Modelling and validation of spectral reflectance for the colon

Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment

BACKGROUND

Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and poorer survival. We investigated diffuse reflectance spectroscopy (DRS) to distinguish tumour and non-tumour tissue in ex vivo colorectal specimens, to aid margin assessment and provide augmented visual maps to the surgeon in real-time.

METHODS

Patients undergoing elective colorectal cancer resection surgery at a London-based hospital were prospectively recruited. A hand-held DRS probe was used on the surface of freshly resected ex vivo colorectal tissue. Spectral data was acquired for tumour and non-tumour tissue. Binary classification was achieved using conventional machine learning classifiers and a convolutional neural network (CNN), which were evaluated in terms of sensitivity, specificity, accuracy and the area under the curve.

RESULTS

A total of 7692 mean spectra were obtained for tumour and non-tumour colorectal tissue. The CNN-based classifier was the best performing machine learning algorithm, when compared to contrastive approaches, for differentiating tumour and non-tumour colorectal tissue, with an overall diagnostic accuracy of 90.8% and area under the curve of 96.8%. Live on-screen classification of tissue type was achieved using a graduated colourmap.

CONCLUSION

A high diagnostic accuracy for a DRS probe and tracking system to differentiate ex vivo tumour and non-tumour colorectal tissue in real-time with on-screen visual feedback was highlighted by this study. Further in vivo studies are needed to ensure integration into a surgical workflow.

Reflectance spectra analysis for mucous assessment

This review report represents an overview of research and development on medical hyperspectral imaging technology and its applications. Spectral imaging technology is attracting attention as a new imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. Considering the recent advances in imaging, this technology provides an opportunity for two-dimensional mapping of oxygen saturation (SatO₂) of blood with high accuracy, spatial spectral imaging, and its analysis and provides detection and diagnostic information about the tissue physiology and morphology. Multispectral imaging also provides information about tissue oxygenation, perfusion, and potential function during surgery. Analytical algorithm has been examined, and indication of accurate map of relative hemoglobin concentration and SatO₂ can be indicated with preferable resolution and frame rate. This technology is expected to provide promising biomedical information in practical use. Several studies suggested that blood flow and SatO₂ are associated with gastrointestinal disorders, particularly malignant tumor conditions. The use and analysis of spectroscopic images are expected to potentially play a role in the detection and diagnosis of these diseases.

Histopathological correlations of bulk tissue polarimetric images: Case study

Polarimetric imaging and image analysis have gained increased interest in soft tissue analysis at the cellular level. However, polarimetric imaging has widely been tested on thin tissue sections to provide reliable information correlated with histopathological findings. Polarimetric bulk tissue analysis always offered an overall assessment of various tissue optical properties for diagnosis. In this study, the histopathological correlation of bulk tissue polarimetry images for soft tissues is discussed. The first-hand information on the use of bulk tissue Mueller polarimetry and image analysis as an alternative to tissue histopathology is presented for surgically extracted colon and breast tissues.

Surgical spectral imaging

Recent technological developments have resulted in the availability of miniaturised spectral imaging sensors capable of operating in the multi- (MSI) and hyperspectral imaging (HSI) regimes. Simultaneous advances in image-processing techniques and artificial intelligence (AI), especially in machine learning and deep learning, have made these data-rich modalities highly attractive as a means of extracting biological information non-destructively. Surgery in particular is poised to benefit from this, as spectrally-resolved tissue optical properties can offer enhanced contrast as well as diagnostic and guidance information during interventions. This is particularly relevant for procedures where inherent contrast is low under standard white light visualisation. This review summarises recent work in surgical spectral imaging (SSI) techniques, taken from Pubmed, Google Scholar and arXiv searches spanning the period 2013-2019. New hardware, optimised for use in both open and minimally-invasive surgery (MIS), is described, and recent commercial activity is summarised. Computational approaches to extract spectral information from conventional colour images are reviewed, as tip-mounted cameras become more commonplace in MIS. Model-based and machine learning methods of data analysis are discussed in addition to simulation, phantom and clinical validation experiments. A wide variety of surgical pilot studies are reported but it is apparent that further work is needed to quantify the clinical value of MSI/HSI. The current trend toward data-driven analysis emphasises the importance of widely-available, standardised spectral imaging datasets, which will aid understanding of variability across organs and patients, and drive clinical translation.

In silico and in vivo investigations using an endocavitary photoplethysmography sensor for tissue viability monitoring

SIGNIFICANCE

Colorectal cancer is one of the major causes of cancer-related deaths worldwide. Surgical removal of the cancerous growth is the primary treatment for this disease. A colorectal cancer surgery, however, is often unsuccessful due to the anastomotic failure that may occur following the surgical incision. Prevention of an anastomotic failure requires continuous monitoring of intestinal tissue viability during and after colorectal surgery. To date, no clinical technology exists for the dynamic and continuous monitoring of the intestinal perfusion.

AIM

A dual-wavelength indwelling bowel photoplethysmography (PPG) sensor for the continuous monitoring of intestinal viability was proposed and characterized through a set of in silico and in vivo investigations.

