This article reviews some of the recent advances in Raman spectroscopy, in areas related to natural tissues and cell biology. It summarizes some of the most widely used peak frequencies and their assignments. The aim of this study is to prepare a database of molecular fingerprints, which will help researchers in defining the chemical structure of the biological tissues introducing most of the important peaks present in the natural tissues. In spite of applying different methods, there seems to be a considerable similarity in defining the peaks of identical areas of the spectra. As a result, it is believed that preparing a unique collection of the frequencies encountered in Raman spectroscopic studies can lead to significant improvements both in the quantity and quality of spectral data and their outcomes. This article is the first review of its kind to provide a precise database on the most important Raman characteristic peak frequencies for researchers aiming to analyze natural tissues by Raman ...

Raman spectroscopy of biological tissues

The optical properties of human skin, subcutaneous adipose tissue and human mucosa were measured in the wavelength range 400–2000 nm. The measurements were carried out using a commercially available spectrophotometer with an integrating sphere. The inverse adding–doubling method was used to determine the absorption and reduced scattering coefficients from the measurements.

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Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm

Keywords: Photomedicine group Reference LPAS-ARTICLE-1998-003View record in Web of Science Record created on 2007-07-20, modified on 2016-08-08

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1751-1097.1998.tb02521.x

In Vivo Fluorescence Spectroscopy and Imaging for Oncological Applications

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Photodynamic therapy (PDT) uses light-activated drugs to treat diseases ranging from cancer to age-related macular degeneration and antibiotic-resistant infections. This paper reviews the current status of PDT with an emphasis on the contributions of physics, biophysics and technology, and the challenges remaining in the optimization and adoption of this treatment modality. A theme of the review is the complexity of PDT dosimetry due to the dynamic nature of the three essential components—light, photosensitizer and oxygen. Considerable progress has been made in understanding the problem and in developing instruments to measure all three, so that optimization of individual PDT treatments is becoming a feasible target. The final section of the review introduces some new frontiers of research including low dose rate (metronomic) PDT, two-photon PDT, activatable PDT molecular beacons and nanoparticle-based PDT.

https://iopscience.iop.org/article/10.1088/0031-9155/53/9/R01/pdf

The physics, biophysics and technology of photodynamic therapy

Background and Objectives
Nonmelanoma skin cancers, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), are the most common skin cancers, presenting nearly as many cases as all other cancers combined. The current gold-standard for clinical diagnosis of these lesions is histopathologic examination, an invasive, time-consuming procedure. There is thus considerable interest in developing a real-time, automated, noninvasive tool for nonmelanoma skin cancer diagnosis. In this study, we explored the capability of Raman microspectroscopy to provide differential diagnosis of BCC, SCC, inflamed scar tissue, and normal tissue in vivo.

Study Design
Based on the results of previous in vitro studies, we developed a portable confocal Raman system with a handheld probe for clinical study. Using this portable system, we measured Raman spectra of 21 suspected nonmelanoma skin cancers in 19 patients with matched normal skin spectra. These spectra were input into nonlinear diagnostic algorithms to predict pathological designation.

Results
All of the BCC (9/9), SCC (4/4), and inflamed scar tissues (8/8) were correctly predicted by the diagnostic algorithm, and 19 out of 21 normal tissues were correctly classified. This translates into a 100% (21/21) sensitivity and 91% (19/21) specificity for abnormality, with a 95% (40/42) overall classification accuracy.

Conclusions
These findings reveal Raman microspectroscopy to be a viable tool for real-time diagnosis and guidance of nonmelanoma skin cancer resection. Lesers Surg. Med. 40:461–467, 2008. © 2008 Wiley-Liss, Inc.

/pdf/in-vivo-nonmelanoma-skin-cancer-diagnosis-using-raman-51xgwu1wh3.pdf

In vivo nonmelanoma skin cancer diagnosis using Raman microspectroscopy.

