Changes in nuclei and peritumoral collagen within nodular basal cell carcinomas via confocal micro-Raman spectroscopy

Raman spectroscopy and topological machine learning for cancer grading

In the last decade, Raman Spectroscopy is establishing itself as a highly promising technique for the classification of tumour tissues as it allows to obtain the biochemical maps of the tissues under investigation, making it possible to observe changes among different tissues in terms of biochemical constituents (proteins, lipid structures, DNA, vitamins, and so on). In this paper, we aim to show that techniques emerging from the cross-fertilization of persistent homology and machine learning can support the classification of Raman spectra extracted from cancerous tissues for tumour grading. In more detail, topological features of Raman spectra and machine learning classifiers are trained in combination as an automatic classification pipeline in order to select the best-performing pair. The case study is the grading of chondrosarcoma in four classes: cross and leave-one-patient-out validations have been used to assess the classification accuracy of the method. The binary classification achieves a validation accuracy of 81% and a test accuracy of 90%. Moreover, the test dataset has been collected at a different time and with different equipment. Such results are achieved by a support vector classifier trained with the Betti Curve representation of the topological features extracted from the Raman spectra, and are excellent compared with the existing literature. The added value of such results is that the model for the prediction of the chondrosarcoma grading could easily be implemented in clinical practice, possibly integrated into the acquisition system.

The emerging applications and advancements of Raman spectroscopy in pediatric cancers

Although the survival rate of pediatric cancer has significantly improved, it is still an important cause of death among children. New technologies have been developed to improve the diagnosis, treatment, and prognosis of pediatric cancers. Raman spectroscopy (RS) is a non-destructive analytical technique that uses different frequencies of scattering light to characterize biological specimens. It can provide information on biological components, activities, and molecular structures. This review summarizes studies on the potential of RS in pediatric cancers. Currently, studies on the application of RS in pediatric cancers mainly focus on early diagnosis, prognosis prediction, and treatment improvement. The results of these studies showed high accuracy and specificity. In addition, the combination of RS and deep learning is discussed as a future application of RS in pediatric cancer. Studies applying RS in pediatric cancer illustrated good prospects. This review collected and analyzed the potential clinical applications of RS in pediatric cancers.

Novel aspects of Raman spectroscopy in skin research

The analytical technology of Raman spectroscopy has an almost 100‐year history. During this period, many modifications and developments happened in the method like discovery of laser, improvements in optical elements and sensitivity of spectrometer and also more advanced light detection systems. Many types of the innovative techniques appeared (e.g. Transmittance Raman spectroscopy, Coherent Raman Scattering microscopy, Surface‐Enhanced Raman scattering and Confocal Raman spectroscopy/microscopy). This review article gives a short description about these different Raman techniques and their possible applications. Then, a short statistical part is coming about the appearance of Raman spectroscopy in the scientific literature from the beginnings to these days. The third part of the paper shows the main application options of the technique (especially confocal Raman spectroscopy) in skin research, including skin composition analysis, drug penetration monitoring and analysis, diagnostic utilizations in dermatology and cosmeto‐scientific applications. At the end, the possible role of artificial intelligence in Raman data analysis and the regulatory aspect of these techniques in dermatology are briefly summarized. For the future of Raman Spectroscopy, increasing clinical relevance and in vivo applications can be predicted with spreading of non‐destructive methods and appearance with the most advanced instruments with rapid analysis time.

Co-localized line-field confocal optical coherence tomography and confocal Raman microspectroscopy for three-dimensional high-resolution morphological and molecular characterization of skin tissues ex vivo

Line-field confocal optical coherence tomography (LC-OCT) is an optical modality that provides three-dimensional (3D) images of the skin at cellular resolution. Confocal Raman microspectroscopy (CRM) is a label-free optical technique that can provide point measurement of the molecular content of the skin. This work presents a method to co-localize LC-OCT and CRM acquisitions for morpho-molecular analysis of ex vivo skin tissues at cellular level. The co-localization method allows acquisition of Raman spectra at specific locations in a sample identified from a 3D LC-OCT image, with an accuracy of ± 20 µm. The method was applied to the characterization of tattooed skin biopsies with adverse tattoo reactions. LC-OCT images allowed to target specific regions in the biopsies where the presence of tattoo ink was revealed by detection of the Raman signature of ink pigments. Micrometer-sized foreign bodies of various materials as well as inflammatory cells were also identified within the biopsies. From these results, we demonstrate the value of the LC-OCT-CRM co-localization method and its potential for future ex vivo analysis of suspicious skin lesions.

