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Published in: Lasers in Medical Science 2/2022

01-03-2022 | Meningioma | Original Article

Intraoperative detection of human meningioma using a handheld visible resonance Raman analyzer

Authors: Liang Zhang, Yan Zhou, Binlin Wu, Shengjia Zhang, Ke Zhu, Cheng-hui Liu, Xinguang Yu, Robert R. Alfano

Published in: Lasers in Medical Science | Issue 2/2022

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Abstract

To report for the first time the preliminary results for the evaluation of a VRR-LRR™ analyzer based on visible resonance Raman technique to identify human meningioma grades and margins intraoperatively. Unprocessed primary and recurrent solid human meningeal tissues were collected from 33 patients and underwent Raman analysis during surgeries. A total of 1180 VRR spectra were acquired from fresh solid tissues using a VRR-LRR™ analyzer. A confocal HR Evolution (HORIBA, France SAS) Raman system with 532-nm excitation wavelength was also used to collect data for part of the ex vivo samples after they were thawed from – 80 °C for comparison. The preliminary analysis led to the following observations. (1) The intensity ratio of VRR peaks of protein to fatty acid (I2934/I2888) decreased with the increase of meningioma grade. (2) The ratio of VRR peaks of phosphorylated protein to amid I (I1588/I1639) decreased for the higher grade of meningioma. (3) Three RR vibration modes at 1378, 3174, and 3224 cm−1 which were related to the molecular vibrational bands of oxy-hemeprotein, amide B, and amide A protein significantly changed in peak intensities in the two types of meningioma tissues compared to normal tissue. (4) The changes in the intensities of VRR modes of carotenoids at 1156 and 1524 cm−1 were also found in the meningioma boundary. The VRR-LRR™ analyzer demonstrates a new approach for label-free, rapid, and objective identification of primary human meningioma in quasi-clinical settings. The accuracy for detecting meningioma tissues using support vector machines (SVMs) was over 70% based on Raman peaks of key biomolecules and up to 100% using principal component analysis (PCA).
Literature
1.
go back to reference Ostrom QT, Gittleman H, Xu J et al (2016) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2009–2013. Neurooncol 18(suppl_5):v1–v75 Ostrom QT, Gittleman H, Xu J et al (2016) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2009–2013. Neurooncol 18(suppl_5):v1–v75
2.
go back to reference Riemenschneider MJ, Perry A, Reifenberger G (2006) Histological classification and molecular genetics of meningiomas. Lancet Neurol 5(12):1045–1054CrossRef Riemenschneider MJ, Perry A, Reifenberger G (2006) Histological classification and molecular genetics of meningiomas. Lancet Neurol 5(12):1045–1054CrossRef
3.
go back to reference Louis DN, Perry A, Reifenberger G et al (2016) The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131(6):803–820CrossRef Louis DN, Perry A, Reifenberger G et al (2016) The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131(6):803–820CrossRef
4.
go back to reference Aizer AA, Bi WL, Kandola MS et al (2015) Extent of resection and overall survival for patients with atypical and malignant meningioma. Cancer 121(24):4376–4381CrossRef Aizer AA, Bi WL, Kandola MS et al (2015) Extent of resection and overall survival for patients with atypical and malignant meningioma. Cancer 121(24):4376–4381CrossRef
5.
go back to reference Oya S, Kawai K, Nakatomi H, Saito N (2012) Significance of Simpson grading system in modern meningioma surgery: integration of the grade with MIB-1 labeling index as a key to predict the recurrence of WHO Grade I meningiomas. J Neurosurg 117(1):121–128CrossRef Oya S, Kawai K, Nakatomi H, Saito N (2012) Significance of Simpson grading system in modern meningioma surgery: integration of the grade with MIB-1 labeling index as a key to predict the recurrence of WHO Grade I meningiomas. J Neurosurg 117(1):121–128CrossRef
6.
go back to reference Choy W, Kim W, Nagasawa D et al (2011) The molecular genetics and tumor pathogenesis of meningiomas and the future directions of meningioma treatments. Neurosurg Focus 30(5):E6CrossRef Choy W, Kim W, Nagasawa D et al (2011) The molecular genetics and tumor pathogenesis of meningiomas and the future directions of meningioma treatments. Neurosurg Focus 30(5):E6CrossRef
7.
