Diffuse reflectance spectroscopy and imaging for non-invasive objective assessment of genitourinary syndrome of menopause: a pilot study

The genitourinary symptom of menopause (GSM) affects up to 65% of women, resulting in symptoms such as vulvovaginal dryness, discomfort, and dysuria, which significantly impacts quality of life. The current assessment methods rely on subjective questionnaires that can be influenced by individual differences, as well as invasive measurements that are time-consuming and not easily accessible. In this study, we explore the potential of a non-invasive and objective assessment tool called diffuse reflectance spectroscopy and imaging (DRSI) to evaluate tissue chromophores, including water, lipid, oxyhemoglobin, and deoxyhemoglobin. These measurements provide information about moisture content, lipid levels, oxygen saturation, and blood fraction, which can serve as surrogate markers for genital estrogen levels. Our findings reveal distinct differences in these chromophores among pre, peri, and postmenopausal subjects. By using lipid and blood fraction tissue chromophores in a K-Nearest Neighbour classifier model, we achieved a prediction accuracy of 65% compared to vaginal maturation index (VMI) that is clinically used to assess estrogen-related hormonal changes. When age was included as the third feature, the accuracy increased to 78%. We believe that by refining the study protocol and configuring the fiber probe to examine tissue chromophores both in the superficial vulva skin for epidermal water content and the deeper layers, DRSI has the potential to provide objective diagnosis and aid in monitoring the treatment outcome of GSM.

Advancing cervical cancer diagnosis and screening with spectroscopy and machine learning

INTRODUCTION

In the UK alone, the incidence of cervical cancer is increasing, hence an urgent need for early and rapid detection of cancer before it develops. Spectroscopy in conjunction with machine learning offers a disruptive technology that promises to be pick up cancer early as compared to the current diagnostic techniques used.

AREAS COVERED

This review article explores the different spectroscopy techniques that have been used for the analysis of cervical cancer. Along with the extensive description of spectroscopic techniques, the various machine learning techniques are also described as well as the applications that have been explored in the diagnosis of cervical cancer. This review delimits the literature specifically associated with cervical cancer studies performed solely with the use of a spectroscopy technique, and machine learning.

EXPERT OPINION

Although there are several methods and techniques to detect cervical cancer, the clinical sector requires to introduce new diagnostic technologies that help improving the quality of life of patient. These innovative technologies involve spectroscopy as a qualitative method and machine learning as a quantitative method. In this article, both the techniques and methodologies that allow and promise to be a new screening tool for the detection of cervical cancer is covered.

In vivo Raman spectroscopy for biochemical monitoring of the human cervix throughout pregnancy

BACKGROUND

The cervix must undergo significant biochemical remodeling to allow for successful parturition. This process is not fully understood, especially in instances of spontaneous preterm birth. In vivo Raman spectroscopy is an optical technique that can be used to investigate the biochemical composition of tissue longitudinally and noninvasively in human beings, and has been utilized to measure physiology and disease states in a variety of medical applications.

OBJECTIVE

The purpose of this study is to measure in vivo Raman spectra of the cervix throughout pregnancy in women, and to identify biochemical markers that change with the preparation for delivery and postpartum repair.

STUDY DESIGN

In all, 68 healthy pregnant women were recruited. Raman spectra were measured from the cervix of each patient monthly in the first and second trimesters, weekly in the third trimester, and at the 6-week postpartum visit. Raman spectra were measured using an in vivo Raman system with an optical fiber probe to excite the tissue with 785 nm light. A spectral model was developed to highlight spectral regions that undergo the most changes throughout pregnancy, which were subsequently used for identifying Raman peaks for further analysis. These peaks were analyzed longitudinally to determine if they underwent significant changes over the course of pregnancy (P < .05). Finally, 6 individual components that comprise key biochemical constituents of the human cervix were measured to extract their contributions in spectral changes throughout pregnancy using a linear combination method. Patient factors including body mass index and parity were included as variables in these analyses.

