Optical adjuncts for enhanced colonoscopic diagnosis

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.

Detection of intestinal cancer by local, topical application of a quenched fluorescence probe for cysteine cathepsins

Early detection of colonic polyps can prevent up to 90% of colorectal cancer deaths. Conventional colonoscopy readily detects the majority of premalignant lesions, which exhibit raised morphology. However, lesions that are flat and depressed are often undetected using this method. Therefore, there is a need for molecular-based contrast agents to improve detection rates over conventional colonoscopy. We evaluated a quenched fluorescent activity-based probe (qABP; BMV109) that targets multiple cysteine cathepsins that are overexpressed in intestinal dysplasia in a genetic model of spontaneous intestinal polyp formation and in a chemically induced model of colorectal carcinoma. We found that the qABP selectively targets cysteine cathepsins, resulting in high sensitivity and specificity for intestinal tumors in mice and humans. Additionally, the qABP can be administered by either intravenous injection or by local delivery to the colon, making it a highly valuable tool for improved detection of colorectal lesions using fluorescence-guided colonoscopy.

Evaluation of a confocal Raman probe for pathological diagnosis during colonoscopy

AIM

Raman spectroscopy of human tissue can provide a unique biochemical 'fingerprint' that alters with disease progression. Light incident on tissue is scattered and may be altered in wavelength, which can be represented as a Raman spectrum. A confocal fibreoptic Raman probe designed to fit down the accessory channel of a colonoscope has been constructed. This in-vitro study evaluated the accuracy of pathological diagnosis in the colon using probe-based Raman spectroscopy.

METHOD

Biopsy samples were collected at colonoscopy, snap frozen and stored at -80 °C. Raman spectra with 10-s and 1-s acquisition periods were measured with the probe tip in contact with the mucosal surface of thawed specimens. Mathematical modelling using principal component analysis followed by linear discriminant analysis was used to correlate Raman spectra with histopathological diagnoses.

RESULTS

Three-hundred and seventy-five Raman spectra were measured from a total of 356 colon biopsies (81 of normal colon mucosa, 79 of hyperplastic polyps, 92 of adenomatous polyps, 64 of adenocarcinoma and 40 of ulcerative colitis) from 177 patients. Spectral classification accuracies comparing pathology pairs ranged from 72.1 to 95.9% for 10-s acquisitions and from 61.5 to 95.1% for 1-s acquisitions. For a three-group model of normal, adenomatous and adenocarcinoma tissue, accuracies were 74.1% for 10-s acquisitions and 63.5% for 1-s acquisitions.

CONCLUSION

The confocal Raman probe system can distinguish between different colorectal pathologies. The probe has potential to establish Raman spectroscopy as a clinical tool for instant diagnosis at colonoscopy.

Model based inversion for deriving maps of histological parameters characteristic of cancer from ex-vivo multispectral images of the colon

A model-based inversion method was used to obtain quantitative estimates of histological parameters from multispectral images of the colon and to examine their potential for discriminating between normal and pathological tissues. Pixel-wise estimates of the mucosal blood volume fraction, density of the scattering particles and thickness were derived using a two-stage method. In the first (forward) stage reflectance spectra corresponding to given instances of the parameter values were computed using Monte Carlo simulation of photon propagation through a multi-layered tissue. In the second (inversion) stage the parameter values were obtained via optimization using an iterated conditional modes algorithm based on Discrete Markov Random Fields. The method was validated on computer generated data contaminated with noise giving a mean normalized root mean square deviation (NRMSD) of 2.04. Validation on ex vivo images demonstrated that parametric maps show gross correspondence with histological features of mucosa characteristic of cancerous, precancerous and noncancerous colon lesions. The key signs of abnormality were shown to be the increase in the blood volume fraction and decrease in the density of scattering particles.

Discriminating adenocarcinoma from normal colonic mucosa through deconvolution of Raman spectra

In this work, we considered the feasibility of Raman spectroscopy for discriminating between adenocarcinomatous and normal mucosal formalin-fixed colonic tissues. Unlike earlier studies in colorectal cancer, a spectral deconvolution model was implemented to derive spectral information. Eleven samples of human colon were used, and 55 spectra were analyzed. Each spectrum was resolved into 25 bands from 975 to 1720 cm(-1), where modes of proteins, lipids, and nucleic acids are observed. From a comparative study of band intensities, those presenting higher differences between tissue types were correlated to biochemical assignments. Results from fitting procedure were further used as inputs for linear discriminant analysis, where combinations of band intensities and intensity ratios were tested, yielding accuracies up to 81%. This analysis yields objective discriminating parameters after fitting optimization. The bands with higher diagnosis relevance detected by spectra deconvolution enable to confine the study to some spectral regions instead of broader ranges. A critical view upon limitations of this approach is presented, along with a comparison of our results to earlier ones obtained in fresh colonic tissues. This enabled to assess the effect of formalin fixation in colonic tissues, and determine its relevance in the present analysis.

