scholarly journals Intraoperative discrimination of native meningioma and dura mater by Raman spectroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Finn Jelke ◽  
Giulia Mirizzi ◽  
Felix Kleine Borgmann ◽  
Andreas Husch ◽  
Rédouane Slimani ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Dura Mater ◽  
Vibrational Analysis ◽  
Histopathological Analysis ◽  
Label Free ◽  
Fresh Tissue ◽  
Tissue Samples ◽  
Surgical Specimen ◽  
Additional Processing ◽  
External Test

AbstractMeningiomas are among the most frequent tumors of the central nervous system. For a total resection, shown to decrease recurrences, it is paramount to reliably discriminate tumor tissue from normal dura mater intraoperatively. Raman spectroscopy (RS) is a non-destructive, label-free method for vibrational analysis of biochemical molecules. On the microscopic level, RS was already used to differentiate meningioma from dura mater. In this study we test its suitability for intraoperative macroscopic meningioma diagnostics. RS is applied to surgical specimen of intracranial meningiomas. The main purpose is the differentiation of tumor from normal dura mater, in order to potentially accelerate the diagnostic workflow. The collected meningioma and dura mater samples (n = 223 tissue samples from a total of 59 patients) are analyzed under untreated conditions using a new partially robotized RS acquisition system. Spectra (n = 1273) are combined with the according histopathological analysis for each sample. Based on this, a classifier is trained via machine learning. Our trained classifier separates meningioma and dura mater with a sensitivity of 96.06 $$\pm $$ ± 0.03% and a specificity of 95.44 $$\pm $$ ± 0.02% for internal fivefold cross validation and 100% and 93.97% if validated with an external test set. RS is an efficient method to discriminate meningioma from healthy dura mater in fresh tissue samples without additional processing or histopathological imaging. It is a quick and reliable complementary diagnostic tool to the neuropathological workflow and has potential for guided surgery. RS offers a safe way to examine unfixed surgical specimens in a perioperative setting.

scholarly journals Glioma biopsies Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1073
Author(s):  
Marco Riva ◽  
Tommaso Sciortino ◽  
Riccardo Secoli ◽  
Ester D’Amico ◽  
Sara Moccia ◽  
...  
Keyword(s):  
Machine Learning ◽  
Raman Spectroscopy ◽  
Brain Tissue ◽  
Ex Vivo ◽  
Biological Significance ◽  
Normal Brain ◽  
Fresh Tissue ◽  
Tissue Samples ◽  
Glioma Resection

Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.

scholarly journals Rapid intraoperative molecular genetic classification of gliomas using Raman spectroscopy

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Laurent James Livermore ◽  
Martin Isabelle ◽  
Ian Mac Bell ◽  
Connor Scott ◽  
John Walsby-Tickle ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Molecular Genetic ◽  
Classification Model ◽  
Wild Type ◽  
Genetic Classification ◽  
Fresh Tissue ◽  
Tissue Samples ◽  
Genetic Subtypes ◽  
Classification Of Gliomas

Abstract Background The molecular genetic classification of gliomas, particularly the identification of isocitrate dehydrogenase (IDH) mutations, is critical for clinical and surgical decision-making. Raman spectroscopy probes the unique molecular vibrations of a sample to accurately characterize its molecular composition. No sample processing is required allowing for rapid analysis of tissue. The aim of this study was to evaluate the ability of Raman spectroscopy to rapidly identify the common molecular genetic subtypes of diffuse glioma in the neurosurgical setting using fresh biopsy tissue. In addition, classification models were built using cryosections, formalin-fixed paraffin-embedded (FFPE) sections and LN-18 (IDH-mutated and wild-type parental cell) glioma cell lines. Methods Fresh tissue, straight from neurosurgical theatres, underwent Raman analysis and classification into astrocytoma, IDH-wild-type; astrocytoma, IDH-mutant; or oligodendroglioma. The genetic subtype was confirmed on a parallel section using immunohistochemistry and targeted genetic sequencing. Results Fresh tissue samples from 62 patients were collected (36 astrocytoma, IDH-wild-type; 21 astrocytoma, IDH-mutated; 5 oligodendroglioma). A principal component analysis fed linear discriminant analysis classification model demonstrated 79%–94% sensitivity and 90%–100% specificity for predicting the 3 glioma genetic subtypes. For the prediction of IDH mutation alone, the model gave 91% sensitivity and 95% specificity. Seventy-nine cryosections, 120 FFPE samples, and LN18 cells were also successfully classified. Meantime for Raman data collection was 9.5 min in the fresh tissue samples, with the process from intraoperative biopsy to genetic classification taking under 15 min. Conclusion These data demonstrate that Raman spectroscopy can be used for the rapid, intraoperative, classification of gliomas into common genetic subtypes.

