Fourier transform infrared imaging analysis in discrimination studies of squamous cell carcinoma

Oral squamous cell carcinoma identification by FTIR spectroscopy of oral biofluids

OBJECTIVES

This case study evaluated the efficacy of mid-infrared spectroscopy on the identification of oral squamous cell carcinoma, following the assessment of unstimulated whole saliva.

STUDY DESIGN AND METHODS

The trial follows a matched case-control design. Saliva samples were characterized through mid-infrared spectroscopy, and chemometric tools were applied to distinguish between case and control participants, further identifying the spectral regions that played a pivotal role in the successful identification of oral squamous cell carcinoma.

RESULTS

Mid-infrared spectroscopy was capable to discriminate between cancer patients and matched controls with 100% of correct predictions. Additionally, the spectral regions mostly contributing to the successful prediction were identified and found to be potentially associated with significant molecular changes crucial to the carcinogenic process.

CONCLUSION

The application of mid-infrared spectroscopy in saliva analysis may be regarded as an innovative, noninvasive, low cost, and sensitive technique contributing to the identification of oral squamous cell carcionma.

An optical photothermal infrared investigation of lymph nodal metastases of oral squamous cell carcinoma

In this study, optical photothermal infrared (O-PTIR) spectroscopy combined with machine learning algorithms were used to evaluate 46 tissue cores of surgically resected cervical lymph nodes, some of which harboured oral squamous cell carcinoma nodal metastasis. The ratios obtained between O-PTIR chemical images at 1252 cm-1 and 1285 cm-1 were able to reveal morphological details from tissue samples that are comparable to the information achieved by a pathologist's interpretation of optical microscopy of haematoxylin and eosin (H&E) stained samples. Additionally, when used as input data for a hybrid convolutional neural network (CNN) and random forest (RF) analyses, these yielded sensitivities, specificities and precision of 98.6 ± 0.3%, 92 ± 4% and 94 ± 5%, respectively, and an area under receiver operator characteristic (AUC) of 94 ± 2%. Our findings show the potential of O-PTIR technology as a tool to study cancer on tissue samples.

Suitability of Fourier transform infrared microscopy for the diagnosis of cystic echinococcosis in human tissue sections

Cystic echinococcosis (CE) is a global health concern caused by cestodes, posing diagnostic challenges due to nonspecific symptoms and inconclusive radiographic results. Diagnosis relies on histopathological evaluation of affected tissue, demanding comprehensive tools. In this retrospective case study, Fourier transform infrared microscopy was explored for detecting and identifying CE through biochemical changes in human tissue sections. Tissue samples from 11 confirmed CE patients were analyzed. Archived FFPE blocks were cut and stained, and then CE-positive unstained sections were examined using Fourier transform infrared microscopy post-deparaffinization. Results revealed the method's ability to distinguish echinococcus elements from human tissue, irrespective of organ type. This research showcases the potential of mid-infrared microscopy as a valuable diagnostic tool for CE, offering promise in enhancing diagnostic precision in the face of the disease's complexities.

Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains

In forensic medicine, estimating human skeletal remains' post-mortem interval (PMI) can be challenging. Following death, bones undergo a series of chemical and physical transformations due to their interactions with the surrounding environment. Post-mortem changes have been assessed using various methods, but estimating the PMI of skeletal remains could still be improved. We propose a new methodology with handheld hyperspectral imaging (HSI) system based on the first results from 104 human skeletal remains with PMIs ranging between 1 day and 2000 years. To differentiate between forensic and archaeological bone material, the Convolutional Neural Network analyzed 65.000 distinct diagnostic spectra: the classification accuracy was 0.58, 0.62, 0.73, 0.81, and 0.98 for PMIs of 0 week-2 weeks, 2 weeks-6 months, 6 months-1 year, 1 year-10 years, and >100 years, respectively. In conclusion, HSI can be used in forensic medicine to distinguish bone materials >100 years old from those <10 years old with an accuracy of 98%. The model has adequate predictive performance, and handheld HSI could serve as a novel approach to objectively and accurately determine the PMI of human skeletal remains.

Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas

The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep learning approach to analyze MIR hyperspectral data obtained from benign and malignant lymph node pathology results in high accuracy for correct classification, learning the distinct region of 3900 to 850 cm-1 . The accuracy is above 95% for every pair of malignant lymphoid tissue and still above 90% for the distinction between benign and malignant lymphoid tissue for binary classification. These results demonstrate that a preliminary diagnosis and subtyping of human lymphoma could be streamlined by applying a deep learning approach to analyze MIR spectroscopic data.

Comparison of Mid-Infrared Handheld and Benchtop Spectrometers to Detect Staphylococcus epidermidis in Bone Grafts

Bone analyses using mid-infrared spectroscopy are gaining popularity, especially with handheld spectrometers that enable on-site testing as long as the data quality meets standards. In order to diagnose Staphylococcus epidermidis in human bone grafts, this study was carried out to compare the effectiveness of the Agilent 4300 Handheld Fourier-transform infrared with the Perkin Elmer Spectrum 100 attenuated-total-reflectance infrared spectroscopy benchtop instrument. The study analyzed 40 non-infected and 10 infected human bone samples with Staphylococcus epidermidis, collecting reflectance data between 650 cm-1 and 4000 cm-1, with a spectral resolution of 2 cm-1 (Agilent 4300 Handheld) and 0.5 cm-1 (Perkin Elmer Spectrum 100). The acquired spectral information was used for spectral and unsupervised classification, such as a principal component analysis. Both methods yielded significant results when using the recommended settings and data analysis strategies, detecting a loss in bone quality due to the infection. MIR spectroscopy provides a valuable diagnostic tool when there is a tissue shortage and time is of the essence. However, it is essential to conduct further research with larger sample sizes to verify its pros and cons thoroughly.

Metric-based analysis of FTIR data to discriminate tissue types in oral cancer

A machine learning algorithm (MLA) has predicted the prognosis of oral potentially malignant lesions and discriminated between lymph node tissue and metastatic oral squamous cell carcinoma (OSCC). The MLA analyses metrics, which are ratios of Fourier transform infrared absorbances, and identifies key wavenumbers that can be associated with molecular biomarkers. The wider efficacy of the MLA is now shown in the more complex primary OSCC tumour setting, where it is able to identify seven types of tissue. Three epithelial and four non-epithelial tissue types were discriminated from each other with sensitivities between 82% and 96% and specificities between 90% and 99%. The wavenumbers involved in the five best discriminating metrics for each tissue type were tightly grouped, indicating that small changes in the spectral profiles of the different tissue types are important. The number of samples used in this study was small, but the information will provide a basis for further, larger investigations.

Visible- and near-infrared hyperspectral imaging for the quantitative analysis of PD-L1+ cells in human lymphomas: Comparison with fluorescent multiplex immunohistochemistry

INTRODUCTION

We analyzed the expression of PD-L1 in human lymphomas using hyperspectral imaging (HSI) compared to visual assessment (VA) and conventional digital image analysis (DIA) to strengthen further the value of HSI as a tool for the evaluation of brightfield-based immunohistochemistry (IHC). In addition, fluorescent multiplex immunohistochemistry (mIHC) was used as a second detection method to analyze the impact of a different detection method.