On-the-fly detection of changes on and below the surface in epithelium mucosal tissue architecture from scattered light

In this paper we present a technique to raise a flag on the fly when a transition occurs between different mucosal architectures on or below the surface. The segmentation is based on a novel difference metric for detecting an abrupt change in the parameters extracted from a Stochastic Decomposition Method (SDM) that models the scattered light reflected from the mucosal tissue structure over an area (2-D scan) illuminated by an optical sensor (fiber) emitting light at either one wavelength or with white light. This work has the potential to enhance the endoscopist's ability to locate and identify abnormal mucosal architectures in particular when the disease is developing below the surface and hence becoming hidden during colonoscopy or endoscopic examination. It also has also potential in helping deciding as to when and where to take biopsies; steps that should lead to improvement in the diagnostic yield.

Evaluation of linear discriminant analysis for automated Raman histological mapping of esophageal high-grade dysplasia

Rapid Raman mapping has the potential to be used for automated histopathology diagnosis, providing an adjunct technique to histology diagnosis. The aim of this work is to evaluate the feasibility of automated and objective pathology classification of Raman maps using linear discriminant analysis. Raman maps of esophageal tissue sections are acquired. Principal component (PC)-fed linear discriminant analysis (LDA) is carried out using subsets of the Raman map data (6483 spectra). An overall (validated) training classification model performance of 97.7% (sensitivity 95.0 to 100% and specificity 98.6 to 100%) is obtained. The remainder of the map spectra (131,672 spectra) are projected onto the classification model resulting in Raman images, demonstrating good correlation with contiguous hematoxylin and eosin (HE) sections. Initial results suggest that LDA has the potential to automate pathology diagnosis of esophageal Raman images, but since the classification of test spectra is forced into existing training groups, further work is required to optimize the training model. A small pixel size is advantageous for developing the training datasets using mapping data, despite lengthy mapping times, due to additional morphological information gained, and could facilitate differentiation of further tissue groups, such as the basal cells∕lamina propria, in the future, but larger pixels sizes (and faster mapping) may be more feasible for clinical application.

Can we see epithelium tissue structure below the surface using an optical probe?

This paper answers the question of whether it is possible to detect changes below the surface in epithelium layered structures using a Stochastic Decomposition Method (SDM) that models the scattered light reflected from the layered structure over an area (2-D scan) illuminated by an optical sensor (fibre) emitting light at either one wavelength or with white light. Our technique correlates the differential changes in the reflected tissue texture with the morphological and physical changes that occur in the tissue occurring inside the structure. This work has great potential for detecting changes in mucosal structures and may lead to enhanced endoscopy when the disease is developing to the outside of the mucosal structure and hence becoming hidden during colonoscopy or endoscopic examination. Tests are performed on layered tissue phantoms, and the results obtained show great effectiveness of the model and method in picking up changes in the morphology of the layered tissue phantoms occurring below the surface. We also establish the robustness of the model to changes in viewing depth by testing it on phantoms viewed at different depths. We show that the model is robust to within a 4-mm-deep viewing range.

Early and Long-Term Outcomes of Patients Undergoing Liver Resection and Diaphragm Excision for Advanced Colorectal Liver Metastases

INTRODUCTION

At present, liver resection offers the best long-term outcome and only chance for cure in patients with colorectal liver metastases. However, there are no large series that report the early and long-term outcomes of patients who require simultaneous diaphragm excision. This study was designed to investigate these patients.

PATIENTS AND METHODS

A total of 285 consecutive liver resections were performed over a 10-year period. Of these, 258 had liver resections alone and 27 underwent liver resection and simultaneous diaphragm excision. Data were collected prospectively and analysed retrospectively. Pre-operative assessment was standardised. The outcomes between the two groups were compared.