APPROACH

The in silico investigation was based on a Monte Carlo model that was executed to quantify the variables such as penetration depth and detected intensity with respect to the sensor-tissue separations and tissue perfusion. Utilizing the simulated information, an indwelling reflectance PPG sensor was designed and tested on 20 healthy volunteers. Two sets of in vivo studies were performed using the driving current intensities 20 and 40 mA for a comparative analysis, using buccal tissue as a proxy tissue-site.

RESULTS

Both simulated and experimental results showed the efficacy of the sensor to acquire good signals through the "contact" to a "noncontact" separation of 5 mm. A very slow wavelength-dependent variation was shown in the detected intensity at the normal and hypoxic states of the tissue, whereas a decay in the intensity was found with the increasing submucosal-blood volume. The simulated detected-to-incident-photon-ratio and the experimental signal-to-noise ratio exhibited strong positive correlations, with the Pearson product-moment correlation coefficient R ranging between 0.65 and 0.87.

CONCLUSIONS

The detailed feasibility analysis presented will lead to clinical trials utilizing the proposed sensor.

A Clinical Prototype Transrectal Diffuse Optical Tomography (TRDOT) System for In vivo Monitoring of Photothermal Therapy (PTT) of Focal Prostate Cancer

We describe the rationale, design, fabrication and performance of a clinical transrectal diffuse optical tomography (TRDOT) system for in vivo monitoring of photothermal therapy (PTT) of localized prostate cancer. The system comprises a 32-channel fiberoptic-based, MRI-compatible transrectal probe connected to a computer-controlled instrument that includes laser diode sources, an optical fiber switch and photomultiplier tube detectors. Performance tests were performed in tissue-simulating phantoms and in ex vivo muscle tissue during PTT treatment. The safety and technical feasibility of in vivo transrectal use were tested in a canine prostate model and in a first-in-human study in a patient before PTT treatment. Limitations of the system are discussed, as well as further developments to translate it into planned clinical trials for monitoring the photocoagulation boundary in the prostate during PTT.

A Multilayer Monte Carlo Model for the Investigation of Optical Path and Penetration Depth at Different Perfusion States of the Colon

There is a great interest in monitoring the oxygen supply delivered to the colon. Insufficient oxygen delivery may lead to hypoxia, sepsis, multiorgan dysfunction and death. For assessing colonic perfusion, more information and understanding is required relating to the light-interaction within the colonic tissue. A multilayer Monte Carlo model of a healthy human colon has been developed to investigate the light-tissue behavior during different perfusion states within the mucosal layer of the colon. Results from a static multilayer model of optical path and reflectance at two wavelengths, 660 nm and 880 nm, through colon tissue, containing different volume fractions of blood with a fixed oxygen saturation are presented. The effect on the optical path and penetration depth with varying blood volumes within the mucosa for each wavelength has been demonstrated. The simulation indicated both wavelengths of photons penetrated similar depths, entering the muscularis layer.

Quantitative Analysis of 4 × 4 Mueller Matrix Transformation Parameters for Biomedical Imaging

Mueller matrix polarimetry is a potentially powerful technique for obtaining microstructural information of biomedical specimens. Thus, it has found increasing application in both backscattering imaging of bulk tissue samples and transmission microscopic imaging of thin tissue slices. Recently, we proposed a technique to transform the 4 × 4 Mueller matrix elements into a group of parameters, which have explicit associations with specific microstructural features of samples. In this paper, we thoroughly analyze the relationships between the Mueller matrix transformation parameters and the characteristic microstructures of tissues by using experimental phantoms and Monte Carlo simulations based on different tissue mimicking models. We also adopt quantitative evaluation indicators to compare the Mueller matrix transformation parameters with the Mueller matrix polar decomposition parameters. The preliminary imaging results of bulk porcine colon tissues and thin human pathological tissue slices demonstrate the potential of Mueller matrix transformation parameters as biomedical diagnostic indicators. Also, this study provides quantitative criteria for parameter selection in biomedical Mueller matrix imaging.

Using spectral reflectance to distinguish between tracheal and oesophageal tissue: applications for airway management

Proper placement of the tracheal tube requires confirmation, and the predominant method in addition to clinical signs is the presence of end-tidal carbon dioxide. Such is the importance of confirmation that novel methods may also have a place. We previously demonstrated using ex-vivo swine tissue a unique spectral reflectance characteristic of tracheal tissue that differs from oesophageal tissue. We hypothesised that this characteristic would be present in living swine tissue and human cadavers. Reflectance spectra in the range 500-650 nm were captured using a customised fibreoptic probe, compact spectrometer and white light source from both the trachea and the oesophagus in anesthetised living swine and in human cadavers. A tracheal detection algorithm using ratio comparisons of reflectance was developed. The existence of the unique tracheal characteristic in both in-vivo swine and cadaver models was confirmed (p < 0.0001 for all comparisons between tracheal and oesophageal tissue at all target wavelengths in both species). Furthermore, our proposed tracheal detection algorithm exhibited a 100% positive predictive value in both models. This has potential utility for incorporation into airway management devices.

