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  • 1
    Language: English
    In: Analytical and bioanalytical chemistry, 2020-11-26, Vol.413 (3), p.911-922
    Description: Biofluids, such as blood plasma or serum, are currently being evaluated for cancer detection using vibrational spectroscopy. These fluids contain information of key biomolecules, such as proteins, lipids, carbohydrates and nucleic acids, that comprise spectrochemical patterns to differentiate samples. Raman is a water-free and practically non-destructive vibrational spectroscopy technique, capable of recording spectrochemical fingerprints of biofluids with minimum or no sample preparation. Herein, we compare the performance of these two common biofluids (blood plasma and serum) together with ascitic fluid, towards ovarian cancer detection using Raman microspectroscopy. Samples from thirty-eight patients were analysed ( n  = 18 ovarian cancer patients, n  = 20 benign controls) through different spectral pre-processing and discriminant analysis techniques. Ascitic fluid provided the best class separation in both unsupervised and supervised discrimination approaches, where classification accuracies, sensitivities and specificities above 80% were obtained, in comparison to 60–73% with plasma or serum. Ascitic fluid appears to be rich in collagen information responsible for distinguishing ovarian cancer samples, where collagen-signalling bands at 1004 cm −1 (phenylalanine), 1334 cm −1 (CH 3 CH 2 wagging vibration), 1448 cm −1 (CH 2 deformation) and 1657 cm −1 (Amide I) exhibited high statistical significance for class differentiation ( P  〈 0.001). The efficacy of vibrational spectroscopy, in particular Raman spectroscopy, combined with ascitic fluid analysis, suggests a potential diagnostic method for ovarian cancer. Graphical abstract Raman microspectroscopy analysis of ascitic fluid allows for discrimination of patients with benign gynaecological conditions or ovarian cancer.
    Subject(s): Analysis ; Analytical Chemistry ; Ascites ; Ascitic fluid ; Biochemistry ; Biofluids ; Biomolecules ; Blood ; Blood plasma ; Cancer ; Carbohydrates ; Characterization and Evaluation of Materials ; Chemistry ; Chemistry and Materials Science ; Collagen ; Collagens ; Comparative analysis ; Diagnosis ; Diagnostic systems ; Discriminant analysis ; Food Science ; general ; Laboratory Medicine ; Lipids ; Liquid biopsies ; Methods ; Monitoring/Environmental Analysis ; Nondestructive testing ; Nucleic acids ; Ovarian cancer ; Ovarian carcinoma ; Phenylalanine ; Raman spectroscopy ; Research Paper ; Sample preparation ; Serum ; Spectroscopy ; Spectrum analysis ; Statistical methods ; Vibration
    ISSN: 1618-2642
    E-ISSN: 1618-2650
    Source: Academic Search Ultimate
    Source: Alma/SFX Local Collection
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  • 2
    Language: English
    In: Analytical and bioanalytical chemistry, 2020-04-25, Vol.412 (17), p.4077-4087
    Description: Raman spectroscopy is a fast and sensitive technique able to identify molecular changes in biological specimens. Herein, we report on three cases where Raman microspectroscopy was used to distinguish normal vs. oesophageal adenocarcinoma (OAC) (case 1) and Barrett’s oesophagus vs. OAC (cases 2 and 3) in a non-destructive and highly accurate fashion. Normal and OAC tissues were discriminated using principal component analysis plus linear discriminant analysis (PCA-LDA) with 97% accuracy (94% sensitivity and 100% specificity) (case 1); Barrett’s oesophagus vs. OAC tissues were discriminated with accuracies ranging from 98 to 100% (97–100% sensitivity and 100% specificity). Spectral markers responsible for class differentiation were obtained through the difference-between-mean spectrum for each group and the PCA loadings, where C–O–C skeletal mode in β-glucose (900 cm −1 ), lipids (967 cm −1 ), phosphodioxy (1296 cm −1 ), deoxyribose (1456 cm −1 ) and collagen (1445, 1665 cm −1 ) were associated with normal and OAC tissue