Characterization of the Striatal Extracellular Matrix in a Mouse Model of Parkinson's Disease

Parkinson’s disease’s etiology is unknown, although evidence suggests the involvement of oxidative modifications of intracellular components in disease pathobiology. Despite the known involvement of the extracellular matrix in physiology and disease, the influence of oxidative stress on the matrix has been neglected. The chemical modifications that might accumulate in matrix components due to their long half-live and the low amount of extracellular antioxidants could also contribute to the disease and explain ineffective cellular therapies. The enriched striatal extracellular matrix from a mouse model of Parkinson’s disease was characterized by Raman spectroscopy. We found a matrix fingerprint of increased oxalate content and oxidative modifications. To uncover the effects of these changes on brain cells, we morphologically characterized the primary microglia used to repopulate this matrix and further quantified the effects on cellular mechanical stress by an intracellular fluorescence resonance energy transfer (FRET)-mechanosensor using the U-2 OS cell line. Our data suggest changes in microglia survival and morphology, and a decrease in cytoskeletal tension in response to the modified matrix from both hemispheres of 6-hydroxydopamine (6-OHDA)-lesioned animals. Collectively, these data suggest that the extracellular matrix is modified, and underscore the need for its thorough investigation, which may reveal new ways to improve therapies or may even reveal new therapies.

Highly accurate colorectal cancer prediction model based on Raman spectroscopy using patient serum

BACKGROUND

Colorectal cancer (CRC) is an important disease worldwide, accounting for the second highest number of cancer-related deaths and the third highest number of new cancer cases. The blood test is a simple and minimally invasive diagnostic test. However, there is currently no blood test that can accurately diagnose CRC.

AIM

To develop a comprehensive, spontaneous, minimally invasive, label-free, blood-based CRC screening technique based on Raman spectroscopy.

METHODS

We used Raman spectra recorded using 184 serum samples obtained from patients undergoing colonoscopies. Patients with malignant tumor histories as well as those with cancers in organs other than the large intestine were excluded. Consequently, the specific diseases of 184 patients were CRC (12), rectal neuroendocrine tumor (2), colorectal adenoma (68), colorectal hyperplastic polyp (18), and others (84). We used the 1064-nm wavelength laser for excitation. The power of the laser was set to 200 mW.

RESULTS

Use of the recorded Raman spectra as training data allowed the construction of a boosted tree CRC prediction model based on machine learning. Therefore, the generalized R² values for CRC, adenomas, hyperplastic polyps, and neuroendocrine tumors were 0.9982, 0.9630, 0.9962, and 0.9986, respectively.

CONCLUSION

For machine learning using Raman spectral data, a highly accurate CRC prediction model with a high R² value was constructed. We are currently planning studies to demonstrate the accuracy of this model with a large amount of additional data.

Biophysical basis of skin cancer margin assessment using Raman spectroscopy

Achieving adequate margins during tumor margin resection is critical to minimize the recurrence rate and maximize positive patient outcomes during skin cancer surgery. Although Mohs micrographic surgery is by far the most effective method to treat nonmelanoma skin cancer, it can be limited by its inherent required infrastructure, including time-consuming and expensive on-site histopathology. Previous studies have demonstrated that Raman spectroscopy can accurately detect basal cell carcinoma (BCC) from surrounding normal tissue; however, the biophysical basis of the detection remained unclear. Therefore, we aim to explore the relevant Raman biomarkers to guide BCC margin resection. Raman imaging was performed on skin tissue samples from 30 patients undergoing Mohs surgery. High correlations were found between the histopathology and Raman images for BCC and primary normal structures (including epidermis, dermis, inflamed dermis, hair follicle, hair shaft, sebaceous gland and fat). A previously developed model was used to extract the biochemical changes associated with malignancy. Our results showed that BCC had a significantly different concentration of nucleus, keratin, collagen, triolein and ceramide compared to normal structures. The nucleus accounted for most of the discriminant power (90% sensitivity, 92% specificity - balanced approach). Our findings suggest that Raman spectroscopy is a promising surgical guidance tool for identifying tumors in the resection margins.

