Development of a Simulation Model for Fluorescence-Guided Brain Tumor Surgery
Martirosyan, Nikolay L.
Lawton, Michael T.
Preul, Mark C.
AffiliationUniv Arizona, Dept Neurosurg
fluorescence-guided tumor surgery
MetadataShow full item record
PublisherFRONTIERS MEDIA SA
CitationValli D, Belykh E, Zhao X, Gandhi S, Cavallo C, Martirosyan NL, Nakaji P, Lawton MT and Preul MC (2019) Development of a Simulation Model for Fluorescence-Guided Brain Tumor Surgery. Front. Oncol. 9:748. doi: 10.3389/fonc.2019.00748
JournalFRONTIERS IN ONCOLOGY
RightsCopyright © 2019 Valli, Belykh, Zhao, Gandhi, Cavallo, Martirosyan, Nakaji, Lawton and Preul. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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AbstractObjective: Fluorescence dyes are increasingly used in brain tumor surgeries, and thus the development of simulation models is important for teaching neurosurgery trainees how to perform fluorescence-guided operations. We aimed to create a tumor model for fluorescence-guided surgery in high-grade glioma (HGG). Methods: The tumor model was generated by the following steps: creating a tumor gel with a similar consistency to HGG, selecting fluorophores at optimal concentrations with realistic color, mixing the fluorophores with tumor gel, injecting the gel into fresh pig/sheep brain, and testing resection of the tumor model under a fluorescence microscope. The optimal tumor gel was selected among different combinations of agar and gelatin. The fluorophores included fluorescein, indocyanine green (ICG), europium, chlorin e6 (Ce6), and protoporphyrin IX (PpIX). The tumor model was tested by neurosurgeons and neurosurgery trainees, and a survey was used to assess the validity of the model. In addition, the photobleaching phenomenon was studied to evaluate its influence on fluorescence detection. Results: The best tumor gel formula in terms of consistency and tactile response was created using 100 mL water at 100 degrees C, 0.5 g of agar, and 3 g of gelatin mixed thoroughly for 3 min. An additional 1 g of agar was added when the tumor gel cooled to 50 degrees C. The optimal fluorophore concentration ranges were fluorescein 1.9 x 10(-4) to 3.8 x 10(-4) mg/mL, ICG 4.9 x 10(-3) to 9.8 x 10(-3) mg/mL, europium 7.0 x 10(-2) to 1.4 x 10(-1) mg/mL, Ce6 2.2 x 10(-3) to 4.4 x 10(-3) mg/mL, and PpIX 1.8 x 10(-2) to 3.5 x 10(-2) mg/mL. No statistical differences among fluorophores were found for face validity, content validity, and fluorophore preference. Europium, ICG, and fluorescein were shown to be relatively stable during photobleaching experiments, while chlorin e6 and PpIX had lower stability. Conclusions: The model can efficiently highlight the "tumor" with 3 different colors-green, yellow, or infrared green with color overlay. These models showed high face and content validity, although there was no significant difference among the models regarding the degree of simulation and training effectiveness. They are useful educational tools for teaching the key concepts of intra-axial tumor resection techniques, such as subpial dissection and nuances of fluorescence-guided surgery.
NoteOpen access journal
VersionFinal published version
SponsorsNewsome Chair in Neurosurgery Research; Barrow Neurological Foundation