Search Results (12)

Artificial intelligence (AI) is increasingly transforming spine surgery, with expanding applications in diagnostics, intraoperative imaging, and surgical navigation. As the field advances toward greater precision and safety, machine learning (ML) and deep learning technologies are being integrated to augment surgeon expertise and optimize operative workflows. In particular, AI-driven innovations in image acquisition and navigation are reshaping intraoperative decision-making and technical execution. This narrative review provides an overview of AI applications relevant to intraoperative imaging and navigation in spine surgery. We begin by defining key concepts in AI, ML, and deep learning and briefly outline the historical evolution of AI within spine practice. We then examine current capabilities in image recognition and automated pathology detection, emphasizing their clinical relevance. Given the central role of imaging accuracy in modern navigation-assisted procedures, we review conventional acquisition platforms, including intraoperative computed tomography (CT) systems (e.g., O-arm, GE, Airo), surface-based registration to preoperative CT (Stryker, Medtronic), and optical surface mapping technologies (e.g., 7D Surgical). Emerging AI-optimized advancements are subsequently discussed, including low-dose intraoperative CT protocols, expanded scan windows, metal artifact reduction algorithms, integration of 2D fluoroscopy with preoperative CT datasets, and 3D reconstruction derived from 2D imaging. These developments aim to improve image quality, reduce radiation exposure, and enhance navigational accuracy. By synthesizing current evidence and technological progress, this review highlights how AI-enhanced imaging systems are redefining intraoperative spine surgery and shaping the future of precision-based care. The primary purpose of this review is to outline the applications of AI and its potential for perioperative and intraoperative optimization, including radiation exposure reduction, workflow streamlining, preoperative planning, robot-assisted surgery, and navigation. The secondary purpose is to define AI, machine learning, and deep learning within the medical context, describe image and pathology recognition, and provide a historical overview of AI in orthopedic spine surgery. Full article

Total knee arthroplasty (TKA) remains a cornerstone of orthopedic surgery, with optimal coronal alignment playing a pivotal role in determining both clinical outcomes and implant longevity. Traditionally, mechanical alignment has been regarded as the gold standard. However, the emergence of alternative philosophies—such as kinematic alignment and hybrid techniques—has shifted the focus toward individualized approaches. Recent advancements in robotic and computer-assisted systems have significantly enhanced the precision of implant positioning, allowing surgeons to better replicate native knee biomechanics and improve patient satisfaction. This narrative review examines current alignment philosophies in TKA, including mechanical, kinematic, and hybrid methods. It analyzes each technique’s principles, functionalities, benefits, and limitations while highlighting ongoing debates regarding their clinical application. Special attention is given to the role of technology in enabling more accurate, patient-specific surgical execution. Despite promising developments, challenges remain in standardizing these techniques and validating their long-term efficacy. To ensure a comprehensive evaluation relevant literature was reviewed, focusing on studies that explore alignment strategies, biomechanical outcomes, and the integration of technology in TKA. This review aims to synthesize current evidence, identify gaps in knowledge, and outline directions for future research needed to optimize alignment strategies in modern knee arthroplasty. Full article

Periacetabular osteotomy (PAO) is an effective approach for the surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip joint and the limited field of view (FoV) during the surgery, it is challenging for surgeons to perform a PAO surgery. To solve this challenge, we propose a robot-assisted, augmented reality (AR)-guided surgical navigation system for PAO. The system mainly consists of a robot arm, an optical tracker, and a Microsoft HoloLens 2 headset, which is a state-of-the-art (SOTA) optical see-through (OST) head-mounted display (HMD). For AR guidance, we propose an optical marker-based AR registration method to estimate a transformation from the optical tracker coordinate system (COS) to the virtual space COS such that the virtual models can be superimposed on the corresponding physical counterparts. Furthermore, to guide the osteotomy, the developed system automatically aligns a bone saw with osteotomy planes planned in preoperative images. Then, it provides surgeons with not only virtual constraints to restrict movement of the bone saw but also AR guidance for visual feedback without sight diversion, leading to higher surgical accuracy and improved surgical safety. Comprehensive experiments were conducted to evaluate both the AR registration accuracy and osteotomy accuracy of the developed navigation system. The proposed AR registration method achieved an average mean absolute distance error (mADE) of 1.96 ± 0.43 mm. The robotic system achieved an average center translation error of 0.96 ± 0.23 mm, an average maximum distance of 1.31 ± 0.20 mm, and an average angular deviation of 3.77 ± 0.85°. Experimental results demonstrated both the AR registration accuracy and the osteotomy accuracy of the developed system. Full article

