Advanced Transmission Raman Spectroscopy: A Promising Tool for Breast Disease Diagnosis

Characterisation of signal enhancements achieved when utilizing a photon diode in deep Raman spectroscopy of tissue

We characterise the performance of a beam enhancing element ('photon diode') for use in deep Raman spectroscopy (DRS) of biological tissues. The optical component enhances the number of laser photons coupled into a tissue sample by returning escaping photons back into it at the illumination zone. The method is compatible with transmission Raman spectroscopy, a deep Raman spectroscopy concept, and its implementation leads to considerable enhancement of detected Raman photon rates. In the past, the enhancement concept was demonstrated with a variety of samples (pharmaceutical tablets, tissue, etc) but it was not systematically characterized with biological tissues. In this study, we investigate the enhancing properties of the photon diode in the transmission Raman geometry as a function of: a) the depth and b) the optical properties of tissue samples. Liquid tissue phantoms were employed to facilitate systematic variation of optical properties. These were chosen to mimic optical properties of human tissues, including breast and prostate. The obtained results evidence that a photon diode can enhance Raman signals of tissues by a maximum of × 2.4, although it can also decrease the signals created towards the back of samples that exhibit high scattering or absorption properties.

Using Raman spectroscopy to characterize biological materials

Raman spectroscopy can be used to measure the chemical composition of a sample, which can in turn be used to extract biological information. Many materials have characteristic Raman spectra, which means that Raman spectroscopy has proven to be an effective analytical approach in geology, semiconductor, materials and polymer science fields. The application of Raman spectroscopy and microscopy within biology is rapidly increasing because it can provide chemical and compositional information, but it does not typically suffer from interference from water molecules. Analysis does not conventionally require extensive sample preparation; biochemical and structural information can usually be obtained without labeling. In this protocol, we aim to standardize and bring together multiple experimental approaches from key leaders in the field for obtaining Raman spectra using a microspectrometer. As examples of the range of biological samples that can be analyzed, we provide instructions for acquiring Raman spectra, maps and images for fresh plant tissue, formalin-fixed and fresh frozen mammalian tissue, fixed cells and biofluids. We explore a robust approach for sample preparation, instrumentation, acquisition parameters and data processing. By using this approach, we expect that a typical Raman experiment can be performed by a nonspecialist user to generate high-quality data for biological materials analysis.

Developing fibre optic Raman probes for applications in clinical spectroscopy

Raman spectroscopy has been shown by various groups over the last two decades to have significant capability in discriminating disease states in bodily fluids, cells and tissues. Recent development in instrumentation, optics and manufacturing approaches has facilitated the design and demonstration of various novel in vivo probes, which have applicability for myriad of applications. This review focusses on key considerations and recommendations for application specific clinical Raman probe design and construction. Raman probes can be utilised as clinical tools able to provide rapid, non-invasive, real-time molecular analysis of disease specific changes in tissues. Clearly the target tissue location, the significance of spectral changes with disease and the possible access routes to the region of interest will vary for each clinical application considered. This review provides insight into design and construction considerations, including suitable probe designs and manufacturing materials compatible with Raman spectroscopy.

Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity

Real-time Raman spectroscopy can be used to assist in assessing skin lesions suspicious for cancer. Most of the diagnostic algorithms are based on full band of the Raman spectra, either in the fingerprint region or the high wavenumber region. In this paper we explored wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Wavenumber selection was implemented using windows of wavenumber and leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected windows of wavenumber using multivariate statistical analyses, including principal component and general discriminate analysis (PC-GDA) and partial least squares (PLS). In total a combined cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included, which were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. It was found that the area under the receiver operating characteristic curve (ROC) was improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for fixed sensitivity 0.99-0.90 was improved from 0.17-0.65 to 0.20-0.75 with wavenumber selection based analysis.

Developing and understanding biofluid vibrational spectroscopy: a critical review

Biofluid vibrational spectroscopy, a promising tool for rapid disease diagnosis.

Development of deep subsurface Raman spectroscopy for medical diagnosis and disease monitoring

The advent of non-invasive deep Raman techniques heralds the emergence of novel diagnostic and disease monitoring methods.