differences. Phenylalanine (1003 cm −1 ), proline/collagen (1066, 1445 cm −1 ), phospholipids (1130 cm −1 ), CH 2 angular deformation (1295 cm −1 ), disaccharides (1462 cm −1 ) and proteins (amide I, 1672/5 cm −1 ) were associated with Barrett’s oesophagus and OAC tissue differences. These findings show the potential of using Raman microspectroscopy imaging for fast and accurate diagnoses of oesophageal pathologies and establishing subtle molecular changes predisposing to adenocarcinoma in a clinical setting. Graphical abstract Graphical abstract demonstrating how oesophageal tissue is processed through Raman mapping analysis in order to detect spectral differences between stages of oesophageal transformation to adenocarcinoma
    Subject(s): Adenocarcinoma ; Adenocarcinoma - chemistry ; Adenocarcinoma - diagnosis ; Adenocarcinoma - pathology ; Aged ; Analytical Chemistry ; Barrett’s oesophagus ; Biochemistry ; Characterization and Evaluation of Materials ; Chemistry ; Chemistry and Materials Science ; Collagen ; Collagens ; Disaccharides ; Discriminant Analysis ; Esophageal Neoplasms - chemistry ; Esophageal Neoplasms - diagnosis ; Esophageal Neoplasms - pathology ; Esophagus ; Esophagus - chemistry ; Esophagus - pathology ; Female ; Food Science ; general ; Humans ; Laboratory Medicine ; Lipids ; Male ; Mapping ; Monitoring/Environmental Analysis ; Oesophageal adenocarcinoma ; Phenylalanine ; Phospholipids ; Principal Component Analysis ; Principal components analysis ; Proline ; Raman mapping ; Raman spectroscopy ; Research Paper ; Spectral sensitivity ; Spectrum Analysis, Raman - methods ; Tissue analysis ; Tissues
    ISSN: 1618-2642
    E-ISSN: 1618-2650
    Source: Academic Search Ultimate
    Source: Alma/SFX Local Collection
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  • 3
    Language: English
    In: Cancers, 2020-06-27, Vol.12 (7), p.1710
    Description: Patients living with brain tumours have the highest average years of life lost of any cancer, ultimately reducing average life expectancy by 20 years. Diagnosis depends on brain imaging and most often confirmatory tissue biopsy for histology. The majority of patients experience non-specific symptoms, such as headache, and may be reviewed in primary care on multiple occasions before diagnosis is made. Sixty-two per cent of patients are diagnosed on brain imaging performed when they deteriorate and present to the emergency department. Histological diagnosis from invasive surgical biopsy is necessary prior to definitive treatment, because imaging techniques alone have difficulty in distinguishing between several types of brain cancer. However, surgery itself does not necessarily control tumour growth, and risks morbidity for the patient. Due to their similar features on brain scans, glioblastoma, primary central nervous system lymphoma and brain metastases have been known to cause radiological confusion. Non-invasive tests that support stratification of tumour subtype would enhance early personalisation of treatment selection and reduce the delay and risks associated with surgery for many patients. Techniques involving vibrational spectroscopy, such as attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer diagnostics. In this study, infrared spectra from 641 blood serum samples obtained from brain cancer and control patients have been collected. Firstly, we highlight the capability of ATR-FTIR to distinguish between healthy controls and brain cancer at sensitivities and specificities above 90%, before defining subtle differences in protein secondary structures between patient groups through Amide I deconvolution. We successfully differentiate several types of brain lesions (glioblastoma, meningioma, primary central nervous system lymphoma and metastasis) with balanced accuracies 〉80%. A reliable blood serum test capable of stratifying brain tumours in secondary care could potentially avoid surgery and speed up the time to definitive therapy, which would be of great value for both neurologists and patients.