MATERIAL AND METHODS

18 cases (6 follicular lymphomas and 12 diffuse large B-cell lymphomas) were stained for PD-L1 by IHC and for PD-L1, CD3, and CD8 by fluorescent mIHC. The percentage of positively stained cells was evaluated with VA, HSI, and DIA for IHC and VA and DIA for mIHC. Results were compared between the different methods of detection and analysis.

RESULTS

An overall high concordance was found between VA, HSI, and DIA in IHC (Cohens Kappa = 0.810^VA/HSI, 0.710 ^VA/DIA, and 0.516 ^HSI/DIA) and for VA^mIHCversus DIA^mIHC (Cohens Kappa = 0.894). Comparing IHC and mIHC general agreement differed depending on the methods compared but reached at most a moderate agreement (Coheńs Kappa between 0.250 and 0.483). This is reflected by the significantly higher percentage of PD-L1+ cells found with mIHC (p^Friedman = 0.014).

CONCLUSION

Our study shows a good concordance for the different analysis methods. Compared to VA and DIA, HSI proved to be a reliable tool for assessing IHC. Understanding the regulation of PD-L1 expression will further enlighten the role of PD-L1 as a biomarker. Therefore it is necessary to develop an instrument, such as HSI, which can offer a reliable and objective evaluation of PD-L1 expression.

Raman microscopic spectroscopy as a diagnostic tool to detect Staphylococcus epidermidis in bone grafts

INTRODUCTION

Raman microscopic spectroscopyis a new approach for further characterization and detection of molecular features in many pathological processes. This technique has been successfully applied to scrutinize the spatial distribution of small molecules and proteins within biological systems by in situ analysis. This study uses Raman microscopic spectroscopyto identify any in-depth benefits and drawbacks in diagnosing Staphylococcus epidermidis in human bone grafts.

MATERIAL AND METHODS

40 non-infected human bone samples and 10 human bone samples infected with Staphylococcus epidermidis were analyzed using Raman microscopic spectroscopy. Reflectance data were collected between 200 cm^-1 and 3600 cm^-1 with a spectral resolution of 4 cm^-1 using a Senterra II microscope (Bruker, Ettlingen, Germany). The acquired spectral information was used for spectral and unsupervised classification, such as principal component analysis.

RESULTS

Raman measurements produced distinct diagnostic spectra that were used to distinguish between non-infected human bone samples and Staphylococcus epidermidis infected human bone samples by spectral and principal component analyses. A substantial loss in bone quality and protein conformation was detected by human bone samples co-cultured with Staphylococcus epidermidis. The mineral-to-matrix ratio using the phosphate/Amide I ratio (p = 0.030) and carbonate/phosphate ratio (p = 0.001) indicates that the loss of relative mineral content in bones upon bacterial infection is higher than in non-infected human bones. Also, an increase of alterations in the collagen network (p = 0.048) and a decrease in the structural organization and relative collagen in infected human bone could be detected. Subsequent principal component analyses identified Staphylococcus epidermidis in different spectral regions, respectively, originating mainly from CH₂ deformation (wagging) of protein (at 1450 cm^-1) and bending and stretching modes of C-H groups (∼2800-3000 cm^-1).

CONCLUSION

Raman microscopic spectroscopyis presented as a promising diagnostic tool to detect Staphylococcus epidermidis in human bone grafts. Further studies in human tissues are warranted.

Non-destructive molecular FTIR spectromicroscopy for real time assessment of redox metallodrugs

Recent emergence of FTIR spectromicroscopy (micro-FTIR) as a dynamic spectroscopy for imaging to study biological chemistry has opened new possibilities for investigating in situ drug release, redox chemistry effects on biological molecules, DNA and drug interactions, membrane dynamics, and redox reactions with proteins at the single cell level. Micro-FTIR applied to metallodrugs has been playing an important role since the last decade because of its great potential to achieve more robust and controlled pharmacological effects against several diseases, including cancer. An important aspect in the development of these drugs is to understand their cellular properties, such as uptake, accumulation, activity, and toxicity. In this review, we present the potential application of micro-FTIR and its importance for studying metal-based drugs, highlighting the perspectives of chemistry of living cells. We also emphasise bioimaging, which is of high importance to localize the cellular processes, for a proper understanding of the mechanism of action.

Oral Cancer Discrimination and Novel Oral Epithelial Dysplasia Stratification Using FTIR Imaging and Machine Learning

The Fourier transform infrared (FTIR) imaging technique was used in a transmission model for the evaluation of twelve oral hyperkeratosis (HK), eleven oral epithelial dysplasia (OED), and eleven oral squamous cell carcinoma (OSCC) biopsy samples in the fingerprint region of 1800–950 cm⁻¹. A series of 100 µm × 100 µm FTIR imaging areas were defined in each sample section in reference to the hematoxylin and eosin staining image of an adjacent section of the same sample. After outlier removal, signal preprocessing, and cluster analysis, a representative spectrum was generated for only the epithelial tissue in each area. Two representative spectra were selected from each sample to reflect intra-sample heterogeneity, which resulted in a total of 68 representative spectra from 34 samples for further analysis. Exploratory analyses using Principal component analysis and hierarchical cluster analysis showed good separation between the HK and OSCC spectra and overlaps of OED spectra with either HK or OSCC spectra. Three machine learning discriminant models based on partial least squares discriminant analysis (PLSDA), support vector machines discriminant analysis (SVMDA), and extreme gradient boosting discriminant analysis (XGBDA) were trained using 46 representative spectra from 12 HK and 11 OSCC samples. The PLSDA model achieved 100% sensitivity and 100% specificity, while both SVM and XGBDA models generated 95% sensitivity and 96% specificity, respectively. The PLSDA discriminant model was further used to classify the 11 OED samples into HK-grade (6), OSCC-grade (4), or borderline case (1) based on their FTIR spectral similarity to either HK or OSCC cases, providing a potential risk stratification strategy for the precancerous OED samples. The results of the current study support the application of the FTIR-machine learning technique in early oral cancer detection.

Grade diagnosis of human glioma using Fourier transform infrared microscopy and artificial neural network

The World Health Organization (WHO) grade diagnosis of cancer is essential for surgical outcomes and patient treatment. Traditional pathological grading diagnosis depends on dyes or other histological approaches, and the result interpretation highly relies on the pathologists, making the process time-consuming (>60 min, including the steps of dewaxing to water and H&E staining), resource-wasting, and labor-intensive. In the present study, we report an alternative workflow that combines the Fourier transform infrared (FTIR) microscopy and artificial neural network (ANN) to diagnose the grade of human glioma in a way that is faster (~20 min, including the processes of sample dewaxing, spectra acquisition and analysis), accurate (the prediction accuracy, specificity and sensitivity can reach above 99%), and without reagent. Moreover, this method is much superior to the common classification method of principal component analysis-linear discriminate analysis (PCA-LDA) (the prediction accuracy, specificity and sensitivity are only 87%, 89% and 86%, respectively). The ANN mainly learned the characteristic region of 800-1800 cm^-1 to classify the major histopathologic classes of human glioma. These results demonstrate that the grade diagnosis of human glioma by FTIR microscopy plus ANN can be streamlined, and could serve as a complementary pathway that is independent of the traditional pathology laboratory.

