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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: 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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  • 4
    Language: English
    In: Journal of neuro-oncology, 2016-02-13, Vol.127 (3), p.463-472
    Description: The ability to diagnose cancer rapidly with high sensitivity and specificity is essential to exploit advances in new treatments to lead significant reductions in mortality and morbidity. Current cancer diagnostic tests observing tissue architecture and specific protein expression for specific cancers suffer from inter-observer variability, poor detection rates and occur when the patient is symptomatic. A new method for the detection of cancer using 1 μl of human serum, attenuated total reflection—Fourier transform infrared spectroscopy and pattern recognition algorithms is reported using a 433 patient dataset (3897 spectra). To the best of our knowledge, we present the largest study on serum mid-infrared spectroscopy for cancer research. We achieve optimum sensitivities and specificities using a Radial Basis Function Support Vector Machine of between 80.0 and 100 % for all strata and identify the major spectral features, hence biochemical components, responsible for the discrimination within each stratum. We assess feature fed-SVM analysis for our cancer versus non-cancer model and achieve 91.5 and 83.0 % sensitivity and specificity respectively. We demonstrate the use of infrared light to provide a spectral signature from human serum to detect, for the first time, cancer versus non-cancer, metastatic cancer versus organ confined, brain cancer severity and the organ of origin of metastatic disease from the same sample enabling stratified diagnostics depending upon the clinical question asked.
    Subject(s): Adolescent ; Adult ; Aged ; Aged, 80 and over ; Algorithms ; Analysis ; ATR-FTIR ; Biomarkers, Tumor - blood ; Brain Neoplasms - blood ; Brain Neoplasms - diagnosis ; Brain tumors ; Cancer ; Case-Control Studies ; Cell Differentiation ; Diagnosis ; Diagnostics ; Early Detection of Cancer ; Female ; Follow-Up Studies ; Glioma ; Gliomas ; Health aspects ; Humans ; Infrared spectroscopy ; Laboratory Investigation ; Male ; Medicine ; Medicine & Public Health ; Metastasis ; Middle Aged ; Mortality ; Neoplasm Grading ; Neurology ; Oncology ; Prognosis ; Rapid ; Serum ; Spectroscopy ; Spectroscopy, Fourier Transform Infrared - methods ; Support Vector Machine ; Young Adult
    ISSN: 0167-594X
    E-ISSN: 1573-7373
    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
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  • 6
    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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  • 7
    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
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  • 8
    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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  • 9
    Language: English
    In: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy, 2022-05-15, Vol.273
    Description: [Display omitted] •Raman hypespectral imaging can diagnose meningiomas tumour grades.•Three-dimensional discriminant analysis algorithms were applied.•The technique is reagent-free, quick and accurate.•High test accuracy, sensitivity and specificity were observed.•This technique could be a robust diagnostic tool. Meningiomas remains a clinical dilemma. They are the commonest “benign” types of brain tumours and, although being typically benign, they are divided into three WHO grades categories (I, II and III) which are associated with the tumour growth rate and likelihood of recurrence. Recurrence depends on extend of surgery as well as histopathological diagnosis. There is a marked variation amongst surgeons in the follow-up arrangements for their patients even within the same unit which has a significant clinical, and financial implication. Knowing the tumour grade rapidly is an important factor to predict surgical outcomes and adequate patient treatment. Clinical follow up sometimes is haphazard and not based on clear evidence. Spectrochemical techniques are a powerful tool for cancer diagnostics. Raman hyperspectral imaging is able to generate spatially-distributed spectrochemical signatures with great sensitivity. Using this technique, 95 brain tissue samples (66 meningiomas WHO grade I, 24 meningiomas WHO grade II and 5 meningiomas that reoccurred) were analysed in order to discriminate grade I and grade II samples. Newly-developed three-dimensional discriminant analysis algorithms were used to process the hyperspectral imaging data in a 3D fashion. Three-dimensional principal component analysis quadratic discriminant analysis (3D-PCA-QDA) was able to distinguish grade I and grade II meningioma samples with 96% test accuracy (100% sensitivity and 95% specificity). This technique is here shown to be a high-throughput, reagent-free, non-destructive, and can give accurate predictive information regarding the meningioma tumour grade, hence, having enormous clinical potential with regards to being developed for intra-operative real-time assessment of disease.
    Subject(s): Algorithms ; Biospectroscopy ; Brain cancer ; Brain tumors ; Cancer ; Hospitals ; Medical research ; Medicine, Experimental ; Meningiomas ; Raman hyperspectral imaging ; Three-dimensional classification
    ISSN: 1386-1425
    Source: Alma/SFX Local Collection
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  • 10
    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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