RESULTS

Raman peaks indicative of extracellular matrix proteins (1248 and 1254 cm^-1) significantly decreased (P < .05), while peaks corresponding to blood (1233 and 1563 cm^-1) significantly increased (P < .0005) in a linear manner throughout pregnancy. In the postpartum cervix, significant increases in peaks corresponding to actin (1003, 1339, and 1657 cm^-1) and cholesterol (1447 cm^-1) were observed when compared to late gestation, while signatures from blood significantly decreased. Postpartum actin signals were significantly higher than early pregnancy, whereas extracellular matrix proteins and water signals were significantly lower than early weeks of gestation. Parity had a significant effect on blood and extracellular matrix protein signals, with nulliparous patients having significant increases in blood signals throughout pregnancy, and higher extracellular matrix protein signals in early pregnancy compared to patients with prior pregnancies. Body mass index significantly affected actin signal contribution, with low body mass index patients showing decreasing actin contribution throughout pregnancy and high body mass index patients demonstrating increasing actin signals.

CONCLUSION

Raman spectroscopy was successfully used to biochemically monitor cervical remodeling in pregnant women during prenatal visits. This foundational study has demonstrated sensitivity to known biochemical dynamics that occur during cervical remodeling, and identified patient variables that have significant effects on Raman spectra throughout pregnancy. Raman spectroscopy has the potential to improve our understanding of cervical maturation, and be used as a noninvasive preterm birth risk assessment tool to reduce the incidence, morbidity, and mortality caused by preterm birth.

Speeding up Raman spectral imaging by the three-dimensional low rank estimation method

Raman spectral imaging has been widely used as a very important analytical tool in various fields. For obtaining the high spectral signal-to-noise ratio Raman images, the long integration time is necessary, which is placing a limit on the application of Raman spectral imaging. We introduce a simple and feasible numerical method of the Three-dimensional Low Rank Estimation (3D-LRE), which can speed up the data acquisition process of the Raman spectral imaging. The spectral signal-to-noise ratio of the Raman images can be increased by over 75 times and the speed of the data acquisition can be improved by over 30 times. By combining with line-scan or multifocus-scan techniques, the Raman images can be obtained in a few seconds.

In vivo Raman spectral analysis of impaired cervical remodeling in a mouse model of delayed parturition

Monitoring cervical structure and composition during pregnancy has high potential for prediction of preterm birth (PTB), a problem affecting 15 million newborns annually. We use in vivo Raman spectroscopy, a label-free, light-based method that provides a molecular fingerprint to non-invasively investigate normal and impaired cervical remodeling. Prostaglandins stimulate uterine contractions and are clinically used for cervical ripening during pregnancy. Deletion of cyclooxygenase-1 (Cox-1), an enzyme involved in production of these prostaglandins, results in delayed parturition in mice. Contrary to expectation, Cox-1 null mice displayed normal uterine contractility; therefore, this study sought to determine whether cervical changes could explain the parturition differences in Cox-1 null mice and gestation-matched wild type (WT) controls. Raman spectral changes related to extracellular matrix proteins, lipids, and nucleic acids were tracked over pregnancy and found to be significantly delayed in Cox-1 null mice at term. A cervical basis for the parturition delay was confirmed by other ex vivo tests including decreased tissue distensibility, hydration, and elevated progesterone levels in the Cox-1 null mice at term. In conclusion, in vivo Raman spectroscopy non-invasively detected abnormal remodeling in the Cox-1 null mouse, and clearly demonstrated that the cervix plays a key role in their delayed parturition.

Raman microspectroscopy of nucleus and cytoplasm for human colon cancer diagnosis

Subcellular Raman analysis is a promising clinic tool for cancer diagnosis, but constrained by the difficulty of deciphering subcellular spectra in actual human tissues. We report a label-free subcellular Raman analysis for use in cancer diagnosis that integrates subcellular signature spectra by subtracting cytoplasm from nucleus spectra (Nuc.-Cyt.) with a partial least squares-discriminant analysis (PLS-DA) model. Raman mapping with the classical least-squares (CLS) model allowed direct visualization of the distribution of the cytoplasm and nucleus. The PLS-DA model was employed to evaluate the diagnostic performance of five types of spectral datasets, including non-selective, nucleus, cytoplasm, ratio of nucleus to cytoplasm (Nuc./Cyt.), and nucleus minus cytoplasm (Nuc.-Cyt.), resulting in diagnostic sensitivity of 88.3%, 84.0%, 98.4%, 84.5%, and 98.9%, respectively. Discriminating between normal and cancerous cells of actual human tissues through subcellular Raman markers is feasible, especially when using the nucleus-cytoplasm difference spectra. The subcellular Raman approach had good stability, and had excellent diagnostic performance for rectal as well as colon tissues. The insights gained from this study shed new light on the general applicability of subcellular Raman analysis in clinical trials.