A New Look into Cancer-A Review on the Contribution of Vibrational Spectroscopy on Early Diagnosis and Surgery Guidance

Simple Summary

Cancer is a leading cause of death worldwide, with the detection of the disease in its early stages, as well as a correct assessment of the tumour margins, being paramount for a successful recovery. While breast cancer is one of most common types of cancer, head and neck cancer is one of the types of cancer with a lower prognosis and poor aesthetic results. Vibrational spectroscopy detects molecular vibrations, being sensitive to different sample compositions, even when the difference was slight. The use of spectroscopy in biomedicine has been extensively explored, since it allows a broader assessment of the biochemical fingerprint of several diseases. This literature review covers the most recent advances in breast and head and neck cancer early diagnosis and intraoperative margin assessment, through Raman and Fourier transform infrared spectroscopies. The rising field of spectral histopathology was also approached. The authors aimed at expounding in a more concise and simple way the challenges faced by clinicians and how vibrational spectroscopy has evolved to respond to those needs for the two types of cancer with the highest potential for improvement regarding an early diagnosis, surgical margin assessment and histopathology.

Abstract

In 2020, approximately 10 million people died of cancer, rendering this disease the second leading cause of death worldwide. Detecting cancer in its early stages is paramount for patients’ prognosis and survival. Hence, the scientific and medical communities are engaged in improving both therapeutic strategies and diagnostic methodologies, beyond prevention. Optical vibrational spectroscopy has been shown to be an ideal diagnostic method for early cancer diagnosis and surgical margins assessment, as a complement to histopathological analysis. Being highly sensitive, non-invasive and capable of real-time molecular imaging, Raman and Fourier transform infrared (FTIR) spectroscopies give information on the biochemical profile of the tissue under analysis, detecting the metabolic differences between healthy and cancerous portions of the same sample. This constitutes tremendous progress in the field, since the cancer-prompted morphological alterations often occur after the biochemical imbalances in the oncogenic process. Therefore, the early cancer-associated metabolic changes are unnoticed by the histopathologist. Additionally, Raman and FTIR spectroscopies significantly reduce the subjectivity linked to cancer diagnosis. This review focuses on breast and head and neck cancers, their clinical needs and the progress made to date using vibrational spectroscopy as a diagnostic technique prior to surgical intervention and intraoperative margin assessment.

Tracking of the biochemical changes upon pleomorphic adenoma progression using vibrational microspectroscopy

Head and neck tumors can be very challenging to treat because of the risk of problems or complications after surgery. Therefore, prompt and accurate diagnosis is extremely important to drive appropriate treatment decisions, which may reduce the chance of recurrence. This paper presents the original research exploring the feasibility of Fourier transform infrared (FT-IR) and Raman spectroscopy (RS) methods to investigate biochemical alterations upon the development of the pleomorphic adenoma. Principal component analysis (PCA) was used for a detailed assessment of the observed changes and to determine the spectroscopic basis for salivary gland neoplastic pathogenesis. It is implied that within the healthy margin, as opposed to the tumoral tissue, there are parts that differ significantly in lipid content. This observation shed new light on the crucial role of lipids in tissue physiology and tumorigenesis. Thus, a novel approach that eliminates the influence of lipids on the elucidation of biochemical changes is proposed. The performed analysis suggests that the highly heterogeneous healthy margin contains more unsaturated triacylglycerols, while the tumoral section is rich in proteins. The difference in protein content was also observed for these two tissue types, i.e. the healthy tissue possesses more proteins in the anti-parallel β-sheet conformation, whereas the tumoral tissue is dominated by proteins rich in unordered random coils. Furthermore, the pathogenic tissue shows a higher content of carbohydrates and reveals noticeable differences in nucleic acid content. Finally, FT-IR and Raman spectroscopy methods were proposed as very promising methods in the discrimination of tumoral and healthy tissues of the salivary gland.

Application of mid-infrared microscopic imaging for the diagnosis and classification of human lymphomas

Mid-infrared (MIR) microscopic imaging of indolent and aggressive lymphomas was performed including formalin-fixed and paraffin-embedded samples of six follicular lymphomas and 12 diffuse large B-cell-lymphomas as well as reactive lymph nodes to investigate benefits and challenges for lymphoma diagnosis. MIR images were compared to defined pathological characteristics such as indolent versus aggressive versus reactive, germinal centre versus activated cell-of-origin (COO) subtypes, or a low versus a high proliferative index and level of PD-L1 expression. We demonstrated that MIR microscopic imaging can differentiate between reactive lymph nodes, indolent and aggressive lymphoma samples. Also, it has potential to be used in the subtyping of lymphomas, as shown with the differentiation between COO subtypes, the level of proliferation and PD-L1 expression. MIR microscopic imaging is a promising tool for diagnosis and subtyping of lymphoma and further evaluation is needed to fully explore the advantages and disadvantages of this method for pathological diagnosis.

Insight into metastatic oral cancer tissue from novel analyses using FTIR spectroscopy and aperture IR-SNOM

A novel machine learning algorithm is shown to accurately discriminate between oral squamous cell carcinoma (OSCC) nodal metastases and surrounding lymphoid tissue on the basis of a single metric, the ratio of Fourier transform infrared (FTIR) absorption intensities at 1252 cm-1 and 1285 cm-1. The metric yields discriminating sensitivities, specificities and precision of 98.8 ± 0.1%, 99.89 ± 0.01% and 99.78 ± 0.02% respectively, and an area under receiver operator characteristic (AUC) of 0.9935 ± 0.0006. The delineation of the OSCC and lymphoid tissue revealed by the image formed from the metric is in better agreement with an immunohistochemistry (IHC) stained image than are either of the FTIR images obtained at the individual wavenumbers. Scanning near-field optical microscopy (SNOM) images of the tissue obtained at a number of key wavenumbers, with high spatial resolution, show variations in the chemical structure of the tissue with a feature size down to ∼4 μm. The image formed from the ratio of the SNOM images obtained at 1252 cm-1 and 1285 cm-1 shows more contrast than the SNOM images obtained at these or a number of other individual wavenumbers. The discrimination between the two tissue types is dominated by the contribution from the 1252 cm-1 signal, which is representative of nucleic acids, and this shows the OSCC tissue to be accompanied by two wide arcs of tissue which are particularly low in nucleic acids. Haematoxylin and eosin (H&E) staining shows the tumour core in this specimen to be ∼40 μm wide and the SNOM topography shows that the core centre is raised by ∼1 μm compared to the surrounding tissue. Line profiles of the SNOM signal intensity taken through the highly keratinised core show that the increase in height correlates with an increase in the protein signal. SNOM line profiles show that the nucleic acids signal decreases at the centre of the tumour core between two peaks of higher intensity. All these nucleic acid features are ∼25 μm wide, roughly the width of two cancer cells.

Saliva based non invasive screening of Oral Submucous Fibrosis using ATR-FTIR spectroscopy

Oral Submucous Fibrosis (OSMF) is a type of precancerous condition of Oral cancer and considered to have the greatest malignant potential. Biopsy is an ultimate option for the conformation of the malignancy. But the invasiveness of the procedure makes it interdict. Therefore, there is an urgent need to identify effective screening and diagnostic methods which would be less invasive, rapid, more accurate and cost effective. Here, we used Attenuated Total Reflection- Fourier transform infrared spectroscopy (ATR-FTIR) with Chemometric analysis coupled with estimation of total salivary protein to discriminate OSMF and Healthy Control (HC). The present study showed the specific Infrared spectrum for OSMF patients, which was specifically differentiated from HC based on the spectral shift of proteins/amide II, carbohydrate and nucleic acid using Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) with small data sets. ATR-FTIR spectroscopy of saliva coupled with total protein estimation can be used to discriminate between OSMF and HC. However, large sample size should be needed to evaluate the ATR-FTIR for consideration as a screening tool for an early diagnosis OSMF.