go back to reference Wang N, Osswald M (2018) Meningiomas: overview and new directions in therapy. Semin Neurol 38(1):112–120CrossRef Wang N, Osswald M (2018) Meningiomas: overview and new directions in therapy. Semin Neurol 38(1):112–120CrossRef
9.
go back to reference Luther E, Matus A, Eichberg DG, Shah AH, Ivan M (2019) Stimulated Raman histology for intraoperative guidance in the resection of a recurrent atypical spheno orbital meningioma a Case report and review of literature. Cureus 11(10):e5905PubMedPubMedCentral Luther E, Matus A, Eichberg DG, Shah AH, Ivan M (2019) Stimulated Raman histology for intraoperative guidance in the resection of a recurrent atypical spheno orbital meningioma a Case report and review of literature. Cureus 11(10):e5905PubMedPubMedCentral
10.
go back to reference Koljenović S, Schut TB, Vincent A, Kros JM, Puppels GJ (2005) Detection of meningioma in dura mater by Raman spectroscopy. Anal Chem 77(24):7958–7965CrossRef Koljenović S, Schut TB, Vincent A, Kros JM, Puppels GJ (2005) Detection of meningioma in dura mater by Raman spectroscopy. Anal Chem 77(24):7958–7965CrossRef
11.
go back to reference Zhou Y, Liu CH, Sun Y et al (2012) Human brain cancer studied by resonance Raman spectroscopy. J Biomed Opt 17(11):116021CrossRef Zhou Y, Liu CH, Sun Y et al (2012) Human brain cancer studied by resonance Raman spectroscopy. J Biomed Opt 17(11):116021CrossRef
12.
go back to reference Zhou Y, Liu CH, Wu B et al (2019) Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy. J Biomed Opt 24(9):1–12CrossRef Zhou Y, Liu CH, Wu B et al (2019) Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy. J Biomed Opt 24(9):1–12CrossRef
13.
go back to reference Liu CH, Boydston-White S, Weisberg A et al (2016) Vulnerable atherosclerotic plaque detection by resonance Raman spectroscopy. J Biomed Opt 21(12):127006CrossRef Liu CH, Boydston-White S, Weisberg A et al (2016) Vulnerable atherosclerotic plaque detection by resonance Raman spectroscopy. J Biomed Opt 21(12):127006CrossRef
15.
go back to reference Palozza P, Krinsky NI (1992) beta-Carotene and alpha-tocopherol are synergistic antioxidants. Arch Biochem Biophys 297(1):184–187CrossRef Palozza P, Krinsky NI (1992) beta-Carotene and alpha-tocopherol are synergistic antioxidants. Arch Biochem Biophys 297(1):184–187CrossRef
16.
go back to reference Darvin ME, Sterry W, Lademann J (2010) Resonance Raman spectroscopy as an effective tool for the determination of antioxidative stability of cosmetic formulations. J Biophotonics 3(1–2):82–88PubMed Darvin ME, Sterry W, Lademann J (2010) Resonance Raman spectroscopy as an effective tool for the determination of antioxidative stability of cosmetic formulations. J Biophotonics 3(1–2):82–88PubMed
17.
go back to reference Surmacki J, Musial J, Kordek R, Abramczyk H (2013) Raman imaging at biological interfaces: applications in breast cancer diagnosis. Mol Cancer 12:48CrossRef Surmacki J, Musial J, Kordek R, Abramczyk H (2013) Raman imaging at biological interfaces: applications in breast cancer diagnosis. Mol Cancer 12:48CrossRef
18.
go back to reference Brazhe A, Mathiesen C, Lauritzen M (2013) Multiscale vision model highlights spontaneous glial calcium waves recorded by 2-photon imaging in brain tissue. Neuroimage 68:192–202CrossRef Brazhe A, Mathiesen C, Lauritzen M (2013) Multiscale vision model highlights spontaneous glial calcium waves recorded by 2-photon imaging in brain tissue. Neuroimage 68:192–202CrossRef
20.
go back to reference Surmacki J, Brozek-Pluska B, Kordek R, Abramczyk H (2015) The lipid-reactive oxygen species phenotype of breast cancer Raman spectroscopy and mapping PCA and PLSDA for invasive ductal carcinoma and invasive lobular carcinoma. Molecular tumorigenic mechanisms beyond Warburg effect. Analyst 140(7):2121–33CrossRef Surmacki J, Brozek-Pluska B, Kordek R, Abramczyk H (2015) The lipid-reactive oxygen species phenotype of breast cancer Raman spectroscopy and mapping PCA and PLSDA for invasive ductal carcinoma and invasive lobular carcinoma. Molecular tumorigenic mechanisms beyond Warburg effect. Analyst 140(7):2121–33CrossRef
21.
go back to reference Mishra S, Nguyen HQ, Huang QR, Lin CK, Kuo JL, Patwari GN (2020) Vibrational spectroscopic signatures of hydrogen bond induced NH stretch-bend Fermi-resonance in amines the methylamine clusters and other N-H⋯N hydrogen-bonded complexes. J Chem Phys 153(19):194301CrossRef Mishra S, Nguyen HQ, Huang QR, Lin CK, Kuo JL, Patwari GN (2020) Vibrational spectroscopic signatures of hydrogen bond induced NH stretch-bend Fermi-resonance in amines the methylamine clusters and other N-H⋯N hydrogen-bonded complexes. J Chem Phys 153(19):194301CrossRef