In-silico and in-vitro investigation of a photonic monitor for intestinal perfusion and oxygenation

The quantification of visceral organ oxygenation after trauma-related systemic hypovolemia and shock is critical to enable effective resuscitation. In this work, a photoplethysmography-based (PPG) sensor was specifically designed for probing the perfusion and oxygenation condition of intestinal tissue with the ultimate goal to monitor patients post trauma to guide resuscitation. Through Monte Carlo modeling, suitable optofluidic phantoms were determined, the wavelength and separation distance for the sensor was optimized, and sensor performance for the quantification of tissue perfusion and oxygenation was tested on the in-vitro phantom. In particular, the Monte Carlo simulated both a standard block three-layer model and a more realistic model including villi. Measurements were collected on the designed three layer optofluidic phantom and the results taken with the small form factor PPG device showed a marked improvement when using shorter visible wavelengths over the more conventional longer visible wavelengths. Overall, in this work a Monte Carlo model was developed, an optofluidic phantom was built, and a small form factor PPG sensor was developed and characterized using the phantom for perfusion and oxygenation over the visible wavelength range. The results show promise that this small form factor PPG sensor could be used as a future guide to shock-related resuscitation.

Shape-based reconstruction for transrectal diffuse optical tomography monitoring of photothermal focal therapy of prostate cancer: simulation studies

We develop and demonstrate a simple shape-based approach for diffuse optical tomographic reconstruction of coagulative lesions generated during interstitial photothermal therapy (PTT) of the prostate. The shape-based reconstruction assumes a simple ellipsoid shape, matching the general dimensions of a cylindrical diffusing fiber used for light delivery in current clinical studies of PTT in focal prostate cancer. The specific requirement is to accurately define the border between the photothermal lesion and native tissue as the photothermal lesion grows, with an accuracy of ? 1 ?? mm , so treatment can be terminated before there is damage to the rectal wall. To demonstrate the feasibility of the shape-based diffuse optical tomography reconstruction, simulated data were generated based on forward calculations in known geometries that include the prostate, rectum, and lesions of varying dimensions. The only source of optical contrast between the lesion and prostate was increased scattering in the lesion, as is typically observed with coagulation. With noise added to these forward calculations, lesion dimensions were reconstructed using the shape-based method. This approach for reconstruction is shown to be feasible and sufficiently accurate for lesions that are within 4 mm from the rectal wall. The method was also robust for irregularly shaped lesions.

Tissue classification for laparoscopic image understanding based on multispectral texture analysis

Intraoperative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study through statistical analysis, we show that (1) multispectral imaging data are superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) combining the tissue texture with the reflectance spectrum improves the classification performance. The classifier reaches an accuracy of 98.4% on our dataset. Multispectral tissue analysis could thus evolve as a key enabling technique in computer-assisted laparoscopy.

Anti-confocal assessment of middle ear inflammation

To improve the diagnostic prediction of recurrence of otitis media with effusion after surgery, an anti-confocal system combined with spectroscopic measurements is proposed to reject unwanted signals from the eardrum and assess the blood content. The anti-confocal system was experimentally evaluated on both optical middle ear phantom and human skin. Results showed effective rejection of signals from the eardrum using a central stop replacing the confocal pinhole, while still detecting signals from the middle ear mucosa. The system is sensitive to changes in blood content, but scattering and absorption characteristics of the eardrum can distort the measurement. Confocal detection of eardrum properties was shown to be a promising approach to correct measurements.

Robust near real-time estimation of physiological parameters from megapixel multispectral images with inverse Monte Carlo and random forest regression

PURPOSE

Multispectral imaging can provide reflectance measurements at multiple spectral bands for each image pixel. These measurements can be used for estimation of important physiological parameters, such as oxygenation, which can provide indicators for the success of surgical treatment or the presence of abnormal tissue. The goal of this work was to develop a method to estimate physiological parameters in an accurate and rapid manner suited for modern high-resolution laparoscopic images.

METHODS

While previous methods for oxygenation estimation are based on either simple linear methods or complex model-based approaches exclusively suited for off-line processing, we propose a new approach that combines the high accuracy of model-based approaches with the speed and robustness of modern machine learning methods. Our concept is based on training random forest regressors using reflectance spectra generated with Monte Carlo simulations.

RESULTS

According to extensive in silico and in vivo experiments, the method features higher accuracy and robustness than state-of-the-art online methods and is orders of magnitude faster than other nonlinear regression based methods.

CONCLUSION

Our current implementation allows for near real-time oxygenation estimation from megapixel multispectral images and is thus well suited for online tissue analysis.

Impact of vessel diameter and bandwidth of illumination in sidestream dark-field oximetry

We investigate the possibility of oxygen saturation estimation from images obtained by the sidestream dark-field (SDF) technique. The SDF technique is a method for microvascular imaging. In SDF imaging, light enters a tissue directly from illumination sources configured around a camera and then the camera captures the light scattered by the tissue. To advance the capability of the SDF imaging system, we develop a SDF oximetry method with LED illumination sources. In this paper, we evaluate some SDF oximetry methods from virtual SDF images obtained by the Monte Carlo photon propagation simulation. As a result, we verify that SDF imaging allows the estimation of oxygen saturation of the individual vessels from virtual images using the average extinction coefficients considering the bandwidth of the illumination and the effect of the integration of the camera.

