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Safety and Complications Related to Emerging Technologies

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Neurospine. 2024;21(1):6-7
Publication date (electronic) : 2024 March 31
doi : https://doi.org/10.14245/ns.2448162.081
1Operative Research Unit of Orthopaedic and Trauma Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
2Research Unit of Orthopaedic and Trauma Surgery, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy
Corresponding Author Luca Ambrosio Operative Research Unit of Orthopaedic and Trauma Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, Rome 200-00128, Italy Email: l.ambrosio@unicampus.it

In the last few decades, the landscape of spine surgery has undergone a paradigm shift with the exponential implementation of emerging technologies, ranging from robotics to artificial intelligence (AI), wearables, and innovative biomaterials. Together, these tools have made it possible to significantly enhance surgical accuracy, identify new disease phenotypes from diverse big data sources, and offer innovative biological treatments [1-3]. However, as spine care providers embrace innovative tools and techniques, there is an inherent need to address the safety concerns and potential complications associated with these advancements.

One of the primary areas of innovation in spine surgery lies in navigation systems. Computer-assisted navigation has revolutionized the way surgeons approach complex spinal procedures, providing real-time imaging and guidance [4]. While these systems offer enhanced accuracy, the reliance on technology introduces new challenges. Malfunctions, software errors, or inaccurate calibration may lead to misguidance during surgery, posing a significant risk to patient safety. Previous studies have, indeed, reported nonnegligible rates of screw misplacement and dural tears, potentially caused by calibration errors, image drift, dislodged reference arrays, or skiving of surgical tools on the bone surface [5].

In this context, the additional incorporation of robotics, augmented reality (AR), and virtual reality (VR) has been demonstrated to allow for a thorough preoperative planning, provide 3-dimensional intraoperative guidance, and further increase surgical precision and efficiency [2]. However, despite these advantages, concerns regarding the learning curve associated with these systems and the potential for technical malfunctions persist. Surgeons must undergo extensive training to master robotic platforms, with early cases often aggravated by longer operation times, lower accuracy, increased radiation exposure, and potentially higher complication rates [6]. While the immersive nature of AR and VR aids in surgical navigation, there is a need to address potential drawbacks. The use of heavy head-mounted displays, attention shifts away from the operative field when using monitor-based systems, and prolonged exposure to virtual environments may lead to physical and visual fatigue, and eventually result in the aborted use of this technology [7].

Another unprecedented innovation in the field is represented by the advent of AI. With its multiple applications, including computer vision, natural language processing, computer-assisted diagnosis, and decision support systems, AI has already been demonstrated to potentially revolutionize how practitioners collect, process, interpret, and produce data. Recent groundbreaking AI applications have been shown to rapidly detect different disorders (such as spondylolisthesis and spinal stenosis), precisely classify spinal pathologies including disc degeneration and scoliosis, and even generate magnetic resonance imaging from computed tomography data [8]. The generation of large language models has not only enabled the automatic extraction of relevant information from text-based data sources (e.g., electronic medical records [EMRs], operation notes) but has also led to the development of human-like conversational chatbots, such as the widely popular ChatGPT [9]. Although apparently harmless, AI-based systems are indeed affected by inherent limitations that may significantly impact the reliability of generated outputs and, consequently, their safe use. One of the most common criticisms against AI and machine learning is the inherent lack of transparency in how outputs are generated. This “Black Box” dilemma hinders clinicians and institutions who, from a legal, regulatory, and ethical standpoint, require an understanding of how a system operates in order to bear the responsibility and consequences of its use [10]. Nonetheless, the inability to comprehend how the system exactly generated a given result might serve as the basis for bias and confounding, which could be challenging to control at an advanced stage [8]. As the reliance on digital platforms and interconnected systems increases, the protection of patient data becomes a critical concern. The integration of EMRs, imaging data, and communication tools in spine surgery highlights the risk of unauthorized access and elaboration of sensitive data. In the AI era, formulating robust regulatory measures and adhering to ethical standards in the collection and utilization of patient data are imperative to safeguard privacy and maintain the trust of both patients and healthcare professionals.

While emerging technologies in spine surgery offer unprecedented opportunities for improved patient outcomes, safety and complications remain at the forefront of the discussion. Collaboration among surgeons, researchers, and industry stakeholders is crucial to addressing the challenges associated with these innovations, striving for a balance between technological advancements and patient safety. Continuous education, training, and thorough scrutiny of emerging technologies will pave the way for a safer and more effective future in spine surgery, ensuring that the benefits of innovation are realized while minimizing potential complications.


Conflict of Interest

The authors have nothing to disclose.


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