Transsphenoidal surgery using robotics to approach the sella turcica: Integrative use of artificial intelligence, realistic motion tracking and telesurgery

Artificial intelligence in orthopaedic surgery

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as 'big data', AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI's limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

History, Current Techniques, and Future Prospects of Surgery to the Sellar and Parasellar Region

The sellar and parasellar region can be affected by diverse pathologies. The deep-seated location and surrounding critical neurovascular structures make treatment challenging; there is no singular, optimal approach for management. The history and development of transcranial and transsphenoidal approaches by pioneers in skull base surgery were largely aimed at treating pituitary adenomas, which are the most common lesions of the sella. This review explores the history of sellar surgery, the most commonly used approaches today, and future considerations for surgery of the sellar/parasellar region.

The use of augmented reality in transsphenoidal surgery: A systematic review

BACKGROUND

Augmented reality (AR) has become a promising tool in neurosurgery. It can minimise the anatomical challenges faced by conventional endoscopic or microscopic transsphenoidal reoperations and can assist in intraoperative guidance, preoperative planning, and surgical training.

OBJECTIVES

The aims of this systematic review are to describe, compare, and evaluate the use of AR in endoscopic and microscopic transsphenoidal surgery, incorporating the latest primary research.

METHODS

A systematic review was performed to explore and evaluate existing primary evidence for using AR in transsphenoidal surgery. A comprehensive search of MEDLINE and EMBASE was conducted from database inception to 11th August 2021 for primary data on the use of AR in microscopic and endoscopic endonasal skull base surgery. Additional articles were identified through searches on PubMed, Google Scholar, JSTOR, SCOPUS, Web of Science, Engineering Village, IEEE transactions, and HDAS. A synthesis without meta-analysis (SWiM) analysis was employed quantitatively and qualitatively on the impact of AR on landmark identification, intraoperative navigation, accuracy, time, surgeon experience, and patient outcomes.

RESULTS

In this systematic review, 17 studies were included in the final analysis. The main findings were that AR provides a convincing improvement to landmark identification, intraoperative navigation, and surgeon experience in transsphenoidal surgery, with a further positive effect on accuracy and time. It did not demonstrate a convincing positive effect on patient outcomes. No studies reported comparative mortalities, morbidities, or cost-benefit indications.

CONCLUSION

AR-guided transsphenoidal surgery, both endoscopic and microscopic, is associated with an overall improvement in the areas of intraoperative guidance and surgeon experience as compared with their conventional counterparts. However, literature on this area, particularly comparative data and evidence, is very limited. More studies with similar methodologies and quantitative outcomes are required to perform appropriate meta-analyses and to draw significant conclusions.