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Proceedings Paper

5-ALA induced PpIX fluorescence guided surgery of gliomas: comparison of expert and machine learning based models
Author(s): P. Leclerc; L. Alston; L. Mahieu-Williame; C. Ray; M. Hébert; P. Kantapareddy; C. Frindel; P. F. Brevet; D. Meyronet; J. Guyotat; D. Rousseau; B. Montcel
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Paper Abstract

Gliomas are diffuse brain tumors still hardly curable due to the difficulties to identify margins. 5-ALA induced PpIX fluorescence measurements enable to gain in sensitivity but are still limited to discriminate margin from healthy tissue. In this fluorescence spectroscopic study, we compare an expert-based model assuming that two states of PpIX contribute to total fluorescence and machine learning-based models. We show that machine learning retrieves the main features identified by the expert approach. We also show that machine learning approach slightly overpasses expert-based model for the identification of healthy tissues. These results might help to improve fluorescence-guided resection of gliomas by discriminating healthy tissues from tumor margins.

Paper Details

Date Published: 17 February 2020
PDF: 4 pages
Proc. SPIE 11225, Clinical and Translational Neurophotonics 2020, 112250D (17 February 2020); doi: 10.1117/12.2546670
Show Author Affiliations
P. Leclerc, Univ. Lyon (France)
L. Alston, Univ. Lyon (France)
L. Mahieu-Williame, Univ. Lyon (France)
C. Ray, Univ. Lyon (France)
M. Hébert, Univ. Lyon (France)
P. Kantapareddy, Ctr. Hospitalier Univ. de Lyon (France)
C. Frindel, Univ. Lyon (France)
P. F. Brevet, Univ. Lyon (France)
D. Meyronet, Ctr. Hospitalier Univ. de Lyon (France)
Univ. Lyon (France)
J. Guyotat, Ctr. Hospitalier Univ. de Lyon (France)
D. Rousseau, Univ. Lyon (France)
Univ. d'Angers (France)
B. Montcel, Univ. Lyon (France)


Published in SPIE Proceedings Vol. 11225:
Clinical and Translational Neurophotonics 2020
Steen J. Madsen; Victor X. D. Yang; Nitish V. Thakor, Editor(s)

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