Modern trends in biophotonics for clinical diagnosis and therapy to solve unmet clinical needs

Frontline clinical diagnosis-FTIR on pancreatic cancer

OBJECTIVE

Accurate, easily accessible and economically viable cancer diagnostic tools are pivotal in improving the abysmal 5% survival rate of pancreatic cancer.

METHODS

A novel, affordable, non-invasive diagnostic method has been developed by combining measurement precision of infrared spectroscopy with classification using machine learning tools.

RESULTS

Diagnosis accuracy as high as 90% has been achieved. The study investigated urine and blood from pancreas cancer patients and healthy volunteers, and significantly improved accuracy by focusing on sweet-spots within blood plasma fractions containing molecules within a narrow range of molecular weights.

Improving Vibrational Spectroscopy Prospects in Frontline Clinical Diagnosis: Fourier Transform Infrared on Buccal Mucosa Cancer

We report a novel method with higher than 90% accuracy in diagnosing buccal mucosa cancer. We use Fourier transform infrared spectroscopic analysis of human serum by suppressing confounding high molecular weight signals, thus relatively enhancing the biomarkers’ signals. A narrower range molecular weight window of the serum was also investigated that yielded even higher accuracy on diagnosis. The most accurate results were produced in the serum’s 10–30 kDa molecular weight region to distinguish between the two hardest to discern classes, i.e., premalignant and cancer patients. This work promises an avenue for earlier diagnosis with high accuracy as well as greater insight into the molecular origins of these signals by identifying a key molecular weight region to focus on.

SP, N. M, Barik AK, Pai KM, Unnikrishnan VK, George SD, Kartha VB, Chidangil S. Photonics of human saliva: potential optical methods for the screening of abnormal health conditions and infections

Human saliva can be treated as a pool of biological markers able to reflect on the state of personal health. Recent years have witnessed an increase in the use of optical devices for the analysis of body fluids. Several groups have carried out studies investigating the potential of saliva as a non-invasive and reliable clinical specimen for use in medical diagnostics. This brief review aims to highlight the optical technologies, mainly surface plasmon resonance (SPR), Raman, and Fourier transform infrared (FTIR) spectroscopy, which are being used for the probing of saliva for diverse biomedical applications. Advances in bio photonics offer the promise of unambiguous, objective and fast detection of abnormal health conditions and viral infections (such as COVID-19) from the analysis of saliva.

Detecting the Near Infrared Autofluorescence of the Human Parathyroid: Hype or Opportunity?

OBJECTIVE

With the recent approval of 2 NIRAF-based devices for label-free identification of PG by the Food and Drug Administration, it becomes crucial to educate the surgical community on the realistic scope of this emerging technology. Here, we have compiled a review of studies that utilize NIRAF and present a critical appraisal of this technique for intraoperative PG detection.

BACKGROUND

Failure to visualize PGs could lead to accidental damage/excision of healthy PGs or inability to localize diseased PGs, resulting in postsurgical complications. The discovery that PGs have NIRAF led to new avenues for intraoperatively identifying PGs with high accuracy in real-time.

METHODS

Using the following key terms: "parathyroid, near infrared, autofluorescence" in various search engines such as PubMed and Google Scholar, we identified various publications relevant to this review of NIRAF as a technique for PG identification. Articles were excluded if they focused solely on contrast agents, served as commentaries/overviews on NIRAF or were not written in English.

RESULTS

To date, studies have investigated the potential of NIRAF detection for (i) identifying PG tissues intraoperatively, (ii) locating PGs before or after dissection, (iii) distinguishing healthy from diseased PGs, and (iv) minimizing postoperative hypocalcemia after total thyroidectomy.

CONCLUSIONS

Because NIRAF-based identification of PG is noninvasive and label-free, the popularity of this approach has considerably surged. As the present limitations of various technologies capable of NIRAF detection are identified, we anticipate that newer device iterations will continue to be developed enhancing the current merits of these modalities to aid surgeons in identifying and preserving PGs. However, more concrete and long-term outcome studies with these modalities are essential to determine the impact of this technique on patient outcome and actual cost-benefits.

Novel techniques for intraoperative parathyroid gland identification: a comprehensive review

INTRODUCTION

The parathyroid glands (PGs) are critical for calcium regulation and homeostasis. The preservation of PGs during neck surgery is crucial to avoid postoperative hypoparathyroidism. There are no existing guidelines for intraoperative PG identification, and the current approach relies heavily on the experience of the operating surgeon. A technique that accurately and rapidly identifies PGs would represent a useful intraoperative adjunct.

AREAS COVERED

This review aims to assess common dye and fluorescence-based PG imaging techniques and examine their utility for intraoperative PG identification. A literature search of published data on methylene blue (MB), indocyanine green (ICG) angiography, near-infrared autofluorescence (NIRAF), and the PGs between 1971 and 2020 was conducted on PubMed.

EXPERT OPINION

NIRAF and near-infrared (NIR) parathyroid angiography have emerged as promising and reliable techniques for intraoperative PG identification. NIRAF may aid with real-time identification of both normal and diseased PGs and reduce the risk of postoperative complications such as hypocalcemia. Further large prospective multicenter studies should be conducted in thyroid and parathyroid surgical patient populations to confirm the clinical efficacy of these intraoperative NIR-based PG detection techniques.

Deep learning a boon for biophotonics?