scholarly journals Biochemical Profiles of In Vivo Oral Mucosa by Using a Portable Raman Spectroscopy System

Optics ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 134-147
Author(s):  
Marcelo Saito Nogueira ◽  
Victoria Ribeiro ◽  
Marianna Pires ◽  
Felipe Peralta ◽  
Luis Felipe das Chagas e Silva de Carvalho
Keyword(s):  
Raman Spectroscopy ◽  
Biochemical Characterization ◽  
Principal Component ◽  
Histopathological Analysis ◽  
Label Free ◽  
Healthy Individuals ◽  
Normal Tissues ◽  
The Difference

Most oral injuries are diagnosed by histopathological analysis of invasive and time-consuming biopsies. This analysis and conventional clinical observation cannot identify biochemically altered tissues predisposed to malignancy if no microstructural changes are detectable. With this in mind, detailed biochemical characterization of normal tissues and their differentiation features on healthy individuals is important in order to recognize biomolecular changes associated with early tissue predisposition to malignant transformation. Raman spectroscopy is a label-free method for characterization of tissue structure and specific composition. In this study, we used Raman spectroscopy to characterize the biochemistry of in vivo oral tissues of healthy individuals. We investigated this biochemistry based on the vibrational modes related to Raman spectra of four oral subsites (buccal, gingiva, lip and tongue) of ten volunteers as well as with principal component (PC) loadings for the difference between the four types of oral subsites. Therefore, we determined the biochemical characteristics of each type of healthy oral subsite and those corresponding to differentiation of the four types of subsites. In addition, we developed a spectral reference of oral healthy tissues of individuals in the Brazilian population for future diagnosis of early pathological conditions using real-time, noninvasive and label-free techniques such as Raman spectroscopy.

scholarly journals Surface-Enhanced Raman Spectroscopy Analysis of Human Breast Cancer via Silver Nanoparticles: An Examination of Fabrication Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Beata Brozek-Pluska ◽  
Monika Kopec ◽  
Jakub Surmacki
Keyword(s):  
Breast Cancer ◽  
Raman Spectroscopy ◽  
Human Breast Cancer ◽  
Surface Enhanced Raman Spectroscopy ◽  
Cancer Diagnostics ◽  
Histopathological Analysis ◽  
Human Breast ◽  
Tissue Samples ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Breast cancer in a traditional way is diagnosed using mammography, computer tomography, ultrasounds, biopsy, and finally, histopathological analysis. Histopathological analysis is a gold standard in breast cancer diagnostics; however, it is time consuming and prone to the human interpretations. That is why new methods based on optical properties of analyzed human tissue samples are needed to be introduced to the clinical practice objective, costless and fast diagnostic protocols. Nowadays, Raman spectroscopy-based methods are gaining more and more importance. Raman spectroscopy and imaging allow to characterize human tissue samples using an electromagnetic radiation from a safe range, and simultaneously, a minimal sample preparation is required. During measurements, a natural differentiation in tissues components’ scattering cross sections is used to build 2D and 3D maps of the chemical component distribution. The paper presents the application of SERS (surface-enhanced Raman spectroscopy) measurements for analysis of human breast cancer (adenocarcinoma). The advantages of SERS application in cancer diagnostics are also discussed. Moreover, the detailed chemical composition of human breast cancer tissue based on Raman bands of DNA/RNA, amino acids, lipids, and proteins which are significantly enhanced is presented. Three different methods of NP preparation are presented, and the effectiveness of Raman signal enhancement of Ag nanoparticles synthetized by these methods is compared. The enhancement effect of NPs synthetized by reduction of silver nitrate with sodium borohydride (method no. 1) and silver nitrate-hydroxylamine hydrochloride reduction (method no. 2) was stronger when compared with the polyol method (method no. 3). Presented SERS results confirmed that the clearly resolved and high-intensity Raman spectra of cancer human breast tissue can be recorded using integration times of the order of fractional seconds and one milliwatt of the excitation laser power.