Ex vivo characterization of normal and adenocarcinoma colon samples by Mueller matrix polarimetry

Mueller matrix polarimetry along with polar decomposition algorithm was employed for the characterization of ex vivo normal and adenocarcinoma human colon tissues by polarized light in the visible spectral range (425-725 nm). Six derived polarization metrics [total diattenuation (DT ), retardance (RT ), depolarization(ΔT ), linear diattenuation (DL), retardance (δ), and depolarization (ΔL)] were compared for normal and adenocarcinoma colon tissue samples. The results show that all six polarimetric properties for adenocarcinoma samples were significantly higher as compared to the normal samples for all wavelengths. The Wilcoxon rank sum test illustrated that total retardance is a good candidate for the discrimination of normal and adenocarcinoma colon samples. Support vector machine classification for normal and adenocarcinoma based on the four polarization properties spectra (ΔT , ΔL, RT ,and δ) yielded 100% accuracy, sensitivity, and specificity, while both DTa nd DL showed 66.6%, 33.3%, and 83.3% accuracy, sensitivity, and specificity, respectively. The combination of polarization analysis and given classification methods provides a framework to distinguish the normal and cancerous tissues.

Trimodal color-fluorescence-polarization endoscopy aided by a tumor selective molecular probe accurately detects flat lesions in colitis-associated cancer

Colitis-associated cancer (CAC) arises from premalignant flat lesions of the colon, which are difficult to detect with current endoscopic screening approaches. We have developed a complementary fluorescence and polarization reporting strategy that combines the unique biochemical and physical properties of dysplasia and cancer for real-time detection of these lesions. Using azoxymethane-dextran sodium sulfate (AOM-DSS) treated mice, which recapitulates human CAC and dysplasia, we show that an octapeptide labeled with a near-infrared (NIR) fluorescent dye selectively identified all precancerous and cancerous lesions. A new thermoresponsive sol-gel formulation allowed topical application of the molecular probe during endoscopy. This method yielded high contrast-to-noise ratios (CNR) between adenomatous tumors (20.6 ± 1.65) and flat lesions (12.1 ± 1.03) and surrounding uninvolved colon tissue versus CNR of inflamed tissues (1.62±0.42) Incorporation of nanowire-filtered polarization imaging into NIR fluorescence endoscopy shows a high depolarization contrast in both adenomatous tumors and flat lesions in CAC, reflecting compromised structural integrity of these tissues. Together, the real-time polarization imaging provides real-time validation of suspicious colon tissue highlighted by molecular fluorescence endoscopy.

Oblique incidence reflectometry: optical models and measurements using a side-viewing gradient index lens-based endoscopic imaging system

A side-viewing, 2.3-mm diameter oblique incidence reflectometry endoscope has been designed to obtain optical property measurements of turbid samples. Light from a single-mode fiber is relayed obliquely onto the tissue with a gradient index lens-based distal optics assembly and the resulting diffuse reflectance profile is imaged and collected with a 30,000 element, 0.72 mm clear aperture fiber bundle. Sampling the diffuse reflectance in two-dimensions allows for fitting of the reflected intensity profile to a well-known theoretical model, permitting the extraction of both absorption and reduced scattering coefficients of the tissue sample. Models and measurements of the endoscopic imaging system are presented in tissue phantoms and in vivo mouse colon, verifying the endoscope's capabilities to accurately measure effective attenuation coefficient and differentiate diseased from normal colon.

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.

Characterization of the anisotropic mechanical behaviour of colonic tissues: experimental activity and constitutive formulation

The aim was to investigate the biomechanical behaviour of colonic tissues by a coupled experimental and numerical approach. The wall of the colon is composed of different tissue layers. Within each layer, different fibre families are distributed according to specific spatial orientations, which lead to a strongly anisotropic configuration. Accounting for the complex histology of the tissues, mechanical tests must be planned and designed to evaluate the behaviour of the colonic wall in different directions. Uni-axial tensile tests were performed on tissue specimens from 15 fresh pig colons, accounting for six different loading directions (five specimens for each loading direction). The next step of the investigation was to define an appropriate constitutive framework and develop a procedure for identification of the constitutive parameters. A specific hyperelastic formulation was developed that accounted for the multilayered conformation of the colonic wall and the fibre-reinforced configuration of the tissues. The parameters were identified by inverse analyses of the mechanical tests. The comparison of model results with experimental data, together with the evaluation of satisfaction of material thermomechanics principles, confirmed the reliability of the analysis developed. This work forms the basis for more comprehensive activities that aim to provide computational tools for the interpretation of surgical procedures that involve the gastrointestinal tract, considering the specific biomedical devices adopted.

Mueller matrix polarimetry for differentiating characteristic features of cancerous tissues

Polarization measurements allow one to enhance the imaging contrast of superficial tissues and obtain new polarization sensitive parameters for better descriptions of the micro- and macro- structural and optical properties of complex tissues. Since the majority of cancers originate in the epithelial layer, probing the morphological and pathological changes in the superficial tissues using an expended parameter set with improved contrast will assist in early clinical detection of cancers. We carry out Mueller matrix imaging on different cancerous tissues to look for cancer specific features. Using proper scattering models and Monte Carlo simulations, we examine the relationship between the microstructures of the samples, which are represented by the parameters of the scattering model and the characteristic features of the Mueller matrix. This study gives new clues on the contrast mechanisms of polarization sensitive measurements for different cancers and may provide new diagnostic techniques for clinical applications.