Quantitative Analysis on Ex Vivo Nonlinear Microscopy Images of Basal Cell Carcinoma Samples in Comparison to Healthy Skin

Basal cell carcinoma (BCC) is the most frequent malignant neoplasm in the Caucasian population. There are several therapeutic options for BCC, but surgical excision is considered gold standard treatment. As BCCs often have poorly defined borders, the clinical assessment of the tumor margins can be challenging. Therefore, there is an increasing demand for efficient in vivo imaging techniques for the evaluation of tumor borders prior to and during surgeries. In the near future, nonlinear microscopy techniques might meet this demand. We measured the two-photon excitation fluorescence (TPEF) signal of nicotinamide adenine dinucleotide hydride (NADH) and elastin and second harmonic generation (SHG) signal of collagen on 10 ex vivo healthy control and BCC skin samples and compared the images by different quantitative image analysis methods. These included integrated optical density (IOD) measurements on TPEF and SHG images and application of fast Fourier transform (FFT), CT-FIRE and CurveAlign algorithms on SHG images to evaluate the collagen structure. In the BCC samples, we found significantly lower IOD of both the TPEF and SHG signals and higher collagen orientation index utilizing FFT. CT-FIRE algorithm revealed increased collagen fiber length and decreased fiber angle while CurveAlign detected higher fiber alignment of collagen fibers in BCC. These results are in line with previous findings which describe pronounced changes in the collagen structure of BCC. In the future, these novel image analysis methods could be integrated in handheld nonlinear microscope systems, for sensitive and specific identification of BCC.

Near-infrared Raman spectroscopy for estimating biochemical changes associated with different pathological conditions of cervix

The molecular level changes associated with oncogenesis precede the morphological changes in cells and tissues. Hence molecular level diagnosis would promote early diagnosis of the disease. Raman spectroscopy is capable of providing specific spectral signature of various biomolecules present in the cells and tissues under various pathological conditions. The aim of this work is to develop a non-linear multi-class statistical methodology for discrimination of normal, neoplastic and malignant cells/tissues. The tissues were classified as normal, pre-malignant and malignant by employing Principal Component Analysis followed by Artificial Neural Network (PC-ANN). The overall accuracy achieved was 99%. Further, to get an insight into the quantitative biochemical composition of the normal, neoplastic and malignant tissues, a linear combination of the major biochemicals by non-negative least squares technique was fit to the measured Raman spectra of the tissues. This technique confirms the changes in the major biomolecules such as lipids, nucleic acids, actin, glycogen and collagen associated with the different pathological conditions. To study the efficacy of this technique in comparison with histopathology, we have utilized Principal Component followed by Linear Discriminant Analysis (PC-LDA) to discriminate the well differentiated, moderately differentiated and poorly differentiated squamous cell carcinoma with an accuracy of 94.0%. And the results demonstrated that Raman spectroscopy has the potential to complement the good old technique of histopathology.

Polarized Raman spectroscopy unravels the biomolecular structural changes in cervical cancer

Polarized Raman spectroscopy has emerged as a promising technique giving a wealth of information about the orientation and symmetry of bond vibrations in addition to the general chemical information from the conventional Raman spectroscopy. In this regard, polarized Raman Spectroscopic technique was employed to study the changes in the orientation of biomolecules in normal and cancerous conditions. This technique was compared to the conventional Raman spectroscopic technique and was found to yield additional information about the orientation of tyrosine, collagen and DNA. The statistically analyzed depolarization ratios by Linear Discriminant Analysis yielded better accuracy than the statistical results of conventional Raman spectroscopy. Thus, this study reveals that polarized Raman spectroscopy has better diagnostic potential than the conventional Raman spectroscopic technique.