Exploring the effect of laser excitation wavelength on signal recovery with deep tissue transmission Raman spectroscopy

The aim of this research was to find the optimal Raman excitation wavelength to attain the largest possible sensitivity in deep Raman spectroscopy of breast tissue.

Characterisation of a fibre optic Raman probe within a hypodermic needle

We demonstrate the first use of a multifibre Raman probe that fits inside the bore of a hypodermic needle. A Raman probe containing multiple collection fibres provides improved signal collection efficiency in biological samples compared with a previous two-fibre design. Furthermore, probe performance (signal-to-noise ratios) compared favourably with the performance achieved in previous Raman microscope experiments able to distinguish between benign lymph nodes, primary malignancies in lymph nodes and secondary malignancies in lymph nodes. The experimental measurements presented here give an indication of the sampling volume of the Raman needle probe in lymphoid tissues. Liquid tissue phantoms were used that contained scattering medium encompassing a range of scattering properties similar to those of a variety of tissue types, including lymph node tissues. To validate the appropriateness of the phantoms, the sampling depth of the probe was also measured in excised lymph node tissue. More than 50 % of Raman photons collected were found to originate from between the tip of the needle and a depth of 500 μm into the tissue. The needle probe presented here achieves spectral quality comparable to that in numerous studies previously demonstrating Raman disease discrimination. It is expected that this approach could achieve targeted subcutaneous tissue measurements and be viable for use for the in vivo Raman diagnostics of solid organs located within a few centimetres below the skin's surface. Graphical Abstract Schematic of multi-fibre Raman needle probe with disposible tips and proximal optical filtration.

Raman spectroscopy for medical diagnostics--From in-vitro biofluid assays to in-vivo cancer detection

Raman spectroscopy is an optical technique based on inelastic scattering of light by vibrating molecules and can provide chemical fingerprints of cells, tissues or biofluids. The high chemical specificity, minimal or lack of sample preparation and the ability to use advanced optical technologies in the visible or near-infrared spectral range (lasers, microscopes, fibre-optics) have recently led to an increase in medical diagnostic applications of Raman spectroscopy. The key hypothesis underpinning this field is that molecular changes in cells, tissues or biofluids, that are either the cause or the effect of diseases, can be detected and quantified by Raman spectroscopy. Furthermore, multivariate calibration and classification models based on Raman spectra can be developed on large "training" datasets and used subsequently on samples from new patients to obtain quantitative and objective diagnosis. Historically, spontaneous Raman spectroscopy has been known as a low signal technique requiring relatively long acquisition times. Nevertheless, new strategies have been developed recently to overcome these issues: non-linear optical effects and metallic nanoparticles can be used to enhance the Raman signals, optimised fibre-optic Raman probes can be used for real-time in-vivo single-point measurements, while multimodal integration with other optical techniques can guide the Raman measurements to increase the acquisition speed and spatial accuracy of diagnosis. These recent efforts have advanced Raman spectroscopy to the point where the diagnostic accuracy and speed are compatible with clinical use. This paper reviews the main Raman spectroscopy techniques used in medical diagnostics and provides an overview of various applications.

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93–98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance.

Emerging technology: applications of Raman spectroscopy for prostate cancer

There is a need in prostate cancer diagnostics and research for a label-free imaging methodology that is nondestructive, rapid, objective, and uninfluenced by water. Raman spectroscopy provides a molecular signature, which can be scaled from micron-level regions of interest in cells to macroscopic areas of tissue. It can be used for applications ranging from in vivo or in vitro diagnostics to basic science laboratory testing. This work describes the fundamentals of Raman spectroscopy and complementary techniques including surface enhanced Raman scattering, resonance Raman spectroscopy, coherent anti-Stokes Raman spectroscopy, confocal Raman spectroscopy, stimulated Raman scattering, and spatially offset Raman spectroscopy. Clinical applications of Raman spectroscopy to prostate cancer will be discussed, including screening, biopsy, margin assessment, and monitoring of treatment efficacy. Laboratory applications including cell identification, culture monitoring, therapeutics development, and live imaging of cellular processes are discussed. Potential future avenues of research are described, with emphasis on multiplexing Raman spectroscopy with other modalities.

