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Quantitation of Tissue Resection Using a Brain Tumor Model and 7-T Magnetic Resonance Imaging Technology

  • Dan Huy Tran
  • , Alexander Winkler-Schwartz
  • , Marius Tuznik
  • , Houssem Eddine Gueziri
  • , David A. Rudko
  • , Aiden Reich
  • , Recai Yilmaz
  • , Bekir Karlik
  • , D. Louis Collins
  • , Adrian Del Maestro
  • , Rolando Del Maestro
  • McGill University
  • University of Tennessee

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Background: Animal brain tumor models can be useful educational tools for the training of neurosurgical residents in risk-free environments. Magnetic resonance imaging (MRI) technologies have not used these models to quantitate tumor, normal gray and white matter, and total tissue removal during complex neurosurgical procedures. This pilot study was carried out as a proof of concept to show the feasibility of using brain tumor models combined with 7-T MRI technology to quantitatively assess tissue removal during subpial tumor resection. Methods: Seven ex vivo calf brain hemispheres were used to develop the 7-T MRI segmentation methodology. Three brains were used to quantitate brain tissue removal using 7-T MRI segmentation methodology. Alginate artificial brain tumor was created in 4 calf brains to assess the ability of 7-T MRI segmentation methodology to quantitate tumor and gray and white matter along with total tissue volumes removal during a subpial tumor resection procedure. Results: Quantitative studies showed a correlation between removed brain tissue weights and volumes determined from segmented 7-T MRIs. Analysis of baseline and postresection alginate brain tumor segmented 7-T MRIs allowed quantification of tumor and gray and white matter along with total tissue volumes removed and detection of alterations in surrounding gray and white matter. Conclusions: This pilot study showed that the use of animal tumor models in combination with 7-T MRI technology provides an opportunity to increase the granularity of data obtained from operative procedures and to improve the assessment and training of learners.

Original languageEnglish
Pages (from-to)e326-e339
JournalWorld Neurosurgery
Volume148
DOIs
StatePublished - Apr 2021

Keywords

  • Alginate
  • Brain tumors
  • Ex vivo model
  • MRI segmentation
  • Quantitative MRI assessment
  • Simulation

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