Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery

Kordon, Florian; Maier, Andreas; Swartman, Benedict; Privalov, Maxim; Barbari, Jan Siad El; Kunze, Holger

doi:10.1007/978-3-030-87202-1_54

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…Experimental results demonstrated the high accuracy of this 2D x-ray planning technology with a deviation of less than 1.5 mm and 1.5°compared to the 3D CT data. Kordon et al (2021) proposed a planning method aiming at reconstruction surgery of torn ligaments, which provided an automatic solution based on bone contour extraction, axis detection, anatomical landmark detection and geometrical construction for the requirement of accuracy. Besides TKA, THA also accounts for a large proportion of the lower limb arthroplasty.…”

Section: Pre-operative Planning In Joint Surgerymentioning

confidence: 99%

A review of advances in image-guided orthopedic surgery

Fan¹,

Zhu²,

Tu³

et al. 2023

Phys. Med. Biol.

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Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of image-guided orthopedic surgery (IGOS) has significantly decreased the surgical risk and improved the operation results. This review focuses on the application of recent advances in Artificial Intelligence (AI), Deep Learning (DL), Augmented Reality (AR) and Robotics in image-guided spine surgery, joint arthroplasty, fracture reduction and bone tumor resection. For the pre-operative stage, key technologies of AI and deep learning based medical image segmentation, 3D reconstruction and surgical planning procedures are systematically reviewed. For the intra-operative stage, the development of novel image registration, surgical tool calibration and real-time navigation are reviewed. Furthermore, the combination of the surgical navigation system with augmented reality (AR) and robotic technology is also discussed. Finally, the current issues and prospects of the IGOS system are discussed, with the goal of establishing a reference and providing guidance for surgeons, engineers, and researchers involved in the research and development of this area.

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Section: Pre-operative Planning In Joint Surgerymentioning

confidence: 99%

A review of advances in image-guided orthopedic surgery

Fan¹,

Zhu²,

Tu³

et al. 2023

Phys. Med. Biol.

View full text Add to dashboard Cite

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“…Visualization addresses intuitive ways of enriching the original image with relevant numeric and geometric information for the application [48]. This information includes the rotational and positional relation of joints [50], anatomic landmarks [51,52], and optimal trajectories for instrumentation and implant positioning [53][54][55][56][57]. Modeling covers the selection and mathematical representations of these data, allowing subsequent optimization of the planning solution, i.e., numerical and geometric analysis.…”

Section: Image-based Surgical Planning In Orthopedics and Traumatologymentioning

confidence: 99%

“…Planning of the transtibial drilling tunnel orientation and PCL insertion site follows the radiographic construction described by Johannsen et al (Figure A2d) [23]. We refer the reader to [55] for a comprehensive explanation of this construction and [50] for details on the utilized anatomical axis detection.…”

Section: Informed Consent Statementmentioning

confidence: 99%

Multi-Stage Platform for (Semi-)Automatic Planning in Reconstructive Orthopedic Surgery

et al. 2022

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Intricate lesions of the musculoskeletal system require reconstructive orthopedic surgery to restore the correct biomechanics. Careful pre-operative planning of the surgical steps on 2D image data is an essential tool to increase the precision and safety of these operations. However, the plan’s effectiveness in the intra-operative workflow is challenged by unpredictable patient and device positioning and complex registration protocols. Here, we develop and analyze a multi-stage algorithm that combines deep learning-based anatomical feature detection and geometric post-processing to enable accurate pre- and intra-operative surgery planning on 2D X-ray images. The algorithm allows granular control over each element of the planning geometry, enabling real-time adjustments directly in the operating room (OR). In the method evaluation of three ligament reconstruction tasks effect on the knee joint, we found high spatial precision in drilling point localization (ε<2.9mm) and low angulation errors for k-wire instrumentation (ε<0.75∘) on 38 diagnostic radiographs. Comparable precision was demonstrated in 15 complex intra-operative trauma cases suffering from strong implant overlap and multi-anatomy exposure. Furthermore, we found that the diverse feature detection tasks can be efficiently solved with a multi-task network topology, improving precision over the single-task case. Our platform will help overcome the limitations of current clinical practice and foster surgical plan generation and adjustment directly in the OR, ultimately motivating the development of novel 2D planning guidelines.

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