Next-generation Raman tomography instrument for non-invasive in vivo bone imaging

Combining diffuse optical tomography methods with Raman spectroscopy of tissue provides the ability for in vivo measurements of chemical and molecular characteristics, which have the potential for being useful in diagnostic imaging. In this study a system for Raman tomography was developed and tested. A third generation microCT coupled system was developed to combine 10 detection fibers and 5 excitation fibers with laser line filtering and a Cytop reference signal. Phantom measurements of hydroxyapatite concentrations from 50 to 300 mg/ml had a linear response. Fiber placement and experiment design was optimized using cadaver animals with live animal measurements acquired to validate the systems capabilities. Promising results from the initial animal experiments presented here, pave the way for a study of longitudinal measurements during fracture healing and the scaling of the Raman tomography system towards human measurements.

A preliminary Raman spectroscopic study of urine: diagnosis of breast cancer in animal models

Analysis of urine by Raman spectroscopy (RS) as an alternative screening and diagnostic tool for breast cancer..

Studying the distribution of deep Raman spectroscopy signals using liquid tissue phantoms with varying optical properties

We studied experimentally the magnitude and origin of Raman signals in a transmission Raman geometry as a function of optical properties of the medium and the location of Raman scatterer within the phantom.

Label-free determination of lipid composition and secondary protein structure of human salivary noncancerous and cancerous tissues by Raman microspectroscopy

The applications of optical spectroscopic methods in cancer detection open new possibilities in oncological diagnostics.

Towards intra-operative diagnosis of tumours during breast conserving surgery by selective-sampling Raman micro-spectroscopy

Breast-conserving surgery (BCS) is increasingly employed for the treatment of early stage breast cancer. One of the key challenges in BCS is to ensure complete removal of the tumour while conserving as much healthy tissue as possible. In this study we have investigated the potential of Raman micro-spectroscopy (RMS) for automated intra-operative evaluation of tumour excision. First, a multivariate classification model based on Raman spectra of normal and malignant breast tissue samples was built and achieved diagnosis of mammary ductal carcinoma (DC) with 95.6% sensitivity and 96.2% specificity (5-fold cross-validation). The tumour regions were discriminated from the healthy tissue structures based on increased concentration of nucleic acids and reduced concentration of collagen and fat. The multivariate classification model was then applied to sections from fresh tissue of new patients to produce diagnosis images for DC. The diagnosis images obtained by raster scanning RMS were in agreement with the conventional histopathology diagnosis but were limited to long data acquisition times (typically 10,000 spectra mm(-2), which is equivalent to ~5 h mm(-2)). Selective-sampling based on integrated auto-fluorescence imaging and Raman spectroscopy was used to reduce the number of Raman spectra to ~20 spectra mm(-2), which is equivalent to an acquisition time of ~15 min for 5 × 5 mm(2) tissue samples. This study suggests that selective-sampling Raman microscopy has the potential to provide a rapid and objective intra-operative method to detect mammary carcinoma in tissue and assess resection margins.

The use of Au@SiO2 shell-isolated nanoparticle-enhanced Raman spectroscopy for human breast cancer detection

This study uses the powerful fingerprint features of Raman spectroscopy to distinguish different types of breast tissues including normal breast tissues (NB), fibroadenoma (FD), atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). Thin frozen tissue sections of fresh breast tissues were measured by Raman spectroscopy. Due to the inherent low sensitivity of Raman spectra, Au@SiO2 shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) technique was utilized to provide supplementary and more informative spectral features. A total of 619 Raman spectra were acquired and compared to 654 SHINERS spectra. The maximum enhancement effect of distinct and specific bands was characterized for different tissue types. When applying the new criteria, excellent separation of FD, DCIS, and IDC was obtained for all tissue types. Most importantly, we were able to distinguish ADH from DCIS. Although only a preliminary distinction was characterized between ADH and NB, the results provided a good foundation of criteria to further discriminate ADH from NB and shed more light toward a better understanding of the mechanism of ADH formation. This is the first report to detect the premalignant (ADH and DCIS) breast tissue frozen sections and also the first report exploiting SHINERS to detect and distinguish breast tissues. The results presented in this study show that SHINERS can be applied to accurately and efficiently identify breast lesions. Further, the spectra can be acquired in a minimally invasive procedure and analyzed rapidly facilitating early and accurate diagnosis in vivo/in situ.