    Subject(s): Biopsy ; Blood tests ; Brain Cancer ; Brain tumors ; Cancer ; Cancer therapies ; Central nervous system ; Data analysis ; Diagnosis ; Diagnostics ; Emergency medical care ; Fourier transforms ; Glioblastoma ; Headache ; Infrared ; Invasiveness ; Life span ; Lymphoma ; Meningioma ; Metastases ; Metastasis ; Morbidity ; Neuroimaging ; Patients ; Principal components analysis ; Radiation therapy ; Serum ; Spectroscopy ; Spectrum analysis ; Surgery ; Tumors ; Tumour Stratification
    ISSN: 2072-6694
    E-ISSN: 2072-6694
    Source: Academic Search Ultimate
    Source: PubMed Central
    Source: Alma/SFX Local Collection
    Source: DOAJ Directory of Open Access Journals - Not for CDI Discovery
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  • 4
    Language: English
    In: Analytical and bioanalytical chemistry, 2019-12-21, Vol.412 (5), p.1077-1086
    Description: Meningiomas are the commonest types of tumours in the central nervous system (CNS). It is a benign type of tumour divided into three WHO grades (I, II and III) associated with tumour growth rate and likelihood of recurrence, where surgical outcomes and patient treatments are dependent on the meningioma grade and histological subtype. The development of alternative approaches based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy could aid meningioma grade determination and its biospectrochemical profiling in an automated fashion. Herein, ATR-FTIR in combination with chemometric techniques is employed to distinguish grade I, grade II and grade I meningiomas that re-occurred. Ninety-nine patients were investigated in this study where their formalin-fixed paraffin-embedded (FFPE) brain tissue samples were analysed by ATR-FTIR spectroscopy. Subsequent classification was performed via principal component analysis plus linear discriminant analysis (PCA-LDA) and partial least squares plus discriminant analysis (PLS-DA). PLS-DA gave the best results where grade I and grade II meningiomas were discriminated with 79% accuracy, 80% sensitivity and 73% specificity, while grade I versus grade I recurrence and grade II versus grade I recurrence were discriminated with 94% accuracy (94% sensitivity and specificity) and 97% accuracy (97% sensitivity and 100% specificity), respectively. Several wavenumbers were identified as possible biomarkers towards tumour differentiation. The majority of these were associated with lipids, protein, DNA/RNA and carbohydrate alterations. These findings demonstrate the potential of ATR-FTIR spectroscopy towards meningioma grade discrimination as a fast, low-cost, non-destructive and sensitive tool for clinical settings. Graphical abstract Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to discriminate meningioma WHO grade I, grade II and grade I recurrence tumours.
    Subject(s): Accuracy ; Analysis ; Analytical Chemistry ; ATR-FTIR ; Biochemistry ; Biomarkers ; Carbohydrates ; Central nervous system ; Characterization and Evaluation of Materials ; Chemistry ; Chemistry and Materials Science ; Chemometrics ; Deoxyribonucleic acid ; Differentiation ; Discriminant Analysis ; DNA ; Food Science ; Fourier transform infrared spectroscopy ; Fourier transforms ; general ; Growth rate ; Humans ; Identification and classification ; Infrared reflection ; Infrared spectroscopy ; Laboratory Medicine ; Lipids ; Meningeal Neoplasms - chemistry ; Meningioma ; Meningioma - chemistry ; Methods ; Monitoring/Environmental Analysis ; Paraffin ; Paraffins ; Principal Component Analysis ; Principal components analysis ; Profiling ; Research Paper ; Ribonucleic acid ; RNA ; Sensitivity ; Sensitivity and Specificity ; Spectroscopy ; Spectroscopy, Fourier Transform Infrared - methods ; Spectrum analysis ; Tissue analysis ; Tumors ; Usage
    ISSN: 1618-2642
    E-ISSN: 1618-2650
    Source: Academic Search Ultimate
    Source: Alma/SFX Local Collection
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  • 5
    Language: English
    In: Scientific reports, 2022-01-20, Vol.12 (1), p.1102-1102
    Description: Brain metastases comprise 40% of all metastatic tumours and breast tumours are among the tumours that most commonly metastasise to the brain, the role that epigenetic gene dysregulation plays in this process is not well understood. We carried out 450 K methylation array analysis to investigate epigenetically dysregulated genes in breast to brain metastases (BBM) compared to normal breast tissues (BN) and primary breast tumours (BP). For this, we referenced 450 K methylation data for BBM tumours prepared in our laboratory with BN and BP from The Cancer Genome Atlas. Experimental validation on our initially identified genes, in an independent cohort of BP and in BBM and their originating primary breast tumours using Combined Bisulphite and Restriction Analysis (CoBRA) and Methylation Specific PCR identified three genes (RP11-713P17.4, MIR124-2, NUS1P3) that are hypermethylated and three genes (MIR3193, CTD-2023M8.1 and MTND6P4) that are hypomethylated in breast to brain metastases. In addition, methylation differences in candidate genes between BBM tumours and originating primary tumours shows dysregulation of DNA methylation occurs either at an early stage of tumour evolution (in the primary tumour) or at a later evolutionary stage (where the epigenetic change is only observed in the brain metastasis). Epigentic changes identified could also be found when analysing tumour free circulating DNA (tfcDNA) in patient's serum taken during BBM biopsies. Epigenetic dysregulation of RP11-713P17.4, MIR3193, MTND6P4 are early events suggesting a potential use for these genes as prognostic markers.
