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Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
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Radiologically derived 3D virtual models for neurosurgical planning.

Hyun-Jae Cho1, Thomas Lloyd2, Adrian Zammit3

  • 1Australian Centre for Complex Integration of Surgical Solutions (ACCISS), Woolloongabba, QLD 4102, Australia; Translational Research Institute, Woolloongabba, QLD 4102, Australia; The Princess Alexandra Hospital, Woolloongabba, QLD 4102, Australia.

Journal of Clinical Neuroscience : Official Journal of the Neurosurgical Society of Australasia
|March 22, 2024
PubMed
Summary

Three dimensional (3D) virtual models enhance neurosurgical planning for neuro-oncology cases. These models aid surgeons in understanding complex anatomy and improve patient education for shared decision-making.

Keywords:
3D modelComputer-aided designNeuro-oncologyNeurosurgerySurgical planning

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Area of Science:

  • Neurosurgery
  • Medical Imaging
  • Computer-Aided Design

Background:

  • Three dimensional (3D) virtual models are increasingly utilized in neurosurgery, particularly for neuro-oncology.
  • Computer-aided design (CAD) modeling of radiological images creates high-quality 3D models for pre-operative surgical planning.

Purpose of the Study:

  • To assess the clinical utility of 3D virtual models in pre-operative surgical planning for complex neuro-oncology cases.
  • To evaluate the impact of 3D virtual models on surgical planning, multidisciplinary team (MDT) meetings, and patient education.

Main Methods:

  • Segmentation of radiological images to create 3D virtual models for three complex neuro-oncology cases.
  • Pre-operative surgical planning using the generated 3D virtual models.
  • Face-to-face interviews with three neurosurgeons to gauge model usefulness.

Main Results:

  • All three neurosurgeons found the 3D virtual models useful for pre-surgical planning.
  • The models facilitated planning of operative positioning, understanding of spatial relationships between lesions and critical anatomy, and intra-operative anatomical identification.
  • 3D models proved beneficial in Multidisciplinary Team (MDT) meetings and for patient education and shared decision-making.

Conclusions:

  • 3D virtual models are beneficial for pre-surgical planning and patient education in neurosurgical neuro-oncology.
  • Integration of 3D virtual models into standard workflows facilitates adoption of advanced modalities like printed, virtual, augmented, and mixed reality models.
  • The utility of 3D virtual models can potentially be expanded to other surgical specialties.