Microfluidics and Raman microscopy: current applications and future challenges

Raman microscopy systems are becoming increasingly widespread and accessible for characterising chemical species. Microfluidic systems are also progressively finding their way into real world applications. Therefore, it is anticipated that the integration of Raman systems with microfluidics will become increasingly attractive and practical. This review aims to provide an overview of Raman microscopy-microfluidics integrated systems for researchers who are actively interested in utilising these tools. The fundamental principles and application strengths of Raman microscopy are discussed in the context of microfluidics. Various configurations of microfluidics that incorporate Raman microscopy methods are presented, with applications highlighted. Data analysis methods are discussed, with a focus on assisting the interpretation of Raman-microfluidics data from complex samples. Finally, possible future directions of Raman-microfluidic systems are presented.

Differentiation of cancer cells in two-dimensional and three-dimensional breast cancer models by Raman spectroscopy

We demonstrate the first application of Raman spectroscopy in diagnosing nonmalignant, premalignant, malignant, and metastatic stages of breast cancer in a three-dimensional (3-D) cell culture model that closely mimics an in vivo environment. Comprehensive study comparing classification in two-dimensional (2-D) and 3-D cell models was performed using statistical methods composed of principal component analysis for exploratory analysis and outlier removal, partial least squares discriminant analysis, and elastic net regularized regression for classification. Our results show that Raman spectroscopy with an appropriate classification tool has excellent resolution to discriminate the four stages of breast cancer progression, with a near 100% accuracy for both 2-D and 3-D cell models. The diversity in chemical groups related to nucleic acids, proteins, and lipids, among other chemicals, were identified by appropriate peaks in the Raman spectra that correspond to the correct classification of the different stages of tumorigenesis model comprising of MCF10A, MCF10AneoT, MCF10CA1h, and MCF10CA1a cell lines. An explicit relationship between wavenumber and the stages of cancer progression was identified by the elastic net variable selection.

Advances in the clinical application of Raman spectroscopy for cancer diagnostics

Light interacts with tissue in a number of ways including, elastic and inelastic scattering, reflection and absorption, leading to fluorescence and phosphorescence. These interactions can be used to measure abnormal changes in tissue. Initial optical biopsy systems have potential to be used as an adjunct to current investigative techniques to improve the targeting of blind biopsy. Future prospects with molecular-specific techniques may enable objective optical detection providing a real-time, highly sensitive and specific measurement of the histological state of the tissue. Raman spectroscopy has the potential to identify markers associated with malignant change and could be used as diagnostic tool for the early detection of precancerous and cancerous lesions in vivo. The clinical requirements for an objective, non-invasive, real-time probe for the accurate and repeatable measurement of pathological state of the tissue are overwhelming. This paper discusses some of the recent advances in the field.

Illuminating disease and enlightening biomedicine: Raman spectroscopy as a diagnostic tool

The discovery of the Raman effect in 1928 not only aided fundamental understanding about the quantum nature of light and matter but also opened up a completely novel area of optics and spectroscopic research that is accelerating at a greater rate during the last decade than at any time since its inception. This introductory overview focuses on some of the most recent developments within this exciting field and how this has enabled and enhanced disease diagnosis and biomedical applications. We highlight a small number of stimulating high-impact studies in imaging, endoscopy, stem cell research, and other recent developments such as spatially offset Raman scattering amongst others. We hope this stimulates further interest in this already exciting field, by 'illuminating' some of the current research being undertaken by the latest in a very long line of dedicated experimentalists interested in the properties and potential beneficial applications of light.

Raman imaging at biological interfaces: applications in breast cancer diagnosis

BACKGROUND

One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment.

RESULTS

The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water.

CONCLUSIONS

We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue.

Recent advances in the development of Raman spectroscopy for deep non-invasive medical diagnosis

Raman spectroscopy has recently undergone major advances in the area of deep non-invasive characterisation of biological tissues. The progress stems from the development of spatially offset Raman spectroscopy (SORS) and renaissance of transmission Raman spectroscopy permitting the assessment of diffusely scattering samples at depths several orders of magnitude deeper than possible with conventional Raman spectroscopy. Examples of emerging applications include non-invasive diagnosis of bone disease, cancer and monitoring of glucose levels. This article reviews this fast moving field focusing on recent developments within the medical area.