Applications of Raman spectroscopy in skin research--From skin physiology and diagnosis up to risk assessment and dermal drug delivery

In the field of skin research, confocal Raman microscopy is an upcoming analytical technique. Substantial technical progress in design and performance of the individual setup components like detectors and lasers as well as the combination with confocal microscopy enables chemically selective and non-destructive sample analysis with high spatial resolution in three dimensions. Due to these advantages, the technique bears tremendous potential for diverse skin applications ranging from the analysis of physiological component distribution in skin tissue and the diagnosis of pathological states up to biopharmaceutical investigations such as drug penetration kinetics within the different tissue layers. This review provides a comprehensive introduction about the basic principles of Raman microscopy highlighting the advantages and considering the limitations of the technique for skin applications. Subsequently, an overview about skin research studies applying Raman spectroscopy is given comprising various in vitro as well as in vivo implementations. Furthermore, the future perspective and potential of Raman microscopy in the field of skin research are discussed.

In vivo study for the discrimination of cancerous and normal skin using fibre probe-based Raman spectroscopy

Raman spectroscopy has proved its capability as an objective, non-invasive tool for the detection of various melanoma and non-melanoma skin cancers (NMSC) in a number of studies. Most publications are based on a Raman microspectroscopic ex vivo approach. In this in vivo clinical evaluation, we apply Raman spectroscopy using a fibre-coupled probe that allows access to a multitude of affected body sites. The probe design is optimized for epithelial sensitivity, whereby a large part of the detected signal originates from within the epidermal layer's depth down to the basal membrane where early stages of skin cancer develop. Data analysis was performed on measurements of 104 subjects scheduled for excision of lesions suspected of being malignant melanoma (MM) (n = 36), basal cell carcinoma (BCC) (n = 39) and squamous cell carcinoma (SCC) (n = 29). NMSC were discriminated from normal skin with a balanced accuracy of 73% (BCC) and 85% (SCC) using partial least squares discriminant analysis (PLS-DA). Discriminating MM and pigmented nevi (PN) resulted in a balanced accuracy of 91%. These results lie within the range of comparable in vivo studies and the accuracies achieved by trained dermatologists using dermoscopy. Discrimination proved to be unsuccessful between cancerous lesions and suspicious lesions that had been histopathologically verified as benign by dermoscopy.

Perturbation factors in the clinical handling of a fiber-coupled Raman probe for cutaneous in vivo diagnostic Raman spectroscopy

The application of fiber-coupled Raman probes for the discrimination of cancerous and normal skin has the advantage of a non-invasive in vivo application, easy clinical handling, and access to the majority of body sites, which would otherwise be limited by stationary Raman microscopes. Nevertheless, including optical fibers and miniaturizing optical components, as well as measuring in vivo, involves the sensibility to external perturbation factors that could introduce artifacts to the acquired Raman spectra and thereby potentially reduce classification performance. In this study, typical perturbation factors of Raman measurements with a Raman fiber probe, optimized for clinical in vivo discrimination of skin cancer, were investigated experimentally. Measurements were performed under standardized conditions in clinical settings in vivo on human skin, as well as ex vivo on porcine ears. Raman spectra were analyzed in the fingerprint region between 1150 and 1730 cm(-1) using principal component analysis. The largest artifacts in the Raman spectra were found in measurements performed under the influence of strong ambient light conditions as well as after miscellaneous pre-treatments to the skin, such as use of a permanent marker or a sunscreen. Minor influences were also found in measurements using H2O immersion and when varying the probe contact force. The effect of reasonable variation of the fiber-bending radius was found to be of negligible impact. The influence of measurements on hairy or sun-exposed body sites, as well as inter-subject variation, was also investigated. The presented results may serve as a guide to avoid negative effects during the process of data acquisition and so avoid misclassification in tumor discrimination.

Label-free identification and characterization of murine hair follicle stem cells located in thin tissue sections with Raman micro-spectroscopy

Stem cells offer tremendous opportunities for regenerative medicine.