Tissue discrimination by uncorrected autofluorescence spectra: a proof-of-principle study for tissue-specific laser surgery

Laser surgery provides a number of advantages over conventional surgery. However, it implies large risks for sensitive tissue structures due to its characteristic non-tissue-specific ablation. The present study investigates the discrimination of nine different ex vivo tissue types by using uncorrected (raw) autofluorescence spectra for the development of a remote feedback control system for tissue-selective laser surgery. Autofluorescence spectra (excitation wavelength 377 ± 50 nm) were measured from nine different ex vivo tissue types, obtained from 15 domestic pig cadavers. For data analysis, a wavelength range between 450 nm and 650 nm was investigated. Principal Component Analysis (PCA) and Quadratic Discriminant Analysis (QDA) were used to discriminate the tissue types. ROC analysis showed that PCA, followed by QDA, could differentiate all investigated tissue types with AUC results between 1.00 and 0.97. Sensitivity reached values between 93% and 100% and specificity values between 94% and 100%. This ex vivo study shows a high differentiation potential for physiological tissue types when performing autofluorescence spectroscopy followed by PCA and QDA. The uncorrected autofluorescence spectra are suitable for reliable tissue discrimination and have a high potential to meet the challenges necessary for an optical feedback system for tissue-specific laser surgery.

Analysis of the biomechanical behaviour of gastrointestinal regions adopting an experimental and computational approach

An integrated experimental and computational procedure is provided for the evaluation of the biomechanical behaviour that characterizes the pressure-volume response of gastrointestinal regions. The experimental activity pertains to inflation tests performed on specific gastrointestinal conduct segments. Different inflation processes are performed according to progressively increasing volumes. Each inflation test is performed by a rapid liquid in-flaw, up to a prescribed volume, which is held constant for about 300s to allow the development of relaxation processes. The different tests are interspersed by 600s of rest to allow the recovery of the specimen mechanical condition. A physio-mechanical model is developed to interpret both the elastic behaviour of the sample, as the pressure-volume trend during the rapid liquid in-flaw, and the time-dependent response, as the pressure drop during the relaxation processes. The minimization of discrepancy between experimental data and model results entails the identification of the parameters that characterize the viscoelastic model adopted for the definition of the behaviour of the gastrointestinal regions. The reliability of the procedure is assessed by the characterization of the response of samples from rat small intestine.

Light Sources for Single-Access Surgery

Background. Minimally invasive surgical techniques such as single access and natural orifice translumenal endoscopic surgery (NOTES) aim to reduce the number of external scars on the patient but impose restrictions on the space available for the light source within the endoscope and, therefore, the size of the field of view that can be sufficiently illuminated. Materials and Methods. This article presents and compares a number of illumination methods (xenon, light-emitting diodes, laser/phosphor, supercontinuum laser) that could be applied in single-access, robotic, and NOTES procedures. The luminance, spectral content, and intensity profile of each source was measured. Standardized images of each illuminating an abdominal simulator were assessed by a group of surgeons to provide an initial clinical impression. Results. The xenon source was found to have the highest luminance when used with a standard laparoscopic light cable, but this was significantly reduced when used with a small cable suitable for single-access applications. The supercontinuum laser–based light source had brightness comparable to the xenon, which was supported by the surgical test group observations. Conclusions. The supercontinuum fiber probe is a potential alternative to xenon light sources for use in single-access surgery with its comparable luminance, small diameter, flexibility, and even illumination. An initial in vivo test is described, providing a guide for future development.

Influence of phase function on modeled optical response of nanoparticle-labeled epithelial tissues

Metal nanoparticles can be functionalized with biomolecules to selectively localize in precancerous tissues and can act as optical contrast enhancers for reflectance-based diagnosis of epithelial precancer. We carry out Monte Carlo (MC) simulations to analyze photon propagation through nanoparticle-labeled tissues and to reveal the importance of using a proper form of phase function for modeling purposes. We first employ modified phase functions generated with a weighting scheme that accounts for the relative scattering strengths of unlabeled tissue and nanoparticles. To present a comparative analysis, we repeat our MC simulations with simplified functions that only approximate the angular scattering properties of labeled tissues. The results obtained for common optical sensor geometries and biologically relevant labeling schemes indicate that the exact form of the phase function used as model input plays an important role in determining the reflectance response and approximating functions often prove inadequate in predicting the extent of contrast enhancement due to labeling. Detected reflectance intensities computed with different phase functions can differ up to ∼60% and such a significant deviation may even alter the perceived contrast profile. These results need to be taken into account when developing photon propagation models to assess the diagnostic potential of nanoparticle-enhanced optical measurements.