scholarly journals Raman spectroscopy to differentiate between fresh tissue samples of glioma and normal brain: a comparison with 5-ALA–induced fluorescence-guided surgery

2020 ◽  
pp. 1-11
Author(s):  
Laurent J. Livermore ◽  
Martin Isabelle ◽  
Ian M. Bell ◽  
Oliver Edgar ◽  
Natalie L. Voets ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Predictive Model ◽  
Raman Spectra ◽  
Aminolevulinic Acid ◽  
Temporal Lobectomy ◽  
Normal Brain ◽  
Fresh Tissue ◽  
Tissue Samples ◽  
Linear Discriminant ◽  
Resection Cavity

OBJECTIVERaman spectroscopy is a biophotonic tool that can be used to differentiate between different tissue types. It is nondestructive and no sample preparation is required. The aim of this study was to evaluate the ability of Raman spectroscopy to differentiate between glioma and normal brain when using fresh biopsy samples and, in the case of glioblastomas, to compare the performance of Raman spectroscopy to predict the presence or absence of tumor with that of 5-aminolevulinic acid (5-ALA)–induced fluorescence.METHODSA principal component analysis (PCA)–fed linear discriminant analysis (LDA) machine learning predictive model was built using Raman spectra, acquired ex vivo, from fresh tissue samples of 62 patients with glioma and 11 glioma-free brain samples from individuals undergoing temporal lobectomy for epilepsy. This model was then used to classify Raman spectra from fresh biopsies from resection cavities after functional guided, supramaximal glioma resection. In cases of glioblastoma, 5-ALA–induced fluorescence at the resection cavity biopsy site was recorded, and this was compared with the Raman spectral model prediction for the presence of tumor.RESULTSThe PCA-LDA predictive model demonstrated 0.96 sensitivity, 0.99 specificity, and 0.99 accuracy for differentiating tumor from normal brain. Twenty-three resection cavity biopsies were taken from 8 patients after supramaximal resection (6 glioblastomas, 2 oligodendrogliomas). Raman spectroscopy showed 1.00 sensitivity, 1.00 specificity, and 1.00 accuracy for predicting tumor versus normal brain in these samples. In the glioblastoma cases, where 5-ALA–induced fluorescence was used, the performance of Raman spectroscopy was significantly better than the predictive value of 5-ALA–induced fluorescence, which showed 0.07 sensitivity, 1.00 specificity, and 0.24 accuracy (p = 0.0009).CONCLUSIONSRaman spectroscopy can accurately classify fresh tissue samples into tumor versus normal brain and is superior to 5-ALA–induced fluorescence. Raman spectroscopy could become an important intraoperative tool used in conjunction with 5-ALA–induced fluorescence to guide extent of resection in glioma surgery.

scholarly journals Neonatal cardiogenic shock revealing obstructive cardiac Hibernoma: case report

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Rym Gribaa ◽  
Marwen Kacem ◽  
Sami Ouannes ◽  
Wiem Majdoub ◽  
Houssem Thabet ◽  
...  
Keyword(s):  
Cardiogenic Shock ◽  
Transthoracic Echocardiography ◽  
Right Atrium ◽  
Benign Tumors ◽  
Histopathological Analysis ◽  
Tricuspid Valve Repair ◽  
Flow Measurements ◽  
Surgical Specimen ◽  
Eosinophilic Cytoplasm ◽  
The Right