In vivo, real-time, transnasal, image-guided Raman endoscopy: defining spectral properties in the nasopharynx and larynx

We report for the first time the implementation of transnasal, image-guided Raman endoscopy to directly assess Raman spectral properties of nasopharyngeal and laryngeal tissue in vivo during clinical endoscopic examinations. A rapid 785-nm excitation Raman endoscopy system, coupled with a miniaturized fiber-optic Raman probe, was utilized for real-time, in vivo Raman measurements of different anatomical locations in the head and neck. A total of 874 high-quality in vivo Raman spectra were successfully acquired from different anatomic locations of the nasopharynx and larynx [i.e., posterior nasopharynx (PN) (n=521), the fossa of Rosenmüller (FOR) (n=157), and true laryngeal vocal chords (LVC) (n=196)] in 23 normal subjects at transnasal endoscopy. Difference spectra and principal component analysis (PCA) were employed for tissue characterization, uncovering the tissue variability at the biomolecular level. The PCA-linear discriminant analysis (LDA) provides sensitivity of 77.0% and specificity of 89.2% for differentiation between PN and FOR, and sensitivity of 68.8% and specificity of 76.0% for distinguishing LVC and PN using the leave-one-subject-out, cross-validation method. This work demonstrates that transnasal, image-guided Raman endoscopy can be used to acquire in vivo Raman spectra from the nasopharynx and larynx in real time. Significant Raman spectral differences (p<0.05) identified as reflecting the distinct composition and morphology in the nasopharynx and larynx should be considered to be important parameters in the interpretation and rendering of diagnostic decision algorithms for in vivo tissue diagnosis and characterization in the head and neck.

Real-time Raman spectroscopy for in vivo skin cancer diagnosis

Raman spectroscopy is a noninvasive optical technique capable of measuring vibrational modes of biomolecules within viable tissues. In this study, we evaluated the application of an integrated real-time system of Raman spectroscopy for in vivo skin cancer diagnosis. Benign and malignant skin lesions (n = 518) from 453 patients were measured within 1 second each, including melanomas, basal cell carcinomas, squamous cell carcinomas, actinic keratoses, atypical nevi, melanocytic nevi, blue nevi, and seborrheic keratoses. Lesion classification was made using a principal component with general discriminant analysis and partial least-squares in three distinct discrimination tasks: skin cancers and precancers from benign skin lesions [receiver operating characteristic (ROC) = 0.879]; melanomas from nonmelanoma pigmented lesions (ROC = 0.823); and melanomas from seborrheic keratoses (ROC = 0.898). For sensitivities between 95% and 99%, the specificities ranged between 15% and 54%. Our findings establish that real-time Raman spectroscopy can be used to distinguish malignant from benign skin lesions with good diagnostic accuracy comparable with clinical examination and other optical-based methods.

Optical diagnosis of laryngeal cancer using high wavenumber Raman spectroscopy

We report the implementation of the transnasal image-guided high wavenumber (HW) Raman spectroscopy to differentiate tumor from normal laryngeal tissue at endoscopy. A rapid-acquisition Raman spectroscopy system coupled with a miniaturized fiber-optic Raman probe was utilized to realize real-time HW Raman (2800-3020 cm(-1)) measurements in the larynx. A total of 94 HW Raman spectra (22 normal sites, 72 tumor sites) were acquired from 39 patients who underwent laryngoscopic screening. Significant differences in Raman intensities of prominent Raman bands at 2845, 2880 and 2920 cm(-1) (CH(2) stretching of lipids), and 2940 cm(-1) (CH(3) stretching of proteins) were observed between normal and cancer laryngeal tissue. The diagnostic algorithms based on principal components analysis (PCA) and linear discriminant analysis (LDA) together with the leave-one subject-out, cross-validation method on HW Raman spectra yielded a diagnostic sensitivity of 90.3% (65/72) and specificity of 90.9% (20/22) for laryngeal cancer identification. This study demonstrates that HW Raman spectroscopy has the potential for the noninvasive, real-time diagnosis and detection of laryngeal cancer at the molecular level.