The advent of many popular commercial forms of natural language processing tools has changed the way we can utilise digital technologies to tackle problems with big data. The objective of this review is to evaluate the current research and landscape of natural language processing tools and explore their potential use and impact in the field of orthopaedic surgery. In doing so, this review aims to answer the research question of how NLP tools can be utilised to streamline processes within orthopedic surgery. To do this, a scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Arksey and O’Malley framework for scoping reviews, as well as a computer-assisted literature search on the Medline, Embase and Google Scholar databases. Papers that evaluated the use of natural language processing tools in the field of orthopaedic surgery were included. Our literature search identified 24 studies that were eligible for inclusion. Our scoping review captured articles that highlighted multiple uses of NLP tools in orthopaedics. In particular, one study reported on the use of NLP for intraoperative monitoring, six for detection of adverse events, five for establishing orthopaedic diagnoses, two for assessing the patient experience, two as an informative resource for patients, one for predicting readmission, one for triaging, five for auditing and one for billing and coding. All studies assessed these various uses of NLP through its tremendous computational ability in extracting structured and unstructured text from the medical record, including operative notes, pathology and imaging reports, and progress notes, for use in orthopaedic surgery. Our review demonstrates that natural language processing tools are becoming increasingly studied for use and integration within various processes of orthopaedic surgery. These AI tools offer tremendous promise in improving efficiency, auditing and streamlining tasks through their immense computational ability and versatility. Despite this, further research to optimise and adapt these tools within the clinical environment, as well as the development of evidence-based policies, guidelines and frameworks are required before their wider integration within orthopaedics can be considered. Full article

Since the da Vinci surgical system was approved by the Food and Drug Administration (FDA) in 2000, the development and deployment of various robot-assisted minimally invasive surgery (MIS) systems have been largely expedited and boomed. With the rapid advancement of robotic techniques in recent decades, robot-assisted systems have been widely used in various surgeries including orthopedics. These robot-related techniques are transforming the conventional ways to conduct surgical procedures. Robot-assisted orthopedic surgeries have become more and more popular due to their potential benefits of increased accuracy and precision in surgical outcomes, enhanced reproducibility, reduced technical variability, decreased pain, and faster recovery time. In this paper, robotic systems and navigation techniques in typical orthopedic surgeries are reviewed, especially for arthroplasty. From the perspective of robotics and engineering, the systems and techniques are divided into two main categories, i.e., robotic systems (RSs), and computer-aided navigation systems (CANSs). The former is further divided into autonomous RS, hands-on RS, and teleoperated RS. For the latter, three key elements in CANS are introduced, including 3D modeling, registration, and navigation. Lastly, the potential advantages and disadvantages of the RS and CANS are summarized and discussed. Future perspectives on robotics in orthopedics, as well as the challenges, are presented. Full article

Background: This article provides a scoping review on the current status of Image-Guided Navigation with various forms of digital technologies, including Extended Reality, Augmented Reality Head-Mounted Displays (AR–HMDs) and Robot-Assisted Surgery (RAS) for Pedicle Screw Placement in orthopedics and spine surgery. Methods: A scoping literature review was performed in the PubMed, Scopus, Embase, Web of Science, Google Scholar and IEEE Xplore databases to collect clinical and user satisfaction data on AR–HMDs and compare those with RAS outcomes. In vivo patient, cadaver and phantom trial accuracy data reports were identified and grouped through the analysis. Over the past two years, 14 publications were retrieved and analyzed. Pedicle screw placement accuracy was described with Linear Tip Error (LTE), Angular Trajectory Error (ATE) and Gertzbein–Robbins Scale (GRS) outcomes. Results: The Pedicle Screw Placement accuracy was seen to increase in the in vivo, cadaver and phantom model groups using AR-HMD compared to the Free-Hand insertion technique. User experience and satisfaction data were limited; however, a clear advantage for the operative results was described when it was added. RAS screwing showed similar accuracy outcomes. The need for benchmarking and quantified situation awareness for AR–HMDs is recognizable. The authors present a method for standardized scoring and visualization of surgical navigation technologies, based on measurements of the surgeon (as the end-users) user satisfaction, clinical accuracy and operation time. Conclusions: computer-technology driven support for spine surgery is well-established and efficient for certain procedures. As a more affordable option next to RAS, AR–HMD navigation has reached technological readiness for surgical use. Ergonomics and usability improvements are needed to match the potential of RAS/XR in human surgeries. Full article