Infrared Microspectroscopy With Multivariate Analysis to Differentiate Oral Hyperplasia From Squamous Cell Carcinoma: A Proof of Concept for Early Diagnosis

BACKGROUND AND OBJECTIVES

Despite having numerous advances in therapeutics, mortality and morbidity due to oral cancer incidence are still very high. Early detection can improve the chances of survival in most patients. However, diagnosis at early stages can be challenging as premalignant conditions are usually asymptomatic. Currently, histological assessment remains the gold standard for diagnosis. Early diagnosis poses challenges to pathologists due to less severe morphological changes associated with early stages. Therefore, a fast and robust method of detection based on molecular changes is needed for early diagnosis. © 2021 Wiley Periodicals LLC.

STUDY DESIGN/MATERIAL AND METHODS

In the present study, Fourier transform infrared (FTIR) spectroscopic imaging has been used to differentiate early-stage oral hyperplasia from adjacent normal (AN) and oral squamous cell carcinoma (OSCC). Hyperplasia is often considered as an initial event in the pathogenesis of oral cancer and OSCC is the most common advanced stage of malignancy. Differentiating normal versus hyperplasia and hyperplasia versus OSCC can remain quite challenging on occasion using conventional staining as the histological assessment is based on morphological changes.

RESULTS

Unsupervised hierarchical cluster analysis (UHCA) has been performed on FTIR images of multiple tissues together that provided some degree of classification among tissue groups. The AN epithelium clustered distinctively using UHCA from both hyperplasia and grades 1 and 2 of OSCC. An increase in the content of DNA, denaturation of protein, and altered lipid structures were more clearly elucidated with spectral analysis.

CONCLUSION

This study demonstrates a simple strategy to differentiate early-stage oral hyperplasia from AN and OSCC using UHCA. This study also proposes a future alternative method where FTIR imaging can be used as a diagnostic tool for cancer at early stages.

Biomedical applications of vibrational spectroscopy: Oral cancer diagnostics

Vibrational spectroscopy, based on either infrared absorption or Raman scattering, has attracted increasing attention for biomedical applications. Proof of concept explorations for diagnosis of oral potentially malignant disorders and cancer are reviewed, and recent advances critically appraised. Specific examples of applications of Raman microspectroscopy for analysis of histological, cytological and saliva samples are presented for illustrative purposes, and the future prospects, ultimately for routine, chairside in vivo screening are discussed.

Automatic Identification of Paraffin Pixels on FTIR Images Acquired on FFPE Human Samples

The transfer of mid-infrared spectral histopathology to the clinic will be possible provided that its application in clinical practice is simple. Rapid analysis of formalin-fixed paraffin-embedded (FFPE) tissue section is thus a prerequisite. The chemical dewaxing of these samples before image acquisition used by the majority of studies is in contradiction with this principle. Fortunately, the in silico analysis of the images acquired on FFPE samples is possible using extended multiplicative signal correction (EMSC). However, the removal of pure paraffin pixels is essential to perform a relevant classification of tissue spectra. So far, this task was possible only if using manual and subjective histogram analysis. In this article, we thus propose a new automatic and multivariate methodology based on the analysis of optimized combinations of EMSC regression coefficients by validity indices and KMeans clustering to separate paraffin and tissue pixels. The validation of our method is performed using simulated infrared spectral images by measuring the Jaccard index between our partitions and the image model, with values always over 0.90 for diverse baseline complexity and signal-to-noise ratio. These encouraging results were also validated on real images by comparing our method with classical ones and by computing the Jaccard index between our partitions and the KMeans partitions obtained on the infrared image acquired on the same samples but after chemical dewaxing, with values always over 0.84.

Fourier Transform Infrared Spectroscopy in Oral Cancer Diagnosis

Oral cancer is one of the most common cancers worldwide. Despite easy access to the oral cavity and significant advances in treatment, the morbidity and mortality rates for oral cancer patients are still very high, mainly due to late-stage diagnosis when treatment is less successful. Oral cancer has also been found to be the most expensive cancer to treat in the United States. Early diagnosis of oral cancer can significantly improve patient survival rate and reduce medical costs. There is an urgent unmet need for an accurate and sensitive molecular-based diagnostic tool for early oral cancer detection. Fourier transform infrared spectroscopy has gained increasing attention in cancer research due to its ability to elucidate qualitative and quantitative information of biochemical content and molecular-level structural changes in complex biological systems. The diagnosis of a disease is based on biochemical changes underlying the disease pathology rather than morphological changes of the tissue. It is a versatile method that can work with tissues, cells, or body fluids. In this review article, we aim to summarize the studies of infrared spectroscopy in oral cancer research and detection. It provides early evidence to support the potential application of infrared spectroscopy as a diagnostic tool for oral potentially malignant and malignant lesions. The challenges and opportunities in clinical translation are also discussed.

Technical Note: Noninvasive mid-IR fiber-optic evanescent wave spectroscopy (FEWS) for early detection of skin cancers

PURPOSE

Melanoma is the most lethal of the three primary skin cancers, including also basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), which are less lethal. The accepted diagnosis process involves manually observing a suspicious lesion through a Dermascope (i.e., a magnifying glass), followed by a biopsy. This process relies on the skill and the experience of a dermatologist. However, to the best of our knowledge, there is no accepted automatic, noninvasive, and rapid method for the early detection of the three types of skin cancer, distinguishing between them and noncancerous lesions, and identifying each of them. It is our aim to develop such a system.

METHODS

We developed a fiber-optic evanescent wave spectroscopy (FEWS) system based on middle infrared (mid-IR) transmitting AgClBr fibers and a Fourier-transform infrared spectrometer (FTIR). We used the system to perform mid-IR spectral measurements on suspicious lesions in 90 patients, before biopsy, in situ, and in real time. The lesions were then biopsied and sent for pathology. The spectra were analyzed and the differences between pathological and healthy tissues were found and correlated.

RESULTS

Five of the lesions measured were identified as melanomas, seven as BCC, and three as SCC. Using mathematical analyses of the spectra of these lesions we were able to tell that all were skin cancers and we found specific and easily identifiable differences between them.

CONCLUSIONS

This FEWS method lends itself to rapid, automatic and noninvasive early detection and characterization of skin cancers. It will be easily implemented in community clinics and has the potential to greatly simplify the diagnosis process.

A de-waxing methodology for scanning probe microscopy

A de-waxing protocol that successfully removes paraffin from tissue microarray (TMA) cores of fixed tissue obtained from oral cancer is described. The success of the protocol is demonstrated by the comparison of Fourier transform infrared (FTIR) results obtained on paraffin-embedded and de-waxed tissue and the absence of any significant correlations between infrared scanning near-field optical microscopy (SNOM) images of de-waxed tissue obtained at the three main paraffin IR peaks. The success of the protocol in removing paraffin from tissue is also demonstrated by images obtained with scanning electron microscopy (SEM) and by energy dispersive spectra (EDS) of a de-waxed CaF2 disc which shows no significant contribution from carbon. The FTIR spectra of the de-waxed TMA core overlaps that obtained from OE19 oesophageal cancer cells which had never been exposed to paraffin.