Impact of model parameters on Monte Carlo simulations of backscattering Mueller matrix images of colon tissue

Polarimetric imaging is emerging as a viable technique for tumor detection and staging. As a preliminary step towards a thorough understanding of the observed contrasts, we present a set of numerical Monte Carlo simulations of the polarimetric response of multilayer structures representing colon samples in the backscattering geometry. In a first instance, a typical colon sample was modeled as one or two scattering "slabs" with monodisperse non absorbing scatterers representing the most superficial tissue layers (the mucosa and submucosa), above a totally depolarizing Lambertian lumping the contributions of the deeper layers (muscularis and pericolic tissue). The model parameters were the number of layers, their thicknesses and morphology, the sizes and concentrations of the scatterers, the optical index contrast between the scatterers and the surrounding medium, and the Lambertian albedo. With quite similar results for single and double layer structures, this model does not reproduce the experimentally observed stability of the relative magnitudes of the depolarizing powers for incident linear and circular polarizations. This issue was solved by considering bimodal populations including large and small scatterers in a single layer above the Lambertian, a result which shows the importance of taking into account the various types of scatterers (nuclei, collagen fibers and organelles) in the same model.

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.

Ex-vivo characterization of human colon cancer by Mueller polarimetric imaging

Cancerous and healthy human colon samples have been analyzed ex-vivo using a multispectral imaging Mueller polarimeter operated in the visible (from 500 to 700 nm) in a backscattering configuration with diffuse light illumination. Three samples of Liberkühn colon adenocarcinomas have been studied: common, mucinous and treated by radiochemotherapy. For each sample, several specific zones have been chosen, based on their visual staging and polarimetric responses, which have been correlated to the histology of the corresponding cuts. The most relevant polarimetric images are those quantifying the depolarization for incident linearly polarized light. The measured depolarization depends on several factors, namely the presence or absence of tumor, its exophytic (budding) or endophytic (penetrating) nature, its thickness (its degree of ulceration) and its level of penetration in deeper layers (submucosa, muscularis externa and serosa). The cellular density, the concentration of stroma, the presence or absence of mucus and the light penetration depth, which increases with wavelength, are also relevant parameters. Our data indicate that the tissues with the lowest and highest depolarizing powers are respectively mucus-free tumoral tissue with high cellular density and healthy serosa, while healthy submucosa, muscularis externa as well as mucinous tumor probably feature intermediate values. Moreover, the specimen coming from a patient treated successfully with radiochemotherapy exhibited a uniform polarimetric response typical of healthy tissue even in the initially pathological zone. These results demonstrate that multi-spectral Mueller imaging can provide useful contrasts to quickly stage human colon cancer ex-vivo and to distinguish between different histological variants of tumor.

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.

Sensitivity of spatially resolved reflectance signals to coincident variations in tissue optical properties

Canonical correlation analysis, a multivariate statistical technique, was used to investigate the degree of association between tissue optical properties and spatially resolved reflectance signals. Monte Carlo modeling was employed to simulate signals corresponding to different combinations of optical properties and these data sets were fed as input to statistical analysis. The results show that it is possible to adjust the separation and angular orientation of source and detector fibers such that the effect of a particular optical property will be augmented among coincident variations in other properties. The trends observed exhibit differences when compared with a conventional univariate sensitivity analysis in which only a single property is varied whereas all other parameters of interest are kept constant.

Mueller matrix imaging of human colon tissue for cancer diagnostics: how Monte Carlo modeling can help in the interpretation of experimental data

Colon samples with both healthy and cancerous regions have been imaged in diffuse light and backscattering geometry by using a Mueller imaging polarimeter. The tumoral parts at the early stage of cancer are found to be less depolarizing than the healthy ones. This trend clearly shows that polarimetric imaging may provide useful contrasts for optical biopsy. Moreover, both types of tissues are less depolarizing when the incident polarization is linear rather than circular. However, to really optimize an optical biopsy technique based on polarimetric imaging a realistic model is needed for polarized light scattering by tissues. Our approach to this goal is based on numerical Monte-Carlo simulations of polarized light propagation in biological tissues modeled as suspensions of monodisperse spherical scatterers representing the cell nuclei. The numerical simulations were validated by comparison with measurements on aqueous polystyrene sphere suspensions, which are commonly used as tissue phantoms. Such systems exhibit lower depolarization for incident linear polarization in the Rayleigh scattering regime, i.e. when the sphere diameters are smaller than the wavelength, which is obviously not the case for cell nuclei. In contrast, our results show that this behaviour can also be seen for "large" scatterers provided the optical index contrast between the spheres and the surrounding medium is small enough, as it is likely to be the case in biological tissues.

Monte carlo model of stricture formation in photodynamic therapy of normal pig esophagus

Photodynamic therapy (PDT) is FDA-approved for use in patients with Barrett's esophagus using porfimer sodium (2 mg per kg) and a recommended light dose of 130 J cm(-1) for high grade dysplasia. Despite uniform drug and light doses, the clinical outcome of PDT is variable. A significant number of PDT cases result in esophageal strictures, a side effect related to excessive energy absorption. The purpose of this project was to model esophageal stricture formation with a Monte Carlo simulation. An original multilayer Monte Carlo computer simulation was developed for esophageal PDT. Optical absorption and scattering coefficients were derived for mucosal and muscle layers of normal porcine esophagus. Porfimer sodium was added to each layer by increasing the absorption coefficient by the appropriate amount. A threshold-absorbed light dose was assumed to be required for stricture formation and ablation. The simulation predicted irreversible damage to the mucosa with a 160 J cm(-1) light dose and damage to the muscle layer with an additional 160 J cm(-1) light dose for a tissue porfimer sodium content of 3.5 mg kg(-1). The simulation accurately modeled photodynamic stricture formation in normal pig in vivo esophageal tissue. This preliminary work suggests that the absorbed light threshold for stricture formation may be between 2 and 4 J per gram of tissue.

