Harvey Lui

Near‐infrared Raman spectroscopy for optical diagnosis of lung cancer

Raman spectroscopy is a vibrational spectroscopic technique that can be used to optically probe the molecular changes associated with diseased tissues. The objective of our study was to explore near‐infrared (NIR) Raman spectroscopy for distinguishing tumor from normal bronchial tissue. Bronchial tissue specimens (12 normal, 10 squamous cell carcinoma (SCC) and 6 adenocarcinoma) were obtained from 10 patients with known or suspected malignancies of the lung. A rapid‐acquisition dispersive‐type NIR Raman spectroscopy system was used for tissue Raman studies at 785 nm excitation. High‐quality Raman spectra in the 700–1,800 cm–1 range from human bronchial tissues in vitro could be obtained within 5 sec. Raman spectra differed significantly between normal and malignant tumor tissue, with tumors showing higher percentage signals for nucleic acid, tryptophan and phenylalanine and lower percentage signals for phospholipids, proline and valine, compared to normal tissue. Raman spectral shape differences between normal and tumor tissue were also observed particularly in the spectral ranges of 1,000–1,100, 1,200–1,400 and 1,500–1,700 cm–1, which contain signals related to protein and lipid conformations and nucleic acids CH stretching modes. The ratio of Raman intensities at 1,445 to 1,655 cm–1 provided good differentiation between normal and malignant bronchial tissue (p < 0.0001). The results of this exploratory study indicate that NIR Raman spectroscopy provides significant potential for the noninvasive diagnosis of lung cancers in vivo based on the optic evaluation of biomolecules.

Automated Autofluorescence Background Subtraction Algorithm for Biomedical Raman Spectroscopy

A significant advantage of Raman spectroscopy as a noninvasive optical technique is its ability to detect subtle molecular or biochemical signatures within tissue. One of the major challenges for biomedical Raman spectroscopy is the removal of intrinsic autofluorescence background signals, which are usually a few orders of magnitude stronger than those arising from Raman scattering. A number of methods have been proposed for fluorescence background removal including excitation wavelength shifting, Fourier transformation, time gating, and simple or modified polynomial fitting. The single polynomial and the modified multi-polynomial fitting methods are relatively simple and effective, and thus are widely used in biological applications. However, their performance in real-time in vivo applications and low signal-to-noise ratio environments is sub-optimal. An improved automated algorithm for fluorescence removal has been developed based on modified multi-polynomial fitting, but with the addition of (1) a peak-removal procedure during the first iteration, and (2) a statistical method to account for signal noise effects. Experimental results demonstrate that this approach improves the automated rejection of the fluorescence background during real-time Raman spectroscopy and for in vivo measurements characterized by low signal-to-noise ratios.

Real-time Raman Spectroscopy for In Vivo Skin Cancer Diagnosis

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

Rapid near-infrared Raman spectroscopy system for real-time in vivo skin measurements.

A rapid dispersive-type near-infrared (NIR) Raman spectroscopy system and a Raman probe were developed to facilitate real-time, noninvasive, in vivo human skin measurements. Spectrograph image aberration was corrected by a parabolic-line fiber array, permitting complete CCD vertical binning, thereby yielding a 3.3-16-fold improvement in signal-to-noise ratio. Good quality in vivo cutaneous NIR Raman spectra free of interference from fiber fluorescence and silica Raman scattering can be acquired in less than 1 s, which greatly facilitates practical noninvasive tissue characterization and clinical diagnosis.

Raman spectroscopy of in vivo cutaneous melanin

We successfully acquire the in vivo Raman spectrum of melanin from human skin using a rapid near-infrared (NIR) Raman spectrometer. The Raman signals of in vivo cutaneous melanin are similar to those observed from natural and synthetic eumelanins. The melanin Raman spectrum is dominated by two intense and broad peaks at about 1580 and 1380 cm(-1), which can be interpreted as originating from the in-plane stretching of the aromatic rings and the linear stretching of the C-C bonds within the rings, along with some contributions from the C-H vibrations in the methyl and methylene groups. Variations in the peak frequencies and bandwidths of these two Raman signals due to differing biological environments have been observed in melanin from different sources. The ability to acquire these unique in vivo melanin signals suggests that Raman spectroscopy may be a useful clinical method for noninvasive in situ analysis and diagnosis of the skin.