Nanoscale infrared probing of amyloid formation within the pleomorphic adenoma tissue

BACKGROUND

The process of malignant transformations of many tumour cases is still unclear and more specific experimental approaches are necessary. The detailed identification of the pathological changes may help in the therapy progression through the development of drugs with more selective action.

METHODS

In this study, the AFM-IR nanospectroscopy was applied for the first time to the pleomorphic adenoma (TM) and the marginal tissue characterizations. In order to verify the obtained spectral information, conventional FT-IR investigations were also performed.

RESULTS

The AFM-IR data (topographies, intensity maps, and spectra) show structural changes observed for the margin and TM samples. Additionally, within the tumour tissue the fibril-like areas, characteristic for amyloid diseases, were distinguished.

CONCLUSIONS

The application of AFM-IR allows to determine changes in the protein secondary structures between the fibrils and the regions outside them. It has been proved that, for the former areas, the α-helix/random coil/ β-sheet components dominate, while for the latter regions the α-helix/random coil indicate the main contribution to the protein composition.

GENERAL SIGNIFICANCE

The FT-IR results remain in good agreement with the AFM-IR data recorded for the areas outside the fibrils of the TM. This observation confirms that by means of the conventional FT-IR method the identification of the considered fibrils structure would be impossible. Only application of the AFM-IR nanospectroscopy allow for characterization and visualization of the fibrillization process occurring within the investigated tumour tissue.

Near-Infrared Spectroscopy in Bio-Applications

Near-infrared (NIR) spectroscopy occupies a specific spot across the field of bioscience and related disciplines. Its characteristics and application potential differs from infrared (IR) or Raman spectroscopy. This vibrational spectroscopy technique elucidates molecular information from the examined sample by measuring absorption bands resulting from overtones and combination excitations. Recent decades brought significant progress in the instrumentation (e.g., miniaturized spectrometers) and spectral analysis methods (e.g., spectral image processing and analysis, quantum chemical calculation of NIR spectra), which made notable impact on its applicability. This review aims to present NIR spectroscopy as a matured technique, yet with great potential for further advances in several directions throughout broadly understood bio-applications. Its practical value is critically assessed and compared with competing techniques. Attention is given to link the bio-application potential of NIR spectroscopy with its fundamental characteristics and principal features of NIR spectra.

Biomolecular and bioanalytical applications of infrared spectroscopy - A review

Infrared (IR; or mid-infrared, MIR; 4000-400 cm^-1; 2500-25,000 nm) spectroscopy has become one of the most powerful and versatile tools at the disposal of modern bioscience. Because of its high molecular specificity, applicability to wide variety of samples, rapid measurement and non-invasivity, IR spectroscopy forms a potent approach to elucidate qualitative and quantitative information from various kinds of biological material. For these reasons, it became an established bioanalytical technique with diverse applications. This work aims to be a comprehensive and critical review of the recent accomplishments in the field of biomolecular and bioanalytical IR spectroscopy. That progress is presented on a wider background, with fundamental characteristics, the basic principles of the technique outlined, and its scientific capability directly compared with other methods being used in similar fields (e.g. near-infrared, Raman, fluorescence). The article aims to present a complete examination of the topic, as it touches the background phenomena, instrumentation, spectra processing and data analytical methods, spectra interpretation and related information. To suit this goal, the article includes a tutorial information essential to obtain a thorough perspective of bio-related applications of the reviewed methodologies. The importance of the fundamental factors to the final performance and applicability of IR spectroscopy in various areas of bioscience is explained. This information is interpreted in critical way, with aim to gain deep understanding why IR spectroscopy finds extraordinarily intensive use in this remarkably diverse and dynamic field of research and utility. The major focus is placed on the diversity of the applications in which IR biospectroscopy has been established so far and those onto which it is expanding nowadays. This includes qualitative and quantitative analytical spectroscopy, spectral imaging, medical diagnosis, monitoring of biophysical processes, and studies of physicochemical properties and dynamics of biomolecules. The application potential of IR spectroscopy in light of the current accomplishments and the future prospects is critically evaluated and its significance in the progress of bioscience is comprehensively presented.

Comparison of structure and composition of a fossil Champsosaurus vertebra with modern Crocodylidae vertebrae: A multi-instrumental approach

Information on the adaptation of bone structures during evolution is rare since histological data are limited. Micro- and nano-computed tomography of a fossilized vertebra from Champsosaurus sp., which has an estimated age of 70-73 million years, revealed lower porosity and higher bone density compared to modern Crocodylidae vertebrae. Mid-infrared reflectance and energy dispersive X-ray mapping excluded a petrification process, and demonstrated a typical carbonate apatite distribution, confirming histology in light- and electron microscopy of the preserved vertebra. As a consequence of this evolutionary process, the two vertebrae of modern Crocodylidae show reduced overall stiffness in the finite element analysis simulation compared to the fossilized Champsosaurus sp. vertebra, with predominant stiffness along the longitudinal z-axes.

Fourier transform infrared and Raman-based biochemical profiling of different grades of pure foetal-type hepatoblastoma

The biomolecular events resulting from the progression of hepatoblastoma remain to be elucidated. Fourier-transform infrared (FTIR) and Raman spectroscopies are capable of noninvasively and accurately capturing the biochemical properties of biological tissue from its pathological status. Our aim was to probe critial biomolecular changes of liver accompanying the progression of pure foetal hepatoblastoma (PFH) by FTIR and Raman spectroscopies. Herein, biochemical alterations were both evident in the FTIR spectra (regions of 3100-2800 cm^-1 and 1800-900 cm^-1 ) and the Raman spectra (region of 1800-400 cm^-1 ) among normal, borderline and malignant liver tissues. Compared with normal tissues, the ratios of protein-to-lipid, α-helix-to-β-sheet, RNA-to-DNA, CH3 methyl-to-CH2 methylene, glucose-to-phospholipids, and unsaturated-to-saturated lipids intensities were significantly higher in malignant tissues, while the ratios of RNA-to-Amide II, DNA-to-Amide II, glycogen-to-cholesterol and Amide I-to-Amide II intensities were remarkably lower. These biochemical alterations in the transition from normal to malignant have profound implications not only for cyto-pathological classification but also for molecular understanding of PFH progression. The successive changes of the spectral characteristics have been shown to be consistent with the development of PFH, indicating that FTIR and Raman spectroscopies are excellent tools to interrogate the biochemical features of different grades of PFH.

New insights into spectral histopathology: infrared-based scoring of tumour aggressiveness of squamous cell lung carcinomas

Spectral histopathology, based on infrared interrogation of tissue sections, proved a promising tool for helping pathologists in characterizing histological structures in a quantitative and automatic manner.