    Subject(s): Biomarkers, Tumor - genetics ; Biopsy ; Brain - metabolism ; Brain Neoplasms - genetics ; Breast cancer ; Breast Neoplasms - genetics ; Breast Neoplasms - pathology ; Coding ; Databases, Genetic ; Deoxyribonucleic acid ; DNA ; DNA - genetics ; DNA methylation ; DNA Methylation - genetics ; Epigenesis, Genetic - genetics ; Epigenetics ; Epigenomics ; Female ; Gene Expression - genetics ; Gene Expression Profiling - methods ; Gene Expression Regulation, Neoplastic - genetics ; Genomes ; Humans ; Metastases ; Metastasis ; MicroRNAs ; Neoplasm Metastasis - genetics ; Prognosis ; Promoter Regions, Genetic - genetics ; Receptors, Cell Surface ; RNA, Untranslated - genetics ; Transcriptome - genetics ; Tumors
    E-ISSN: 2045-2322
    Source: Nature Open Access
    Source: Academic Search Ultimate
    Source: PubMed Central
    Source: DOAJ Directory of Open Access Journals - Not for CDI Discovery
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  • 6
    Language: English
    In: Scientific reports, 2016-02-04, Vol.6 (1), p.20173-20173
    Description: Accurate early diagnosis is critical to patient survival, management and quality of life. Biofluids are key to early diagnosis due to their ease of collection and intimate involvement in human function. Large-scale mid-IR imaging of dried fluid deposits offers a high-throughput molecular analysis paradigm for the biomedical laboratory. The exciting advent of tuneable quantum cascade lasers allows for the collection of discrete frequency infrared data enabling clinically relevant timescales. By scanning targeted frequencies spectral quality, reproducibility and diagnostic potential can be maintained while significantly reducing acquisition time and processing requirements, sampling 16 serum spots with 0.6, 5.1 and 15% relative standard deviation (RSD) for 199, 14 and 9 discrete frequencies respectively. We use this reproducible methodology to show proof of concept rapid diagnostics; 40 unique dried liquid biopsies from brain, breast, lung and skin cancer patients were classified in 2.4 cumulative seconds against 10 non-cancer controls with accuracies of up to 90%.
