Texture Analysis of Fibrous Meningioma Using Label‐Free Multiphoton Microscopy

Fibrous meningiomas, a common type of brain tumor, present surgical challenges due to their variable hardness, which is crucial for complete resection and patient prognosis. This study explores the use of label-free multiphoton microscopy (MPM) for the objective assessment of the texture of fibrous meningiomas. Fresh tumor samples from 20 patients were analyzed using both multichannel and lambda mode MPM, with quantitative image analysis algorithms determining collagen content and multi-peak spectral fitting providing additional optical collagen metrics. The study compared medium and hard fibrous meningiomas, utilizing receiver operating characteristic analysis to evaluate predictive performance. Microstructural features were clearly visualized, enabling accurate diagnosis. Collagen-related parameters significantly differentiated between moderate and hard tumors (p < 0.05). High predictive values were observed for collagen content, collagen-to-NADH-free ratio, and collagen-to-FAD ratio (AUC = 0.748-0.839). A multivariate logistic model combining these biomarkers significantly improved diagnostic accuracy (AUC = 0.907). The findings suggest that MPM, with its ability to visualize and quantify microstructures such as collagen and cells without the need for staining, holds strong potential for rapid, objective, and accurate assessment of tumor texture during neurosurgery. The integration of MPM with multiphoton endoscopy paves the way for potential in vivo applications in the future.

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Publication Details

Journal
Journal of Biophotonics
Published
2024-11-28
DOI
https://doi.org/10.1002/jbio.202400241
Primary Topic
Meningioma and schwannoma management
Type
article
Field-Weighted Citation Impact
0.00

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article

Texture Analysis of Fibrous Meningioma Using Label‐Free Multiphoton Microscopy

Lianhuang Li, Rong Chen, Zanyi Wu, Linjing Shi et al.
Journal of Biophotonics
Meningioma and schwannoma management
article

Texture Analysis of Fibrous Meningioma Using Label‐Free Multiphoton Microscopy

Lianhuang Li, Rong Chen, Zanyi Wu, Linjing Shi, Jianxin Chen, Xingfu Wang, Liwen Hu, Na Fang, Xiaoli Su
article en

Abstract

Fibrous meningiomas, a common type of brain tumor, present surgical challenges due to their variable hardness, which is crucial for complete resection and patient prognosis. This study explores the use of label-free multiphoton microscopy (MPM) for the objective assessment of the texture of fibrous meningiomas. Fresh tumor samples from 20 patients were analyzed using both multichannel and lambda mode MPM, with quantitative image analysis algorithms determining collagen content and multi-peak spectral fitting providing additional optical collagen metrics. The study compared medium and hard fibrous meningiomas, utilizing receiver operating characteristic analysis to evaluate predictive performance. Microstructural features were clearly visualized, enabling accurate diagnosis. Collagen-related parameters significantly differentiated between moderate and hard tumors (p < 0.05). High predictive values were observed for collagen content, collagen-to-NADH-free ratio, and collagen-to-FAD ratio (AUC = 0.748-0.839). A multivariate logistic model combining these biomarkers significantly improved diagnostic accuracy (AUC = 0.907). The findings suggest that MPM, with its ability to visualize and quantify microstructures such as collagen and cells without the need for staining, holds strong potential for rapid, objective, and accurate assessment of tumor texture during neurosurgery. The integration of MPM with multiphoton endoscopy paves the way for potential in vivo applications in the future.

Journal of BiophotonicsVol. 18(2)
Fujian Normal University (CN), Fujian Medical University (CN), First Affiliated Hospital of Fujian Medical University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province
Openalex Percentile: Top 67%
Meningioma and schwannoma management
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Texture Analysis of Fibrous Meningioma Using Label‐Free Multiphoton Microscopy — Lianhuang Li, Rong Chen, et al. · Journal of Biophotonics (2024) | TGRS Research Map | TGRS