Spectral histopathology, based on infrared interrogation of tissue sections, proved a promising tool for helping pathologists in characterizing histological structures in a quantitative and automatic manner. In cancer diagnosis, the use of chemometric methods permits establishing numerical models able to detect cancer cells and to characterize their tissular environment. In this study, we focused on exploiting multivariate infrared data to score the tumour aggressiveness in preneoplastic lesions and squamous cell lung carcinomas. These lesions present a wide range of aggressive phenotypes; it is also possible to encounter cases with various degrees of aggressiveness within the same lesion. Implementing an infrared-based approach for a more precise histological determination of the tumour aggressiveness should arouse interest among pathologists with direct benefits for patient care. In this study, the methodology was developed from a set of samples including all degrees of tumour aggressiveness and by constructing a chain of data processing steps for an automated analysis of tissues currently manipulated in routine histopathology.

Biochemical Changes in Irradiated Oral Mucosa: A FTIR Spectroscopic Study

Radiation exposure during the course of treatment in head and neck cancer (HNC) patients can induce both structural and biochemical anomalies. The present study is focused on utilizing infrared imaging for the identification of the minor biochemical alterations in the oral mucosa. Chemical maps generated using glycoprotein band indicates its differential distribution along the superficial layer. Spectra extracted from this layer suggests changes in overall nucleic acid and protein content in response to the therapeutic irradiation. Discrimination among control and irradiated groups have been achieved using principal component analysis. Findings of this preliminary study further support prospective utilization of Fourier Transform InfraRed (FTIR) imaging as a non-destructive, label-free tool for objective assessment of the oral mucosa in patient groups with or without radiation therapy.

Chemometric analysis of integrated FTIR and Raman spectra obtained by non-invasive exfoliative cytology for the screening of oral cancer

FTIR spectroscopy and Raman spectroscopy of biological analytes are increasingly explored as screening tools for early detection of cancer.

Amalgam tattoo versus melanocytic neoplasm - Differential diagnosis of dark pigmented oral mucosa lesions using infrared spectroscopy

Background

Dark pigmented lesions of the oral mucosa can represent a major diagnostic challenge. A biopsy is usually required to determine the nature of such intraoral discolorations. This study investigates the potential use of infrared spectroscopy for differential diagnosis of amalgam tattoos versus benign or malignant melanocytic neoplasms.

Materials and methods

For this retrospective study, formalin-fixed paraffin-embedded tissue (FFPE) specimens of dark pigmented lesions concerning the oral mucosa or the lip were investigated using mid infrared spectroscopy. The samples were chosen from patients who had undergone a mucosal biopsy at the University Hospital Innsbruck (Austria) between the years 2000 and 2017. Principal component analysis was used for data exploration. Evaluation was based on the superimposition of the recorded spectra and the corresponding histologic slides.

Results

In total, 22 FFPE specimens were analyzed. Clear differences were found between amalgam and non-amalgam samples. A general weakening of the penetrating infrared radiation allowed for unspecific discrimination between these two classes. An overall accuracy in predicting the correct class of 95.24% was achieved.

Conclusion

Infrared spectroscopy appears to be a suitable technique to differentiate between amalgam tattoos and melanocytic lesions in FFPE samples. It could potentially be applied in vivo, too, serving as a non-invasive diagnostic tool for intraoral dark pigmented lesions.

MIR-biospectroscopy coupled with chemometrics in cancer studies

This review focuses on chemometric techniques applied in MIR-biospectroscopy for cancer diagnosis and analysis over the last ten years of research. Experimental applications of chemometrics coupled with biospectroscopy are discussed throughout this work. The advantages and drawbacks of this association are also highlighted. Chemometric algorithms are evidenced as a powerful tool for cancer diagnosis, classification, and in different matrices. In fact, it is shown how chemometrics can be implemented along all different types of cancer analyses.

Clinical infrared microscopic imaging: An overview

New developments in Mid-infrared microscopic imaging instrumentation and data analysis have turned this method into a conventional technique. This imaging method offers a global analysis of samples, with a resolution close to the cellular level enabling the acquisition of local molecular expression profiles. It is possible to get chemo-morphological information about the tissue status, which represents an essential benefit for future analytical interpretation of pathological changes of tissue. In this review, we give an overview of Mid-infrared microscopic imaging and its applications in clinical research.

Serum-based diagnostic prediction of oral submucous fibrosis using FTIR spectrometry

Oral submucous fibrosis (OSF) is found to have the highest malignant potentiality among all other pre-cancerous lesions. However, its detection prior to tissue biopsy can be challenging in clinics. Moreover, biopsy examination is invasive and painful. Hence, there is an urgent need of new technology that facilitates accurate diagnostic prediction of OSF prior to biopsy. Here, we used FTIR spectroscopy coupled with chemometric techniques to distinguish the serum metabolic signatures of OSF patients (n=30) and healthy controls (n=30). Serum biochemical analyses have been performed to further support the FTIR findings. Absorbance intensities of 45 infrared wavenumbers differed significantly between OSF and normal serum FTIR spectra representing alterations in carbohydrates, proteins, lipids and nucleic acids. Nineteen prominent significant wavenumbers (P≤0.001) at 1020, 1025, 1035, 1039, 1045, 1078, 1055, 1100, 1117, 1122, 1151, 1169, 1243, 1313, 1398, 1453, 1544, 1650 and 1725cm^-1 provided excellent segregation of OSF spectra from normal using multivariate statistical techniques. These findings provided essential information on the metabolic features of blood serum of OSF patients and established that FTIR spectroscopy coupled with chemometric analysis can be potentially useful in the rapid and accurate preoperative screening/diagnosis of OSF.

"Omics" in oral cancer: New approaches for biomarker discovery

OBJECTIVES

In this review paper, we explored the application of "omics" approaches in the study of oral cancer (OC). It will provide a better understanding of how "omics" approaches may lead to novel biomarker molecules or molecular signatures with potential value in clinical practice. A future direction of "omics"-driven research in OC is also discussed.

METHODS

Studies on "omics"-based approaches [genomics/proteomics/transcriptomics/metabolomics] were investigated for differentiating oral squamous cell carcinoma,oral sub-mucous fibrosis, oral leukoplakia, oral lichen planus, oral erythroplakia from normal cases. Electronic databases viz., PubMed, Springer, and Google Scholar were searched.

RESULTS

One eighty-one studies were included in this review. The review shows that the fields of genomics, transcriptomics, proteomics, and metabolomics-based marker identification have implemented advanced tools to screen early changes in DNA, RNA, protein, and metabolite expression in OC population.

CONCLUSIONS

It may be concluded that despite advances in OC therapy, symptomatic presentation occurs at an advanced stage, where various curative treatment options become very limited. A molecular level study is essential for detecting an OC biomarker at an early stage. Modern "Omics" strategies can potentially make a major contribution to meet this need.