In vivo diagnosis of esophageal cancer using image-guided Raman endoscopy and biomolecular modeling

The aim of this work was to evaluate the biochemical foundation and clinical merit of multimodal image-guided Raman endoscopy technique for real-time in vivo diagnosis of cancer in the esophagus during clinical endoscopic examinations. A novel fiber-optic Raman endoscopy system was utilized for in vivo esophageal Raman measurements at 785 nm laser excitation within 0.5 second under the multimodal wide-field endoscopic imaging (white light reflectance (WLR) imaging, narrow-band imaging (NBI) and autofluorescence imaging (AFI) guidance. A total of 75 esophageal tissue sites from 27 patients were measured, in which 42 in vivo Raman spectra were from normal tissues and 33 in vivo Raman spectra were from malignant tumors as confirmed by histopathology. The biomolecular modeling (non-negativity-constrained least-squares minimization (NNCLSM) utilizing six basis reference spectra from the representative biochemicals (i.e., actin, collagen, DNA, histones, triolein and glycogen) were employed to estimate the biochemical compositions of esophageal tissue. The resulting diagnostically significant fit coefficients were further utilized through linear discriminant analysis (LDA) and leave-one tissue site-out, cross validation method to develop diagnostic algorithms for esophageal cancer diagnosis. High-quality in vivo Raman spectra in the range of 800-1800 cm-1 can be acquired from normal and cancerous esophageal mucosa in real-time under multimodal endoscopic imaging guidance. Esophageal cancer tissue showed distinct Raman signals mainly associated with cell proliferation, lipid reduction, abnormal nuclear activity and neovasculation. The fit coefficients for actin, DNA, histones, triolein, and glycogen were found to be most significant for construction of the LDA diagnostic model, giving rise to an accuracy of 96.0% (i.e., sensitivity of 97.0% and specificity of 95.2%) for in vivo diagnosis of esophageal cancer. This study demonstrates that multimodal image-guided Raman endoscopy technique in conjunction with biomolecular modeling has promising potential for the real-time, in vivo diagnosis and detection of esophageal cancer during clinical endoscopic examination.

Raman imaging of single living cells: probing effects of non-cytotoxic doses of an anti-cancer drug

Identifying cell response to a chemotherapy drug treatment, in particular at the single cell level, is an important issue in patient management. This study aims at evaluating the effect of gemcitabine on single living cells using micro-Raman imaging. We used as a model the non-small lung cancer cell line, Calu-1, exposed to cytostatic doses (1 nM to 1 μM for 24 h and 48 h) of gemcitabine, an antitumor drug currently used in the treatment of lung cancer. Following drug treatment as a function of doses and incubation times, the Raman maps of single living cells were acquired. Cell biomolecules (DNA, RNA, and proteins) were chemically extracted and their spectral signatures used to evaluate their respective distribution in the cellular spectral information of control and treated cells. The quantification of these distributions reveals a significant effect of 100 nM gemcitabine at 48 h incubation (concomitant decrease of nucleic acids and increase of proteins). PCA analyses performed both on nuclear and extracted biomolecules spectra show a time-dependent effect of the drug. These promising results reveal that effects of subtoxic doses can be monitored at the single cell level highlighting the importance of such studies for clinical applications.

A novel blood plasma analysis technique combining membrane electrophoresis with silver nanoparticle-based SERS spectroscopy for potential applications in noninvasive cancer detection

Combining membrane electrophoresis with silver nanoparticle-based surface-enhanced Raman spectroscopy (SERS), we have developed a novel method for blood plasma analysis for cancer detection applications. In this method, total serum proteins are isolated from blood plasma by membrane electrophoresis and mixed with silver nanoparticles to perform SERS spectral analysis. The obtained SERS spectra present information-rich, fingerprint-type signatures of the biochemical constituents of whole proteins. We evaluated the utility of this method by analyzing blood plasma samples from patients with gastric cancer (n=31) and healthy volunteers (n=33). Principal components analysis of the spectra revealed that the data points for the two groups form distinct, completely separated clusters with no overlap. The gastric cancer group can be unambiguously distinguished from the normal group in this initial test-that is, with both diagnostic sensitivity and specificity of 100%. These results are very promising for developing a label-free, noninvasive clinical tool for cancer detection and screening.