Diagnostic power of diffuse reflectance spectroscopy for targeted detection of breast lesions with microcalcifications

Microcalcifications geographically target the location of abnormalities within the breast and are of critical importance in breast cancer diagnosis. However, despite stereotactic guidance, core needle biopsy fails to retrieve microcalcifications in up to 15% of patients. Here, we introduce an approach based on diffuse reflectance spectroscopy for detection of microcalcifications that focuses on variations in optical absorption stemming from the calcified clusters and the associated cross-linking molecules. In this study, diffuse reflectance spectra are acquired ex vivo from 203 sites in fresh biopsy tissue cores from 23 patients undergoing stereotactic breast needle biopsies. By correlating the spectra with the corresponding radiographic and histologic assessment, we have developed a support vector machine-derived decision algorithm, which shows high diagnostic power (positive predictive value and negative predictive value of 97% and 88%, respectively) for diagnosis of lesions with microcalcifications. We further show that these results are robust and not due to any spurious correlations. We attribute our findings to the presence of proteins (such as elastin), and desmosine and isodesmosine cross-linkers in the microcalcifications. It is important to note that the performance of the diffuse reflectance decision algorithm is comparable to one derived from the corresponding Raman spectra, and the considerably higher intensity of the reflectance signal enables the detection of the targeted lesions in a fraction of the spectral acquisition time. Our findings create a unique landscape for spectroscopic validation of breast core needle biopsy for detection of microcalcifications that can substantially improve the likelihood of an adequate, diagnostic biopsy in the first attempt.

Protein and oil composition predictions of single soybeans by transmission Raman spectroscopy

The soybean industry requires rapid, accurate, and precise technologies for the analyses of seed/grain constituents. While the current gold standard for nondestructive quantification of economically and nutritionally important soybean components is near-infrared spectroscopy (NIRS), emerging technology may provide viable alternatives and lead to next generation instrumentation for grain compositional analysis. In principle, Raman spectroscopy provides the necessary chemical information to generate models for predicting the concentration of soybean constituents. In this communication, we explore the use of transmission Raman spectroscopy (TRS) for nondestructive soybean measurements. We show that TRS uses the light scattering properties of soybeans to effectively homogenize the heterogeneous bulk of a soybean for representative sampling. Working with over 1000 individual intact soybean seeds, we developed a simple partial least-squares model for predicting oil and protein content nondestructively. We find TRS to have a root-mean-standard error of prediction (RMSEP) of 0.89% for oil measurements and 0.92% for protein measurements. In both calibration and validation sets, the predicative capabilities of the model were similar to the error in the reference methods.

Precision of Raman spectroscopy measurements in detection of microcalcifications in breast needle biopsies

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. We developed Raman spectroscopy decision algorithms to detect breast microcalcifications, based on fit coefficients (FC) derived by modeling tissue Raman spectra as a linear combination of the Raman spectra of 9 chemical and morphologic components of breast tissue. However, little or no information is available on the precision of such measurements and its effect on the ability of Raman spectroscopy to make predictions for breast microcalcification detection. Here we report the precision, that is, the closeness of agreement between replicate Raman spectral measurements--and the model FC derived from them--obtained ex vivo from fresh breast biopsies from patients undergoing stereotactic breast needle biopsy, using a compact clinical Raman system. The coefficients of variation of the model FC averaged 0.03 for normal breast tissue sites, 0.12 for breast lesions without, and 0.22 for breast lesions with microcalcifications. Imprecision in the FC resulted in diagnostic discordance among replicates only for line-sitters, that is, tissue sites with FC values near the decision line or plane. The source of this imprecision and their implications for the use of Raman spectroscopy for guidance of stereotactic breast biopsies for microcalcifications are also discussed. In summary, we conclude that the precision of Raman spectroscopy measurements in breast tissue obtained using our compact clinical system is more than adequate to make accurate and repeatable predictions of microcalcifications in breast tissue using decision algorithms based on model FC. This provides strong evidence of the potential of Raman spectroscopy guidance of stereotactic breast needle biopsies for microcalcifications.