Assessing various Infrared (IR) microscopic imaging techniques for post-mortem interval evaluation of human skeletal remains

Due to the influence of many environmental processes, a precise determination of the post-mortem interval (PMI) of skeletal remains is known to be very complicated. Although methods for the investigation of the PMI exist, there still remains much room for improvement. In this study the applicability of infrared (IR) microscopic imaging techniques such as reflection-, ATR- and Raman- microscopic imaging for the estimation of the PMI of human skeletal remains was tested. PMI specific features were identified and visualized by overlaying IR imaging data with morphological tissue structures obtained using light microscopy to differentiate between forensic and archaeological bone samples. ATR and reflection spectra revealed that a more prominent peak at 1042 cm-1 (an indicator for bone mineralization) was observable in archeological bone material when compared with forensic samples. Moreover, in the case of the archaeological bone material, a reduction in the levels of phospholipids, proteins, nucleic acid sugars, complex carbohydrates as well as amorphous or fully hydrated sugars was detectable at (reciprocal wavelengths/energies) between 3000 cm-1 to 2800 cm-1. Raman spectra illustrated a similar picture with less ν2PO43-at 450 cm-1 and ν4PO43- from 590 cm-1 to 584 cm-1, amide III at 1272 cm-1 and protein CH2 deformation at 1446 cm-1 in archeological bone material/samples/sources. A semi-quantitative determination of various distributions of biomolecules by chemi-maps of reflection- and ATR- methods revealed that there were less carbohydrates and complex carbohydrates as well as amorphous or fully hydrated sugars in archaeological samples compared with forensic bone samples. Raman- microscopic imaging data showed a reduction in B-type carbonate and protein α-helices after a PMI of 3 years. The calculated mineral content ratio and the organic to mineral ratio displayed that the mineral content ratio increases, while the organic to mineral ratio decreases with time. Cluster-analyses of data from Raman microscopic imaging reconstructed histo-anatomical features in comparison to the light microscopic image and finally, by application of principal component analyses (PCA), it was possible to see a clear distinction between forensic and archaeological bone samples. Hence, the spectral characterization of inorganic and organic compounds by the afore mentioned techniques, followed by analyses such as multivariate imaging analysis (MIAs) and principal component analyses (PCA), appear to be suitable for the post mortem interval (PMI) estimation of human skeletal remains.

Comparison of multivariate analysis methods for extracting the paraffin component from the paraffin-embedded cancer tissue spectra for Raman imaging

This study aimed to extract the paraffin component from paraffin-embedded oral cancer tissue spectra using three multivariate analysis (MVA) methods; Independent Component Analysis (ICA), Partial Least Squares (PLS) and Independent Component - Partial Least Square (IC-PLS). The estimated paraffin components were used for removing the contribution of paraffin from the tissue spectra. These three methods were compared in terms of the efficiency of paraffin removal and the ability to retain the tissue information. It was found that ICA, PLS and IC-PLS could remove the paraffin component from the spectra at almost the same level while Principal Component Analysis (PCA) was incapable. In terms of retaining cancer tissue spectral integrity, effects of PLS and IC-PLS on the non-paraffin region were significantly less than that of ICA where cancer tissue spectral areas were deteriorated. The paraffin-removed spectra were used for constructing Raman images of oral cancer tissue and compared with Hematoxylin and Eosin (H&E) stained tissues for verification. This study has demonstrated the capability of Raman spectroscopy together with multivariate analysis methods as a diagnostic tool for the paraffin-embedded tissue section.

Vibrational Micro-Spectroscopy of Human Tissues Analysis: Review

Vibrational spectroscopy (Infrared (IR) and Raman) and, in particular, micro-spectroscopy and micro-spectroscopic imaging have been used to characterize developmental changes in tissues, to monitor these changes in cell cultures and to detect disease and drug-induced modifications. The conventional methods for biochemical and histophatological tissue characterization necessitate complex and "time-consuming" sample manipulations and the results are rarely quantifiable. The spectroscopy of molecular vibrations using mid-IR or Raman techniques has been applied to samples of human tissue. This article reviews the application of these vibrational spectroscopic techniques for analysis of biological tissue published between 2005 and 2015.

In Vivo Monitoring of the Growth of Fertilized Eggs of Medaka Fish (Oryzias latipes) by Near-Infrared Spectroscopy and Near-Infrared Imaging-A Marked Change in the Relative Content of Weakly Hydrogen-Bonded Water in Egg Yolk Just before Hatching

The present study develops further our previous study of in vivo monitoring at the molecular level of the embryonic development in Japanese medaka fish (Oryzias latipes) using near-infrared (NIR) spectroscopy and NIR imaging. NIR spectra were measured nondestructively for three major parts of fertilized medaka eggs (the embryonic body, oil droplets, and egg yolk) from the first day after fertilization to the day just before hatching (JBH). Changes in the contents of chemical components such as proteins, water, and lipids were monitored in situ during embryonic development. A marked change in the relative content of weakly hydrogen-bonded water was observed in the egg yolk JBH. Principal component analysis (PCA) was carried out using the NIR spectra data of the egg yolk and embryo on the fifth day after fertilization. The PCA clearly separates the egg yolk data from the embryo body parts. Principal component PC1 and PC2 loading plots suggest that the hydrogen bonding structure of water in the egg yolk is considerably different to those of the other parts and the fraction of weakly hydrogen-bonded water in the egg yolk is smaller than that in the embryonic body. NIR images developed from the intensities of peaks of second derivative spectra owing to water and proteins show their different distribution patterns. Images of the ratio of strongly and weakly hydrogen-bonded water confirmed that oil droplets and embryonic body parts have higher and lower ratios, respectively, of strongly hydrogen-bonded water than do the other parts. The images developed from the intensity of the peaks at 4864 and 4616 cm⁻¹ related to the proteins indicated that the egg yolk contains a higher concentration of protein than do the other parts. The peaks at 5756 and 4530 cm⁻¹ caused by the protein secondary structures of α-helix and β-sheet showed the configuration of the egg cell membrane. The present study might lead to new understanding at the molecular level regarding the growth of fertilized eggs and provides a new tool to visualize egg development in a nondestructive manner.

High-resolution FTIR imaging of colon tissues for elucidation of individual cellular and histopathological features

Comparison of spectral-histopathological features of a colon tissue measured using a conventional (5.5 μm × 5.5 μm, left) and a high-magnification (1.1 μm × 1.1 μm, right) FTIR imaging system with respect to HE stained tissue (middle).

Recent advances in optical diagnosis of oral cancers: Review and future perspectives

Optical diagnosis techniques offer several advantages over traditional approaches, including objectivity, speed, and cost, and these label-free, noninvasive methods have the potential to change the future workflow of cancer management. The oral cavity is particularly accessible and, thus, such methods may serve as alternate/adjunct tools to traditional methods. Recently, in vivo human clinical studies have been initiated with a view to clinical translation of such technologies. A comprehensive review of optical methods in oral cancer diagnosis is presented. After an introduction to the epidemiology and etiological factors associated with oral cancers currently used, diagnostic methods and their limitations are presented. A thorough review of fluorescence, infrared absorption, and Raman spectroscopic methods in oral cancer diagnosis is presented. The applicability of minimally invasive methods based on serum/saliva is also discussed. The review concludes with a discussion on future demands and scope of developments from a clinical point of view. © 2015 Wiley Periodicals, Inc. Head Neck 38: E2403-E2411, 2016.

Application of mid-infrared (MIR) microscopy imaging for discrimination between follicular hyperplasia and follicular lymphoma in transgenic mice

Mid-infrared (MIR) microscopy imaging is a vibrational spectroscopic technique that uses infrared radiation to image molecules of interest in thin tissue sections. A major advantage of this technology is the acquisition of local molecular expression profiles, while maintaining the topographic integrity of the tissue. Therefore, this technology has become an essential tool for the detection and characterization of the molecular components of many biological processes. Using this method, it is possible to investigate the spatial distribution of proteins and small molecules within biological systems by in situ analysis. In this study, we have evaluated the potential of mid-infrared microscopy imaging to study biochemical changes which distinguish between reactive lymphadenopathy and cancer in genetically modified mice with different phenotypes. We were able to demonstrate that MIR microscopy imaging and multivariate image analyses of different mouse genotypes correlated well with the morphological tissue features derived from HE staining. Using principal component analyses, we were also able to distinguish spectral clusters from different phenotype samples, particularly from reactive lymphadenopathy (follicular hyperplasia) and cancer (follicular lymphoma).

