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Immersive Neurosurgical Anatomy Using Photogrammetry: Technical Note and Scoping Review.

Jhon E Bocanegra-Becerra1, Daniel Ballesteros-Herrera2, Khaled Alhwaishel3

  • 1Academic Department of Surgery, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru.

Journal of Neurological Surgery. Part B, Skull Base
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PubMed
Summary

Photogrammetry creates high-fidelity 3D anatomical models for neurosurgery education. While promising for visuospatial skills, challenges in accuracy and depth perception need addressing for microsurgical training.

Keywords:
3D imagingmicrosurgeryneuroanatomyneurosurgeryphotogrammetry

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Area of Science:

  • Neurosurgery
  • Medical Education
  • Medical Imaging

Background:

  • Photogrammetry offers potential for advancing microsurgical education.
  • This study explores photogrammetry's application in neurosurgical anatomy and education.

Purpose of the Study:

  • To review the use of photogrammetry in neurosurgical anatomy.
  • To identify technical guidelines and implementation areas for photogrammetry in education.

Main Methods:

  • Created 3D models of neuroanatomy (white matter, brainstem, cranial nerves) using photogrammetry.
  • Conducted a scoping review of photogrammetry in neurosurgical anatomy education across PubMed, Scopus, and Embase.

Main Results:

  • High-quality 3D models of neuroanatomy were generated.
  • The review identified 28 relevant articles, detailing photogrammetry's three stages: acquisition, processing, and visualization.
  • Most studies reported high-fidelity reconstruction (75%), but fewer assessed depth perception (42.9%). Cranial region models dominated (96.4%).

Conclusions:

  • Photogrammetry enables creation of portable, high-fidelity virtual anatomical models for neurosurgery.
  • These models can enhance visuospatial skills training.
  • Objective accuracy and depth perception remain key challenges for effective microsurgical education.