Development and preliminary results of an endoscopic Raman probe for potential in vivo diagnosis of lung cancers

A near-infrared Raman system was developed to collect real-time in vivo human lung spectra. The excitation light and the emission were guided to and from the tissue surface by a reusable fiber catheter passed down the instrument channel of a bronchoscope. Two-stage filtering was used to reduce laser noise, fluorescence, and Raman emissions from the fibers. A second fiber bundle guided the emission to a spectrometer where the fibers, in a round packing geometry, were spread out to form a parabolic arc that improved the signal-to-noise ratio 20-fold, facilitating real-time spectral measurements. Preliminary clinical tests show that clear and reliable Raman spectra can be obtained.

Raman Spectroscopy in Combination with Background Near-infrared Autofluorescence Enhances the In Vivo Assessment of Malignant Tissues

Abstract The diagnostic ability of optical spectroscopy techniques, including near-infrared (NIR) Raman spectroscopy, NIR autofluorescence spectroscopy and the composite Raman and NIR autofluorescence spectroscopy, for in vivo detection of malignant tumors was evaluated in this study. A murine tumor model, in which BALB/c mice were implanted with Meth-A fibrosarcoma cells into the subcutaneous region of the lower back, was used for this purpose. A rapid-acquisition dispersive-type NIR Raman system was employed for tissue Raman and NIR autofluorescence spectroscopic measurements at 785-nm laser excitation. High-quality in vivo NIR Raman spectra associated with an autofluorescence background from mouse skin and tumor tissue were acquired in 5 s. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA), were used to develop diagnostic algorithms for differentiating tumors from normal tissue based on their spectral features. Spectral classification of tumor tissue was tested using a leave-one-out, cross-validation method, and the receiver operating characteristic (ROC) curves were used to further evaluate the performance of diagnostic algorithms derived. Thirty-two in vivo Raman, NIR fluorescence and composite Raman and NIR fluorescence spectra were analyzed (16 normal, 16 tumors). Classification results obtained from cross-validation of the LDA model based on the three spectral data sets showed diagnostic sensitivities of 81.3%, 93.8% and 93.8%; specificities of 100%, 87.5% and 100%; and overall diagnostic accuracies of 90.6%, 90.6% and 96.9% respectively, for tumor identification. ROC curves showed that the most effective diagnostic algorithms were from the composite Raman and NIR autofluorescence techniques.

Efficacy of once-daily treatment regimens with calcipotriol/betamethasone dipropionate ointment and calcipotriol ointment in psoriasis vulgaris

Background  A two‐compound ointment containing calcipotriol 50 µg g−1 and betamethasone dipropionate 0·5 mg g−1 has recently been shown to be an effective treatment for psoriasis.

Single-wall carbon nanotubes assisted photothermal cancer therapy: Animal study with a murine model of squamous cell carcinoma†

There has been a dramatic increase in photothermal therapy as a minimally invasive treatment modality for cancer treatment due to the development of novel nanomaterials as the light absorption agents. Single‐wall carbon nanotubes (SWNTs) with strong optical absorption in the broad visible and near IR offer unique advantages for photothermal cancer therapy. A broad range of wavelengths can be used for the treatment with SWNTs, whereas conventional photothermal therapeutic agent is designed to absorb light only near one selected wavelength. The objective of this study is to validate the hypothesis that intratumoral injected SWNTs can absorb 785 nm near IR laser light and generate significant local hyperthermia to destroy tumors.

Photodynamic Therapy of Nonmelanoma Skin Cancer With Topical Aminolevulinic Acid: A Clinical and Histologic Study

In dermatology, photodynamic therapy (PDT) has been used primarily for treating malignant skin tumors and involves the sequential administration of photosensitizing drugs and light to patients. Aminolevulinic acid is a naturally occurring porphyrin precursor that can photosensitize cutaneous neoplasms for destruction by light when applied topically in pharmacologic doses. Exogenous topical aminolevulinic acid appears to be taken up preferentially by tumors and metabolized in situ to protoporphyrin IX, a photosensitive compound. 1,2 Kennedy et al 1,2 reported first on the use of topical aminolevulinic acid and red light to photosensitize skin tumors in patients. There has been limited longterm clinical follow-up data concerning patients treated with aminolevulinic acid and light, and there is also a lack of detailed histologic studies assessing microscopic tumor responses to therapy. Subjects and Methods. Five patients with one or more biopsy-proven and previously untreated basal cell or squamous cell (in situ or invasive) carcinomas measuring