    Subject(s): Automation ; Biopsy ; Body Fluids - chemistry ; Brain Neoplasms - metabolism ; Brain Neoplasms - pathology ; Breast cancer ; Breast Neoplasms - metabolism ; Breast Neoplasms - pathology ; Dried Blood Spot Testing - instrumentation ; Dried Blood Spot Testing - methods ; Female ; Frequencies ; Humans ; Lasers ; Lasers, Semiconductor ; Lung cancer ; Microscopy, Confocal ; Neuroimaging ; Quality of life ; Reproducibility of Results ; Scanning ; Skin cancer ; Skin Neoplasms - metabolism ; Skin Neoplasms - pathology ; Spectrophotometry, Infrared - instrumentation ; Spectrophotometry, Infrared - methods
    ISSN: 2045-2322
    E-ISSN: 2045-2322
    Source: Nature Open Access
    Source: Academic Search Ultimate
    Source: PubMed Central
    Source: DOAJ Directory of Open Access Journals - Not for CDI Discovery
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  • 7
    Language: English
    In: Biosensors (Basel), 2019-06-01, Vol.9 (2), p.49
    Description: With brain tumour incidence increasing, there is an urgent need for better diagnostic tools. Intraoperatively, brain tumours are diagnosed using a smear preparation reported by a neuropathologist. These have many limitations, including the time taken for the specimen to reach the pathology department and for results to be communicated to the surgeon. There is also a need to assist with resection rates and identifying infiltrative tumour edges intraoperatively to improve clearance. We present a novel study using a handheld Raman probe in conjunction with gold nanoparticles, to detect primary and metastatic brain tumours from fresh brain tissue sent for intraoperative smear diagnosis. Fresh brain tissue samples sent for intraoperative smear diagnosis were tested using the handheld Raman probe after application of gold nanoparticles. Derived Raman spectra were inputted into forward feature extraction algorithms to build a predictive model for sensitivity and specificity of outcome. These results demonstrate an ability to detect primary from metastatic tumours (especially for normal and low grade lesions), in which accuracy, sensitivity and specificity were respectively equal to 98.6%, 94.4% and 99.5% for normal brain tissue; 96.1%, 92.2% and 97.0% for low grade glial tumours; 90.3%, 89.7% and 90.6% for high grade glial tumours; 94.8%, 63.9% and 97.1% for meningiomas; 95.4%, 79.2% and 98.8% for metastases; and 99.6%, 88.9% and 100% for lymphoma, based on smear samples (kappa = 0.87). Similar results were observed when compared to the final formalin-fixed paraffin embedded tissue diagnosis (kappa = 0.85). Overall, our results have demonstrated the ability of Raman spectroscopy to match results provided by intraoperative smear diagnosis and raise the possibility of use intraoperatively to aid surgeons by providing faster diagnosis. Moving this technology into theatre will allow it to develop further and thus reach its potential in the clinical arena.
    Subject(s): Accuracy ; Algorithms ; Biopsy ; Brain ; Brain cancer ; Brain surgery ; Brain tumors ; brain tumour diagnosis ; Chemistry ; Chemistry, Analytical ; classification ; Diagnosis ; Feature extraction ; forward feature extraction algorithm ; Gold ; Instruments & Instrumentation ; intraoperative use ; Laboratories ; Lymphatic system ; Lymphoma ; Metastases ; Nanoparticles ; Nanoscience & Nanotechnology ; Neuropathology ; Paraffin ; Paraffins ; Physical Sciences ; Prediction models ; Principal components analysis ; Raman probe ; Raman spectra ; Raman spectroscopy ; Science & Technology ; Science & Technology - Other Topics ; Sensitivity ; Software ; Spectrochemical analysis ; Spectrum analysis ; Surgeons ; Technology ; Tissues ; Tumors
    ISSN: 2079-6374
    E-ISSN: 2079-6374
    Source: Web of Science - Science Citation Index Expanded - 2019〈img src="http://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /〉
    Source: PubMed Central
    Source: DOAJ Directory of Open Access Journals - Not for CDI Discovery
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  • 8
    Language: English
    In: Journal of biophotonics, 2020-03, Vol.13 (3), p.e201960132-n/a
    Description: The aim of this study was to determine whether Raman spectroscopy combined with chemometric analysis can be applied to interrogate biofluids (plasma, serum, saliva and urine) towards detecting oesophageal stages through to oesophageal adenocarcinoma [normal/squamous epithelium, inflammatory, Barrett's, low‐grade dysplasia, high‐grade dysplasia and oesophageal adenocarcinoma (OAC)]. The chemometric analysis of the spectral data was performed using principal component analysis, successive projections algorithm or genetic algorithm (GA) followed by quadratic discriminant analysis (QDA). The genetic algorithm quadratic discriminant analysis (GA‐QDA) model using a few selected wavenumbers for saliva and urine samples achieved 100% classification for all classes. For plasma and serum, the GA‐QDA model achieved excellent accuracy in all oesophageal stages (〉90%). The main GA‐QDA features responsible for sample discrimination were: 1012 cm−1 (C─O stretching of ribose), 1336 cm−1 (Amide III and CH2 wagging vibrations from glycine backbone), 1450 cm−1 (methylene deformation) and 1660 cm−1 (Amide I). The results of this study are promising and support the concept that Raman on biofluids may become a useful and objective diagnostic tool to identify oesophageal disease stages from squamous epithelium to OAC. Four biofluids (plasma, serum, urine and saliva) were measured through Raman spectroscopy in order to detect oesophageal transformation stages to adenocarcinoma.