We report measurement of optical transport parameters of normal and malignant (ductal carcinoma) human breast tissue. A spatially resolved steady-state diffuse reflectance technique was used for measurement of the reduced scattering coefficient (mu(s)?) and the absorption coefficient (mu(a)) of the tissue. The anisotropy parameter of scattering (g) was estimated by goniophotometric measurements of the scattering phase function. The values of mu(s)? and mu(a) for malignant breast tissue were observed to be larger than those for normal breast tissue over the wavelength region investigated (450-650 nm). Further, by using both the diffuse reflectance and the goniophotometric measurements, we estimated the Mie equivalent average radius of tissue scatterers to be larger in malignant tissue than in normal tissue.

Measurement of optical transport properties of normal and malignant human breast tissue

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.

https://www.spiedigitallibrary.org/journals/Journal-of-Biomedical-Optics/volume-13/issue-02/024013/Raman-microspectroscopy-for-skin-cancer-detection-in-vitro/10.1117/1.2899155.pdf

Raman microspectroscopy for skin cancer detection in vitro

Background and Objective

Most women with early stage breast cancer have the option of breast conserving therapy, which involves a partial mastectomy for removal of the primary tumor, usually followed by radiotherapy. The presence of tumor at or near the margin is strongly correlated with the risk of local tumor recurrence, so there is a need for a non-invasive, real-time tool to evaluate margin status. This study examined the use of autofluorescence and diffuse reflectance spectroscopy and spectral imaging to evaluate margin status intraoperatively.



Materials and Methods

Spectral measurements were taken from the surface of the tissue mass immediately following removal during partial mastectomies and/or from tissues immediately after sectioning by surgical pathology. A total of 145 normal spectra were obtained from 28 patients, and 34 tumor spectra were obtained from 12 patients.



Results

After correlation with histopathology, a multivariate statistical algorithm classified the spectra as normal (negative margins) or tumor (positive margins) with 85% sensitivity and 96% specificity. A separate algorithm achieved 100% classification between neo-adjuvant chemotherapy-treated tissues and non-treated tissues. Fluorescence and reflectance-based spectral images were able to demarcate a calcified lesion on the surface of a resected specimen as well.



Conclusion

Fluorescence and reflectance spectroscopy could be a valuable tool for examining the superficial margin status of excised breast tumor specimens, particularly in the form of spectral imaging to examine entire margins in a single acquisition. Lasers Surg. Med. 42:15–23, 2010. © 2010 Wiley-Liss, Inc.

Autofluorescence and diffuse reflectance spectroscopy and spectral imaging for breast surgical margin analysis.

Background and Objective: This article reports results of an in vitro study involving 63 patients for the evaluation of the diagnostic potential of N 2 laser excited autofluorescence spectroscopy of human breast tissues. Materials and Methods: The N 2 laser-excited spectra were recorded from benign (fibroadenomas, 35 patients), cancerous (ductal carcinomas, 28 patients), and normal (the uninvolved areas of the resected cancerous specimens). A stepwise multivariate linear regression (MVLR) analysis was developed to analyze the diagnostic content of the breast tissue fluorescence spectra. Results: Significant changes were observed in the autofluorescence from normal, benign, and cancerous breast tissues, particularly in the spectrally integrated fluorescence intensity. The ratio of mean spectrally integrated intensity from cancerous tissues to that from benign tumor and normal tissues were 3.2 and 2.8, respectively. A discrimination parameter based on spectrally integrated intensity alone provided a sensitivity and specificity of up to 99.6% over the sample size investigated for discrimination of cancerous breast tissues from benign/normal. Conclusion: Our results suggest that a straightforward measurement of the total integrated fluorescence intensity can provide excellent discrimination between cancerous and benign/normal breast tissues.

Shovan K. Majumder

Papers

In vivo nonmelanoma skin cancer diagnosis using Raman microspectroscopy.

Measurement of optical transport properties of normal and malignant human breast tissue

Raman microspectroscopy for skin cancer detection in vitro

Autofluorescence and diffuse reflectance spectroscopy and spectral imaging for breast surgical margin analysis.

Breast cancer diagnosis using N 2 laser excited autofluorescence spectroscopy