Assessment of thermal coagulation in ex-vivo tissues using Raman spectroscopy

Raman spectroscopy is used to study the effects of heating on specific molecular bonds present in albumen-based coagulation phantoms and ex-vivo tissues. Thermal coagulation is induced by submerging albumen-based phantoms in a 75°C water bath to achieve target temperatures of 45, 55, 65, and 75°C. Laser photocoagulation is performed on ex-vivo bovine muscle samples, yielding induced temperatures between 46 and 90°C, as reported by implanted microthermocouples. All phantoms and tissue samples are cooled to room temperature, and Raman spectra are acquired at the microthermocouple locations. Shifts in major Raman bands are observed with laser heating in bovine muscle, specifically from the amide-1 α-helix group (∼1655 cm(-1)), the CH(2)/CH(3) group (∼1446 cm(-1)), the Cα-H stretch group (∼1312 cm(-1)), and the CN stretch group (∼1121cm(-1)). Raman bands at 1334 cm(-1) (tryptophan), 1317 cm(-1) [ν(Cα-H)], and 1655 cm(-1) (amide-1 α-helix) also show a decrease in intensity following heating. The results suggest that Raman band locations and relative intensities are affected by thermal denaturation of proteins, and hence, may be a useful tool for monitoring the onset and progression of coagulation during thermal therapies.

Infrared microspectroscopy analysis of ibuprofen release from drug eluting beads in uterine tissue

Ibuprofen loaded embolization beads (IBU-BB) have been developed to reduce inflammation and pain following uterine artery embolization for the treatment of uterine fibroids. The present work has investigated the elution properties of IBU-BB in situ after embolization with Fourier Transform Infrared Microspectroscopy (FTIRMS). Twelve sheep underwent uterine artery embolization with IBU-BB (485 mM) or control unloaded beads. IBU concentration was determined inside the beads and in the tissue surrounding the beads using FTIRMS of uterine tissue sections sampled 24 h or 1 week after embolization. After 24 h, IBU concentration inside the bead was only 18.6 mM out of the 485 mM initially loaded (p < 0.0001, univariate sign test). The concentration in the tissue around the beads was 8 mM, which is well above the in vitro therapeutic levels (6 microM). After one week the concentration of IBU had decreased to 4.9 mM in the beads (p = 0.0502, Mann Whitney) and no IBU was detected in the surrounding tissue. This work has demonstrated that IBU-BB can provide a sustained release of the anti-inflammatory drug over at least one week. The in vivo elution properties of IBU-BB may be suitable to alleviate pain and inflammation after embolization.

Towards oncological application of Raman spectroscopy

As the possibilities in the treatment of cancer continue to evolve, its early detection and correct diagnosis are becoming increasingly important. From the early detection of cancer to the guidance of oncosurgical procedures new sensitive in vivo diagnostic tools are much needed. Many studies report the Raman spectroscopic detection of malignant and premalignant tissues in different sites of the body with high sensitivities. The great appeal of this technique lies in its potential for in vivo clinical implementation. We present an overview of the in vitro and in vivo work on the oncological application of Raman spectroscopy and discuss its potential as a new tool in the clinico-oncological practice. Opportunities for integration of Raman spectroscopy in oncological cure and care as a real-time guidance tool during diagnostic (i.e. biopsy) and therapeutic (surgical resection) modalities as well as technical shortcomings are discussed from a clinician's point of view.

Parameters defining the potential applicability of Raman spectroscopy as a diagnostic tool for oral disease

Raman spectroscopy can provide information about the molecular composition of tissues, with potential to be applied as a diagnostic tool in lieu of histopathology. Our objectives are to determine if laser Raman spectra (RS) can be acquired reliably from the oral mucosa of patients, and to determine if the RS signature of normal oral mucosa is reproducible among anatomic oral sites and among subjects of different races and gender. 25 Caucasian and 26 Asian subjects are studied using RS with a signal acquisition time of 1 s at seven specified sites within the mouth. Multivariate analysis is used to determine the variability between tissue types and between races and gender. Unique spectra are defined for various sites in the mouth and are likely related to the degree of keratinization. However, spectral concordance by site is not greatly influenced by subject ethnicity or gender. We demonstrate, for the first time, the potential in-vivo application of RS for oral mucosal disease and demonstrate its specificity for particular mucosal types in the mouth. RS offers the potential to provide a diagnosis of disease using a noninvasive, convenient, sensitive technology that provides immediate results.

