Revising Fourier-transform infrared (FT-IR) and Raman spectroscopy towards brain cancer detection

Photodiagnosis and Photodynamic Therapy - Tập 38 - Trang 102785 - 2022
Taha Lilo1,2, Camilo L.M. Morais2, Catriona Shenton1, Arup Ray1, Nihal Gurusinghe1
1Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
2School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK

Tài liệu tham khảo

Skoog, 2007

Navas, 2008, Benefits of applying combined diffuse reflectance FTIR spectroscopy and principal component analysis for the study of blue tempera historical painting, Anal. Chim. Acta, 630, 141, 10.1016/j.aca.2008.10.008

Movasaghi, 2008, Fourier transform infrared (FTIR) spectroscopy of biological tissues, Appl. Spectrosc. Rev., 43, 134, 10.1080/05704920701829043

Livingston, 1973

Duraipandian, 2013, Near-infrared-excited confocal Raman spectroscopy advances in vivo diagnosis of cervical precancer, J. Biomed. Opt., 18, 10.1117/1.JBO.18.6.067007

Vandenabeele, 2018

Santos, 2017, Spectroscopy with computational analysis in virological studies: a decade (2006–2016), Trends Anal. Chem., 97, 244, 10.1016/j.trac.2017.09.015

Baker, 2014, Using Fourier transform IR spectroscopy to analyze biological materials, Nat. Protoc., 9, 1771, 10.1038/nprot.2014.110

Kelly, 2011, Biospectroscopy to metabolically profile biomolecular structure: a multistage approach linking computational analysis with biomarkers, J. Proteome Res., 10, 1437, 10.1021/pr101067u

Morais, 2019, Determination of meningioma brain tumour grades using Raman microspectroscopy imaging, Analyst, 144, 7024, 10.1039/C9AN01551E

Butler, 2016, Using Raman spectroscopy to characterize biological materials, Nat. Protoc., 11, 664, 10.1038/nprot.2016.036

Movasaghi, 2007, Raman spectroscopy of biological tissues, Appl. Spectrosc. Rev., 42, 493, 10.1080/05704920701551530

Poletto, 2012, Structural differences between wood species: evidence from chemical composition, FTIR spectroscopy, and thermogravimetric analysis, J. Appl. Polym. Sci., 126, E337, 10.1002/app.36991

Bury, 2020, Discrimination of fresh frozen non-tumour and tumour brain tissue using spectrochemical analyses and a classification model, Br. J. Neurosurg., 34, 40, 10.1080/02688697.2019.1679352

Hollon, 2016, Improving the accuracy of brain tumor surgery via Raman-based technology, Neurosurg. Focus, 40, E9, 10.3171/2015.12.FOCUS15557

Gajjar, 2013, Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis, Anal. Methods, 5, 89, 10.1039/C2AY25544H

Huntoon, 2020, Meningioma: a review of clinicopathological and molecular aspects, Front. Oncol., 10, 10.3389/fonc.2020.579599

Mehta, 2018, An early investigative serum Raman spectroscopy study of meningioma, Analyst, 143, 1916, 10.1039/C8AN00224J

Bury, 2019, Spectral classification for diagnosis involving numerous pathologies in a complex clinical setting: a neuro-oncology example, Spectrochim. Acta A Mol. Biomol. Spectrosc., 206, 89, 10.1016/j.saa.2018.07.078

Morais, 2020, Tutorial: multivariate classification for vibrational spectroscopy in biological samples, Nat. Protoc., 15, 2143, 10.1038/s41596-020-0322-8

Tandel, 2019, A review on a deep learning perspective in brain cancer classification, Cancers, 11, 111, 10.3390/cancers11010111

Theakstone, 2021, Rapid spectroscopic liquid biopsy for the universal detection of brain tumours, Cancers, 13, 3851, 10.3390/cancers13153851

Qu, 2021, Application of serum mid-infrared spectroscopy combined with an ensemble learning method in rapid diagnosis of gliomas, Anal. Methods, 13, 4642, 10.1039/D1AY00802A

Fabelo, 2018, SVM optimization for brain tumor identification using infrared spectroscopic samples, Sensors, 18, 4487, 10.3390/s18124487

Depciuch, 2020, Raman and FTIR spectroscopy in determining the chemical changes in healthy brain tissues and glioblastoma tumor tissues, Spectrochim. Acta A Mol. Biomol. Spectrosc., 225, 10.1016/j.saa.2019.117526

Kopec, 2021, Raman imaging and statistical methods for analysis various type of human brain tumors and breast cancers, Spectrochim. Acta A Mol. Biomol. Spectrosc., 262, 10.1016/j.saa.2021.120091

Riva, 2021, Glioma biopsies classification using raman spectroscopy and machine learning models on fresh tissue samples, Cancers, 13, 1073, 10.3390/cancers13051073

