Automated online safety margin (GLIOVIS) for glioma surgery model

• Published in: Frontiers in oncology Vol. 14; p. 1361022
• Main Authors: Mazevet, Marianne, Oberli, Christian, Marinelli, Sebastiano, Zaed, Ismail, Bauer, Stefanie, Kaelin-Lang, Alain, Marchi, Francesco, Gardenghi, Roberto, Reinert, Michael, Cardia, Andrea
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 29.04.2024
• Subjects: 5-ALA–guided surgery; fluorescence quantification; glioblastoma; gliolan; Oncology; safety margins; glioblastoma; safety margins; fluorescence quantification; gliolan; 5-ALA–guided surgery
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2024.1361022

Glioblastoma is the most common type of primary brain malignancy and has a poor prognosis. The standard treatment strategy is based on maximal safe surgical resection followed by radiotherapy and chemotherapy. Surgical resection can be optimized by using 5-delta-aminolevulinic acid (5-ALA)-induced fluorescence, which is the current mainstay. Although 5-ALA-induced fluorescence has gained general acceptance, it is also limited by inter-observer variability and non-standardized fluorescence parameters. We present a new software for processing images analysis to better recognize the tumor infiltration margins using an intraoperative immediate safety map of 5-ALA-induced fluorescence. We tested this in a brain model using a commercial surgical exoscope. A dedicated software GLIOVIS (ACQuF-II, Advanced Colorimetry-based Quantification of Fluorescence) was designed for processing analysis of images taken on the Intraoperative Orbital Camera Olympus Orbeye (IOC) to determine the relative quantification of Protoporphyrin IX (5-ALA metabolite) fluorescence. The software allows to superpose the new fluorescence intensity map and the safety margins over the original images. The software was tested on gel-based brain models. Two surrogate models were developed: PpIX agarose gel-integrated in gelatin-based brain model at different scales (1:25 and 1:1). The images taken with the IOC were then processed using GLIOVIS. The intensity map and safety margins could be obtained for all available models. GLIOVIS for 5-ALA-guided surgery image processing was validated on various gelatin-based brain models. Different levels of fluorescence could be qualitatively digitalized using this technique. These results need to be further confirmed and corroborated and validated clinically in order to define a new standard of care for glioblastoma resection.