A multimodal spectroscopy system for real-time disease diagnosis

The combination of reflectance, fluorescence, and Raman spectroscopy-termed multimodal spectroscopy (MMS)-provides complementary and depth-sensitive information about tissue composition. As such, MMS is a promising tool for disease diagnosis, particularly in atherosclerosis and breast cancer. We have developed an integrated MMS instrument and optical fiber spectral probe for simultaneous collection of all three modalities in a clinical setting. The MMS instrument multiplexes three excitation sources, a xenon flash lamp (370-740 nm), a nitrogen laser (337 nm), and a diode laser (830 nm), through the MMS probe to excite tissue and collect the spectra. The spectra are recorded on two spectrograph/charge-coupled device modules, one optimized for visible wavelengths (reflectance and fluorescence) and the other for the near-infrared (Raman), and processed to provide diagnostic parameters. We also describe the design and calibration of a unitary MMS optical fiber probe 2 mm in outer diameter, containing a single appropriately filtered excitation fiber and a ring of 15 collection fibers, with separate groups of appropriately filtered fibers for efficiently collecting reflectance, fluorescence, and Raman spectra from the same tissue location. A probe with this excitation/collection geometry has not been used previously to collect reflectance and fluorescence spectra, and thus physical tissue models ("phantoms") are used to characterize the probe's spectroscopic response. This calibration provides probe-specific modeling parameters that enable accurate extraction of spectral parameters. This clinical MMS system has been used recently to analyze artery and breast tissue in vivo and ex vivo.

Fluorescence spectroscopy of oral tissue: Monte Carlo modeling with site-specific tissue properties

A Monte Carlo model with site-specific input is used to predict depth-resolved fluorescence spectra from individual normal, inflammatory, and neoplastic oral sites. Our goal in developing this model is to provide a computational tool to study how the morphological characteristics of the tissue affect clinically measured spectra. Tissue samples from the measured sites are imaged using fluorescence confocal microscopy; autofluorescence patterns are measured as a function of depth and tissue sublayer for each individual site. These fluorescence distributions are used as input to the Monte Carlo model to generate predictions of fluorescence spectra, which are compared to clinically measured spectra on a site-by-site basis. A lower fluorescence intensity and longer peak emission wavelength observed in clinical spectra from dysplastic and cancerous sites are found to be associated with a decrease in measured fluorescence originating from the stroma or deeper fibrous regions, and an increase in the measured fraction of photons originating from the epithelium or superficial tissue layers. The simulation approach described here can be used to suggest an optical probe design that samples fluorescence at a depth that gives optimal separation in the spectral signal measured for benign, dysplastic, and cancerous oral mucosa.

Model-based spectroscopic analysis of the oral cavity: impact of anatomy

In order to evaluate the impact of anatomy on the spectral properties of oral tissue, we used reflectance and fluorescence spectroscopy to characterize nine different anatomic sites. All spectra were collected in vivo from healthy oral mucosa. We analyzed 710 spectra collected from the oral cavity of 79 healthy volunteers. From the spectra, we extracted spectral parameters related to the morphological and biochemical properties of the tissue. The parameter distributions for the nine sites were compared, and we also related the parameters to the physical properties of the tissue site. k-Means cluster analysis was performed to identify sites or groups of sites that showed similar or distinct spectral properties. For the majority of the spectral parameters, certain sites or groups of sites exhibited distinct parameter distributions. Sites that are normally keratinized, most notably the hard palate and gingiva, were distinct from nonkeratinized sites for a number of parameters and frequently clustered together. The considerable degree of spectral contrast (differences in the spectral properties) between anatomic sites was also demonstrated by successfully discriminating between several pairs of sites using only two spectral parameters. We tested whether the 95% confidence interval for the distribution for each parameter, extracted from a subset of the tissue data could correctly characterize a second set of validation data. Excellent classification accuracy was demonstrated. Our results reveal that intrinsic differences in the anatomy of the oral cavity produce significant spectral contrasts between various sites, as reflected in the extracted spectral parameters. This work provides an important foundation for guiding the development of spectroscopic-based diagnostic algorithms for oral cancer.

Monte Carlo model to describe depth selective fluorescence spectra of epithelial tissue: applications for diagnosis of oral precancer

We present a Monte Carlo model to predict fluorescence spectra of the oral mucosa obtained with a depth-selective fiber optic probe as a function of tissue optical properties. A model sensitivity analysis determines how variations in optical parameters associated with neoplastic development influence the intensity and shape of spectra, and elucidates the biological basis for differences in spectra from normal and premalignant oral sites. Predictions indicate that spectra of oral mucosa collected with a depth-selective probe are affected by variations in epithelial optical properties, and to a lesser extent, by changes in superficial stromal parameters, but not by changes in the optical properties of deeper stroma. The depth selective probe offers enhanced detection of epithelial fluorescence, with 90% of the detected signal originating from the epithelium and superficial stroma. Predicted depth-selective spectra are in good agreement with measured average spectra from normal and dysplastic oral sites. Changes in parameters associated with dysplastic progression lead to a decreased fluorescence intensity and a shift of the spectra to longer emission wavelengths. Decreased fluorescence is due to a drop in detected stromal photons, whereas the shift of spectral shape is attributed to an increased fraction of detected photons arising in the epithelium.