Raman spectroscopy and imaging: applications in human breast cancer diagnosis

The applications of spectroscopic methods in cancer detection open new possibilities in early stage diagnostics. Raman spectroscopy and Raman imaging represent novel and rapidly developing tools in cancer diagnosis. In the study described in this paper Raman spectroscopy has been employed to examine noncancerous and cancerous human breast tissues of the same patient. The most significant differences between noncancerous and cancerous tissues were found in regions characteristic for the vibrations of carotenoids, lipids and proteins. Particular attention was paid to the role played by unsaturated fatty acids in the differentiation between the noncancerous and the cancerous tissues. Comparison of Raman spectra of the noncancerous and the cancerous tissues with the spectra of oleic, linoleic, α-linolenic, γ-linolenic, docosahexaenoic and eicosapentaenoic acids has been presented. The role of sample preparation in the determination of cancer markers is also discussed in this study.

Chemically Specific Imaging Through Stimulated Raman Photoexcitation and Ultrasound Detection: Minireview

A powerful combination of chemically specific Raman excitation and deep tissue ultrasound imaging holds the promise to attain spatially resolved distribution of chemical compounds inside the scattering medium. In this report, an attempt is made to evaluate the recent achievements and possible challenges with an eye on potential clinical applications.

Raman's "effect" on molecular imaging

Raman spectroscopy is an optical technique that offers unsurpassed sensitivity and multiplexing capabilities to the field of molecular imaging. In the past, Raman spectroscopy had predominantly been used as an analytic tool for routine chemical analysis, but more recently, researchers have been able to harness its unique properties for imaging and spectral analysis of molecular interactions in cell populations and preclinical animal models. Additionally, researchers have already begun to translate this optical technique into a novel clinical diagnostic tool using various endoscopic strategies.

Raman spectroscopy--a potential new method for the intra-operative assessment of axillary lymph nodes

Sentinel Lymph Node Biopsy has become the standard surgical procedure for the sampling of axillary lymph nodes in breast cancer. Intra-operative node assessment of these nodes would allow definitive axillary surgery to take place immediately with associated benefits for patient management. Our experimental study aims to demonstrate that a Raman spectroscopy probe system could overcome many of the disadvantages of current intra-operative methods. 59 axillary lymph nodes, 43 negative and 16 positive from 58 patients undergoing breast surgery at our district general hospital were mapped using Raman micro-spectroscopy. These maps were then used to model the effect of using a Raman spectroscopic probe by selecting 5 and 10 probe points across the mapped images and evaluating the impact on disease detection. Results demonstrated sensitivities of up to 81% and specificities of up to 97% when differentiating between positive and negative lymph nodes, dependent on the number of probe points included. The results would have concurred with histopathology assessment in 89% and 91% of cases in the 5 and 10 point models respectively. Using Raman spectroscopy in this way could allow lymph node assessment within a time-frame suitable for intra-operative use.

Influence of tissue absorption and scattering on the depth dependent sensitivity of Raman fiber probes investigated by Monte Carlo simulations

We present a Monte Carlo model, which we use to calculate the depth dependent sensitivity or sampling volume of different single fiber and multi-fiber Raman probes. A two-layer skin model is employed to investigate the dependency of the sampling volume on the absorption and reduced scattering coefficients in the near infrared wavelength range (NIR). The shape of the sampling volume is mainly determined by the scattering coefficient and the wavelength dependency of absorption and scattering has only a small effect on the sampling volume of a typical fingerprint spectrum. An increase in the sampling depth in nonmelanoma skin cancer, compared to normal skin, is obtained.

Towards a safe non-invasive method for evaluating the carbonate substitution levels of hydroxyapatite (HAP) in micro-calcifications found in breast tissue

A new diagnostic concept based on deep Raman spectroscopy is proposed permitting the non-invasive determination of the level of carbonate substitution in type II calcifications (HAP). The carbonate substitution has shown to be directly associated with the pathology of the surrounding breast tissue and different pathology groups can therefore be separated using specific features in the Raman spectra of the calcifications. This study explores the principle of distinguishing between type II calcifications, found in proliferating lesions, by using the strongest Raman peak from calcium hydroxyapatites (the phosphate peak at 960 cm(-1)) to act as a surrogate marker for carbonate substitution levels. It is believed that carbonate ion substitution leads to a perturbation of the hydroxyapatite lattice which in turn affects the phosphate vibrational modes. By studying calcifications, with known carbonate content, buried in porcine tissue it has been possible to evaluate the feasibility of using the proposed approach to probe the composition of the calcifications in vivo and hence provide pathology specific information non-invasively, in real time. Using the proposed concept we were able to determine the level of carbonate substitutions through soft tissue phantom samples (total thickness of 5.6 mm). As the level of carbonate substitution has been previously correlated with mid-FTIR to the lesion type, i.e. whether benign or invasive or in situ carcinoma, the new findings provide a major step forward towards establishing a new capability for diagnosing benign and malignant lesions in breast tissue in a safe and non-invasive manner in vivo.

