Biophysical basis of skin cancer detection using Raman spectroscopy

The goal of this dissertation is to study the potential of Raman spectroscopy in improving the clinical diagnosis of skin cancer, including two main applications: noninvasive screening of melanoma skin cancer and surgical margin detection of nonmelanoma skin cancer. Skin cancer is the most common type of malignancy, accounting for over 5.4 million cases and 10 thousand deaths per year in the United States alone. Like most cancers, the current “gold standard” diagnosis relies on biopsy and histopathology, which is invasive, time-consuming, and costly. Moreover, large numbers of benign lesions are biopsied for melanoma diagnosis, resulting in substantial financial burden and patient discomfort. Therefore, an urgent need exists to develop a noninvasive, fast, and accurate method for skin cancer detection. The first part of the dissertation focuses on exploring the biophysical origin of in vivo melanoma detection. Our group has previously reported on the development of a clinical Raman spectroscopy system towards spectral biopsy of skin; however, the biochemical changes that Raman spectroscopy relies on for accurate melanoma diagnosis remained unclear. As a result, we proposed a biophysical inverse model to address this issue. To build the model, we established a custom confocal Raman microscope to extract in situ human skin constituents spanning normal and various diseased states. Our results indicate collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin, and water are the most important model components. Furthermore, collagen and triolein are the most relevant markers to discriminate malignant melanoma from benign nevi. The second part of the dissertation discusses the biophysical basis of nonmelanoma skin cancer margin delineation. We discovered the diagnostic markers to accurately differentiate tumor from normal skin, which is critical to maximize positive patient outcomes in skin cancer surgery. The biochemical changes derived from our model were highly correlated with histopathological diagnosis. We further demonstrated the feasibility of a superpixel acquisition approach for rapid classification of tumor boundaries in skin biopsies. Our results suggest Raman spectroscopy will be a powerful tool for intraoperative surgical guidanceBiomedical Engineerin

VIBRATIONAL SPECTROSCOPY FOR THE ASSESSMENT OF VULVAL DISEASE

Vibrational spectroscopic diagnostic techniques have significant potential to improve the care of women with benign, premalignant and malignant vulval diseases by reducing the reliance on traditional biopsy and histopathology. These techniques also have the potential to augment clinicians’ ability to differentiate different types of vulval disease at the time of surgery for neoplastic vulval disease. In addition, vibrational spectroscopic techniques offer the opportunity to assess molecular changes associated with the development of vulval cancer that are not apparent on routine histopathological assessment. The work outlined in this thesis evaluates the role of emerging techniques in vibrational spectroscopy to address this need within three key themes: 1. Developmentofavibrationalspectroscopicdiagnostictechniquetoreducethe reliance on traditional biopsy and histopathological diagnosis. 2. Developmentofavibrationalspectroscopicdiagnostictechniqueforimproving the delineation of disease margins at the time of surgery for pre-malignant and malignant vulval conditions. 3. Evaluation of a vibrational spectroscopic tool for augmenting and automating aspects of vulval histopathology. Raman spectroscopic mapping of 91 fresh frozen vulval tissue sections combined with multivariate spectral analysis was used to demonstrate that malignant vulval disease could be differentiated from non-neoplastic and premalignant vulval disease with a sensitivity of 97% and specificity of 78%. The technique was then tested in experimental conditions closer to in-vivo application, measuring spectra from 91 whole fresh frozen tissue blocks using microscope and probe Raman systems. This demonstrated the technique could differentiate malignant from non-neoplastic and premalignant vulval disease with sensitivities of 84% to 92% and specificities of 84% to 64% respectively. In a separate investigation vulval tissue blocks from 27 women with suspected lichen sclerosus underwent Raman spectroscopic point measurements. Multivariate analysis demonstrated Raman spectroscopy could be used to differentiate lichen sclerosus from other vulval disorders with a similar clinical appearance with a sensitivity of sensitivity of 91% and specificity of 80%. Fourier transform infrared (FTIR) spectroscopic mapping of 93 fixed paraffin embedded tissue sections was used to demonstrate that malignant vulval disease could be differentiated from non-neoplastic and premalignant with vulval disease with an approximate sensitivity of 100% and specificity of 79%. In addition FTIR spectroscopy was used to differentiate molecular changes in vulval intraepithelial neoplasia (VIN) and lichen sclerosus (LS) found in association with vulval squamous cell carcinoma (SCC). Analysis of FTIR spectroscopic tissue maps from 48 patients demonstrated the technique could differentiate LS associated with SCC with a sensitivity of approximately 100% and specificity of 84% and VIN associated with SCC with a sensitivity of approximately 100% and specificity 58%. This thesis demonstrates the considerable potential of vibrational spectroscopy in this clinical setting. The research has made significant progress in each of the three themes outlined above and indicates that further work is warranted to develop the techniques towards routine clinical application

Deep learning data augmentation for Raman spectroscopy cancer tissue classification.

Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular biochemical changes between cancerous vs. normal tissues and cells. In order to design computational approaches for cancer detection, the quality and quantity of tissue samples for RS are important for accurate prediction. In reality, however, obtaining skin cancer samples is difficult and expensive due to privacy and other constraints. With a small number of samples, the training of the classifier is difficult, and often results in overfitting. Therefore, it is important to have more samples to better train classifiers for accurate cancer tissue classification. To overcome these limitations, this paper presents a novel generative adversarial network based skin cancer tissue classification framework. Specifically, we design a data augmentation module that employs a Generative Adversarial Network (GAN) to generate synthetic RS data resembling the training data classes. The original tissue samples and the generated data are concatenated to train classification modules. Experiments on real-world RS data demonstrate that (1) data augmentation can help improve skin cancer tissue classification accuracy, and (2) generative adversarial network can be used to generate reliable synthetic Raman spectroscopic data

The future of medical diagnostics: Review paper

While histopathology of excised tissue remains the gold standard for diagnosis, several new, non-invasive diagnostic techniques are being developed. They rely on physical and biochemical changes that precede and mirror malignant change within tissue. The basic principle involves simple optical techniques of tissue interrogation. Their accuracy, expressed as sensitivity and specificity, are reported in a number of studies suggests that they have a potential for cost effective, real-time, in situ diagnosis. We review the Third Scientific Meeting of the Head and Neck Optical Diagnostics Society held in Congress Innsbruck, Innsbruck, Austria on the 11th May 2011. For the first time the HNODS Annual Scientific Meeting was held in association with the International Photodynamic Association (IPA) and the European Platform for Photodynamic Medicine (EPPM). The aim was to enhance the interdisciplinary aspects of optical diagnostics and other photodynamic applications. The meeting included 2 sections: oral communication sessions running in parallel to the IPA programme and poster presentation sessions combined with the IPA and EPPM posters sessions. © 2011 Jerjes et al; licensee BioMed Central Ltd

Intra-operative spectroscopic assessment of surgical margins during breast conserving surgery

Background: In over 20% of breast conserving operations, postoperative pathological assessment of the excised tissue reveals positive margins, requiring additional surgery. Current techniques for intra-operative assessment of tumor margins are insufficient in accuracy or resolution to reliably detect small tumors. There is a distinct need for a fast technique to accurately identify tumors smaller than 1 mm2 in large tissue surfaces within 30 min. Methods: Multi-modal spectral histopathology (MSH), a multimodal imaging technique combining tissue auto-fluorescence and Raman spectroscopy was used to detect microscopic residual tumor at the surface of the excised breast tissue. New algorithms were developed to optimally utilize auto-fluorescence images to guide Raman measurements and achieve the required detection accuracy over large tissue surfaces (up to 4 × 6.5 cm2). Algorithms were trained on 91 breast tissue samples from 65 patients. Results: Independent tests on 121 samples from 107 patients - including 51 fresh, whole excision specimens - detected breast carcinoma on the tissue surface with 95% sensitivity and 82% specificity. One surface of each uncut excision specimen was measured in 12–24 min. The combination of high spatial-resolution auto-fluorescence with specific diagnosis by Raman spectroscopy allows reliable detection even for invasive carcinoma or ductal carcinoma in situ smaller than 1 mm2. Conclusions: This study provides evidence that this multimodal approach could provide an objective tool for intra-operative assessment of breast conserving surgery margins, reducing the risk for unnecessary second operations

A roadmap for the clinical implementation of optical-imaging biomarkers

Clinical workflows for the non-invasive detection and characterization of disease states could benefit from optical-imaging biomarkers. In this Perspective, we discuss opportunities and challenges towards the clinical implementation of optical-imaging biomarkers for the early detection of cancer by analysing two case studies: the assessment of skin lesions in primary care, and the surveillance of patients with Barrett’s oesophagus in specialist care. We stress the importance of technical and biological validations and clinical-utility assessments, and the need to address implementation bottlenecks. In addition, we define a translational roadmap for the widespread clinical implementation of optical imaging-technologies