Combined Monte Carlo and finite-difference time-domain modeling for biophotonic analysis: implications on reflectance-based diagnosis of epithelial precancer

Monte Carlo (MC) modeling of photon transport in tissues is generally performed using simplified functions that only approximate the angular scattering properties of tissue constituents. However, such approximations may not be sufficient for fully characterizing tissue scatterers such as cells. Finite-difference time-domain (FDTD) modeling provides a flexible approach to compute realistic tissue phase functions that describe probability of scattering at different angles. We describe a computational framework that combines MC and FDTD modeling, and allows random sampling of scattering directions from FDTD phase functions. We carry out simulations to assess the influence of incorporating realistic FDTD phase functions on modeling spectroscopic reflectance signals obtained from normal and precancerous epithelial tissues. Simulations employ various fiber optic probe designs to analyze the sensitivity of different probe geometries to FDTD-generated phase functions. Combined MC/FDTD modeling results indicate that the form of the phase function used is an important factor in determining the reflectance profile of tissues, and detected reflectance intensity can change up to approximately 30% when a realistic FDTD phase function is used instead of an approximating function. The results presented need to be taken into account when developing photon propagation models or implementing inverse algorithms to extract optical properties from measurements.

Thermal coagulation-induced changes of the optical properties of normal and adenomatous human colon tissues in vitro in the spectral range 400-1,100 nm

The absorption coefficients, the reduced scattering coefficients and the optical penetration depths for native and coagulated human normal and adenomatous colon tissues in vitro were determined over the range of 400-1,100 nm using a spectrophotometer with an internal integrating sphere system, and the inverse adding-doubling method was applied to calculate the tissue optical properties from diffuse reflectance and total transmittance measurements. The experimental results showed that in the range of 400-1,100 nm there were larger absorption coefficients (P < 0.01) and smaller reduced scattering coefficients (P < 0.01) for adenomatous colon tissues than for normal colon tissues, and there were smaller optical penetration depths for adenomatous colon tissues than for normal colon tissues, especially in the near-infrared wavelength. Thermal coagulation induced significant increase of the absorption coefficients and reduced scattering coefficients for the normal and adenomatous colon tissues, and significantly reduced decrease of the optical penetration depths for the normal and adenomatous colon tissues. The smaller optical penetration depth for coagulated adenomatous colon tissues is a disadvantage for laser-induced thermotherapy (LITT) and photodynamic therapy (PDT). It is necessary to adjust the application parameters of lasers to achieve optimal therapy.

Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements

We present Monte Carlo modeling studies to provide a quantitative understanding of contrast observed in spatially resolved reflectance spectra of normal and highly dysplastic cervical tissue. Simulations have been carried out to analyze the sensitivity of spectral measurements to a range of changes in epithelial and stromal optical properties that are reported to occur as dysplasia develops and to predict reflectance spectra of normal and highly dysplastic tissue at six different source-detector separations. Simulation results provide important insights into specific contributions of different optical parameters to the overall spectral response. Predictions from simulations agree well with in vivo measurements from cervical tissue and successfully describe spectral differences observed in reflectance measurements from normal and precancerous tissue sites. Penetration depth statistics of photons detected at the six source-detector separations are also presented to reveal the sampling depth profile of the fiber-optic probe geometry simulated. The modeling studies presented provide a framework to meaningfully interpret optical signals obtained from epithelial tissues and to optimize design of optical sensors for in vivo reflectance measurements for precancer detection. Results from this study can facilitate development of analytical photon propagation models that enable inverse estimation of diagnostically relevant optical parameters from in vivo reflectance measurements.

Time-resolved photon migration in bi-layered tissue models

In this article, we describe a novel Monte Carlo code for time-integrated and time-resolved photon migration simulations of excitation and fluorescent light propagation (with reabsorption) in bi-layered models of biological tissues. The code was experimentally validated using bi-layered, tissue-simulating phantoms and the agreement between simulations and experiment was better than 3%. We demonstrate the utility of the code for quantitative clinical optical diagnostics in epithelial tissues by examining design characteristics for clinically compatible waveguides with arbitrarily complex source-detector configurations. Results for human colonic tissues included a quantitative comparison of simulation predictions with time-resolved fluorescence data measured in vivo and spatio-temporal visualizations of photon migration characteristics in tissue models in both two- and three-dimensions for source-detector configurations, including variable waveguide spacing, numerical aperture, and diameter. These results were then extended from surface point spectroscopy to imaging modalities for both time-gated (fluorescence lifetime) and steady-state (fluorescence intensity) experimental conditions. To illustrate the flexibility of this computational approach, time-domain results were extended to simulate predictions for frequency-domain instrumentation. This work is the first demonstration and validation of a time-domain, multi-wavelength photon transport model with these capabilities in layered turbid-media.