ArticleBMC musculoskeletal disorders2024
Spinal navigation with AI-driven 3D-reconstruction of fluoroscopy images: an ex-vivo feasibility study.
Article in BMC musculoskeletal disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI applications in lumbar and lumbosacral pedicle screw placement: a systematic review of limited evidence and future directions.Neurosurgical review · 2026Pooled it
- Advanced systems for intraoperative cartilage evaluation and treatment demonstrate early feasibility and a shift towards integrating artificial intelligence: A scoping review.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Article
- The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms.Journal of evaluation in clinical practice · 2026Review
- Artificial Intelligence Applications in Implant Positioning, Dislocation Risk Prediction, and Surgical Indications in Orthopaedic Surgery.Bioengineering (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Intraoperative Imaging and Navigation for Spine Surgery: A Narrative Review.Journal of clinical medicine · 2026Review
- Preoperative evaluation of C2 pedicle screw placement using a deep learning model: Development and validation study.PloS one · 2026Article
- The accuracy of artificial intelligence in 3D preoperative planning for total hip arthroplasty: A systematic review and meta-analysis.Journal of experimental orthopaedics · 2026Review
- Artificial intelligence in medicine: Current applications in cardiology, oncology, and radiology.World journal of methodology · 2025Review
- Intraoperative 3D reconstruction from sparse arbitrarily posed real X-rays.Scientific reports · 2025Article
- Artificial Intelligence in Spine Surgery: Imaging-Based Applications for Diagnosis and Surgical Techniques.Current reviews in musculoskeletal medicine · 2025Review
- Beyond traditional orthopaedic data analysis: AI, multimodal models and continuous monitoring.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Review
- DeepSeek's impact on thoracic surgeons' work patterns-past, present and future.Journal of thoracic disease · 2025Article
- Artificial intelligence in spine care: a paradigm shift in diagnosis, surgery, and rehabilitation.Journal of spine surgery (Hong Kong) · 2024Article
- Artificial intelligence in telemedicine: Topic modelling and network analysis of patents (1992-2024).Digital healthArticle
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the increasing number of surgeries utilizing spinal instrumentation, three-dimensional surgical navigation aims to improve the accuracy of implant placement. However, its widespread clinical adaption has been hindered by factors such as high radiation exposure and interference with standard surgical workflows.
methodsX23D is a novel AI-based fluoroscopy reconstruction technique that generates a 3D anatomical model of the spine from only four fluoroscopy images. Based on this technology, we developed a prototype for the surgical navigation of pedicle screws placement of the lumbar spine, visualizing the 3D-reconstructed spine anatomy and the surgical drill position in real-time. An ex-vivo study was conducted to compare the accuracy of the X23D-based navigation approach with fluoroscopy-aided freehand instrumentation. Five board-certified surgeons placed pedicle screws on six human torsi within a realistic surgical environment. Breach rate, site and extent (Gertzbein-Robbins) were evaluated in postoperative CT scans, as well as execution time, radiation dose, and user experience. Specimens, operating side, and surgeon were randomised.
resultsForty-nine pedicle screws (n = 24 × 23D, n = 25 2D-fluoroscopy) were evaluated, with six breaches occurring in the control group, one of which was considered clinically significant (medial breach grade C). Five breaches with one clinically significant breach were observed in the X23D group. Breach rate, execution time for each lumbar level (X23D 167 s vs. control 156 s), radiation dose (X23D 33.26 mGy vs. control 49.5 mGy), and user experience did not reveal significant differences (p > 0.05) between the groups.
conclusionsSpinal navigation using the X23D-based approach shows promise and performs well in a realistic surgical ex-vivo setting. With further refinements, its accuracy is expected to match clinical-grade navigation systems while reducing radiation dose.
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