Multimodal optical systems for clinical oncology

This thesis presents three multimodal optical (light-based) systems designed to improve the capabilities of existing optical modalities for cancer diagnostics and theranostics. Optical diagnostic and therapeutic modalities have seen tremendous success in improving the detection, monitoring, and treatment of cancer. For example, optical spectroscopies can accurately distinguish between healthy and diseased tissues, fluorescence imaging can light up tumours for surgical guidance, and laser systems can treat many epithelial cancers. However, despite these advances, prognoses for many cancers remain poor, positive margin rates following resection remain high, and visual inspection and palpation remain crucial for tumour detection. The synergistic combination of multiple optical modalities, as presented here, offers a promising solution. The first multimodal optical system (Chapter 3) combines Raman spectroscopic diagnostics with photodynamic therapy using a custom-built multimodal optical probe. Crucially, this system demonstrates the feasibility of nanoparticle-free theranostics, which could simplify the clinical translation of cancer theranostic systems without sacrificing diagnostic or therapeutic benefit. The second system (Chapter 4) applies computer vision to Raman spectroscopic diagnostics to achieve spatial spectroscopic diagnostics. It provides an augmented reality display of the surgical field-of-view, overlaying spatially co-registered spectroscopic diagnoses onto imaging data. This enables the translation of Raman spectroscopy from a 1D technique to a 2D diagnostic modality and overcomes the trade-off between diagnostic accuracy and field-of-view that has limited optical systems to date. The final system (Chapter 5) integrates fluorescence imaging and Raman spectroscopy for fluorescence-guided spatial spectroscopic diagnostics. This facilitates macroscopic tumour identification to guide accurate spectroscopic margin delineation, enabling the spectroscopic examination of suspicious lesions across large tissue areas. Together, these multimodal optical systems demonstrate that the integration of multiple optical modalities has potential to improve patient outcomes through enhanced tumour detection and precision-targeted therapies.Open Acces

Raman Spectroscopy Applied to Health Sciences

Raman spectroscopy has remarkable analytical abilities to scientists who want to study biological samples. The use of Raman spectroscopy within biologic samples has been increasing in the last years because it can provide biochemical information, allows discrimination between two or more sample groups, and, contrary to what happens with other spectroscopic techniques, water has no interference in the spectra. Biological samples typically do not require extensive preparation, and biochemical and structural information extracted from spectroscopic data can be used to characterize different groups. This chapter presents the general features of Raman spectroscopy and Raman spectroscopic tools relevant to the application in health sciences. In order to emphasize the potential of Raman in this research field, examples of its application in oncology, in bacterial identification and in dementia diagnosis are given

An Investigation of the Diagnostic Potential of Autofluorescence Lifetime Spectroscopy and Imaging for Label-Free Contrast of Disease

The work presented in this thesis aimed to study the application of fluorescence lifetime spectroscopy (FLS) and fluorescence lifetime imaging microscopy (FLIM) to investigate their potential for diagnostic contrast of diseased tissue with a particular emphasis on autofluorescence (AF) measurements of gastrointestinal (GI) disease. Initially, an ex vivo study utilising confocal FLIM was undertaken with 420 nm excitation to characterise the fluorescence lifetime (FL) images obtained from 71 GI samples from 35 patients. A significant decrease in FL was observed between normal colon and polyps (p = 0.024), and normal colon and inflammatory bowel disease (IBD) (p = 0.015). Confocal FLIM was also performed on 23 bladder samples. A longer, although not significant, FL for cancer was observed, in paired specimens (n = 5) instilled with a photosensitizer. The first in vivo study was a clinical investigation of skin cancer using a fibre-optic FL spectrofluorometer and involved the interrogation of 27 lesions from 25 patients. A significant decrease in the FL of basal cell carcinomas compared to healthy tissue was observed (p = 0.002) with 445 nm excitation. A novel clinically viable FLS fibre-optic probe was then applied ex vivo to measure 60 samples collected from 23 patients. In a paired analysis of neoplastic polyps and normal colon obtained from the same region of the colon in the same patient (n = 12), a significant decrease in FL was observed (p = 0.021) with 435 nm excitation. In contrast, with 375 nm excitation, the mean FL of IBD specimens (n = 4) was found to be longer than that of normal tissue, although not statistically significant. Finally, the FLS system was applied in vivo in 17 patients, with initial data indicating that 435 nm excitation results in AF lifetimes that are broadly consistent with ex vivo studies, although no diagnostically significant differences were observed in the signals obtained in vivo.Open Acces