Abstract Background Cardiac Hibernomas are very rare benign tumors and usually remain asymptomatic. Neonatal cardiogenic shock due to cardiac tumors is extremely very rare. Until this date a few cases of cardiac hibernoma have been reported in the literature. Transthoracic echocardiography help in the differential diagnosis, but the definitive diagnosis is histological. The management strategy is not clearly codified. The Aim is to report and discuss the clinical features of a cardiac Hibernoma and review the relevant literature. Case presentation We describe a case of a 2-day-old Caucasian full-term male neonate admitted in neonate intensive care with cardiogenic shock, having fluid resuscitation and inotropic drugs. Ventilatory support was started immediately with the subsequent reestablishment of normal blood pressure. Then he was transferred to the echocardiography laboratory. Transthoracic echocardiography showed two echogenic masses in the right atrium and right ventricle. The masses were extended to the pulmonary trunk. Pulmonary artery flow measurements showed the presence of pulmonary and tricuspid obstruction. Surgery was rapidly considered since the baby was hemodynamically unstable. Intraoperative evaluation showed a mass embedded in the interventricular septum that occupy the right ventricular cavity and the right atrium. The tumor involved also the chordae of the tricuspid. Partial resection was done. Tricuspid valve repair was performed by construction of new chordae from the autologous pericardium. The specimen was sent for histopathological analysis. The baby died immediately after surgery. Histological examination of the surgical specimen revealed clear multivacuolated cells filled with lipid droplets and granular intense eosinophilic cytoplasm which confirms the diagnosis of Hibernoma. Conclusion Cardiac Hibernomas are rare benign tumors. The prognosis and treatment strategy is closely dependent on the location, initial clinical presentation and possible complications. The prognosis can be unfavorable if the tumor was obstructive and infiltrate the myocardium.

EXPRESS: Characterization of Drug Resistance in Chronic Myeloid Leukemia Cells Based on Laser Tweezers Raman Spectroscopy

2021 ◽  
pp. 000370282110245
Author(s):  
Qian Zhang ◽  
Minlu Ye ◽  
Lingyan Wang ◽  
Dongmei Jiang ◽  
Shuting Yao ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Chronic Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
K562 Cells ◽  
Laser Tweezers ◽  
Label Free ◽  
Multivariate Statistical ◽  
Analytical Strategy ◽  
Specificity And Sensitivity ◽  
Acid Protein

Multidrug resistance (MDR) is highly associated with poor prognosis of chronic myeloid leukemia (CML). This work aims to explore whether the laser tweezers Raman spectroscopy (LTRS) could be practical in separating adriamycin (ADR) resistance CML cells K562/ADR from its parental cells K562, and to explore the potential mechanisms. Detection of LTRS initially reflected the spectral differences caused by chemoresistance including bands assigned to carbohydrates, amino acid, protein, lipids and nucleic acid. In addition, principal components analysis (PCA) as well as the classification and regression trees (CRT) algorithms showed that the specificity and sensitivity were above 90%. Moreover, the band data-based CRT model and receiver operating characteristic (ROC) curve further determined some important bands and band intensity ratios to be reliable indexes in discriminating K562 chemoresistance status. Finally, we highlighted three metabolism pathways correlated with chemoresistance. This work demonstrates that the label-free LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single-cell level for rapid evaluation the chemoresistance status of K562 cells.

scholarly journals Alteration of protein expression and spliceosome pathway activity during Barrett’s carcinogenesis

2021 ◽  
Author(s):  
Christoph Stingl ◽  
Angela Bureo Gonzalez ◽  
Coşkun Güzel ◽  
Kai Yi Nadine Phoa ◽  
Michail Doukas ◽  
...  
Keyword(s):  
Micro Rna ◽  
Differentially Expressed ◽  
Epithelial Tissue ◽  
Label Free ◽  
Tissue Samples ◽  
Damage Repair ◽  
Inter Observer Variability ◽  
Stromal Tissue ◽  
The Face ◽  
Abundance And Diversity

