study presents a novel approach for generating synthetic ultrasound images for rare disease detection, such as hemarthrosis in hemophiliac knees. By leveraging deep generative models and integrating domain knowledge, the proposed framework successfully addresses the limitations of sparse datasets and enhances AI model training and robustness. The synthetic images produced are of high quality and contribute significantly to AI-driven diagnostics in rare diseases, highlighting the potential of synthetic data in medical imaging.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"415-431"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142911124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unsupervised stain augmentation enhanced glomerular instance segmentation on pathology images.","authors":"Fan Yang, Qiming He, Yanxia Wang, Siqi Zeng, Yingming Xu, Jing Ye, Yonghong He, Tian Guan, Zhe Wang, Jing Li","doi":"10.1007/s11548-024-03154-7","DOIUrl":"10.1007/s11548-024-03154-7","url":null,"abstract":"<p><strong>Purpose: </strong>In pathology images, different stains highlight different glomerular structures, so a supervised deep learning-based glomerular instance segmentation model trained on individual stains performs poorly on other stains. However, it is difficult to obtain a training set with multiple stains because the labeling of pathology images is very time-consuming and tedious. Therefore, in this paper, we proposed an unsupervised stain augmentation-based method for segmentation of glomerular instances.</p><p><strong>Methods: </strong>In this study, we successfully realized the conversion between different staining methods such as PAS, MT and PASM by contrastive unpaired translation (CUT), thus improving the staining diversity of the training set. Moreover, we replaced the backbone of mask R-CNN with swin transformer to further improve the efficiency of feature extraction and thus achieve better performance in instance segmentation task.</p><p><strong>Results: </strong>To validate the method presented in this paper, we constructed a dataset from 216 WSIs of the three stains in this study. After conducting in-depth experiments, we verified that the instance segmentation method based on stain augmentation outperforms existing methods across all metrics for PAS, PASM, and MT stains. Furthermore, ablation experiments are performed in this paper to further demonstrate the effectiveness of the proposed module.</p><p><strong>Conclusion: </strong>This study successfully demonstrated the potential of unsupervised stain augmentation to improve glomerular segmentation in pathology analysis. Future research could extend this approach to other complex segmentation tasks in the pathology image domain to further explore the potential of applying stain augmentation techniques in different domains of pathology image analysis.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"225-236"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141285348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preoperative and intraoperative laparoscopic liver surface registration using deep graph matching of representative overlapping points.","authors":"Yue Dai, Xiangyue Yang, Junchen Hao, Huoling Luo, Guohui Mei, Fucang Jia","doi":"10.1007/s11548-024-03312-x","DOIUrl":"10.1007/s11548-024-03312-x","url":null,"abstract":"<p><strong>Purpose: </strong>In laparoscopic liver surgery, registering preoperative CT-extracted 3D models with intraoperative laparoscopic video reconstructions of the liver surface can help surgeons predict critical liver anatomy. However, the registration process is challenged by non-rigid deformation of the organ due to intraoperative pneumoperitoneum pressure, partial visibility of the liver surface, and surface reconstruction noise.</p><p><strong>Methods: </strong>First, we learn point-by-point descriptors and encode location information to alleviate the limitations of descriptors in location perception. In addition, we introduce a GeoTransformer to enhance the geometry perception to cope with the problem of inconspicuous liver surface features. Finally, we construct a deep graph matching module to optimize the descriptors and learn overlap masks to robustly estimate the transformation parameters based on representative overlap points.</p><p><strong>Results: </strong>Evaluation of our method with comparative methods on both simulated and real datasets shows that our method achieves state-of-the-art results, realizing the lowest surface registration error(SRE) 4.12 mm with the highest inlier ratios (IR) 53.31% and match scores (MS) 28.17%.</p><p><strong>Conclusion: </strong>Highly accurate and robust initialized registration obtained from partial information can be achieved while meeting the speed requirement. Non-rigid registration can further enhance the accuracy of the registration process on this basis.