Integrated Mueller-matrix near-infrared imaging and point-wise spectroscopy improves colonic cancer detection

We report the development and implementation of a unique integrated Mueller-matrix (MM) near-infrared (NIR) imaging and Mueller-matrix point-wise diffuse reflectance (DR) spectroscopy technique for improving colonic cancer detection and diagnosis. Point-wise MM DR spectra can be acquired from any suspicious tissue areas indicated by MM imaging. A total of 30 paired colonic tissue specimens (normal vs. cancer) were measured using the integrated MM imaging and point-wise MM DR spectroscopy system. Polar decomposition algorithms are employed on the acquired images and spectra to derive three polarization metrics including depolarization, diattentuation and retardance for colonic tissue characterization. The decomposition results show that tissue depolarization and retardance are significantly decreased (p<0.001, paired 2-sided Student's t-test, n = 30); while the tissue diattentuation is significantly increased (p<0.001, paired 2-sided Student's t-test, n = 30) associated with colonic cancer. Further partial least squares discriminant analysis (PLS-DA) and leave-one tissue site-out, cross validation (LOSCV) show that the combination of the three polarization metrics provide the best diagnostic accuracy of 95.0% (sensitivity: 93.3%, and specificity: 96.7%) compared to either of the three polarization metrics (sensitivities of 93.3%, 83.3%, and 80.0%; and specificities of 90.0%, 96.7%, and 80.0%, respectively, for the depolarization, diattentuation and retardance metrics) for colonic cancer detection. This work suggests that the integrated MM NIR imaging and point-wise MM NIR diffuse reflectance spectroscopy has the potential to improve the early detection and diagnosis of malignant lesions in the colon.

Preliminary study of differentiating smears from cancerous and non-cancerous nasopharyngeal tissue using confocal Raman spectroscopy

PURPOSE

Current practice for diagnosing nasopharyngeal carcinoma (NPC) is based on invasive tissue biopsy. This study aims to explore the feasibility of using Raman spectroscopy to differentiate cancerous and non-cancerous nasopharyngeal tissue smears, expecting to realize minimal invasive diagnosis using smears from in vivo mucosa tissue by Raman spectroscopy.

METHODS

Biopsy tissue smears were acquired from 74 patients with pathologically diagnosed nasopharyngeal diseases and measured using confocal Raman spectroscopy.

RESULTS

Both fingerprint region and high wavenumber Raman spectra were acquired with distinguish features. Multivariate statistical analysis was used to differentiate cancerous and non-cancerous groups, achieving a diagnostic sensitivity of 87.2 and specificity of 85.7 % for differentiating NPC from nasopharyngeal non-cancerous smears.

CONCLUSIONS

This work indicates that the method has a unique advantage in microanalysis for tissue smears which may provide a promising minimal invasive (or noninvasive) diagnosing tool for cancer diagnosis.

Current Advances in the Application of Raman Spectroscopy for Molecular Diagnosis of Cervical Cancer

Raman spectroscopy provides a unique biochemical fingerprint capable of identifying and characterizing the structure of molecules, cells, and tissues. In cervical cancer, it is acknowledged as a promising biochemical tool due to its ability to detect premalignancy and early malignancy stages. This review summarizes the key research in the area and the evidence compiled is very encouraging for ongoing and further research. In addition to the diagnostic potential, promising results for HPV detection and monitoring treatment response suggest more than just a diagnosis prospective. A greater body of evidence is however necessary before Raman spectroscopy is fully validated for clinical use and larger comprehensive studies are required to fully establish the role of Raman spectroscopy in the molecular diagnostics of cervical cancer.