Augmented Reality in Surgical Navigation: A Review of Evaluation and Validation Metrics

Malhotra, S.; Halabi, Osama; Dakua, Sarada Prasad; Padhan, Jhasketan; Paul, Santu; Palliyali, Waseem

doi:10.3390/app13031629

Cited by 33 publications

(10 citation statements)

References 107 publications

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“…Moreover, it is also challenging to achieve and demonstrate a statistically significant difference between results with and without the use of an intraoperative XR navigation system. Thus, more studies of the effective and comprehensive evaluation and validation of XR-assisted navigation systems that are employed in surgery are expected ( 55 ). Furthermore, one limitation of our study is that surgeries were conducted by experienced orthopedic surgeons in most of the cases in this narrative review, and the high rate of accuracy might have been related to their expertise rather than solely to the XR-technology-assisted navigation systems.…”

Section: Discussionmentioning

confidence: 99%

The application of extended reality technology-assisted intraoperative navigation in orthopedic surgery

Bian,

Lin,

et al. 2024

Front. Surg.

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Extended reality (XR) technology refers to any situation where real-world objects are enhanced with computer technology, including virtual reality, augmented reality, and mixed reality. Augmented reality and mixed reality technologies have been widely applied in orthopedic clinical practice, including in teaching, preoperative planning, intraoperative navigation, and surgical outcome evaluation. The primary goal of this narrative review is to summarize the effectiveness and superiority of XR-technology-assisted intraoperative navigation in the fields of trauma, joint, spine, and bone tumor surgery, as well as to discuss the current shortcomings in intraoperative navigation applications. We reviewed titles of more than 200 studies obtained from PubMed with the following search terms: extended reality, mixed reality, augmented reality, virtual reality, intraoperative navigation, and orthopedic surgery; of those 200 studies, 69 related papers were selected for abstract review. Finally, the full text of 55 studies was analyzed and reviewed. They were classified into four groups—trauma, joint, spine, and bone tumor surgery—according to their content. Most of studies that we reviewed showed that XR-technology-assisted intraoperative navigation can effectively improve the accuracy of implant placement, such as that of screws and prostheses, reduce postoperative complications caused by inaccurate implantation, facilitate the achievement of tumor-free surgical margins, shorten the surgical duration, reduce radiation exposure for patients and surgeons, minimize further damage caused by the need for visual exposure during surgery, and provide richer and more efficient intraoperative communication, thereby facilitating academic exchange, medical assistance, and the implementation of remote healthcare.

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Section: Discussionmentioning

confidence: 99%

The application of extended reality technology-assisted intraoperative navigation in orthopedic surgery

Bian,

Lin,

et al. 2024

Front. Surg.

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“…The segmented structures (in this case organs and their disorders) may be next applied to the development of the 3D virtual environment [105]. These 3D objects may be implemented through for example, holograms displayed in the head-mounted display (HDMs) like Mixed Reality glasses in medical diagnostics [113], pre-operative imaging [114], surgical assistance [115,116], robotics surgery [117], and medical education [81,82]. However, the crucial issue is connected with the quality of obtained segmented structures, and this process can be significantly accelerated and improved by the use of Artificial Intelligence.…”

Section: Neural Network and Learning Algorithms In The Medical Image ...mentioning

confidence: 99%

Artificial Intelligence-Based Algorithms in Medical Image Scan Segmentation and Intelligent Visual-Content Generation

Rudnicka,

Szczepanski,

Pregowska

2023

Preprint

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Recently, Artificial Intelligence (AI)-based algorithms have revolutionized the medical image segmentation processes. Thus, the precise segmentation of organs and their lesions may contribute to an efficient diagnostics process and a more effective selection of targeted therapies as well as increasing the effectiveness of the training process. Thus, AI may contribute to the automatization of the image scan segmentation process and increase the quality of the resulting 3D objects, which may lead to the generation of more realistic virtual objects. In this paper, we focus on the AI-based solutions applied in the medical image scan segmentation, and intelligent visual-content generation, i.e. computer-generated three-dimensional (3D) images in the context of Extended Reality (XR). We consider different types of neural networks used with a special emphasis on the learning rules applied, taking into account algorithm accuracy and performance, as well as open data availability. This paper also attempts to summarize the current development of AI-based segmentation methods in medical imaging and intelligent visual content generation that are applied in XR. Finally, this paper concludes with possible developments and open challenges in AI application in Extended Reality-based solutions. Finally, the future lines of research and development directions of Artificial Intelligence applications both in medical image segmentation and Extended reality-based medical solutions are discussed.

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“…Augmented reality in surgery has been widely studied for neurosurgery, orthopedic and spine, laparoscopic and oral surgery [ 6 ]. The proposed methods enable localization and visualization of a region of interest using image registration via video (RGB, infrared, depth-sensing, stereo, ultrasound) and, most of the time, tracking of fiducials such as optical, EM, RFID or fluorescent [ 7 ] markers.…”

Section: Introductionmentioning

confidence: 99%

3D magnetic seed localization for augmented reality in surgery

Ambrosini,

AzizianAmiri,

Zeestraten

et al. 2024

Int J CARS

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Purpose For tumor resection, surgeons need to localize the tumor. For this purpose, a magnetic seed can be inserted into the tumor by a radiologist and, during surgery, a magnetic detection probe informs the distance to the seed for localization. In this case, the surgeon still needs to mentally reconstruct the position of the tumor from the probe’s information. The purpose of this study is to develop and assess a method for 3D localization and visualization of the seed, facilitating the localization of the tumor. Methods We propose a method for 3D localization of the magnetic seed by extending the magnetic detection probe with a tracking-based localization. We attach a position sensor (QR-code or optical marker) to the probe in order to track its 3D pose (respectively, using a head-mounted display with a camera or optical tracker). Following an acquisition protocol, the 3D probe tip and seed position are subsequently obtained by solving a system of equations based on the distances and the 3D probe poses. Results The method was evaluated with an optical tracking system. An experimental setup using QR-code tracking (resp. using an optical marker) achieves an average of 1.6 mm (resp. 0.8 mm) 3D distance between the localized seed and the ground truth. Using a breast phantom setup, the average 3D distance is 4.7 mm with a QR-code and 2.1 mm with an optical marker. Conclusion Tracking the magnetic detection probe allows 3D localization of a magnetic seed, which opens doors for augmented reality target visualization during surgery. Such an approach should enhance the perception of the localized region of interest during the intervention, especially for breast tumor resection where magnetic seeds can already be used in the protocol.

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Augmented Reality in Surgical Navigation: A Review of Evaluation and Validation Metrics

Cited by 33 publications

References 107 publications

The application of extended reality technology-assisted intraoperative navigation in orthopedic surgery

The application of extended reality technology-assisted intraoperative navigation in orthopedic surgery

Artificial Intelligence-Based Algorithms in Medical Image Scan Segmentation and Intelligent Visual-Content Generation

3D magnetic seed localization for augmented reality in surgery

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