    Subject(s): Adenocarcinoma ; Algorithms ; biofluids ; chemometrics ; classification techniques ; Diagnostic software ; Diagnostic systems ; Discriminant analysis ; Discrimination ; Dysplasia ; Epithelium ; Esophagus ; Genetic algorithms ; Genetic analysis ; Genetic transformation ; Glycine ; Inflammation ; Model accuracy ; oesophageal cancer ; Principal components analysis ; Raman spectroscopy ; Ribose ; Saliva ; Vibrations
    ISSN: 1864-063X
    E-ISSN: 1864-0648
    Source: Get It Now
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  • 9
    Language: English
    In: Journal of biophotonics, 2014-04, Vol.7 (3-4), p.189-199
    Description: Gliomas are the most frequent primary brain tumours in adults with over 9,000 people diagnosed each year in the UK. A rapid, reagent‐free and cost‐effective diagnostic regime using serum spectroscopy would allow for rapid diagnostic results and for swift treatment planning and monitoring within the clinical environment. We report the use of ATR‐FTIR spectral data combined with a RBF‐SVM for the diagnosis of gliomas (high‐grade and low‐grade) from non‐cancer with sensitivities and specificities on average of 93.75 and 96.53% respectively. The proposed diagnostic regime has the ability to reduce mortality and morbidity rates. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
    Subject(s): Adolescent ; Adult ; Aged ; Aged, 80 and over ; ATR-FTIR ; Brain Neoplasms - blood ; Brain Neoplasms - diagnosis ; Brain tumors ; cancer ; Drugstores ; Early Detection of Cancer ; Female ; filtrate ; glioma ; Glioma - blood ; Glioma - diagnosis ; Gliomas ; Hospitals ; Humans ; infrared ; Male ; Mass Screening - methods ; Middle Aged ; Mortality ; Pharmacy ; rapid ; Reproducibility of Results ; Sensitivity and Specificity ; serum ; spectroscopy ; Spectroscopy, Fourier Transform Infrared - methods ; Young Adult
    ISSN: 1864-063X
    E-ISSN: 1864-0648
    Source: Get It Now
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  • 10
    Language: English
    In: British journal of neurosurgery, 2020-01-02, Vol.34 (1), p.40-45
    Description: Introduction: In order for brain tumours to be successfully treated, maximal resection is beneficial. A method to detect infiltrative tumour edges intraoperatively, improving on current methods would be clinically useful. Vibrational spectroscopy offers the potential to provide a handheld, reagent-free method for tumour detection. Purpose: This study was designed to determine the ability of both Raman and Fourier-transform infrared (FTIR) spectroscopy towards differentiating between normal brain tissue, glioma or meningioma. Method: Unfixed brain tissue, which had previously only been frozen, comprising normal, glioma or meningioma tissue was placed onto calcium fluoride slides for analysis using Raman and attenuated total reflection (ATR)-FTIR spectroscopy. Matched haematoxylin and eosin slides were used to confirm tumour areas. Analyses were then conducted to generate a classification model. Results: This study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to discriminate tumour from non-tumour fresh frozen brain tissue with 94% and 97.2% of cases correctly classified, with sensitivities of 98.8% and 100%, respectively. This decreases when spectroscopy is used to determine tumour type. Conclusion: The study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to detect tumour tissue from non-tumour brain tissue with a high degree of accuracy. This demonstrates the ability of spectroscopy when targeted for a cancer diagnosis. However, further improvement would be required for a classification model to determine tumour type using this technology, in order to make this tool clinically viable.
    Subject(s): Brain cancer ; Brain tumours ; classification model ; intraoperative diagnosis ; neurosurgery ; spectrochemical analyses ; Spectrum analysis
    ISSN: 0268-8697
    E-ISSN: 1360-046X
    Source: Academic Search Ultimate
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