Evaluation of wavelength ranges and tissue depth probed by diffuse reflectance spectroscopy for colorectal cancer detection

Raman spectroscopy for colorectal tumor margin assessment: A promising tool for real-time surgical delimitation

Raman spectroscopy is a promising non-invasive technique not only for the rapid and accurate detection of colorectal cancer (CRC) but also for the identification of positive surgical margins. In this study, micro-Raman spectroscopy was used to explore biochemical differences in surgically resected intestinal segments, with a focus on boundary tumor zone. Spectral and statistical analyses, including Partial least squares discriminant analysis (PLS-DA), were performed to identify significant molecular signatures and distinguish different tissue types. Our findings suggest that boundary tumor zone contain a mix of cancerous and normal cells, complicating the discrimination of these regions. Despite this challenge, we achieved a classification accuracy of 82 % for tumor margin differentiation from normal tissue along with identifying several biochemically significant spectroscopic differences. Rapid Raman measurements using a portable system, taken from resected tissues immediately after surgery, further demonstrated the technique's ability to differentiate cancerous from healthy tissues with 97 % accuracy, 98 % sensitivity, and 96 % specificity, underscoring the potential of Raman spectroscopy for real-time clinical applications in CRC surgery.

Sub-diffuse Reflectance Spectroscopy Combined With Machine Learning Method for Oral Mucosal Disease Identification

OBJECTIVES

Oral squamous cell carcinoma (OSCC) is the sixth-highest incidence of malignant tumors worldwide. However, early diagnosis is complex owing to the impracticality of biopsying every potentially premalignant intraoral lesion. Here, we present a sub-diffuse reflectance spectroscopy combined with a machine learning method for oral mucosal disease identification. This method provides a noninvasive cost-effective identification option for early signs of malignancy.

METHODS

Sub-diffuse spectra of three oral sites (hypoglottis, buccal, and gingiva) from healthy subjects and three types of mucosal lesions (oral lichen planus, OLP, oral leukoplakia, OLK, and OSCC) from patients were collected by using a home-made sub-diffuse reflectance spectroscopy prototype system, and three features including spectra ratio (SR), first-order derivative(DE) of the spectra and optical parameters (OP) were derived from the original spectra to enhance the insights into the optical properties of the oral mucosal tissues. To accurately classify the spectral features, a support vector machine (SVM) and probabilistic neural network (PNN) were employed.

RESULT

Most of the statistical distributions of the spectral features demonstrated obvious differences and the two classification methods exhibited comparable performances. For the classification in the oral sites of healthy subjects, the OP-based classification results were unsatisfactory, while the classification results utilizing DR, SR, and DE achieved a least accuracy of 0.8289, sensitivity of 0.8495, sensitivity of 0.9311, and Matthews correlation coefficient of 0.8085. Comparatively, the classification results between OLP, OLK, OSCC, and normal tissue obtained achieved high indexes even using the OP feature.

CONCLUSION

Integrating sub-diffuse reflectance spectroscopy measurement and suitable machine learning methods can obtain remarkable precision in differentiating different sites of oral mucosa and identifying different types of oral mucosal diseases, especially based on DE features. It is of great help in detecting OSCC and is expected to be a highly sensitive, time-sensitive, and accurate method for oral disease detection.

Study of Minor Chromophores in Biological Tissues by Diffuse Optical Spectroscopy (Review)

Diffuse optical spectroscopy (DOS) is a rapidly advancing non-invasive diagnostic technique to investigate biological tissue, based on probing the target object with optical radiation in the visible and/or near-infrared wavelength range and detecting the diffusely scattered light from the tissue. The signals obtained through DOS provide extensive information about the biochemical composition of tissues due to the presence of light-absorbing compounds known as chromophores. To date, DOS is widely employed to detect major chromophores such as deoxygenated (Hb) and oxygenated (HbO2) hemoglobin, water, lipids, and melanin. The concentrations of Hb and HbO2 in biological tissues are highly significant in clinical research, as they offer valuable insights into tissue oxygenation status and enable the detection of hypoxia. However, biological tissues also contain less-studied chromophores - minor chromophores - which also contribute to the overall absorption spectrum. These include various globins, such as methemoglobin, carboxyhemoglobin, and myoglobin, as well as cytochromes and cytochrome c oxidase. Identifying minor chromophores using DOS is challenging due to their relatively low absorption contributions compared to major chromophores, as well as the limited understanding of their specific absorption spectra. Nevertheless, the simultaneous detection of both major and minor chromophores could provide a comprehensive understanding of metabolic processes within vascular, intracellular, and mitochondrial compartments of tissues. This would substantially expand the potential applications of DOS in both research and clinical studies. In this review we examine literature sources that explore the investigation of minor chromophores in biological tissues by DOS, discuss the role of major chromophores, and evaluate the potential for simultaneous detection of both major and minor chromophores with DOS.

Evaluating Normalization Methods for Robust Spectral Performance Assessments of Hyperspectral Imaging Cameras

Hyperspectral imaging (HSI) technology, which offers both spatial and spectral information, holds significant potential for enhancing diagnostic performance during endoscopy and other medical procedures. However, quantitative evaluation of HSI cameras is challenging due to various influencing factors (e.g., light sources, working distance, and illumination angle) that can alter the reflectance spectra of the same target as these factors vary. Towards robust, universal test methods, we evaluated several data normalization methods aimed at minimizing the impact of these factors. Using a high-resolution HSI camera, we measured the reflectance spectra of diffuse reflectance targets illuminated by two different light sources. These spectra, along with the reference spectra from the target manufacturer, were normalized with nine different methods (e.g., area under the curve, standard normal variate, and centering power methods), followed by a uniform scaling step. We then compared the measured spectra to the reference to evaluate the capability of each normalization method in ensuring a consistent, standardized performance evaluation. Our results demonstrate that normalization can mitigate the impact of some factors during HSI camera evaluation, with performance varying across methods. Generally, noisy spectra pose challenges for normalization methods that rely on limited reflectance values, while methods based on reflectance values across the entire spectrum (such as standard normal variate) perform better. The findings also suggest that absolute reflectance spectral measurements may be less effective for clinical diagnostics, whereas normalized spectral measurements are likely more appropriate. These findings provide a foundation for standardized performance testing of HSI-based medical devices, promoting the adoption of high-quality HSI technology for critical applications such as early cancer detection.

Camera-on-tip endoscope for in vivo cardiovascular diagnostics and surgical guidance

Cardiovascular imaging with camera-on-tip endoscopes has the potential to provide physiologically relevant data on the tissue state and device placement that can improve clinical outcomes. In this work, we review the unmet clinical need for image-based in vivo cardiovascular diagnostics and guidance for minimally invasive procedures. We present a 7 Fr camera-on-tip endoscope with fibre-coupled multispectral illumination that includes methods for imaging in a blood-filled field of view (FOV). We demonstrate that the endoscope can be navigated from the femoral artery to cardiac regions such as the left atrium and left ventricle in a porcine model, where in vivo images of the cardiac walls are recorded. We further show that physiologically relevant parameters such as heart rate and respiration can be extracted from the images and that changes to tissue state can be inferred from the imaging data. Finally, a methodology for merging the imaging data with diffuse reflection spectroscopy (DRS) recorded through the optical fibre is outlined.

Effects of FOLFOX Chemotherapy on Tumor Oxygenation and Perfused Vasculature: An In Vivo Study by Optical Techniques

The effects of cytotoxic chemotherapy on tumor vasculature and oxygenation are in the focus of modern investigations because vascular structure and distribution of oxygen influence tumor behavior and treatment response. The aim of our study was to monitor changes in the vascular component of colorectal tumor xenografts induced by a clinical combination of chemotherapy drugs FOLFOX in vivo using two complementary techniques: diffuse reflectance spectroscopy (DRS) and optical coherence tomography–based microangiography (OCT‐MA). These techniques revealed a slower decrease in tumor blood oxygenation in treated tumors as compared to untreated ones, faster suppression of tumor vasculature perfusion and increase in water content as a result of treatment, and decrease in total hemoglobin in untreated tumors. Immunohistochemical analysis of hypoxia‐inducible factor HIF‐2α detected tissue hypoxia as a consequence of inappropriate oxygen supply in the treated tumors. The obtained results show the prospects for monitoring of treatment efficacy using DRS and OCT‐MA.

Towards a sensing model using a random laser combined with diffuse reflectance spectroscopy

The previous research proves that the random laser emission reflects not only the scattering properties but also the absorption properties. The random laser is therefore considered a potential tool for optical properties sensing. Although the qualitative sensing using the random laser is extensively investigated, a quantitative measurement of optical properties is still rare. In this study, a generalized mathematical quantitative model using random laser combined with diffuse reflectance spectroscopy is proposed for optical sensing in turbid media. This model describes the gain effect of the active medium and the optical properties effect of the passive medium separately. Rhodamine 6G is used as the active medium. Intralipid and ink are employed to demonstrate the effect of the scattering and absorption, respectively. The peak wavelength shift of the random laser is proved to be an ideal sensing parameter for this sensing model. It is also revealed that the scaling parameters in the sensing model are interrelated and can be simplified to one. With this combined model, the direct sensing of optical properties in diverse turbid media is promising.

Enhancing Intraoperative Tissue Identification: Investigating a Smart Electrosurgical Knife's Functionality During Electrosurgery

OBJECTIVE

Detecting the cancerous growth margin and achieving a negative margin is one of the challenges that surgeons face during cancer procedures. A smart electrosurgical knife with integrated optical fibers has been designed previously to enable real-time use of diffuse reflectance spectroscopy for intraoperative margin assessment. In this paper, the thermal effect of the electrosurgical knife on tissue sensing is investigated.

METHODS

Porcine tissues and phantoms were used to investigate the performance of the smart electrosurgical knife after electrosurgery. The fat-to-water content ratio (F/W-ratio) served as the discriminative parameter for distinguishing tissues and tissue mimicking phantoms with varying fat content. The F/W-ratio of tissues and phantoms was measured with the smart electrosurgical knife before and after 14 minutes of electrosurgery. Additionally, a layered porcine tissue and phantom were sliced and measured from top to bottom with the smart electrosurgical knife.

RESULTS

Mapping the thermal activity of the electrosurgical knife's electrode during animal tissue electrosurgery revealed temperatures exceeding 400 °C. Electrosurgery for 14 minutes had no impact on the device's accurate detection of the F/W-ratio. The smart electrosurgical knife enables real-time tissue detection and predicts the fat content of the next layer from 4 mm ahead.

CONCLUSION

The design of the smart electrosurgical knife outlined in this paper demonstrates its potential utility for tissue detection during electrosurgery.

SIGNIFICANCE

In the future, the smart electrosurgical knife could be a valuable intraoperative margin assessment tool, aiding surgeons in detecting tumor borders and achieving negative margins.

Label-Free Optical Technologies to Enhance Noninvasive Endoscopic Imaging of Early-Stage Cancers

White light endoscopic imaging allows for the examination of internal human organs and is essential in the detection and treatment of early-stage cancers. To facilitate diagnosis of precancerous changes and early-stage cancers, label-free optical technologies that provide enhanced malignancy-specific contrast and depth information have been extensively researched. The rapid development of technology in the past two decades has enabled integration of these optical technologies into clinical endoscopy. In recent years, the significant advantages of using these adjunct optical devices have been shown, suggesting readiness for clinical translation. In this review, we provide an overview of the working principles and miniaturization considerations and summarize the clinical and preclinical demonstrations of several such techniques for early-stage cancer detection. We also offer an outlook for the integration of multiple technologies and the use of computer-aided diagnosis in clinical endoscopy.

Dual excitation spectral autofluorescence lifetime and reflectance imaging for fast macroscopic characterization of tissues

Advancements in optical imaging techniques have revolutionized the field of biomedical research, allowing for the comprehensive characterization of tissues and their underlying biological processes. Yet, there is still a lack of tools to provide quantitative and objective characterization of tissues that can aid clinical assessment in vivo to enhance diagnostic and therapeutic interventions. Here, we present a clinically viable fiber-based imaging system combining time-resolved spectrofluorimetry and reflectance spectroscopy to achieve fast multiparametric macroscopic characterization of tissues. An essential feature of the setup is its ability to perform dual wavelength excitation in combination with recording time-resolved fluorescence data in several spectral intervals. Initial validation of this bimodal system was carried out in freshly resected human colorectal cancer specimens, where we demonstrated the ability of the system to differentiate normal from malignant tissues based on their autofluorescence and reflectance properties. To further highlight the complementarity of autofluorescence and reflectance measurements and demonstrate viability in a clinically relevant scenario, we also collected in vivo data from the skin of a volunteer. Altogether, integration of these modalities in a single platform can offer multidimensional characterization of tissues, thus facilitating a deeper understanding of biological processes and potentially advancing diagnostic and therapeutic approaches in various medical applications.

Evaluating the relationship between ocular blood flow and systemic organ blood flow in hemorrhagic shock using a rabbit model

This study aimed to investigate the feasibility of utilizing noninvasive ocular blood flow measurements as potential indicators of systemic circulation in rabbits experiencing hemorrhagic shock. Using Laser speckle flowgraphy, ocular blood flow indices, relative flow volume (RFV), and mean blur rate in the choroidal area (MBR-CH) were assessed in New Zealand White rabbits (n = 10) subjected to controlled blood removal and return. Hemodynamic parameters and biochemical markers were monitored alongside ocular circulation during blood removal and return phases. Additionally, correlations between ocular parameters and systemic indices were examined. The results indicated that RFV and MBR-CH exhibited significant correlations with renal and intestinal blood flows, with stronger correlations observed during blood removal. Additionally, ocular blood flow changes closely mirrored systemic dynamics, suggesting their potential as real-time indicators of shock progression and recovery. These findings indicate that ocular blood flow measurements may serve as real-time indicators of the systemic circulation status during hemorrhagic shock, offering potential insights into shock management and guiding tailored interventions. Thus, noninvasive ocular blood flow evaluation holds promise as an innovative tool for assessing systemic circulation dynamics during hemorrhagic shock.

Point Projection Mapping System for Tracking, Registering, Labeling, and Validating Optical Tissue Measurements

The validation of newly developed optical tissue-sensing techniques for tumor detection during cancer surgery requires an accurate correlation with the histological results. Additionally, such an accurate correlation facilitates precise data labeling for developing high-performance machine learning tissue-classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with the histopathology results is proposed and validated on a case study. The proposed framework provides a more-robust and accurate method for the tracking and validation of optical tissue-sensing techniques, which saves time and resources compared to the available conventional techniques.

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.

Diffuse reflectance spectroscopy for colorectal cancer surgical guidance: towards real-time tissue characterization and new biomarkers

Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide, representing 11.3% of the diagnosed cancer cases and resulting in 10.2% (0.88 million) of the cancer related deaths in 2020. CRCs are typically detected at the late stage, which leads to high mortality and morbidity. Mortality and poor prognosis are partially caused by cancer recurrence and postoperative complications. Patient survival could be increased by improving precision in surgical resection using accurate surgical guidance tools based on diffuse reflectance spectroscopy (DRS). DRS enables real-time tissue identification for potential cancer margin delineation through determination of the circumferential resection margin (CRM), while also supporting non-invasive and label-free approaches for laparoscopic surgery to avoid short-term complications of open surgery as suitable. In this study, we have estimated the scattering properties and chromophore concentrations based on 2949 DRS measurements of freshly excised ex vivo specimens of 47 patients, and used this estimation to classify normal colorectal wall (CW), fat and tumor tissues. DRS measurements were performed with fiber-optic probes of 630 μm source-detector distance (SDD; probe 1) and 2500 μm SDD (probe 2) to measure tissue layers ∼0.5-1 mm and ∼0.5-2 mm deep, respectively. By using the 5-fold cross-validation of machine learning models generated with the classification and regression tree (CART) algorithm, we achieved 95.9 ± 0.7% sensitivity, 98.9 ± 0.3% specificity, 90.2 ± 0.4% accuracy, and 95.5 ± 0.3% AUC for probe 1. Similarly, we achieved 96.9 ± 0.8% sensitivity, 98.9 ± 0.2% specificity, 94.0 ± 0.4% accuracy, and 96.7 ± 0.4% AUC for probe 2.

In situ detection of human glioma based on tissue optical properties using diffuse reflectance spectroscopy

Safely maximizing brain cancer removal without injuring adjacent healthy tissue is crucial for optimal treatment outcomes. However, it is challenging to distinguish cancer from noncancer intraoperatively. This study aimed to explore the feasibility of diffuse reflectance spectroscopy (DRS) as a label-free and real-time detection technology for discrimination between brain cancer and noncancer tissues. Fifty-five fresh cancer and noncancer specimens from 19 brain surgeries were measured with DRS, and the results were compared with co-registered clinical standard histopathology. Tissue optical properties were quantitatively obtained from the diffuse reflectance spectra and compared among different types of brain tissues. A machine learning-based classifier was trained to differentiate cancerous versus noncancerous tissues. Our method could achieve a sensitivity of 93% and specificity of 95% for discriminating high-grade glioma from normal white matter. Our results showed that DRS has the potential to be used for label-free, real-time in vivo cancer detection during brain surgery.

A combined autofluorescence and diffuse reflectance spectroscopy for mucosa tissue diagnosis: Dual-distance system and data-driven decision

Combined autofluorescence (AF) and diffuse reflectance (DR) spectroscopies have been expected to offer enhanced diagnostic accuracies for noninvasive early detection of mucosa lesions, that is, oral cavity carcinoma and cervical carcinoma. This work reports on a hybrid AF and DR spectroscopic system that is developed for quantification and diagnosis of mucosa abnormalities. The system stability and reliability are firstly assessed by phantom experiments, showing a measurement variation lower than 1% within 20 min. In vitro and in vivo validations are then conducted for tissue identification and lesion differentiation. For enhanced decision, a data-driven diagnosis algorithm is explored in pilot under different experimental configurations. The results conclude a promising accuracy of >96% for the in vivo classification as well as an excellent sensitivity of >88% for the in vitro mucosa lesions detection, and demonstrate sound potential of the system in early detection of mucosa lesions.

Diagnostic and monitoring applications using Near infrared (NIR) Spectroscopy in cancer and other diseases

Early cancer diagnosis plays a critical role in improving treatment outcomes and increasing survival rates for certain cancers. NIR spectroscopy offers a rapid and cost-effective approach to evaluate the optical properties of tissues at the microvessel level and provides valuable molecular insights. The integration of NIR spectroscopy with advanced data-driven algorithms in portable instruments has made it a cutting-edge technology for medical applications. NIR spectroscopy is a simple, non-invasive and affordable analytical tool that complements expensive imaging modalities such as functional magnetic resonance imaging, positron emission tomography and computed tomography. By examining tissue absorption, scattering, and concentrations of oxygen, water, and lipids, NIR spectroscopy can reveal inherent differences between tumor and normal tissue, often revealing specific patterns that help stratify disease. In addition, the ability of NIR spectroscopy to assess tumor blood flow, oxygenation, and oxygen metabolism provides a key paradigm for its application in cancer diagnosis. This review evaluates the effectiveness of NIR spectroscopy in the detection and characterization of disease, particularly in cancer, with or without the incorporation of chemometrics and machine learning algorithms. The report highlights the potential of NIR spectroscopy technology to significantly improve discrimination between benign and malignant tumors and accurately predict treatment outcomes. In addition, as more medical applications are studied in large patient cohorts, consistent advances in clinical implementation can be expected, making NIR spectroscopy a valuable adjunct technology for cancer therapy management. Ultimately, the integration of NIR spectroscopy into cancer diagnostics promises to improve prognosis by providing critical new insights into cancer patterns and physiology.

Biochemical differentiation between cancerous and normal human colorectal tissues by micro-Raman spectroscopy

Human colorectal tissues obtained by ten cancer patients have been examined by multiple micro-Raman spectroscopic measurements in the 500-3200 cm^-1 range under 785 nm excitation. Distinct spectral profiles are recorded from different spots on the samples: a predominant 'typical' profile of colorectal tissue, as well as those from tissue topologies with high lipid, blood or collagen content. Principal component analysis identified several Raman bands of amino acids, proteins and lipids which allow the efficient discrimination of normal from cancer tissues, the first presenting plurality of Raman spectral profiles while the last showing off quite uniform spectroscopic characteristics. Tree-based machine learning experiment was further applied on all data as well as on filtered data keeping only those spectra which characterize the largely inseparable data clusters of 'typical' and 'collagen-rich' spectra. This purposive sampling evidences statistically the most significant spectroscopic features regarding the correct identification of cancer tissues and allows matching spectroscopic results with the biochemical changes induced in the malignant tissues.

Diffuse Reflectance Spectroscopy of the Oral Mucosa: In Vivo Experimental Validation of the Precancerous Lesions Early Detection Possibility

This article is devoted to the experimental validation of the possibility of early detection of precancerous lesions in the oral mucosa in vivo using diffuse reflectance spectroscopy in the wavelength range from 360 to 1000 nm. During the study, a sample of 119 patients with precancerous lesions has been collected and analyzed. As a result of the analysis, the most informative wavelength ranges were determined, in which the maximum differences in the backscattering spectra of lesions and intact tissues were observed, methods for automatic classification of backscattering spectra of the oral mucosa were studied, sensitivity and specificity values, achievable using diffuse reflectance spectroscopy for detecting hyperkeratosis on the tongue ventrolateral mucosa surface and buccal mucosa, were evaluated. As a result of preliminary experimental studies in vivo, the possibility of automatic detection of precancerous lesions of the oral mucosa surface using diffuse reflectance spectroscopy in the wavelength range from 500 to 900 nm with an accuracy of at least 75 percent has been shown.

Visible to near-infrared single pixel microspectrometer using electrothermal MEMS grating

Compact spectrometers facilitate non-destructive and point-of-care spectral analysis. Here we report a single-pixel microspectrometer (SPM) for visible to near-infrared (VIS-NIR) spectroscopy using MEMS diffraction grating. The SPM consists of slits, electrothermally rotating diffraction grating, spherical mirror, and photodiode. The spherical mirror collimates an incident beam and focuses the beam on the exit slit. The photodiode detects spectral signals dispersed by electrothermally rotating diffraction grating. The SPM was fully packaged within 1.7 cm³ and provides a spectral response range of 405 nm to 810 nm with an average 2.2 nm spectral resolution. This optical module provides an opportunity for diverse mobile spectroscopic applications such as healthcare monitoring, product screening, or non-destructive inspection.

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

Photoplethysmography (PPG) is a widely emerging method to assess vascular health in humans. The origins of the signal of reflective PPG on peripheral arteries have not been thoroughly investigated. We aimed to identify and quantify the optical and biomechanical processes that influence the reflective PPG signal. We developed a theoretical model to describe the dependence of reflected light on the pressure, flow rate, and the hemorheological properties of erythrocytes. To verify the theory, we designed a silicone model of a human radial artery, inserted it in a mock circulatory circuit filled with porcine blood, and imposed static and pulsatile flow conditions. We found a positive, linear relationship between the pressure and the PPG and a negative, non-linear relationship, of comparable magnitude, between the flow and the PPG. Additionally, we quantified the effects of the erythrocyte disorientation and aggregation. The theoretical model based on pressure and flow rate yielded more accurate predictions, compared to the model using pressure alone. Our results indicate that the PPG waveform is not a suitable surrogate for intraluminal pressure and that flow rate significantly affects PPG. Further validation of the proposed methodology in vivo could enable the non-invasive estimation of arterial pressure from PPG and increase the accuracy of health-monitoring devices.

VIS-NIR Diffuse Reflectance Spectroscopy System with Self-Calibrating Fiber-Optic Probe: Study of Perturbation Resistance

We report on the comparative analysis of self-calibrating and single-slope diffuse reflectance spectroscopy in resistance to different measurement perturbations. We developed an experimental setup for diffuse reflectance spectroscopy (DRS) in a wide VIS-NIR range with a fiber-optic probe equipped with two source and two detection fibers capable of providing measurements employing both single- and dual-slope (self-calibrating) approaches. In order to fit the dynamic range of a spectrometer in the wavelength range of 460-1030 nm, different exposure times have been applied for short (2 mm) and long (4 mm) source-detector distances. The stability of the self-calibrating and traditional single-slope approaches to instrumental perturbations were compared in phantom and in vivo studies on human palm, including attenuations in individual channels, fiber curving, and introducing optical inhomogeneities in the probe-tissue interface. The self-calibrating approach demonstrated high resistance to instrumental perturbations introduced in the source and detection channels, while the single-slope approach showed resistance only to perturbations introduced into the source channels.

Diffuse reflection spectroscopy at the fingertip: design and performance of a compact side-firing probe for tissue discrimination during colorectal cancer surgery

Optical technologies are widely used for tissue sensing purposes. However, maneuvering conventional probe designs with flat-tipped fibers in narrow spaces can be challenging, for instance during pelvic colorectal cancer surgery. In this study, a compact side-firing fiber probe was developed for tissue discrimination during colorectal cancer surgery using diffuse reflectance spectroscopy. The optical behavior was compared to flat-tipped fibers using both Monte Carlo simulations and experimental phantom measurements. The tissue classification performance was examined using freshly excised colorectal cancer specimens. Using the developed probe and classification algorithm, an accuracy of 0.92 was achieved for discriminating tumor tissue from healthy tissue.

Label-Free Optical Spectroscopy for Early Detection of Oral Cancer

Oral cancer is the 16th most common cancer worldwide. It commonly arises from painless white or red plaques within the oral cavity. Clinical outcome is highly related to the stage when diagnosed. However, early diagnosis is complex owing to the impracticality of biopsying every potentially premalignant intraoral lesion. Therefore, there is a need to develop a non-invasive cost-effective diagnostic technique to differentiate non-malignant and early-stage malignant lesions. Optical spectroscopy may provide an appropriate solution to facilitate early detection of these lesions. It has many advantages over traditional approaches including cost, speed, objectivity, sensitivity, painlessness, and ease-of use in clinical setting for real-time diagnosis. This review consists of a comprehensive overview of optical spectroscopy for oral cancer diagnosis, epidemiology, and recent improvements in this field for diagnostic purposes. It summarizes major developments in label-free optical spectroscopy, including Raman, fluorescence, and diffuse reflectance spectroscopy during recent years. Among the wide range of optical techniques available, we chose these three for this review because they have the ability to provide biochemical information and show great potential for real-time deep-tissue point-based in vivo analysis. This review also highlights the importance of saliva-based potential biomarkers for non-invasive early-stage diagnosis. It concludes with the discussion on the scope of development and future demands from a clinical point of view.

Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization

Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide. Early detection not only reduces mortality but also improves patient prognosis by allowing the use of minimally invasive techniques to remove cancer while avoiding major surgery. Expanding the use of microsurgical techniques requires accurate diagnosis and delineation of the tumor margins in order to allow complete excision of cancer. We have used diffuse reflectance spectroscopy (DRS) to identify the main optical CRC biomarkers and to optimize parameters for the integration of such technologies into medical devices. A total number of 2889 diffuse reflectance spectra were collected in ex vivo specimens from 47 patients. Short source-detector distance (SDD) and long-SDD fiber-optic probes were employed to measure tissue layers from 0.5 to 1 mm and from 0.5 to 1.9 mm deep, respectively. The most important biomolecules contributing to differentiating DRS between tissue types were oxy- and deoxy-hemoglobin (Hb and HbO₂), followed by water and lipid. Accurate tissue classification and potential DRS device miniaturization using Hb, HbO₂, lipid and water data were achieved particularly well within the wavelength ranges 350-590 nm and 600-1230 nm for the short-SDD probe, and 380-400 nm, 420-610 nm, and 650-950 nm for the long-SDD probe.

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.

Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy

During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice.

Real-time tracking of a diffuse reflectance spectroscopy probe used to aid histological validation of margin assessment in upper gastrointestinal cancer resection surgery

SIGNIFICANCE

Diffuse reflectance spectroscopy (DRS) allows discrimination of tissue type. Its application is limited by the inability to mark the scanned tissue and the lack of real-time measurements.

AIM

This study aimed to develop a real-time tracking system to enable localization of a DRS probe to aid the classification of tumor and non-tumor tissue.

APPROACH

A green-colored marker attached to the DRS probe was detected using hue-saturation-value (HSV) segmentation. A live, augmented view of tracked optical biopsy sites was recorded in real time. Supervised classifiers were evaluated in terms of sensitivity, specificity, and overall accuracy. A developed software was used for data collection, processing, and statistical analysis.

RESULTS

The measured root mean square error (RMSE) of DRS probe tip tracking was 1.18  ±  0.58  mm and 1.05  ±  0.28  mm for the x and y dimensions, respectively. The diagnostic accuracy of the system to classify tumor and non-tumor tissue in real time was 94% for stomach and 96% for the esophagus.

CONCLUSIONS

We have successfully developed a real-time tracking and classification system for a DRS probe. When used on stomach and esophageal tissue for tumor detection, the accuracy derived demonstrates the strength and clinical value of the technique to aid margin assessment in cancer resection surgery.

[Raman spectroscopy and its application in different areas of medicine]

The aim of the review is to learn about the areas of application of the Raman spectroscopy in medicine, particularly in dentistry. The method is widely used in biology, medicine, pharmacy, forensic science, gemology, food industry and other industries. The main advantages of Raman spectroscopy are no need for sample preparation and small amounts of the object of study, as well as the ability to contactlessly obtain unique information about the conformation and microenvironment of living cell molecules. The disadvantages are high costs of the equipment that are compensated with the long-term use by having no costs for additional reagents. The combinatorial scattering is used in dermatology, as it is a high-accuracy automated method of visualization and diagnostics of both benign growths as pigmented nevus, seborrheic keratosis, and malignant neoplasms as melanoma and basal cell carcinoma. This method is an analytical tool for diagnosing various diseases, making the direct measurements in hard and liquid media easier, does not require special treatment of samples and is not sensitive to absorption bands. The Raman spectroscopy use in dentistry allows diagnosing and comparative analysis of the changes of hard tissues of teeth and mucous membrane of the mouth, which improves security and rationalization of treatment and further prevention of complications before and after making different operations.