RESULT

There was no difference in age, hospital stay or intra-operative blood loss. The diaphragm was histologically involved in four out of 27 resections. As a result, the cancer involved resection margin incidence was greater in the liver resection and diaphragm excision group (14.8% versus 3.9%; P = 0.12). The median tumour size was also different between the two groups (60 mm versus 30 mm; P = 0.001). The liver and diaphragm resection group had a greater peri-operative complication rate (44.4% versus 21.3%; P = 0.02) and mortality (7.4% versus 1.6%; P = 0.25). Overall and disease-free survival was significantly worse in the group who underwent simultaneous diaphragm excision and liver resection (P = 0.04 and P = 0.005, respectively). Diaphragm invasion was found to be an independent predictor of poor overall outcome (P = 0.02).

CONCLUSION

Liver resection and simultaneous diaphragm excision have a greater incidence of peri-operative morbidity and mortality and a significantly worse long-term outcome compared with liver resection alone. However, these data suggest that liver resection in the presence of diaphragm invasion may still offer a favourable outcome compared with chemotherapy treatment alone. Therefore, we believe that diaphragm involvement by tumour should not be a contra-indication to hepatectomy.

Sentinel node biopsy for the individualization of surgical strategy for cure of early-stage colon cancer

INTRODUCTION

The requirement for nodal analysis currently confounds the oncological propriety of focused purely endoscopic resection for early-stage colon cancer and complicates the evolution of innovative alternatives such as natural orifice transluminal endoscopic surgery (NOTES) and its hybrids. Adjunctive sentinel node biopsy (SNB) deserves consideration as a means of addressing this shortfall.

METHODS

Data from two prospectively maintained databases established for multicentric studies of SNB in colon cancer that employed similar methodologies were pooled to establish technique potency selectively in T1/T2 disease (both overall and under optimized conditions) and to project potential clinical impact.

RESULTS

Of 891 patients with T1-4, M0 intraperitoneal colon cancer, 225 had T1/T2 disease. Sentinel nodes were either not found or were falsely negative in 18 patients with T1/T2 cancers (8%) as compared with 17% (112/646) in those with T3/T4 disease (P = 0.001). Negative predictive value (NPV) in the former exceeded 95%, while sensitivity [including immunohistochemistry (IHC)] was 81%. In the 193 patients with T1/T2 disease recruited from those centers contributing >22 patients, sensitivity was 89% and NPV 97%. Thus, in this cohort, SNB could have correctly prompted localized resection (obviating en bloc mesenteric dissection) in 75% (144) of patients, including 59 with T1 lesions potentially amenable to intraluminal resection alone as their definitive treatment. Forty-four patients (23.4%) would still have conventional resection, leaving three patients (1.6% overall) understaged (11% false-negative rate).

CONCLUSION

These findings support the further investigation of SNB as oncological augment for localized resective techniques. Specific prospective study should pursue this goal.

Vibrational spectroscopy: a clinical tool for cancer diagnostics

Vibrational spectroscopy techniques have demonstrated potential to provide non-destructive, rapid, clinically relevant diagnostic information. Early detection is the most important factor in the prevention of cancer. Raman and infrared spectroscopy enable the biochemical signatures from biological tissues to be extracted and analysed. In conjunction with advanced chemometrics such measurements can contribute to the diagnostic assessment of biological material. This paper also illustrates the complementary advantage of using Raman and FTIR spectroscopy technologies together. Clinical requirements are increasingly met by technological developments which show promise to become a clinical reality. This review summarises recent advances in vibrational spectroscopy and their impact on the diagnosis of cancer.

The potential for histological screening using a combination of rapid Raman mapping and principal component analysis

Rapid Raman mapping was carried out on 20 microm sections of oesophageal biopsy samples. Contiguous 7 microm sections were stained with haematoxylin and eosin (H&E) with histopathology provided by an expert pathologist. The step size and acquisition times were varied and the resulting spectra, principal component (PC) score maps and loads were compared. Overall mapping times were also compared to traditional Raman point mapping. The principal component loads for each of the maps were seen to be similar despite varying the acquisition time and number of spectra. Gross biochemical information was extracted showing good correlation with the H&E sections even for short overall mapping times (30-90 minutes for a 2 mm biopsy, 0.5 s acquisition time per 25.3 microm Raman pixel). This demonstrates that low signal to noise spectral maps are sufficient for the identification of histologically relevant biochemistry using principal component analysis as long as the spectral dataset is large enough.