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"269-278"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142910423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of percutaneous intervention robotic system for skin insertion force.","authors":"Benfang Duan, Biao Jia, Cheng Wang, Shijia Chen, Jun Xu, Gao-Jun Teng","doi":"10.1007/s11548-024-03274-0","DOIUrl":"10.1007/s11548-024-03274-0","url":null,"abstract":"<p><strong>Purpose: </strong>Percutaneous puncture is a common interventional procedure, and its effectiveness is influenced by the insertion force of the needle. To optimize outcomes, we focus on reducing the peak force of the needle in the skin, aiming to apply this method to other tissue layers.</p><p><strong>Methods: </strong>We developed a clinical puncture system, setting and measuring various variables. We analyzed their effects, introduced admittance control, set thresholds, and adjusted parameters. Finally, we validated these methods to ensure their effectiveness.</p><p><strong>Results: </strong>Our system meets application requirements. We assessed the impact of various variables on peak force and validated the effectiveness of the new method. Results show a reduction of about 50% in peak force compared to the maximum force condition and about 13% compared to the minimum force condition. Finally, we summarized the factors to consider when applying this method.</p><p><strong>Conclusion: </strong>To achieve peak force suppression, initial puncture variables should be set based on the trends in variable impact. Additionally, the factors of the new method should be introduced using these initial settings. When selecting these factors, the characteristics of the new method must also be considered. This process will help to better optimize peak puncture force.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"345-355"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of thoracic endovascular aortic repair in a perfused patient-specific model of type B aortic dissection.","authors":"Lukas Mohl, Roger Karl, Matthias N Hagedorn, Armin Runz, Stephan Skornitzke, Malte Toelle, C Soeren Bergt, Johannes Hatzl, Christian Uhl, Dittmar Böckler, Katrin Meisenbacher, Sandy Engelhardt","doi":"10.1007/s11548-024-03190-3","DOIUrl":"10.1007/s11548-024-03190-3","url":null,"abstract":"<p><strong>Purpose: </strong>Complicated type B Aortic dissection is a severe aortic pathology that requires treatment through thoracic endovascular aortic repair (TEVAR). During TEVAR a stentgraft is deployed in the aortic lumen in order to restore blood flow. Due to the complicated pathology including an entry, a resulting dissection wall with potentially several re-entries, replicating this structure artificially has proven to be challenging thus far.</p><p><strong>Methods: </strong>We developed a 3d printed, patient-specific and perfused aortic dissection phantom with a flexible dissection flap and all major branching vessels. The model was segmented from CTA images and fabricated out of a flexible material to mimic aortic wall tissue. It was placed in a pulsatile hemodynamic flow loop. Hemodynamics were investigated through pressure and flow measurements and doppler ultrasound imaging. Surgeons performed a TEVAR intervention including stentgraft deployment under fluoroscopic guidance.</p><p><strong>Results: </strong>The flexible aortic dissection phantom was successfully incorporated in the hemodynamic flow loop, a systolic pressure of 112 mmHg and physiological flow of 4.05 L per minute was reached. Flow velocities were higher in true lumen with a up to 35.7 cm/s compared to the false lumen with a maximum of 13.3 cm/s, chaotic flow patterns were observed on main entry and reentry sights. A TEVAR procedure was successfully performed under fluoroscopy. The position of the stentgraft was confirmed using CTA imaging.</p><p><strong>Conclusions: </strong>This perfused in-vitro phantom allows for detailed investigation of the complex inner hemodynamics of aortic dissections on a patient-specific level and enables the simulation of TEVAR procedures in a real endovascular operating environment. Therefore, it could provide a dynamic platform for future surgical training and research.