Automatic Path-Planning Techniques for Minimally Invasive Stereotactic Neurosurgical Procedures-A Systematic Review

Authors

Reza Monfaredi, Sheikh Zayed Institute of Pediatrics Surgical Innovation, Children's National Hospital, Washington, DC 20010, USA.
Alondra Concepcion-Gonzalez, School of Medicine and Health Sciences, George Washington University School of Medicine, Washington, DC 20052, USA.
Jose Acosta Julbe, Department of Orthopaedic Surgery & Orthopaedic and Arthritis Center for Outcomes Research, Brigham and Women's Hospital, Boston, MA 02115, USA.
Elizabeth Fischer, Sheikh Zayed Institute of Pediatrics Surgical Innovation, Children's National Hospital, Washington, DC 20010, USA.
Gabriel Hernandez-Herrera, Mayo Clinic, College of Medicine and Science, Rochester, MN 55905, USA.
Kevin Cleary, Sheikh Zayed Institute of Pediatrics Surgical Innovation, Children's National Hospital, Washington, DC 20010, USA.
Chima Oluigbo, Sheikh Zayed Institute of Pediatrics Surgical Innovation, Children's National Hospital, Washington, DC 20010, USA.

Document Type

Journal Article

Publication Date

8-13-2024

Journal

Sensors (Basel, Switzerland)

Volume

24

Issue

16

DOI

10.3390/s24165238

Keywords

automatic; brain; neurosurgery; path; planning; trajectory

Abstract

This review systematically examines the recent research from the past decade on diverse path-planning algorithms tailored for stereotactic neurosurgery applications. Our comprehensive investigation involved a thorough search of scholarly papers from Google Scholar, PubMed, IEEE Xplore, and Scopus, utilizing stringent inclusion and exclusion criteria. The screening and selection process was meticulously conducted by a multidisciplinary team comprising three medical students, robotic experts with specialized knowledge in path-planning techniques and medical robotics, and a board-certified neurosurgeon. Each selected paper was reviewed in detail, and the findings were synthesized and reported in this review. The paper is organized around three different types of intervention tools: straight needles, steerable needles, and concentric tube robots. We provide an in-depth analysis of various path-planning algorithms applicable to both single and multi-target scenarios. Multi-target planning techniques are only discussed for straight tools as there is no published work on multi-target planning for steerable needles and concentric tube robots. Additionally, we discuss the imaging modalities employed, the critical anatomical structures considered during path planning, and the current status of research regarding its translation to clinical human studies. To the best of our knowledge and as a conclusion from this systematic review, this is the first review paper published in the last decade that reports various path-planning techniques for different types of tools for minimally invasive neurosurgical applications. Furthermore, this review outlines future trends and identifies existing technology gaps within the field. By highlighting these aspects, we aim to provide a comprehensive overview that can guide future research and development in path planning for stereotactic neurosurgery, ultimately contributing to the advancement of safer and more effective neurosurgical procedures.

APA Citation

Monfaredi, Reza; Concepcion-Gonzalez, Alondra; Acosta Julbe, Jose; Fischer, Elizabeth; Hernandez-Herrera, Gabriel; Cleary, Kevin; and Oluigbo, Chima, "Automatic Path-Planning Techniques for Minimally Invasive Stereotactic Neurosurgical Procedures-A Systematic Review" (2024). GW Authored Works. Paper 5483.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/5483

Department

Neurological Surgery