Abstract Background Barrett’s esophagus (BE) is a known precursor lesion and the strongest risk factor for esophageal adenocarcinoma (EAC), a common and lethal type of cancer. Prediction of risk, the basis for efficient intervention, is commonly solely based on histologic examination. This approach is challenged by problems such as inter-observer variability in the face of the high heterogeneity of dysplastic tissue. Molecular markers might offer an additional way to understand the carcinogenesis and improve the diagnosis—and eventually treatment. In this study, we probed significant proteomic changes during dysplastic progression from BE into EAC. Methods During endoscopic mucosa resection, epithelial and stromal tissue samples were collected by laser capture microdissection from 10 patients with normal BE and 13 patients with high-grade dysplastic/EAC. Samples were analyzed by mass spectrometry-based proteomic analysis. Expressed proteins were determined by label-free quantitation, and gene set enrichment was used to find differentially expressed pathways. The results were validated by immunohistochemistry for two selected key proteins (MSH6 and XPO5). Results Comparing dysplastic/EAC to non-dysplastic BE, we found in equal volumes of epithelial tissue an overall up-regulation in terms of protein abundance and diversity, and determined a set of 226 differentially expressed proteins. Significantly higher expressions of MSH6 and XPO5 were validated orthogonally and confirmed by immunohistochemistry. Conclusions Our results demonstrate that disease-related proteomic alterations can be determined by analyzing minute amounts of cell-type-specific collected tissue. Further analysis indicated that alterations of certain pathways associated with carcinogenesis, such as micro-RNA trafficking, DNA damage repair, and spliceosome activity, exist in dysplastic/EAC.

scholarly journals Optical Biomarkers for the Diagnosis of Osteoarthritis through Raman Spectroscopy: Radiological and Biochemical Validation Using Ex Vivo Human Cartilage Samples

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 546
Author(s):  
Paula Casal-Beiroa ◽  
Vanesa Balboa-Barreiro ◽  
Natividad Oreiro ◽  
Sonia Pértega-Díaz ◽  
Francisco J. Blanco ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Articular Cartilage ◽  
Ex Vivo ◽  
Cartilage Degradation ◽  
Calcium Pyrophosphate ◽  
Calcium Pyrophosphate Dihydrate ◽  
Label Free ◽  
Molecular Fingerprint ◽  
Human Cartilage ◽  
Biochemical Validation

Osteoarthritis (OA) is the most common rheumatic disease, characterized by progressive articular cartilage degradation. Raman spectroscopy (RS) has been recently proposed as a label-free tool to detect molecular changes in musculoskeletal tissues. We used cartilage samples derived from human femoral heads to perform an ex vivo study of different Raman signals and ratios, related to major and minor molecular components of articular cartilage, hereby proposed as candidate optical biomarkers for OA. Validation was performed against the radiological Kellgren–Lawrence (K-L) grading system, as a gold standard, and cross-validated against sulfated glycosaminoglycans (sGAGs) and total collagens (Hyp) biochemical contents. Our results showed a significant decrease in sGAGs (SGAGs, A1063 cm−1/A1004 cm−1) and proteoglycans (PGs, A1375 cm−1/A1004 cm−1) and a significant increase in collagen disorganization (ColD/F, A1245 cm−1/A1270 cm−1), with OA severity. These were correlated with sGAGs or Hyp contents, respectively. Moreover, the SGAGs/HA ratio (A1063 cm−1/A960 cm−1), representing a functional matrix, rich in proteoglycans, to a mineralized matrix-hydroxyapatite (HA), was significantly lower in OA cartilage (K-L I vs. III–IV, p < 0.05), whilst the mineralized to collagenous matrix ratio (HA/Col, A960 cm−1/A920 cm−1) increased, being correlated with K-L. OA samples showed signs of tissue mineralization, supported by the presence of calcium crystals-related signals, such as phosphate, carbonate, and calcium pyrophosphate dihydrate (MGP, A960 cm−1/A1004 cm−1, MGC, A1070 cm−1/A1004 cm−1 and A1050 cm−1/A1004 cm−1). Finally, we observed an increase in lipids ratio (IL, A1450 cm−1/A1670 cm−1) with OA severity. As a conclusion, we have described the molecular fingerprint of hip cartilage, validating a panel of optical biomarkers and the potential of RS as a complementary diagnostic tool for OA.

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