22.
go back to reference Salunkhe S, Mishra SV, Ghorai A et al (2020) Metabolic rewiring in drug resistant cells exhibit higher OXPHOS and fatty acids as preferred major source to cellular energetics. Biochim Biophys Acta Bioenerg 1861(12):148300CrossRef Salunkhe S, Mishra SV, Ghorai A et al (2020) Metabolic rewiring in drug resistant cells exhibit higher OXPHOS and fatty acids as preferred major source to cellular energetics. Biochim Biophys Acta Bioenerg 1861(12):148300CrossRef
23.
go back to reference Jain M, Robinson BD, Wu B et al (2018) Exploring multiphoton microscopy as a novel tool to differentiate chromophobe renal cell carcinoma from oncocytoma in fixed tissue sections. Arch Pathol Lab Med 142(3):383–390CrossRef Jain M, Robinson BD, Wu B et al (2018) Exploring multiphoton microscopy as a novel tool to differentiate chromophobe renal cell carcinoma from oncocytoma in fixed tissue sections. Arch Pathol Lab Med 142(3):383–390CrossRef
24.
go back to reference Wu B, Nebylitsa SV, Mukherjee S, et al (2015) Quantitative diagnosis of bladder cancer by morphometric analysis of HE images. Proc SPIE 9303:930317 Wu B, Nebylitsa SV, Mukherjee S, et al (2015) Quantitative diagnosis of bladder cancer by morphometric analysis of HE images. Proc SPIE 9303:930317
25.
go back to reference Garcia CR, Slone SA, Dolecek TA, Huang B, Neltner JH, Villano JL (2019) Primary central nervous system tumor treatment and survival in the United States, 2004–2015. J Neurooncol 144(1):179–191CrossRef Garcia CR, Slone SA, Dolecek TA, Huang B, Neltner JH, Villano JL (2019) Primary central nervous system tumor treatment and survival in the United States, 2004–2015. J Neurooncol 144(1):179–191CrossRef
26.
go back to reference Hua L, Wang D, Zhu H et al (2020) Long-term outcomes of multimodality management for parasagittal meningiomas. J Neurooncol 147(2):441–450CrossRef Hua L, Wang D, Zhu H et al (2020) Long-term outcomes of multimodality management for parasagittal meningiomas. J Neurooncol 147(2):441–450CrossRef
27.
go back to reference Kwon SM, Kim JH, Yoo HJ et al (2020) Predictive factors for high-grade transformation in benign meningiomas. Clin Neurol Neurosurg 195:105897CrossRef Kwon SM, Kim JH, Yoo HJ et al (2020) Predictive factors for high-grade transformation in benign meningiomas. Clin Neurol Neurosurg 195:105897CrossRef
28.
go back to reference Hollon T, Lewis S, Freudiger CW, Sunney Xie X, Orringer DA (2016) Improving the accuracy of brain tumor surgery via Raman-based technology. Neurosurg Focus 40(3):E9CrossRef Hollon T, Lewis S, Freudiger CW, Sunney Xie X, Orringer DA (2016) Improving the accuracy of brain tumor surgery via Raman-based technology. Neurosurg Focus 40(3):E9CrossRef
29.
go back to reference Orringer DA, Pandian B, Niknafs YS et al (2017) Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nat Biomed Eng 1:0027CrossRef Orringer DA, Pandian B, Niknafs YS et al (2017) Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nat Biomed Eng 1:0027CrossRef
30.
go back to reference Morais CLM, Lilo T, Ashton KM et al (2019) Determination of meningioma brain tumour grades using Raman microspectroscopy imaging. Analyst 144(23):7024–7031CrossRef Morais CLM, Lilo T, Ashton KM et al (2019) Determination of meningioma brain tumour grades using Raman microspectroscopy imaging. Analyst 144(23):7024–7031CrossRef
31.
go back to reference Moroni F (1999) Tryptophan metabolism and brain function: focus on kynurenine and other indole metabolites. Eur J Pharmacol 375:87–100CrossRef Moroni F (1999) Tryptophan metabolism and brain function: focus on kynurenine and other indole metabolites. Eur J Pharmacol 375:87–100CrossRef
Metadata
Title
Intraoperative detection of human meningioma using a handheld visible resonance Raman analyzer
Authors
Liang Zhang
Yan Zhou
Binlin Wu
Shengjia Zhang
Ke Zhu
Cheng-hui Liu
Xinguang Yu
Robert R. Alfano
Publication date
01-03-2022
Publisher
Springer London
Published in
Lasers in Medical Science / Issue 2/2022
Print ISSN: 0268-8921
Electronic ISSN: 1435-604X
DOI
https://doi.org/10.1007/s10103-021-03390-2

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