Prospects of deep Raman spectroscopy for noninvasive detection of conjugated surface enhanced resonance Raman scattering nanoparticles buried within 25 mm of mammalian tissue

This letter discusses the potential of deep Raman spectroscopy, surface enhanced spatially offset Raman spectroscopy (SESORS and its variants), for noninvasively detecting small, deeply buried lesions using surface enhanced resonance Raman scattering (SERRS) active nanoparticles. An experimental demonstration of this concept is performed in transmission Raman geometry. This method opens prospects for in vivo, noninvasive, specific detection of molecular changes associated with disease up to depths of several centimeters representing significant improvement over traditionally detected Raman signals by 2 orders of magnitude. The disease specific signals can be achieved using uniquely tagged nanoparticles conjugated to target molecules, e.g., antibodies for production of the SERRS signal. This provides the molecular specific signal which is many orders of magnitude greater than normal biological Raman signals and can be easily multiplexed. To date, there have been no studies demonstrating the viability of deep Raman spectroscopy coupled to surface enhanced techniques for detecting low concentrations of molecules of interest at depths of greater than 5.5 mm in tissue. Such a breakthrough would open a host of new applications in medical diagnoses. Here we propose to facilitate such capability by combining SERRS (as a probe for disease specific changes) with deep Raman spectroscopy techniques. This permits noninvasive measurement of Raman signatures from conjugated SERRS nanoparticles at clinically relevant concentrations through tissues of between 15 and 25 mm thick.

New relationships between breast microcalcifications and cancer

Background:

Breast microcalcifications are key diagnostically significant radiological features for localisation of malignancy. This study explores the hypothesis that breast calcification composition is directly related to the local tissue pathological state.

Methods:

A total of 236 human breast calcifications from 110 patients were analysed by mid-Fouries transform infrared (FTIR) spectroscopy from three different pathology types (112 invasive carcinoma (IC), 64 in-situ carcinomas and 60 benign). The biochemical composition and the incorporation of carbonate into the hydroxyapatite lattice of the microcalcifications were studied by infrared microspectroscopy. This allowed the spectrally identified composition to be directly correlated with the histopathology grading of the surrounding tissue.

Results:

The carbonate content of breast microcalcifications was shown to significantly decrease when progressing from benign to malignant disease. In this study, we report significant correlations (P<0.001) between microcalcification chemical composition (carbonate content and protein matrix : mineral ratios) and distinct pathology grades (benign, in-situ carcinoma and ICs). Furthermore, a significant correlation (P<0.001) was observed between carbonate concentrations and carcinoma in-situ sub-grades. Using the two measures of pathology-specific calcification composition (carbonate content and protein matrix : mineral ratios) as the inputs to a two-metric discriminant model sensitivities of 79, 84 and 90% and specificities of 98, 82 and 96% were achieved for benign, ductal carcinoma in situ and invasive malignancies, respectively.

Conclusions:

We present the first demonstration of a direct link between the chemical nature of microcalcifications and the grade of the pathological breast disease. This suggests that microcalcifications have a significant association with cancer progression, and could be used for future objective analytical classification of breast pathology. A simple two-metric model has been demonstrated, more complex spectral analysis may yeild greater discrimination performance. Furthermore there appears to be a sequential progression of calcification composition.

Modern breast cancer detection: a technological review

Breast cancer is a serious threat worldwide and is the number two killer of women in the United States. The key to successful management is screening and early detection. What follows is a description of the state of the art in screening and detection for breast cancer as well as a discussion of new and emerging technologies. This paper aims to serve as a starting point for those who are not acquainted with this growing field.

Diagnosing breast cancer using Raman spectroscopy: prospective analysis

We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided.