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

Quantitative prediction of AFB1 in various types of edible oil based on absorption, scattering and fluorescence signals at dual wavelengths

This study aims to address the challenge of matrix interference of various types of edible oils on intrinsic fluorescence of aflatoxin B1 (AFB1) by developing a novel solution. Considering the fluorescence internal filtering effect, the absorption (μa) and reduced scattering (μ's) coefficients at dual wavelengths (excitation: 375 nm, emission: 450 nm) were obtained by using integrating sphere technique, and were used to improve the quantitative prediction results for AFB1 contents in six different kinds of edible oils. A research process of "Monte Carlo (MC) simulation - phantom verification - actual sample validation" was conducted. The MC simulation was used to determine interference rule and correction parameters for fluorescence, the results indicated that the escaped fluorescence flux nonlinearly decreased with the μa, μ's at emission wavelength (μa,em, μ's,em) and μa at excitation wavelength (μa,ex), however increased with the μ's at excitation wavelength (μ's,ex). And the required optical parameters to eliminate the interference of matrix on fluorescence intensity are: effective attenuation coefficients at excitation and emission wavelengths (μeff,ex, μeff,em) and μ's,ex. Phantom verification was conducted to explore the feasibility of fluorescence correction based on the identified parameters by MC simulation, and determine the optimal machine learning method. The modelling results showed that least squares support vector regression (LSSVR) model could reach the best performance. Three kinds of edible oil (peanut, rapeseed, corn), each with two brands were used to prepare oil samples with different AFB1 contamination. The LSSVR model for AFB1 based on μeff,ex, μeff,em, μ's,ex and fluorescence intensity at 450 nm was calibrated, both correlation coefficients for calibration (Rc) and the validation (Rv) sets could reach 1.000, root mean square errors for calibration (RMSEC) and the validation (RMSEV) sets were as low as 0.038 and 0.099 respectively. This study proposed a novel method which is based solely on the absorption, scattering, and fluorescence characteristics at excitation and emission wavelengths to achieve accurate prediction of AFB1 content in different types of vegetable oils.

Noninvasive Digital Method for Determining Inflammation after Dental Implantation

This study shows that the luminescent diagnostic of oral fluid allows the determination of the severity of inflammatory markers after implantation. The noninvasive diagnostic method, which is used, allows the rapid detection of the stages of development of the inflammatory process after intraosseous implantation and prevents the development of complications in the postoperative period.

Model-based characterization platform of fiber optic extended-wavelength diffuse reflectance spectroscopy for identification of neurovascular bundles

SIGNIFICANCE

Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements.

AIM

The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications.

APPROACH

A model-based platform consisting of an ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses.

RESULTS

EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus.

CONCLUSIONS

Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications.

Simulations of fluorescence imaging in the oral cavity

We describe an end-to-end image systems simulation that models a device capable of measuring fluorescence in the oral cavity. Our software includes a 3D model of the oral cavity and excitation-emission matrices of endogenous fluorophores that predict the spectral radiance of oral mucosal tissue. The predicted radiance is transformed by a model of the optics and image sensor to generate expected sensor image values. We compare simulated and real camera data from tongues in healthy individuals and show that the camera sensor chromaticity values can be used to quantify the fluorescence from porphyrins relative to the bulk fluorescence from multiple fluorophores (elastin, NADH, FAD, and collagen). Validation of the simulations supports the use of soft-prototyping in guiding system design for fluorescence imaging.

Development of an integrated multimodal optical imaging system with real-time image analysis for the evaluation of oral premalignant lesions

Oral premalignant lesions (OPLs), such as leukoplakia, are at risk of malignant transformation to oral cancer. Clinicians can elect to biopsy OPLs and assess them for dysplasia, a marker of increased risk. However, it is challenging to decide which OPLs need a biopsy and to select a biopsy site. We developed a multimodal optical imaging system (MMIS) that fully integrates the acquisition, display, and analysis of macroscopic white-light (WL), autofluorescence (AF), and high-resolution microendoscopy (HRME) images to noninvasively evaluate OPLs. WL and AF images identify suspicious regions with high sensitivity, which are explored at higher resolution with the HRME to improve specificity. Key features include a heat map that delineates suspicious regions according to AF images, and real-time image analysis algorithms that predict pathologic diagnosis at imaged sites. Representative examples from ongoing studies of the MMIS demonstrate its ability to identify high-grade dysplasia in OPLs that are not clinically suspicious, and to avoid unnecessary biopsies of benign OPLs that are clinically suspicious. The MMIS successfully integrates optical imaging approaches (WL, AF, and HRME) at multiple scales for the noninvasive evaluation of OPLs.

A Kalman Filtering and Nonlinear Penalty Regression Approach for Noninvasive Anemia Detection with Palpebral Conjunctiva Images

Noninvasive medical procedures are usually preferable to their invasive counterparts in the medical community. Anemia examining through the palpebral conjunctiva is a convenient noninvasive procedure. The procedure can be automated to reduce the medical cost. We propose an anemia examining approach by using a Kalman filter (KF) and a regression method. The traditional KF is often used in time-dependent applications. Here, we modified the traditional KF for the time-independent data in medical applications. We simply compute the mean value of the red component of the palpebral conjunctiva image as our recognition feature and use a penalty regression algorithm to find a nonlinear curve that best fits the data of feature values and the corresponding levels of hemoglobin (Hb) concentration. To evaluate the proposed approach and several relevant approaches, we propose a risk evaluation scheme, where the entire Hb spectrum is divided into high-risk, low-risk, and doubtful intervals for anemia. The doubtful interval contains the Hb threshold, say 11 g/dL, separating anemia and nonanemia. A suspect sample is the sample falling in the doubtful interval. For the anemia screening purpose, we would like to have as less suspect samples as possible. The experimental results show that the modified KF reduces the number of suspect samples significantly for all the approaches considered here.

Spectroscopic characterization of oral epithelial dysplasia and squamous cell carcinoma using multiphoton autofluorescence micro-spectroscopy

OBJECTIVE

Multiphoton autofluorescence microscopy (MPAM) has shown potential in identifying features that are directly related to tissue microstructural and biochemical changes throughout epithelial neoplasia. In this study, we evaluate the autofluorescence spectral characteristics of neoplastic epithelium in dysplasia and oral squamous cell carcinoma (OSCC) using multiphoton autofluorescence spectroscopy (MPAS) in an in vivo hamster model of oral neoplasia in order to identify unique signatures that could be used to delineate normal oral mucosa from neoplasia.

MATERIALS/METHODS

A 9,10-dimethyl-1,2-benzanthracene (DMBA) hamster model of oral precancer and OSCC was used for in vivo MPAM and MPAS. Multiphoton Imaging and spectroscopy were performed with 780 nm excitation while a bandpass emission 450-650 nm was used for MPAM. Autofluorescence spectra was collected in the spectral window of 400-650 nm.

RESULTS

MPAS with fluorescence excitation at 780 nm revealed an overall red shift of a primary blue-green peak (480-520 nm) that is attributed to NADH and FAD. In the case of oral squamous cell carcinoma (OSCC) and some high-grade dysplasia an additional prominent peak at 635 nm, attributed to PpIX was observed. The fluorescence intensity at 635 nm and an intensity ratio of the primary blue-green peak versus 635 nm peak, showed statistically significant difference between control and neoplastic tissue.

DISCUSSION

Neoplastic transformation in the epithelium is known to alter the intracellular homeostasis of important tissue metabolites such as NADH, FAD, and PpIX, which was observed by MPAS in their native environment. A combination of deep tissue microscopy owing to higher penetration depth of multiphoton excitation and depth resolved spectroscopy could prove to be invaluable in identification of cytologic as well as biomolecular spectral characteristic of oral epithelial neoplasia. Lasers Surg. Med. 49:866-873, 2017. © 2017 Wiley Periodicals, Inc.

Automated algorithm for actinic cheilitis diagnosis by wide-field fluorescence imaging

Actinic cheilitis (AC) is a disease caused by prolonged and cumulative sun exposure that mostly affects the lower lip, which can progress to a lip squamous cell carcinoma. Routine diagnosis relies on clinician experience and training. We investigated the diagnostic efficacy of wide-field fluorescence imaging coupled to an automated algorithm for AC recognition. Fluorescence images were acquired from 57 patients with confirmed AC and 46 normal volunteers. Three different algorithms were employed: two based on the emission characteristics of local heterogeneity, entropy and intensity range, and one based on the number of objects after K-mean clustering. A classification model was obtained using a fivefold cross correlation algorithm. Sensitivity and specificity rates were 86% and 89.1%, respectively.

Examining palpebral conjunctiva for anemia assessment with image processing methods

Examining the hemoglobin level of blood is an important way to achieve the diagnosis of anemia, but it requires blood drawing and blood test. Examining the color distribution of palpebral conjunctiva is a standard procedure of anemia diagnosis, which requires no blood test. However, since color perception is not always consistent among different people, we attempt to imitate the way of physical examination of palpebral conjunctiva to detect anemia, so that computers can identify anemia patients automatically in a consolidated manner for a screening process. In this paper we propose two algorithms for anemia diagnosis. The first algorithm is intended to be simple and fast, while the second one to be more sophisticated and robust, providing an option for different applications. The first algorithm consists of a simple two-stage classifier. In the first stage, we use a thresholding decision technique based on a feature called high hue rate (HHR) (extracted from the HSI color space). In the second stage, a feature called pixel value in the middle (PVM) (extracted from the RGB color space) is proposed, followed by the use of a minimum distance classifier based on Mahalanobis distance. In the second algorithm, we consider 18 possible features, including a newly added entropy feature, some improved features from the first algorithm, and 13 features proposed in a previous work. We use correlation and simple statistics to select 3 relatively independent features (entropy, binarization of HHR, and PVM of G component) for classification using a support vector machine or an artificial neural network. Finally, we evaluate the classification performance of the proposed algorithms in terms of sensitivity, specificity, and Kappa value. The experimental results show relatively good performance and prove the feasibility of our attempt, which may encourage more follow-up study in the future.

Time-resolved fluorescence spectroscopy for clinical diagnosis of actinic cheilitis

Actinic cheilitis is a potentially malignant disorder of the lips. Its first cause is believed to be UV sun radiation. The lesion is highly heterogeneous, making the choice of area to be biopsied difficult. This study exploits the capabilities of time-resolved fluorescence spectroscopy for the identification of the most representative area to be biopsied. A preliminary study was performed on fourteen patients. A classification algorithm was used on data acquired on nine different biopsies. The algorithm discriminated between absent, mild, and moderate dysplasia with a sensitivity of 92.9%, 90.0%, and 80.0%, respectively. The false positive rate for healthy tissue (specificity) was 88.8%.

Computational model of bladder tissue based on its measured optical properties

Urinary bladder diseases are a common problem throughout the world and often difficult to accurately diagnose. Furthermore, they pose a heavy financial burden on health services. Urinary bladder tissue from male pigs was spectrophotometrically measured and the resulting data used to calculate the absorption, transmission, and reflectance parameters, along with the derived coefficients of scattering and absorption. These were employed to create a "generic" computational bladder model based on optical properties, simulating the propagation of photons through the tissue at different wavelengths. Using the Monte-Carlo method and fluorescence spectra of UV and blue excited wavelength, diagnostically important biomarkers were modeled. Additionally, the multifunctional noninvasive diagnostics system "LAKK-M" was used to gather fluorescence data to further provide essential comparisons. The ultimate goal of the study was to successfully simulate the effects of varying excited radiation wavelengths on bladder tissue to determine the effectiveness of photonics diagnostic devices. With increased accuracy, this model could be used to reliably aid in differentiating healthy and pathological tissues within the bladder and potentially other hollow organs.

Mobile fiber-optic sensor for detection of oral and cervical cancer in the developing world

Oral and cervical cancers are a growing global health problem that disproportionately impacts women and men living in the developing world. The high death rate in developing countries is largely due to the fact that these countries do not have the appropriate medical infrastructure and resources to support the organized screening and diagnostic programs that are available in the developed world. Diffuse reflectance spectroscopy (DRS) with a fiber-optic probe can noninvasively quantify the optical properties of epithelial tissues and has shown the potential as a cost-effective, easy-to-use, and sensitive tool for diagnosis of early precancerous changes in the cervix and oral cavity. However, current fiber-optic DRS systems have not been designed to be robust and reliable for use in developing countries. They are subject to various sources of systematic or random errors, arising from the uncontrolled probe-tissue interface and lack of real-time calibration, use bulky and expensive optical components, and require extensive training. This chapter describes a portable DRS device that is specifically designed for detection of oral and cervical cancers in resource-poor settings. The device uses an innovative smart fiber-optic probe to eliminate operator bias, state-of-the-art photonics components to reduce size and power consumption, and automated software to reduce the need of operator training. The size and cost of the smart fiber-optic DRS system may be further reduced by incorporating a smartphone based spectrometer.

Autofluorescence spectroscopy and imaging: a tool for biomedical research and diagnosis

Native fluorescence, or autofluorescence (AF), consists in the emission of light in the UV-visible, near-IR spectral range when biological substrates are excited with light at suitable wavelength. This is a well-known phenomenon, and the strict relationship of many endogenous fluorophores with morphofunctional properties of the living systems, influencing their AF emission features, offers an extremely powerful resource for directly monitoring the biological substrate condition. Starting from the last century, the technological progresses in microscopy and spectrofluorometry were convoying attention of the scientific community to this phenomenon. In the future, the interest in the autofluorescence will certainly continue. Current instrumentation and analytical procedures will likely be overcome by the unceasing progress in new devices for AF detection and data interpretation, while a progress is expected in the search and characterization of endogenous fluorophores and their roles as intrinsic biomarkers.

Monte Carlo simulation of in vivo Raman spectral measurements of human skin with a multi-layered tissue optical model

Raman photon generation inside human skin and escaping to skin surface were modeled in an eight-layered skin optical model. Intrinsic Raman spectra of different skin layers were determined by microscopy measurements of excised skin tissue sections. Monte Carlo simulation was used to study the excitation light distribution and intrinsic Raman signal distortion caused by tissue reabsorption and scattering during in vivo measurements. The simulation results demonstrated how different skin layers contributed to the observed in vivo Raman spectrum. Using the strongest Raman peak at 1445 cm(-1) as an example, the simulation suggested that the integrated contributions of the stratum corneum layer is 1.3%, the epidermis layer 28%, the dermis layer 70%, and the subcutaneous fat layer 1.1%. Reasonably good matching between the calculated spectrum and the measured in vivo Raman spectra was achieved, thus demonstrated great utility of our modeling method and approaches for help understanding the clinical measurements.

Analysis of surgical margins in oral cancer using in situ fluorescence spectroscopy

Oral cancer is a public health problem with high prevalence in the population. Local tumor control is best achieved by complete surgical resection with adequate margins. A disease-free surgical margin correlates with a lower rate of local recurrence and a higher rate of disease-free survival. Fluorescence spectroscopy is a noninvasive diagnostic tool that can aid in real-time cancer detection. The technique, which evaluates the biochemical composition and structure of tissue fluorescence, is relatively simple, fast and, accurate.

OBJECTIVES

This study aimed to compare oral squamous cell carcinoma lesions to surgical margins and the mucosa of healthy volunteers by fluorescence spectroscopy.

MATERIALS AND METHODS

The sample consisted of 56 individuals, 28 with oral squamous cell carcinoma and 28 healthy volunteers with normal oral mucosa. Thirty six cases (64.3%) were male and the mean age was 60.9 years old. The spectra were classified and compared to histopathology to determine fluorescence efficiency for diagnostic discrimination of tumors.

RESULTS

In the analysis of the other cases we observed discrimination between normal mucosa, injury and margins. At two-year follow up, three individuals had local recurrence, and in two cases investigation fluorescence in the corresponding area showed qualitative differences in spectra between the recurrence area and the area without recurrence at the same anatomical site in the same patient.

CONCLUSION

In situ analysis of oral mucosa showed the potential of fluorescence spectroscopy as a diagnostic tool that can aid in discrimination of altered mucosa and normal mucosa.

Diffuse reflectance spectroscopy of epithelial tissue with a smart fiber-optic probe

Diffuse reflectance spectroscopy (DRS) with a fiber-optic probe can noninvasively quantify the optical properties of epithelial tissues and has shown the potential as a cost-effective, fast and sensitive tool for diagnosis of early precancerous changes in the cervix and oral cavity. However, current DRS systems are susceptible to several sources of systematic and random errors, such as uncontrolled probe-to-tissue pressure and lack of a real-time calibration that can significantly impair the measurement accuracy, reliability and validity of this technology as well as its clinical utility. In addition, such systems use bulky, high power and expensive optical components which impede their widespread use in low- and middle-income countries (LMICs) where epithelial cancer related death is disproportionately high. In this paper we report a portable, easy-to-use and low cost, yet accurate and reliable DRS device that can aid in the screening and diagnosis of oral and cervical cancer. The device uses an innovative smart fiber-optic probe to eliminate operator bias, state-of-the-art photonics components to reduce size and power consumption, and automated software to reduce the need of operator training. The device showed a mean error of 1.4 ± 0.5% and 6.8 ± 1.7% for extraction of phantom absorption and reduced scattering coefficients, respectively. A clinical study on healthy volunteers indicated that a pressure below 1.0 psi is desired for oral mucosal tissues to minimize the probe effects on tissue physiology and morphology.

Combined reflectance spectroscopy and stochastic modeling approach for noninvasive hemoglobin determination via palpebral conjunctiva

A combination of stochastic photon propagation model in a multilayered human eyelid tissue and reflectance spectroscopy was used to study palpebral conjunctiva spectral reflectance for hemoglobin (Hgb) determination. The developed model is the first biologically relevant model of eyelid tissue, which was shown to provide very good approximation to the measured spectra. Tissue optical parameters were defined using previous histological and microscopy studies of a human eyelid. After calibration of the model parameters the responses of reflectance spectra to Hgb level and blood oxygenation variations were calculated. The stimulated reflectance spectra in adults with normal and low Hgb levels agreed well with experimental data for Hgb concentrations from 8.1 to 16.7 g/dL. The extracted Hgb levels were compared with in vitro Hgb measurements. The root mean square error of cross-validation was 1.64 g/dL. The method was shown to provide 86% sensitivity estimates for clinically diagnosed anemia cases. A combination of the model with spectroscopy measurements provides a new tool for noninvasive study of human conjunctiva to aid in diagnosing blood disorders such as anemia.

Rapid determination of oxygen saturation and vascularity for cancer detection

A rapid heuristic ratiometric analysis for estimating tissue hemoglobin concentration and oxygen saturation from measured tissue diffuse reflectance spectra is presented. The analysis was validated in tissue-mimicking phantoms and applied to clinical measurements in head and neck, cervical and breast tissues. The analysis works in two steps. First, a linear equation that translates the ratio of the diffuse reflectance at 584 nm and 545 nm to estimate the tissue hemoglobin concentration using a Monte Carlo-based lookup table was developed. This equation is independent of tissue scattering and oxygen saturation. Second, the oxygen saturation was estimated using non-linear logistic equations that translate the ratio of the diffuse reflectance spectra at 539 nm to 545 nm into the tissue oxygen saturation. Correlations coefficients of 0.89 (0.86), 0.77 (0.71) and 0.69 (0.43) were obtained for the tissue hemoglobin concentration (oxygen saturation) values extracted using the full spectral Monte Carlo and the ratiometric analysis, for clinical measurements in head and neck, breast and cervical tissues, respectively. The ratiometric analysis was more than 4000 times faster than the inverse Monte Carlo analysis for estimating tissue hemoglobin concentration and oxygen saturation in simulated phantom experiments. In addition, the discriminatory power of the two analyses was similar. These results show the potential of such empirical tools to rapidly estimate tissue hemoglobin in real-time spectral imaging applications.

Advances in optical adjunctive AIDS for visualisation and detection of oral malignant and potentially malignant lesions

Traditional methods of screening for oral potentially malignant disorders and oral malignancies involve a conventional oral examination with digital palpation. Evidence indicates that conventional examination is a poor discriminator of oral mucosal lesions. A number of optical aids have been developed to assist the clinician to detect oral mucosal abnormalities and to differentiate benign lesions from sinister pathology. This paper discusses advances in optical technologies designed for the detection of oral mucosal abnormalities. The literature regarding such devices, VELscope and Identafi, is critically analysed, and the novel use of Narrow Band Imaging within the oral cavity is also discussed. Optical aids are effective in assisting with the detection of oral mucosal abnormalities; however, further research is required to evaluate the usefulness of these devices in differentiating benign lesions from potentially malignant and malignant lesions.

Endoscopic fluorescence lifetime imaging for in vivo intraoperative diagnosis of oral carcinoma

A clinically compatible fluorescence lifetime imaging microscopy (FLIM) system was developed. The system was applied to intraoperative in vivo imaging of head and neck squamous cell carcinoma (HNSCC). The endoscopic FLIM prototype integrates a gated (down to 0.2 ns) intensifier imaging system and a fiber-bundle endoscope (0.5-mm-diameter, 10,000 fibers with a gradient index lens objective 0.5 NA, 4-mm field of view), which provides intraoperative access to the surgical field. Tissue autofluorescence was induced by a pulsed laser (337 nm, 700 ps pulse width) and collected in the 460 ± 25 nm spectral band. FLIM experiments were conducted at 26 anatomic sites in ten patients during head and neck cancer surgery. HNSCC exhibited a weaker florescence intensity (~50% less) when compared with healthy tissue and a shorter average lifetime (τ(HNSCC) = 1.21 ± 0.04 ns) than the surrounding normal tissue (τN = 1.49 ± 0.06 ns). This work demonstrates the potential of FLIM for label-free head and neck tumor demarcation during intraoperative surgical procedures.

A novel approach for the detection of early gastric cancer: fluorescence spectroscopy of gastric juice

OBJECTIVE

This study aimed to investigate the efficacy of fluorescence spectroscopy of gastric juice for early gastric cancer (EGC) screening.

METHODS

Gastric juice was collected from 101 participants who underwent endoscopy in the Outpatient Endoscopy Center of Peking University Third Hospital. The participants were divided into three groups: the normal mucosa or chronic non-atrophic gastritis (NM-CNAG) group (n = 35), advanced gastric cancer (AGC) group (n = 33) and EGC group (n = 33). Fluorescence spectroscopic analysis was performed in all the gastric juice samples and the maximum fluorescence intensity of the first peak (P1 FI) was measured.

RESULTS

The mean fluorescence intensity of P1 FI of gastric juice in AGC (92.1 ± 10.7) and EGC (90.8 ± 12.0) groups was significantly higher than that in the NM-CNAG group (55.7 ± 7.5) (AGC vs NM-CNAG, P = 0.006 and EGC vs NM-CNAG, P = 0.015, respectively). The areas under the receiver operating characteristic curves for the detection of AGC and EGC were 0.681 (95% confidence interval [CI] 0.553-0.810, P = 0.010) and 0.655 (95% CI 0.522-0.787, P = 0.028). With the P1 FI of ≥47.7, the sensitivity, specificity and accuracy for detecting EGC were 69.7%, 57.1% and 63.2%, respectively.

CONCLUSIONS

The enhancement of P1 FI of gastric juice occurs at the early stage of gastric cancer. Fluorescence spectroscopy of gastric juice may be used as a novel screening tool for the early detection of gastric cancer.

Monte Carlo model of the penetration depth for polarization gating spectroscopy: influence of illumination-collection geometry and sample optical properties

Polarization-gating has been widely used to probe superficial tissue structures, but the penetration depth properties of this method have not been completely elucidated. This study employs a polarization-sensitive Monte Carlo method to characterize the penetration depth statistics of polarization-gating. The analysis demonstrates that the penetration depth depends on both the illumination-collection geometry [illumination-collection area (R) and collection angle (θ(c))] and on the optical properties of the sample, which include the scattering coefficient (μ(s)), absorption coefficient (μ(a)), anisotropy factor (g), and the type of the phase function. We develop a mathematical expression relating the average penetration depth to the illumination-collection beam properties and optical properties of the medium. Finally, we quantify the sensitivity of the average penetration depth to changes in optical properties for different geometries of illumination and collection. The penetration depth model derived in this study can be applied to optimizing application-specific fiber-optic probes to target a sampling depth of interest with minimal sensitivity to the optical properties of the sample.

Fluorescence lifetime techniques in medical applications

This article presents an overview of time-resolved (lifetime) fluorescence techniques used in biomedical diagnostics. In particular, we review the development of time-resolved fluorescence spectroscopy (TRFS) and fluorescence lifetime imaging (FLIM) instrumentation and associated methodologies which allow in vivo characterization and diagnosis of biological tissues. Emphasis is placed on the translational research potential of these techniques and on evaluating whether intrinsic fluorescence signals provide useful contrast for the diagnosis of human diseases including cancer (gastrointestinal tract, lung, head and neck, and brain), skin and eye diseases, and atherosclerotic cardiovascular disease.

Models of light propagation in human tissue applied to cancer diagnostics

Optical methods such as reflectance and fluorescence spectroscopy are being investigated for their potential to aid cancer detection in a quantitative, minimally invasive manner. Mathematical models of reflectance and fluorescence provide an important link between measured optical data and biomedically-relevant tissue parameters that can be extracted from these data to characterize the presence or absence of disease. The most commonly-used mathematical models in biomedical optics are the diffusion approximation (DA) to the radiative transfer equation, Monte Carlo (MC) computational models of light transport, and semi-empirical models. This paper presents a review of the applications of these models to reflectance and endogenous fluorescence sensing for cancer diagnostics in human tissues. Specific examples are given for cervical, breast, and pancreatic tissues. A comparison of the DA and MC methods in two biologically-relevant regimes of optical parameter space will also be discussed.

Three aromatic amino acids in gastric juice as potential biomarkers for gastric malignancies

For screening early-stage gastric malignancies, the existing serum biomarkers have limited sensitivity and specificity. Gastric juice biomarkers are scarce and require further investigation. We divided this study on searching potential biomarkers into four parts: (1) detection of differential fluorescence spectrum and peaks in the gastric juice from patients using fluorescence spectroscopy and HPLC, (2) identification and validation of differential peaks using LC/MS and NMR, (3) quantification of potential biomarkers, and (4) establishment of diagnostic detection. The fluorescence intensity (FI), tyrosine, phenylalanine, tryptophan and total protein content were significantly higher in the gastric juice of patients with gastric malignancies (all P<0.01). With all P<0.001, the areas under the receiver operating characteristic curves of the biomarkers were tyrosine, 0.838; phenylalanine, 0.856; and tryptophan, 0.816. At a specificity of 79.4%, the sensitivity for gastric malignancy detection with phenylalanine was 87.9% only. Aromatic amino acids in gastric juices could be used as potential diagnostic biomarkers to screen gastric malignancies. It is a less-invasive and economical method compared to gastric biopsy.

Instrument independent diffuse reflectance spectroscopy

Diffuse reflectance spectroscopy with a fiber optic probe is a powerful tool for quantitative tissue characterization and disease diagnosis. Significant systematic errors can arise in the measured reflectance spectra and thus in the derived tissue physiological and morphological parameters due to real-time instrument fluctuations. We demonstrate a novel fiber optic probe with real-time, self-calibration capability that can be used for UV-visible diffuse reflectance spectroscopy in biological tissue in clinical settings. The probe is tested in a number of synthetic liquid phantoms over a wide range of tissue optical properties for significant variations in source intensity fluctuations caused by instrument warm up and day-to-day drift. While the accuracy for extraction of absorber concentrations is comparable to that achieved with the traditional calibration (with a reflectance standard), the accuracy for extraction of reduced scattering coefficients is significantly improved with the self-calibration probe compared to traditional calibration. This technology could be used to achieve instrument-independent diffuse reflectance spectroscopy in vivo and obviate the need for instrument warm up and post∕premeasurement calibration, thus saving up to an hour of precious clinical time.

Prospective evaluation of a portable depth-sensitive optical spectroscopy device to identify oral neoplasia

A portable, depth-sensitive clinical spectroscopy device for noninvasive early diagnosis of oral cancer is described. We carried out a pilot study to evaluate the ability of the device to identify oral neoplasia using a previously developed diagnostic algorithm. A total of 79 oral sites in 33 subjects, including 28 patients with oral lesions and 5 healthy volunteers, were measured and analyzed. Measurements of 54 nonkeratinized oral sites yielded an area under the receiver operating characteristic curve of 0.90. Measurements of 25 keratinized oral sites yielded an area under the receiver operating characteristic curve of 0.83.

Advances in fluorescence imaging techniques to detect oral cancer and its precursors

Oral cancer is a significant health problem in the USA and throughout the world. Most oral cancer patients are diagnosed at a late stage, when treatment is less successful and treatment-associated morbidity is more severe. A number of new diagnostic aids to conventional oral examination have recently been introduced to assist in the early detection of oral neoplasia. In particular, autofluorescence imaging has emerged as a promising adjunctive technique to improve early identification of oral premalignant lesions. Direct visual inspection of tissue autofluorescence has shown encouraging results in high-prevalence populations, but the technique requires subjective interpretation and depends on the visual recognition skills of the examiner. Capturing and analyzing digital fluorescence images can reduce subjectivity and potentially improve sensitivity of detection of precancerous changes. Recent studies of wide-field autofluorescence imaging in low-prevalence populations suggest that benign lesions such as inflammation may give rise to false-positive results. High-resolution fluorescence imaging is a new modality that can be used in conjunction with wide-field imaging to improve specificity by imaging subcellular detail of neoplastic tissues. The combination of wide-field and high-resolution fluorescence imaging systems with automated image analysis should be investigated to maximize overall diagnostic performance for early detection of oral neoplasia.