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"391-404"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807923/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141285347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid registration of the fibula for electromagnetically navigated osteotomies in mandibular reconstructive surgery: a phantom study.","authors":"L M N Aukema, A F de Geer, M J A van Alphen, W H Schreuder, R L P van Veen, T J M Ruers, F J Siepel, M B Karakullukcu","doi":"10.1007/s11548-024-03282-0","DOIUrl":"10.1007/s11548-024-03282-0","url":null,"abstract":"<p><strong>Purpose: </strong>In mandibular reconstructive surgery with free fibula flap, 3D-printed patient-specific cutting guides are the current state of the art. Although these guides enable accurate transfer of the virtual surgical plan to the operating room, disadvantages include long waiting times until surgery and the inability to change the virtual plan intraoperatively in case of tumor growth. Alternatively, (electromagnetic) surgical navigation combined with a non-patient-specific cutting guide could be used, requiring accurate image-to-patient registration. In this phantom study, we evaluated the accuracy of a hybrid registration method for the fibula and the additional error that is caused by navigating with a prototype of a novel non-patient-specific cutting guide to virtually planned osteotomy planes.</p><p><strong>Methods: </strong>The accuracy of hybrid registration and navigation was assessed in terms of target registration error (TRE), angular difference, and length difference of the intended fibula segments using three 3D-printed fibular phantoms with assessment points on osteotomy planes. Using electromagnetic tracking, hybrid registration was performed with point registration followed by surface registration on the lateral fibular surface. The fibula was fixated in the non-patient-specific cutting guide to navigate to planned osteotomy planes after which the accuracy was assessed.</p><p><strong>Results: </strong>Registration was achieved with a mean TRE, angular difference, and segment length difference of 2.3 ± 0.9 mm, 2.1 ± 1.4°, and 0.3 ± 0.3 mm respectively after hybrid registration. Navigation with the novel cutting guide increased the length difference (0.7 ± 0.6 mm), but decreased the angular difference (1.8 ± 1.3°).</p><p><strong>Conclusion: </strong>Hybrid registration showed to be a feasible and noninvasive method to register the fibula in phantom setup and could be used for electromagnetically navigated osteotomies with a novel non-patient-specific cutting guide. Future studies should focus on testing this registration method in clinical setting.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"369-377"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142711739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time intraoperative ultrasound registration for accurate surgical navigation in patients with pelvic malignancies.","authors":"M A J Hiep, W J Heerink, H C Groen, L Aguilera Saiz, B A Grotenhuis, G L Beets, A G J Aalbers, K F D Kuhlmann, T J M Ruers","doi":"10.1007/s11548-024-03299-5","DOIUrl":"10.1007/s11548-024-03299-5","url":null,"abstract":"<p><strong>Purpose: </strong>Surgical navigation aids surgeons in localizing and adequately resecting pelvic malignancies. Accuracy of the navigation system highly depends on the preceding registration procedure, which is generally performed using intraoperative fluoroscopy or CT. However, these ionizing methods are time-consuming and peroperative updates of the registration are cumbersome. In this present clinical study, several real-time intraoperative ultrasound (iUS) registration methods have been developed and evaluated for accuracy.</p><p><strong>Methods: </strong>During laparotomy in prospectively included patients, sterile electromagnetically tracked iUS acquisitions of the pelvic vessels and bones were collected. An initial registration and five other rigid iUS registration methods were developed including real-time deep learning bone and artery segmentation of 2D ultrasound. For each registration method, the accuracy was computed as the target registration error (TRE) using pelvic lymph nodes (LNs) as targets.</p><p><strong>Results: </strong>Thirty patients were included. The mean ± SD ultrasound acquisition time was 4.2 ± 1.4 min for the pelvic bone and 4.0 ± 1.1 min for the arteries. Deep learning bone and artery ultrasound segmentation resulted in an average (centerline)Dice of 0.85 and a mean surface distance below 2 mm. In 21 patients with visible LNs, initial registration resulted in a median (interquartile range [IQR]) TRE of 7.4 (5.9-10.9) mm. For the other five methods, 2D and 3D bone registration resulted in significantly lower TREs than 2D artery, 3D artery and bifurcation registration (two-sided Wilcoxon rank-sum test p < 0.01). The real-time 2D bone registration method was most accurate with a median (IQR) TRE of 2.6 (1.3-5.7) mm.</p><p><strong>Conclusion: </strong>Real-time 2D iUS bone registration is a fast and accurate method for patient registration prior to surgical navigation and has advantages over current registration techniques. Because of the user dependency of iUS, intuitive software is crucial for optimal clinical implementation. Trial registration number ClinicalTrials.gov (No. NCT05637346).