SURG-57. FLUORESCENCE LIFETIME IMAGING (FLIM) PROVIDES HIGHLY ACCURATE, DYE-FREE TUMOR MARGIN DETECTION DURING GLIOMA RESECTIONS

Abstract INTRODUCTION Fluorescence guided tumor margin detection is an important tool to enhance the extent of resection for gliomas. Existing dyes, such as 5-ALA, require planned administration, surgical resection in dark conditions, and are only effective for high-grade tumors. We have developed a novel laser scanning probe to assess tissue autofluorescence decay (lifetime) which allows tumor margin detection without exogenous dyes and under normal room light conditions. This technology has been optimized for margin detection in low-grade and high-grade gliomas. METHODS Patients undergoing craniotomy for resection of gliomas were enrolled. During resection of the final tumor margin, multiple 1x1 mm regions were scanned with FLIm and biopsied for evaluation by a neuropathologist. FLIm data and ground truth pathology were processed by a machine-learning algorithm to develop classifiers for the FLIm data. Classifiers were then applied to the full data set to determine the accuracy of FLIm predictions. RESULTS 12 patients with non-enhancing (LGG) and 25 patients with enhancing (HGG) tumors were enrolled, with a total of 228 biopsies obtained. For LGG, sensitivity of FLIm for detection of residual tumor was 0.89 (95% CI 0.8-0.98) with a specificity of 0.92 (95% CI 0.86-0.97), resulting in a positive predictive value of 0.76 and negative predictive value of 0.96 with an overall accuracy of 0.91. For HGG, sensitivity of FLIm for detection of residual tumor was 0.92 (95% CI 0.84-1.0) with a specificity of 0.95 (95% CI 0.91-0.99), resulting in a positive predictive value of 0.90 and negative predictive value of 0.96 with an overall accuracy of 0.94, exceeding reported values for 5-ALA. CONCLUSION FLIm can distinguish between residual low and high-grade glioma and normal brain at resection margins with very high sensitivity and specificity. This quantitative technology does not require administration of exogenous dyes and can be used under normal room light illumination.

Authors

Institutions

Publication Details

Journal
Neuro-Oncology
Published
2024-11-01
DOI
https://doi.org/10.1093/neuonc/noae165.1136
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SURG-57. FLUORESCENCE LIFETIME IMAGING (FLIM) PROVIDES HIGHLY ACCURATE, DYE-FREE TUMOR MARGIN DETECTION DURING GLIOMA RESECTIONS

Alba Alfonso‐García, Robert Riestenberg, Orin Bloch, Jeong Han Lee et al.
Neuro-Oncology
Glioma Diagnosis and Treatment
article

SURG-57. FLUORESCENCE LIFETIME IMAGING (FLIM) PROVIDES HIGHLY ACCURATE, DYE-FREE TUMOR MARGIN DETECTION DURING GLIOMA RESECTIONS

Alba Alfonso‐García, Robert Riestenberg, Orin Bloch, Jeong Han Lee, Laura Marcu, Silvia Noble Anbunesan
article en

Abstract

Abstract INTRODUCTION Fluorescence guided tumor margin detection is an important tool to enhance the extent of resection for gliomas. Existing dyes, such as 5-ALA, require planned administration, surgical resection in dark conditions, and are only effective for high-grade tumors. We have developed a novel laser scanning probe to assess tissue autofluorescence decay (lifetime) which allows tumor margin detection without exogenous dyes and under normal room light conditions. This technology has been optimized for margin detection in low-grade and high-grade gliomas. METHODS Patients undergoing craniotomy for resection of gliomas were enrolled. During resection of the final tumor margin, multiple 1x1 mm regions were scanned with FLIm and biopsied for evaluation by a neuropathologist. FLIm data and ground truth pathology were processed by a machine-learning algorithm to develop classifiers for the FLIm data. Classifiers were then applied to the full data set to determine the accuracy of FLIm predictions. RESULTS 12 patients with non-enhancing (LGG) and 25 patients with enhancing (HGG) tumors were enrolled, with a total of 228 biopsies obtained. For LGG, sensitivity of FLIm for detection of residual tumor was 0.89 (95% CI 0.8-0.98) with a specificity of 0.92 (95% CI 0.86-0.97), resulting in a positive predictive value of 0.76 and negative predictive value of 0.96 with an overall accuracy of 0.91. For HGG, sensitivity of FLIm for detection of residual tumor was 0.92 (95% CI 0.84-1.0) with a specificity of 0.95 (95% CI 0.91-0.99), resulting in a positive predictive value of 0.90 and negative predictive value of 0.96 with an overall accuracy of 0.94, exceeding reported values for 5-ALA. CONCLUSION FLIm can distinguish between residual low and high-grade glioma and normal brain at resection margins with very high sensitivity and specificity. This quantitative technology does not require administration of exogenous dyes and can be used under normal room light illumination.

Neuro-OncologyVol. 26(Supplement_8)
University of California, Davis (US)
Openalex Percentile: Top 64%
Glioma Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.