PATH-29. POTENTIAL OF RAMAN SPECTROSCOPY IN ONCOLOGICAL NEUROSURGERY

Abstract Raman spectroscopy (RS) has gained increasing interest for the analysis of biological tissues within the recent years. It is a label-free, non-destructive method providing insights in biochemical properties of tumor cells. It is possible to compare RS signals with histological properties of identical tissue parts. Therefore, RS bears promising potentials in neurosurgical neurooncology. On one hand, it could potentially be used for both intraoperative tumor diagnostics and resection control. On the other hand, it could provide important knowledge on tumor biochemistry and used for a subclassification of tumors with a potential impact on personalized therapy approaches. Within our group, we analyzed over 3000 measurement points in different brain tumors ex vivo with a robotized RS system and correlated the spectral curves with histopathological results. We separated and subclassified the data by AI-based methods. Additionally, we compared the latter results with those of a handheld probe, which is potentially navigatable for in vivo, intraoperative applications. We could demonstrate, that it is possible to separate distinct tumor groups only based on RS signals, especially by using computer-based signal analysis. Furthermore, we could demonstrate the differences of the spectra of deep-frozen and formalin-fixed tissues versus non-fixed tissues. Based on our results, we will highlight the potentials of RS for intraoperative neurosurgical application in resection control for brain tumors, as well as we will focus on the potentials for brain tumor diagnostics based purely on this method or by using it as an adjunct. Those methods bear additional potentials in the field of personalized chemotherapy approaches.

Download Full-text

Applications of Vibrational Spectroscopy for Analysis of Connective Tissues

Molecules ◽

10.3390/molecules26040922 ◽

2021 ◽

Vol 26 (4) ◽

pp. 922

Author(s):

William Querido ◽

Shital Kandel ◽

Nancy Pleshko

Keyword(s):

Raman Spectroscopy ◽

Vibrational Spectroscopy ◽

Near Infrared ◽

Ex Vivo ◽

Biological Tissues ◽

Label Free ◽

Connective Tissues ◽

Bone Properties ◽

Composition And Structure

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how “spectral fingerprints” can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.

Download Full-text

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

Diagnostics ◽

10.3390/diagnostics11030546 ◽

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.

Download Full-text

Numerical Sensitivity Analysis for Dielectric Characterization of Biological Samples by Open-Ended Probe Technique

Sensors ◽

10.3390/s20133756 ◽

2020 ◽

Vol 20 (13) ◽

pp. 3756

Author(s):

Marta Cavagnaro ◽

Giuseppe Ruvio

Keyword(s):

Water Content ◽

Ex Vivo ◽

High Water ◽

Biological Tissues ◽

Fundamental Aspect ◽

High Water Content ◽

Insertion Depth ◽

Dielectric Characterization

Dielectric characterization of biological tissues has become a fundamental aspect of the design of medical treatments based on electromagnetic energy delivery and their pre-treatment planning. Among several measuring techniques proposed in the literature, broadband and minimally-invasive open-ended probe measurements are best-suited for biological tissues. However, several challenges related to measurement accuracy arise when dealing with biological tissues in both ex vivo and in vivo scenarios such as very constrained set-ups in terms of limited sample size and probe positioning. By means of the Finite Integration Technique in the CST Studio Suite® software, the numerical accuracy of the reconstruction of the complex permittivity of a high water-content tissue such as liver and a low water-content tissue such as fat is evaluated for different sample dimensions, different location of the probe, and considering the influence of the background environment. It is found that for high water-content tissues, the insertion depth of the probe into the sample is the most critical parameter on the accuracy of the reconstruction. Whereas when low water-content tissues are measured, the probe could be simply placed in contact with the surface of the sample but a deeper and wider sample is required to mitigate biasing effects from the background environment. The numerical analysis proves to be a valid tool to assess the suitability of a measurement set-up for a target accuracy threshold.

Download Full-text

Ratiometric analysis using Raman spectroscopy as a powerful predictor of structural properties of fatty acids

Royal Society Open Science ◽

10.1098/rsos.181483 ◽

2018 ◽

Vol 5 (12) ◽

pp. 181483 ◽

Cited By ~ 9

Author(s):

Lauren E. Jamieson ◽

Angela Li ◽

Karen Faulds ◽

Duncan Graham

Keyword(s):

Fatty Acids ◽

Raman Spectroscopy ◽

Biological Sample ◽

Ex Vivo ◽

Degree Of Saturation ◽

Specific Information ◽

Analytical Technique ◽

Starting Point

Raman spectroscopy has been used extensively for the analysis of biological samples in vitro , ex vivo and in vivo . While important progress has been made towards using this analytical technique in clinical applications, there is a limit to how much chemically specific information can be extracted from a spectrum of a biological sample, which consists of multiple overlapping peaks from a large number of species in any particular sample. In an attempt to elucidate more specific information regarding individual biochemical species, as opposed to very broad assignments by species class, we propose a bottom-up approach beginning with a detailed analysis of pure biochemical components. Here, we demonstrate a simple ratiometric approach applied to fatty acids, a subsection of the lipid class, to allow the key structural features, in particular degree of saturation and chain length, to be predicted. This is proposed as a starting point for allowing more chemically and species-specific information to be elucidated from the highly multiplexed spectrum of multiple overlapping signals found in a real biological sample. The power of simple ratiometric analysis is also demonstrated by comparing the prediction of degree of unsaturation in food oil samples using ratiometric and multivariate analysis techniques which could be used for food oil authentication.