</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"249-258"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142781677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative in-vitro assessment of a novel robot-assisted system for cochlear implant electrode insertion.","authors":"Philipp Aebischer, Lukas Anschuetz, Marco Caversaccio, Georgios Mantokoudis, Stefan Weder","doi":"10.1007/s11548-024-03276-y","DOIUrl":"10.1007/s11548-024-03276-y","url":null,"abstract":"<p><strong>Purpose: </strong>As an increasing number of cochlear implant candidates exhibit residual inner ear function, hearing preservation strategies during implant insertion are gaining importance. Manual implantation is known to induce traumatic force and pressure peaks. In this study, we use a validated in-vitro model to comprehensively evaluate a novel surgical tool that addresses these challenges through motorized movement of a forceps.</p><p><strong>Methods: </strong>Using lateral wall electrodes, we examined two subgroups of insertions: 30 insertions were performed manually by experienced surgeons, and another 30 insertions were conducted with a robot-assisted system under the same surgeons' supervision. We utilized a realistic, validated model of the temporal bone. This model accurately reproduces intracochlear frictional conditions and allows for the synchronous recording of forces on intracochlear structures, intracochlear pressure, and the position and deformation of the electrode array within the scala tympani.</p><p><strong>Results: </strong>We identified a significant reduction in force variation during robot-assisted insertions compared to the conventional procedure, with average values of 12 mN/s and 32 mN/s, respectively. Robotic assistance was also associated with a significant reduction of strong pressure peaks and a 17 dB reduction in intracochlear pressure levels. Furthermore, our study highlights that the release of the insertion tool represents a critical phase requiring surgical training.</p><p><strong>Conclusion: </strong>Robotic assistance demonstrated more consistent insertion speeds compared to manual techniques. Its use can significantly reduce factors associated with intracochlear trauma, highlighting its potential for improved hearing preservation. Finally, the system does not mitigate the impact of subsequent surgical steps like electrode cable routing and cochlear access sealing, pointing to areas in need of further research.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"323-332"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807918/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A virtual patient authoring tool for transcatheter aortic valve replacement.","authors":"Seyedsina Razavizadeh, Markus Kofler, Matthias Kunz, Joerg Kempfert, Ruediger Braun-Dullaeus, Janine Weidling, Bernhard Preim, Christian Hansen","doi":"10.1007/s11548-024-03293-x","DOIUrl":"10.1007/s11548-024-03293-x","url":null,"abstract":"<p><strong>Purpose: </strong>Computer-based medical training scenarios, derived from patient's records, often lack variability, modifiability, and availability. Furthermore, generating image datasets and creating scenarios is resource-intensive. Therefore, patient authoring tools for rapid dataset-independent creation of virtual patients (VPs) is a pressing need.</p><p><strong>Methods: </strong>An authoring tool and a virtual catheterization laboratory environment were developed. The tool allows customised VP generation through a real-time morphable heart model and Euroscore parameters. The generated VP can be examined inside the vCathLab using a fluoroscopy and monitoring device, both on desktop and immersive virtual reality. Seven board-certified experts evaluated the proposed method from three aspects, i.e. System Usability Scale, qualitative feedback, and its performance in VR.</p><p><strong>Results: </strong>All participants agreed that this method could provide the necessary information and is anatomically correct within an educational context. Its modifiability, variability, and simplicity were well recognised. The prototype achieved excellent usability score and considerable performance results.</p><p><strong>Conclusion: </strong>We present a highly variable VP authoring tool that enhances variability in medical training scenarios. Although this work does not aim to explore didactic aspects, the potential of using this approach in an educational context has been confirmed in our study. Accordingly, these aspects can benefit from a thorough investigation in the future. In addition, our tool can be improved to provide more realistic parameter ranges for procedure-specific cases.</p>","PeriodicalId":51251,"journal":{"name":"International Journal of Computer Assisted Radiology and Surgery","volume":" ","pages":"379-389"},"PeriodicalIF":2.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142856078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}