Polarized Raman microspectroscopy can reveal structural changes of peritumoral dermis in basal cell carcinoma

Polarized Raman microspectroscopy can provide precious information regarding the orientation and ordering of the molecules in a sample without staining or particular preparation. This technique is used for the first time on a human skin section to probe the molecular modifications of the surrounding dermis in superficial basal cell carcinoma. Spectra using polarized and conventional Raman microspectroscopies were recorded on dermis bordering either the tumor or healthy epidermis. Band areas and spectral decomposition on selected vibrations were computed. Significant differences in dermal collagen vibration bands are detected using both polarized and conventional micro-spectroscopies, but the spectral changes between tumor and healthy tissues are enhanced using polarized Raman microspectroscopy. The analysis of these spectral differences highlights structural modifications of the triple helix of collagen. We see polarized Raman microspectroscopy as a potential tool that could be implemented for clinical analyses to guide clinicians and surgeons in the treatment of aggressive skin cancers. The information obtainable could also help better elucidate the molecular mechanisms induced in basal cell carcinoma development.

Raman microspectroscopy for skin cancer detection in vitro

We investigate the potential of near-infrared Raman microspectroscopy to differentiate between normal and malignant skin lesions. Thirty-nine skin tissue samples consisting of normal, basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma from 39 patients were investigated. Raman spectra were recorded at the surface and at 20-microm intervals below the surface for each sample, down to a depth of at least 100 microm. Data reduction algorithms based on the nonlinear maximum representation and discrimination feature (MRDF) and discriminant algorithms using sparse multinomial logistic regression (SMLR) were developed for classification of the Raman spectra relative to histopathology. The tissue Raman spectra were classified into pathological states with a maximal overall sensitivity and specificity for disease of 100%. These results indicate the potential of using Raman microspectroscopy for skin cancer detection and provide a clear rationale for future clinical studies.

Molecular characterization of reconstructed skin model by Raman microspectroscopy: comparison with excised human skin

Human skin is directly exposed to different exogenous agents. Many research works have studied the diffusion, interactions, absorption mechanisms, and/or toxicity of these agents toward different cutaneous structures. With the use of living animals for such tests being more and more rejected; and the number of human volunteers being limited; different types of skin models are used. In the last few years, reconstructed epidermis from cell cultures has been frequently employed, and recent changes in the European chemical policy have approved and encouraged the use of these reconstructed models for skin-related research works and assessments. Among the techniques used actually to study the skin, Raman microspectroscopy is a rising and powerful nondestructive technique that detects characteristic molecular vibrations. In this study, we created a spectral database to index the vibration peaks and bands of a well-known reconstructed epidermis model, the Episkin. The comparison with a native epidermis signal enabled us to put in evidence several spectral differences associated with molecular and structural differences between the skin and the reconstructed model, both maintained in living conditions. In addition to that, we have showed the feasibility of tracking the penetration of a pharmaceutical molecule through the Episkin model. (

Discriminating basal cell carcinoma from perilesional skin using high wave-number Raman spectroscopy

An expanding body of literature suggests Raman spectroscopy is a promising tool for skin cancer diagnosis and in-vivo tumor border demarcation. The development of an in-vivo diagnostic tool is, however, hampered by the fact that construction of fiber optic probes suitable for Raman spectroscopy in the so-called fingerprint region is complicated. In contrast, the use of the high wave-number region allows for fiber optic probes with a very simple design. We investigate whether high wave-number Raman spectroscopy (2800 to 3125 cm(-1)) is able to provide sufficient information for noninvasive discrimination between basal cell carcinoma (BCC) and noninvolved skin. Using a simple fiber optic probe, Raman spectra are obtained from 19 BCC biopsy specimens and 9 biopsy specimens of perilesional skin. A linear discriminant analysis (LDA)-based tissue classification model is developed, which discriminates between BCC and noninvolved skin with high accuracy. This is a crucial step in the development of clinical dermatological applications based on fiber optic Raman spectroscopy.