Zhang, 2020, Label-free serum detection based on Raman spectroscopy for the diagnosis and classification of glioma, J. Raman Spectrosc., 51, 1977, 10.1002/jrs.5931

Galli, 2019, Rapid label-free analysis of brain tumor biopsies by near infrared raman and fluorescence spectroscopy—a study of 209 patients, Front. Oncol., 9, 1165, 10.3389/fonc.2019.01165

Verma, 2016, Magnetic resonance spectroscopy - revisiting the biochemical and molecular milieu of brain tumors, BBA Clin., 5, 170, 10.1016/j.bbacli.2016.04.002

Marie, 2011, Metabolism and brain cancer, Clinics, 66, 33, 10.1590/S1807-59322011001300005

Ernestus, 2001, Polyamine metabolism in brain tumours: diagnostic relevance of quantitative biochemistry, J. Neurol. Neurosurg. Psychiatry, 71, 88, 10.1136/jnnp.71.1.88

Delgado-Martín, 2020, Advances in the knowledge of the molecular biology of glioblastoma and its impact in patient diagnosis, stratification, and treatment, Adv. Sci., 7, 10.1002/advs.201902971

Palani, 2010, Biochemical and cytogenetic analysis of brain tissues in different grades of glioma patients, Ann. Neurosci., 17, 120, 10.5214/ans.0972-7531.1017305

Cameron, 2020, Stratifying brain tumour histological sub-types: the application of ATR-FTIR serum spectroscopy in secondary care, Cancers, 12, 1710, 10.3390/cancers12071710

Ali, 2019, Detection of human brain tumours via evaluation of their biochemical composition using ATR-FTIR spectroscopy, Biomed. Phys. Eng. Express, 6, 10.1088/2057-1976/ab5cea

Hollon, 2021, Label-free brain tumor imaging using Raman-based methods, J. Neurooncol., 151, 393, 10.1007/s11060-019-03380-z

Anna, 2017, Novel strategies of Raman imaging for brain tumor research, Oncotarget, 8, 85290, 10.18632/oncotarget.19668

Steiner, 2003, Distinguishing and grading human gliomas by IR spectroscopy, Biopolymers, 72, 464, 10.1002/bip.10487

Nikulin, 1998, Near-optimal region selection for feature space reduction: novel preprocessing methods for classifying MR spectra, NMR Biomed., 11, 209, 10.1002/(SICI)1099-1492(199806/08)11:4/5<209::AID-NBM510>3.0.CO;2-5

Koljenović, 2005, Detection of meningioma in dura mater by Raman spectroscopy, Anal. Chem., 77, 7958, 10.1021/ac0512599

Zhou, 2012, Human brain cancer studied by resonance Raman spectroscopy, J. Biomed. Opt., 17, 10.1117/1.JBO.17.11.116021

Hands, 2014, Attenuated total reflection fourier transform infrared (ATR-FTIR) spectral discrimination of brain tumour severity from serum samples, J. Biophotonics, 7, 189, 10.1002/jbio.201300149

Smith, 2016, Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology, Analyst, 141, 3668, 10.1039/C5AN02452H

Cameron, 2019, Developing infrared spectroscopic detection for stratifying brain tumour patients: glioblastoma multiforme vs. Lymphoma, Analyst, 144, 6736, 10.1039/C9AN01731C

Butler, 2019, Development of high-throughput ATR-FTIR technology for rapid triage of brain cancer, Nat. Commun., 10, 4501, 10.1038/s41467-019-12527-5

Bury, 2019, Ex vivo Raman spectrochemical analysis using a handheld probe demonstrates high predictive capability of brain tumour status, Biosensors, 9, 49, 10.3390/bios9020049

Cameron, 2020, Interrogation of IDH1 status in gliomas by fourier transform infrared spectroscopy, Cancers, 12, 3682, 10.3390/cancers12123682

Morais, 2017, Comparing unfolded and two-dimensional discriminant analysis and support vector machines for classification of EEM data, Chemometr. Intell. Lab. Syst., 170, 1, 10.1016/j.chemolab.2017.09.001

Morais, 2019, A three-dimensional principal component analysis approach for exploratory analysis of hyperspectral data: identification of ovarian cancer samples based on Raman microspectroscopy imaging of blood plasma, Analyst, 144, 2312, 10.1039/C8AN02031K

Bro, 2014, Principal component analysis, Anal. Methods, 6, 2812, 10.1039/C3AY41907J

Brereton, 2014, Partial least squares discriminant analysis: taking the magic away, J. Chemom., 28, 213, 10.1002/cem.2609

Morais, 2019, Standardization of complex biologically derived spectrochemical datasets, Nat. Protoc., 14, 1546, 10.1038/s41596-019-0150-x

Morais, 2019, Improving data splitting for classification applications in spectrochemical analyses employing a random-mutation Kennard-Stone algorithm approach, Bioinformatics, 35, 5257, 10.1093/bioinformatics/btz421