Download Full-text

Characterization of Atherosclerotic Plaque Depositions in vivo by Fiber-Optic Raman Spectroscopy and ex vivo by FTIR, Raman and Non-Linear Imaging Techniques

Biomedical Engineering / Biomedizinische Technik ◽

10.1515/bmt-2012-4295 ◽

2012 ◽

Vol 57 (SI-1 Track-E) ◽

Cited By ~ 2

Author(s):

C. Matthäus ◽

R. Cicchi ◽

S. Dochow ◽

C. Krafft ◽

A. Lattermann ◽

...

Keyword(s):

Raman Spectroscopy ◽

Atherosclerotic Plaque ◽

Fiber Optic ◽

Ex Vivo ◽

Imaging Techniques ◽

Non Linear

Download Full-text

Assessment of ex-vivo and in-vivo near-infrared Raman spectroscopy for the classification of dysplasia within Barrett's esophagus

10.1117/12.384963 ◽

2000 ◽

Cited By ~ 4

Author(s):

Martin G. Shim ◽

Louis-Michel Wong Kee Song ◽

Norman E. Marcon ◽

Shirley Hassaram ◽

Brian C. Wilson

Keyword(s):

Raman Spectroscopy ◽

Barrett’S Esophagus ◽

Barrett's Esophagus ◽

Near Infrared ◽

Ex Vivo

Download Full-text

Fluid Structural Analysis of Urine Flow in a Stented Ureter

Computational and Mathematical Methods in Medicine ◽

10.1155/2016/5710798 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7 ◽

Cited By ~ 4

Author(s):

J. Carlos Gómez-Blanco ◽

F. Javier Martínez-Reina ◽

Domingo Cruz ◽

J. Blas Pagador ◽

Francisco M. Sánchez-Margallo ◽

...

Keyword(s):

Computational Models ◽

Mechanical Characterization ◽

Ex Vivo ◽

Biological Tissues ◽

Urine Flow ◽

Computational Environment ◽

Computational Fluid Dynamics Cfd

Many urologists are currently studying new designs of ureteral stents to improve the quality of their operations and the subsequent recovery of the patient. In order to help during this design process, many computational models have been developed to simulate the behaviour of different biological tissues and provide a realistic computational environment to evaluate the stents. However, due to the high complexity of the involved tissues, they usually introduce simplifications to make these models less computationally demanding. In this study, the interaction between urine flow and a double-J stented ureter with a simplified geometry has been analysed. The Fluid-Structure Interaction (FSI) of urine and the ureteral wall was studied using three models for the solid domain: Mooney-Rivlin, Yeoh, and Ogden. The ureter was assumed to be quasi-incompressible and isotropic. Data obtained in previous studies from ex vivo and in vivo mechanical characterization of different ureters were used to fit the mentioned models. The results show that the interaction between the stented ureter and urine is negligible. Therefore, we can conclude that this type of models does not need to include the FSI and could be solved quite accurately assuming that the ureter is a rigid body and, thus, using the more simple Computational Fluid Dynamics (CFD) approach.

Download Full-text

Prospective evaluation of the utility of intraoperative confocal laser endomicroscopy in patients with brain neoplasms using fluorescein sodium: experience with 74 cases

Neurosurgical FOCUS ◽

10.3171/2016.1.focus15559 ◽

2016 ◽

Vol 40 (3) ◽

pp. E11 ◽

Cited By ~ 39

Author(s):

Nikolay L. Martirosyan ◽

Jennifer M. Eschbacher ◽

M. Yashar S. Kalani ◽

Jay D. Turner ◽

Evgenii Belykh ◽

...

Keyword(s):

Brain Tumors ◽

Ex Vivo ◽

Confocal Laser Endomicroscopy ◽

Confocal Laser ◽

Fluorescein Sodium ◽

Frozen Sections ◽

Diagnostic Image ◽

Tissue Samples ◽

Specificity And Sensitivity

OBJECTIVE This study evaluated the utility, specificity, and sensitivity of intraoperative confocal laser endomicroscopy (CLE) to provide diagnostic information during resection of human brain tumors. METHODS CLE imaging was used in the resection of intracranial neoplasms in 74 consecutive patients (31 male; mean age 47.5 years; sequential 10-month study period). Intraoperative in vivo and ex vivo CLE was performed after intravenous injection of fluorescein sodium (FNa). Tissue samples from CLE imaging–matched areas were acquired for comparison with routine histological analysis (frozen and permanent sections). CLE images were classified as diagnostic or nondiagnostic. The specificities and sensitivities of CLE and frozen sections for gliomas and meningiomas were calculated using permanent histological sections as the standard. RESULTS CLE images were obtained for each patient. The mean duration of intraoperative CLE system use was 15.7 minutes (range 3–73 minutes). A total of 20,734 CLE images were correlated with 267 biopsy specimens (mean number of images/biopsy location, in vivo 84, ex vivo 70). CLE images were diagnostic for 45.98% in vivo and 52.97% ex vivo specimens. After initiation of CLE, an average of 14 in vivo images and 7 ex vivo images were acquired before identification of a first diagnostic image. CLE specificity and sensitivity were, respectively, 94% and 91% for gliomas and 93% and 97% for meningiomas. CONCLUSIONS CLE with FNa provided intraoperative histological information during brain tumor removal. Specificities and sensitivities of CLE for gliomas and meningiomas were comparable to those for frozen sections. These data suggest that CLE could allow the interactive identification of tumor areas, substantially improving intraoperative decisions during the resection of brain tumors.

Download Full-text