We conducted a systematic review of recent literature to understand the current challenges in the use of optical see-through head-mounted displays (OST-HMDs) for augmented reality (AR) assisted surgery. Using Google Scholar, 57 relevant articles from 1 January 2021 through 18 March 2022 were identified. Selected articles were then categorized based on a taxonomy that described the required components of an effective AR-based navigation system: data, processing, overlay, view, and validation. Our findings indicated a focus on orthopedic ($n=20$) and maxillofacial surgeries ($n=8$). For preoperative input data, computed tomography (CT) ($n=34$), and surface rendered models ($n=39$) were most commonly used to represent image information. Virtual content was commonly directly superimposed with the target site ($n=47$); this was achieved by surface tracking of fiducials ($n=30$), external tracking ($n=16$), or manual placement ($n=11$). Microsoft HoloLens devices ($n=24$ in 2021, $n=7$ in 2022) were the most frequently used OST-HMDs; gestures and/or voice ($n=32$) served as the preferred interaction paradigm. Though promising system accuracy in the order of 2–5 mm has been demonstrated in phantom models, several human factors and technical challenges—perception, ease of use, context, interaction, and occlusion—remain to be addressed prior to widespread adoption of OST-HMD led surgical navigation. Full article

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 ($\epsilon <2.9\mathrm{mm}$) and low angulation errors for k-wire instrumentation ($\epsilon <{0.75}^{\circ }$) 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. Full article

Computer-assisted orthopedic surgery and patient-specific instruments are widely used in orthopedic fields that utilize contralateral side bone data as a template to restore the affected side bone. The essential precondition for these techniques is that the left and right bone features are similar. Although proximal humerus fracture accounts for 4% to 8% of all fractures, the bilateral asymmetry of the proximal humerus is not fully understood. The aim of this study is to investigate anthropometric differences of the bilateral proximal humerus. One hundred one pairs of Korean humerus CT data from 51 females and 50 males were selected for this research. To investigate bilateral shape differences, we divided the proximal humerus into three regions and the proximal humerus further into five sections in each region. The distance from the centroid to the cortical outline at every 10 degrees was measured in each section. Differences were detected in all regions of the left and right proximal humerus; however, males had a larger number of significant differences than females. Large bilateral differences were measured in the greater tubercle. Nevertheless, using contralateral data as a template for repairing an affected proximal humerus might be possible. Full article

Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems. Full article

Since the advantages of precise operation and effective reduction of radiation, robots have become one of the best choices for solving the defects of traditional fracture reduction surgery. This paper focuses on the application of robots in fracture reduction surgery, design of the mechanism, navigation technology, robotic control, interaction technology, and the bone–robot connection technology. Through literature review, the problems in current fracture reduction robot and its future development are discussed. Full article

The study aimed to investigate whether pelvic tilt (PT) angles differ between the supine and upright position in symptom-free young adults. Additionally, the concurrent validity of the measurement system was tested on a pelvis phantom against a digital inclinometer. A new smartphone-based navigated ultrasound system was used to perform the measurements. The sample consisted of 12 symptom-free young adults. A multivariate regression model was used to analyze the data. The subjects’ pelvis in supine position was significantly more tilted anteriorly (mean PT = −7.3°, 95% C.I.: −10.6 to −3.9) than in upright position (mean PT = 0.8°, 95% C.I.: −2.5 to 4.1) (mean. diff. 8.1°; p < 0.001). Rater and trial order had no significant effects on the measured PT angles (p = 0.5). The accuracy of the system when measuring PT angles on the pelvis phantom was 0.3° (0.1° to 0.7°) and 0.2° (−0.09° to 0.6°) for the supine and upright positions respectively. Pelvic tilt angles differed significantly between the supine and the upright position in symptom-free young adults. Concurrent validity showed no differences for measurements in the upright position and small (under 0.4°) significant differences for measurements in the supine position. Full article