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Towards machine learning-based quantitative hyperspectral image guidance for brain tumor resection.

David Black1, Declan Byrne1, Anna Walke2

  • 1Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada.

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|July 4, 2024
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Summary

Five fluorophores identified using hyperspectral imaging show promise as optical biomarkers for distinguishing brain tumor types and grades during surgery. This aids in achieving complete tumor resection in fluorescence-guided neurosurgery.

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Area of Science:

  • Neurosurgery
  • Medical Imaging
  • Biomarkers

Background:

  • Distinguishing malignant gliomas at infiltration zones is crucial for complete resection.
  • 5-aminolevulinic acid (5-ALA) fluorescence guidance aids tumor visualization.
  • Hyperspectral imaging has characterized five fluorophores in brain tumors.

Purpose of the Study:

  • To evaluate the effectiveness of five fluorophore emission spectra for classifying brain tumors and tissues.
  • To develop machine-learning models for intraoperative tumor classification.
  • To assess the potential of these fluorophores as optical biomarkers.

Main Methods:

  • 184 patients with various brain tumors and tissues were analyzed using 891 hyperspectral measurements.
  • Four machine-learning models were trained to classify tumor type, grade, glioma margins, and IDH mutation.
  • Random forests and multilayer perceptrons were employed for classification.

Main Results:

  • Classifiers achieved average test accuracies of 84-87% for tumor type, 96.1% for grade, 86% for margins, and 91% for IDH mutation.
  • Fluorophore abundances significantly varied between tumor margin types and grades (p < 0.01).
  • At least four fluorophore abundances differed significantly between tissue types (p < 0.01).

Conclusions:

  • The study demonstrates distinct fluorophore abundances across different tissue classes.
  • The five fluorophores show potential as optical biomarkers for intraoperative classification.
  • This research opens avenues for advanced fluorescence-guided neurosurgery systems.