Fourier-transform-infrared-spectroscopy based spectral-biomarker selection towards optimum diagnostic differentiation of oral leukoplakia and cancer

In search of specific label-free biomarkers for differentiation of two oral lesions, namely oral leukoplakia (OLK) and oral squamous-cell carcinoma (OSCC), Fourier-transform infrared (FTIR) spectroscopy was performed on paraffin-embedded tissue sections from 47 human subjects (eight normal (NOM), 16 OLK, and 23 OSCC). Difference between mean spectra (DBMS), Mann-Whitney's U test, and forward feature selection (FFS) techniques were used for optimising spectral-marker selection. Classification of diseases was performed with linear and quadratic support vector machine (SVM) at 10-fold cross-validation, using different combinations of spectral features. It was observed that six features obtained through FFS enabled differentiation of NOM and OSCC tissue (1782, 1713, 1665, 1545, 1409, and 1161 cm(-1)) and were most significant, able to classify OLK and OSCC with 81.3 % sensitivity, 95.7 % specificity, and 89.7 % overall accuracy. The 43 spectral markers extracted through Mann-Whitney's U Test were the least significant when quadratic SVM was used. Considering the high sensitivity and specificity of the FFS technique, extracting only six spectral biomarkers was thus most useful for diagnosis of OLK and OSCC, and to overcome inter and intra-observer variability experienced in diagnostic best-practice histopathological procedure. By considering the biochemical assignment of these six spectral signatures, this work also revealed altered glycogen and keratin content in histological sections which could able to discriminate OLK and OSCC. The method was validated through spectral selection by the DBMS technique. Thus this method has potential for diagnostic cost minimisation for oral lesions by label-free biomarker identification.

Infrared and Raman imaging for characterizing complex biological materials: a comparative morpho-spectroscopic study of colon tissue

Complementary diagnostic methods to conventional histopathology are currently being investigated for developing rapid and objective molecular-level understanding of various disorders, especially cancers. Spectral histopathology using vibrational spectroscopic imaging has been put in the frontline as potentially promising in this regard as it provides a "spectral fingerprint" of the biochemical composition of cells and tissues. In order to ascertain the feasible conditions of vibrational spectroscopic methods for tissue-imaging analysis, vibrational multimodal imaging (infrared transmission, infrared-attenuated total reflection, and Raman imaging) of the same colon tissue has been implemented. The spectral images acquired were subjected to multivariate clustering analysis in order to identify on a molecular level the constituent histological organization of the colon tissue such as the epithelium, connective tissue, etc., by comparing the cluster images with the histological reference images. Based on this study, a comparative analysis of important factors involved in the vibrational multimodal imaging approaches such as image resolution, time constraints, their advantages and limitations, and their applicability to biological tissues has been carried out. Out of the three different vibrational imaging modalities tested, infrared-attenuated total reflection mode of imaging appears to provide a good compromise between the tissue histology and the time constraints in achieving similar image contrast to that of Raman imaging at an approximately 33-fold faster measurement time. The present study demonstrates the advantages, the limitations of the important parameters involved in vibrational multimodal imaging approaches, and their potential application toward imaging of biological tissues.

Fourier transform infrared for noninvasive optical diagnosis of oral, oropharyngeal, and laryngeal cancer

The 5-year survival rate for advanced head and neck cancers is 50%. There is currently no noninvasive method or effective screening procedure available to diagnose head and neck cancer at the earliest stages when it is still highly curable. This study aims to show how Fourier transform infrared (FTIR) spectroscopy could be used as a sensitive, noninvasive, low cost technique to diagnose head and neck cancer at an earlier stage and, thus, increase the likelihood of survival. Sputum samples were collected from 16 cases with oral or oropharyngeal cancer, 8 cases with laryngeal cancer patients and 15 normal controls. Cell pellets were produced from each of these samples and used to generate FTIR spectra within the 'biochemical fingerprint' wavenumber region of 1800 to 950 cm(-1). Discrimination between cancer and normal sputum was achieved using infrared wavenumbers 1650 cm(-1), 1550 cm(-1), and 1042 cm(-1) determined by robust feature selection. These 3 wavenumbers were used to develop potential models to discriminate both oropharyngeal and laryngeal cancer from normal control. In cancer cases, the absorbance levels for 1550 cm(-1) were increased relative to controls, whereas 1042 cm(-1) absorbance was decreased suggesting changes to protein and glycoprotein structure within sputa cells. This preliminary study shows potential for how FTIR could be developed into a simplistic diagnostic tool that could easily be implemented by a nonspecialist to diagnose and monitor head and neck cancer. The method could especially provide a means for detecting laryngeal cancer hidden from noninvasive observation.

Infrared spectral histopathology for cancer diagnosis: a novel approach for automated pattern recognition of colon adenocarcinoma

Automated and label-free colon cancer diagnosis and identification of tumor-associated features using FTIR spectral histopathology directly on paraffinized tissue arrays.

Infrared metrics for fixation-free liver tumor detection

Infrared (IR) spectroscopic imaging of human liver tissue slices has been used to identify and characterize liver tumors. Liver tissue, containing a liver metastasis of breast origin (mucinous carcinoma), was surgically removed from a consenting patient and frozen without formalin fixation or dehydration procedures, so that lipids and water remained in the tissues. A set of IR metrics (ratios of various IR peaks) was determined for tumors in fixation-free liver tissues. K-means cluster analysis was used to tell tumor from nontumor. In this case, there was a large reduction in lipid content upon going from nontumor to tumor tissue, and a well-resolved IR spectrum of nontumor liver lipid was obtained and analyzed. These IR metrics may someday guide work on IR spectroscopic diagnostics on patients in the operating room. This work also suggests utility for these methods beyond the identification of liver tumors, perhaps in the study of liver lipids.

Proteomics-based identification of novel proteins in temporal tendons of patients with masticatory muscle tendon--aponeurosis hyperplasia

Masticatory muscle tendon-aponeurosis hyperplasia (MMTAH) is a new disease associated with limited mouth opening that is often misdiagnosed as a temporomandibular disorder; subsequently, patients are mistakenly treated with irreversible operations. Due to the poor presentation and characterization of symptoms, the underlying pathological conditions remain unclear. We have previously conducted a proteomic analysis of tendons derived from one MMTAH subject and one facial deformity subject using two-dimensional fluorescence difference gel electrophoresis and liquid chromatography coupled with tandem mass spectrometry. However, the results were obtained for only one subject. The aim of the present study was to confirm the expression of specific molecules in tendon tissues from multiple subjects with MMTAH by applying two-dimensional polyacrylamide gel electrophoresis with matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Of the 19 proteins identified in tendons from both MMTAH and facial deformity patients, fibrinogen fragment D and beta-crystallin A4 were up-regulated, whereas myosin light chain 4 was down-regulated in MMTAH. We also found fibrinogen to be expressed robustly in tendon tissues of MMTAH patients. Our data provide the possibility that the distinctive expression of these novel proteins is associated with the pathology of MMTAH.