Anita Mahadevan-Jansen

Automated method for subtraction of fluorescence from biological Raman spectra

One of the challenges of using Raman spectroscopy for biological applications is the inherent fluorescence generated by many biological molecules that underlies the measured spectra. This fluorescence can sometimes be several orders of magnitude more intense than the weak Raman scatter, and its presence must be minimized in order to resolve and analyze the Raman spectrum. Several techniques involving hardware and software have been devised for this purpose; these include the use of wavelength shifting, time gating, frequency-domain filtering, first- and second-order derivatives, and simple curve fitting of the broadband variation with a high-order polynomial. Of these, polynomial fitting has been found to be a simple but effective method. However, this technique typically requires user intervention and thus is time consuming and prone to variability. An automated method for fluorescence subtraction, based on a modification to least-squares polynomial curve fitting, is described. Results indicate that the presented automated method is proficient in fluorescence subtraction, repeatability, and in retention of Raman spectral lineshapes.

Raman spectroscopy for the detection of cancers and precancers.

Optical spectroscopy has been extensively studied as a potential in vivo diagnostic tool that can provide information about both the chemical and morphologic structure of tissue in near real time. Most in vivo studies have concentrated on elastic scattering and fluorescence spectroscopies since these signals can be obtained with a good signal-to-noise ratio quickly. However, Raman spectroscopy, an inelastic scattering process, provides a wealth of spectrally narrow features that can be related to the specific molecular structure of the sample. Because of these advantages, Raman spectroscopy has been used to study static and dynamic properties of biologically important molecules in solution, in single living cells, in cell cultures, and more recently, in tissues. This article reviews recent developments in the attempt to develop diagnostic techniques for precancers and cancers, based on Raman spectroscopy. The article surveys important transformations that occur as tissues progress from normal to precancer and cancerous stages. We briefly review the extensive literature that summarizes the features and interpretation of Raman spectra of these molecules in solution, and in progressively more complex biological systems. Finally, spectra obtained from intact tissues are comprehensively reviewed and discussed in terms of the molecular and microscopic literature to develop a framework for analyzing Raman signals to yield information about the molecular changes that occur with neoplasia. The article concludes with our perspective on the potential role of Raman spectroscopy in diagnosing precancer and cancerous tissues.

Near-infrared Raman spectroscopy for in vitro detection of cervical precancers

Abstract— In this study, we investigate the potential of near‐infrared Raman spectroscopy to differentiate cervical precancers from normal tissues, inflammation and metaplasia and to differentially diagnose low‐grade and high‐grade precancers. Near infrared Raman spectra were measured from 36 biopsies from 18 patients in vitro. Detection algorithms were developed and evaluated relative to histopathologic examination. Algorithms based on empirically selected peak intensities, ratios of peak intensities and a combination of principal component analysis for data reduction and Fisher discriminant analysis for classification were investigated. Spectral peaks were tentatively identified from measured spectra of potential chromophores. Empirically selected normalized intensities can differentiate precancers from other tissues with an average sensitivity and specificity of 88 ± 4% and 92 ± 4%. Ratios of un‐normalized intensities can differentiate precancers from other tissues with a sensitivity and specificity of 82% and 88% and high‐grade from low‐grade lesions with a sensitivity and specificity of 100%. Using multivariate methods, intensities at eight frequencies can be used to differentiate precancers from all other tissues with a sensitivity and specificity of 82% and 92% in an unbiased test. Raman algorithms can potentially separate benign abnormalities such as inflammation and metaplasia from precancers. Comparison of tissue spectra to published and measured chromophore spectra indicate that the most likely primary contributors to the tissue spectra are collagen, nucleic acids, phospholipids and glucose 1‐phos‐phate. These results suggest that near‐infrared Raman spectroscopy can be used for cervical precancer diagnosis and may be able to accurately separate samples with inflammation and metaplasia from precancer.

Application of infrared light for in vivo neural stimulation

A novel method for damage-free, artifact-free stimulation of neural tissue using pulsed, low-energy infrared laser light is presented. Optical stimulation elicits compound nerve and muscle potentials similar to responses obtained with conventional electrical neural stimulation in a rat sciatic nerve model. Stimulation and damage thresholds were determined as a function of wavelength using a tunable free electron laser source (lambda = 2 to 10 microm) and a solid state holmium:YAG laser (lambda = 2.12 microm). Threshold radiant exposure required for stimulation varies with wavelength from 0.312 Jcm2 (lambda = 3 microm) to 1.22 Jcm2 (lambda = 2.1 microm). Histological analysis indicates no discernable thermal damage with suprathreshold stimulation. The largest damage/stimulation threshold ratios (>6) were at wavelengths corresponding to valleys in the IR spectrum of soft tissue absorption (4 and 2.1 microm). Furthermore, optical stimulation can be used to generate a spatially selective response in small fascicles of the sciatic nerve that has significant advantages (e.g., noncontact, spatial resolution, lack of stimulation artifact) over conventional electrical methods in diagnostic and therapeutic procedures in neuroscience, neurology, and neurosurgery.

CERVICAL PRECANCER DETECTION USING A MULTIVARIATE STATISTICAL ALGORITHM BASED ON LASER-INDUCED FLUORESCENCE SPECTRA AT MULTIPLE EXCITATION WAVELENGTHS

Abstract— A portable fluorimeter was developed and utilized to acquire fluorescence spectra from 381 cervical sites in 95 patients at 337, 380 and 460 nm excitation immediately prior to colposcopy. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired in vivo. Two full‐parameter algorithms were developed using tissue fluorescence emission spectra at all three excitation wavelengths (161 excitation‐emission wavelength pairs) for cervical precancer (squamous intraepithelial lesion [SIL]) detection: a screening algorithm that discriminates between SIL and non‐SIL with a sensitivity of 82 ± 1.4% and specificity of 68 ± 0.0%, and a diagnostic algorithm that differentiates high‐grade SIL from non‐high‐grade SIL with a sensitivity and specificity of 79 ± 2% and 78 ± 6%, respectively. Multivariate statistical analysis was also employed to reduce the number of fluorescence excitation‐emission wavelength pairs needed to redevelop algorithms that demonstrate a minimum decrease in classification accuracy. Two reduced‐parameter algorithms that employ fluorescence intensities at only 15 excitation‐emission wavelength pairs were developed: the screening algorithm differentiates SIL from non‐SIL with a sensitivity of 84 ± 1.5% and specificity of 65 ± 2% and the diagnostic algorithm discriminates high‐grade SIL from non‐high‐grade SIL with a sensitivity and specificity of 78 ± 0.7% and 74 ± 2%, respectively. Both the full‐parameter and reduced‐parameter screening algorithms discriminate between SIL and non‐SIL with a similar specificity (±5%) and a substantially improved sensitivity relative to Pap smear screening. A comparison of the full‐parameter and reduced‐parameter diagnostic algorithms to colposcopy in expert hands indicates that all three have a very similar sensitivity and specificity for differentiating high‐grade SIL from non‐high‐grade SIL.

Near-Infrared Raman Spectroscopy for in Vivo Detection of Cervical Precancers

This study evaluates the potential of near-infrared Raman spectroscopy for in vivo detection of squamous dysplasia, a precursor to cervical cancer. A pilot clinical trial was carried out at three clinical sites. Raman spectra were measured from one colposcopically normal and one abnormal area of the cervix. These sites were then biopsied and submitted for routine histologic analysis. Twentyfour evaluable measurements were made in vivo in 13 patients. Cervical tissue Raman spectra contain peaks in the vicinity of 1070, 1180, 1195, 1210, 1245, 1330, 1400, 1454, 1505, 1555, 1656, and 1760 cm−1. The ratio of intensities at 1454 to 1656 cm−1 is greater for squamous dysplasia than all other tissue types, while the ratio of intensities at 1330 to 1454 cm−1 is lower for samples with squamous dysplasia than all other tissue types. A simple algorithm based on these two intensity ratios separates high-grade squamous dysplasia from all others, misclassifying only one sample. Spectra measured in vivo resemble those measured in vitro. Cervical epithelial cells may contribute to tissue spectra at 1330 cm−1, a region associated with DNA. In contrast, epithelial cells probably do not contribute to tissue spectra at 1454 cm−1, a region associated with collagen and phospholipids.

Optical stimulation of neural tissue in vivo.

For more than a century, the traditional method of stimulating neural activity has been based on electrical methods, and it remains the gold standard to date. We report a technological breakthrough in neural activation in which low-level, pulsed infrared laser light is used to elicit compound nerve and muscle potentials in mammalian peripheral nerve in vivo. Optically induced neural action potentials are spatially precise, artifact free, and damage free and are generated by use of energies well below tissue ablation threshold. Thus optical stimulation presents a simple yet novel approach to contact-free in vivo neural activation that has major implications for clinical neurosurgery, basic neurophysiology, and neuroscience.

Development of a Fiber Optic Probe to Measure NIR Raman Spectra of Cervical Tissue In Vivo

The goal of this study was to develop a compact fiber optic probe to measure near infrared Raman spectra of human cervical tissue in vivo for the clinical diagnosis of cervical precancers. A Raman spectrometer and fiber optic probe were designed, constructed and tested. The probe was first tested using standards with known Raman spectra, and then the probe was used to acquire Raman spectra from normal and precancerous cervical tissue in vivo. Raman spectra of cervical tissue could be acquired in vivo in 90 s using incident powers comparable to the threshold limit values for laser exposure of the skin. Although some silica signal obscured tissue Raman bands below 900 cm‐1, Raman features from cervical tissue could clearly be discerned with an acceptable signal‐to‐noise ratio above 900 cm‐1. The success of the Raman probe described here indicates that near infrared Raman spectra can be measured in vivo from cervical tissues. Increasing the power of the excitation source could reduce the integration time to below 20 s.

In Vivo Brain Tumor Demarcation Using Optical Spectroscopy

Abstract The applicability of optical spectroscopy for intraoperative detection of brain tumors/tumor margins was investigated in a pilot clinical trial consisting of 26 brain tumor patients. The results of this clinical trial suggest that brain tumors and infiltrating tumor margins (ITM) can be effectively separated from normal brain tissues in vivo using combined autofluorescence and diffuse-reflectance spectroscopy. A two-step empirical discrimination algorithm based on autofluorescence and diffuse reflectance at 460 and 625 nm was developed. This algorithm yields a sensitivity and specificity of 100 and 76%, respectively, in differentiating ITM from normal brain tissues. Blood contamination was found to be a major obstacle that attenuates the accuracy of brain tumor demarcation using optical spectroscopy. Overall, this study indicates that optical spectroscopy has the potential to guide brain tumor resection intraoperatively with high sensitivity.

In vivo nonmelanoma skin cancer diagnosis using Raman microspectroscopy

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.