This review covers original articles using deep learning in the biophotonic field published in the last years. In these years deep learning, which is a subset of machine learning mostly based on artificial neural network geometries, was applied to a number of biophotonic tasks and has achieved state-of-the-art performances. Therefore, deep learning in the biophotonic field is rapidly growing and it will be utilized in the next years to obtain real-time biophotonic decision-making systems and to analyze biophotonic data in general. In this contribution, we discuss the possibilities of deep learning in the biophotonic field including image classification, segmentation, registration, pseudostaining and resolution enhancement. Additionally, we discuss the potential use of deep learning for spectroscopic data including spectral data preprocessing and spectral classification. We conclude this review by addressing the potential applications and challenges of using deep learning for biophotonic data.

Coregistered Spectral Optical Coherence Tomography and Two-Photon Microscopy for Multimodal Near-Instantaneous Deep-Tissue Imaging

Two-photon microscopy (2PM) has brought unique insight into the mechanisms underlying immune system dynamics and function since it enables monitoring of cellular motility and communication in complex systems within their genuine environment-the living organism. However, use of 2PM in clinical settings is limited. In contrast, optical coherence tomography (OCT), a noninvasive label-free diagnostic imaging method, which allows monitoring morphologic changes of large tissue regions in vivo, has found broad application in the clinic. Here we developed a combined multimodal technology to achieve near-instantaneous coregistered OCT, 2PM, and second harmonic generation (SHG) imaging over large volumes (up to 1,000 × 1,000 × 300 μm³ ) of tendons and other tissue compartments in mouse paws, as well as in mouse lymph nodes, spleens, and femurs. Using our multimodal imaging approach, we found differences in macrophage cell shape and motility behavior depending on whether they are located in tendons or in the surrounding tissue compartments of the mouse paw. The cellular shape of tissue-resident macrophages, indicative for their role in tissue, correlated with the supramolecular organization of collagen as revealed by SHG and OCT. Hence, the here-presented approach of coregistered OCT and 2PM has the potential to link specific cellular phenotypes and functions (as revealed by 2PM) to tissue morphology (as highlighted by OCT) and thus, to build a bridge between basic research knowledge and clinical observations. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Skin and subcutaneous fat morphology alterations under the LED or laser treatment in rats in vivo

The main objective of this work is to quantify the impact of photodynamic/photothermal treatment by using visible LED and NIR laser irradiation through the skin of subcutaneous fat in vivo followed up by tissue sampling and histology. The optical method may provide reduction of regional or site-specific accumulations of abdominal or subcutaneous adipose tissue precisely and least-invasively by inducing cell apoptosis and controlled necrosis of fat tissue. As photodynamic/photothermal adipose tissue sensitizers Brilliant Green (BG) or Indocyanine Green (ICG) dyes were injected subcutaneously in rats. The CW LED device (625 nm) or CW diode laser (808 nm) were used as light sources, respectively. Biopsies of skin together with subcutaneous tissues were taken for histology. The combined action BG-staining and LED-irradiation (BG + LED) or ICG-staining and NIR-laser irradiation (ICG + NIR) causes pronounced signs of damage of adipose tissue characterized by a strong stretching, thinning, folding and undulating of cell membranes and appearance of necrotic areas. As a posttreatment after 14 days only connective tissue was observed at the site of necrotic areas. The data obtained are important for safe light treatment of site-specific fat accumulations, including cellulite. This work provides a basis for the development of fat lipolysis technologies and to move them to clinical applications. Schematics of animal experiment.

Developing Fully Automated Quality Control Methods for Preprocessing Raman Spectra of Biomedical and Biological Samples

Spectral preprocessing is frequently required to render Raman spectra useful for further processing and analyses. The various preprocessing steps, individually and sequentially, are increasingly being automated to cope with large volumes of data from, for example, hyperspectral imaging studies. Full automation of preprocessing is especially desirable when it produces consistent results and requires minimal user input. It is therefore essential to evaluate the "quality" of such preprocessed spectra. However, relatively few methods exist to evaluate preprocessing quality, and fully automated methods for doing so are virtually non-existent. Here we provide a brief overview of fully automated spectral preprocessing and fully automated quality assessment of preprocessed spectra. We follow this with the introduction of fully automated methods to establish figures-of-merit that encapsulate preprocessing quality. By way of illustration, these quantitative methods are applied to simulated and real Raman spectra. Quality factor and quality parameter figures-of-merit resulting from individual preprocessing step quality tests, as well as overall figures-of-merit, were found to be consistent with the quality of preprocessed spectra.

Label-free imaging and spectroscopy for early detection of cervical cancer

The label-free imaging and spectroscopy method was studied on cervical unstained tissue sections obtained from 36 patients. The native fluorescence spectra of tissues are analyzed by the optical redox ratio (ORR), which is defined as fluorescence intensity ratio between NADH and FAD, and indicates the metabolism change with the cancer development. The ORRs of normal tissues are consistently higher than those of precancer or cancerous tissues. A criterion line of ORR at 5.0 can be used to discriminate cervical precancer/cancer from normal tissues. The sensitivity and specificity of the native fluorescence spectroscopy method for cervical cancer diagnosis are determined as 100% and 91%. Moreover, the native fluorescence spectroscopy study is much more sensitive on the healthy region of cervical precancer/cancer patients compared with the traditional clinical staining method. The results suggest label-free imaging and spectroscopy is a fast, highly sensitive and specific method on the detection of cervical cancer.

Imaging the Cardiac Extracellular Matrix

Cardiovascular disease is the global leading cause of death. One route to address this problem is using biomedical imaging to measure the molecules and structures that surround cardiac cells. This cellular microenvironment, known as the cardiac extracellular matrix, changes in composition and organization during most cardiac diseases and in response to many cardiac treatments. Measuring these changes with biomedical imaging can aid in understanding, diagnosing, and treating heart disease. This chapter supports those efforts by reviewing representative methods for imaging the cardiac extracellular matrix. It first describes the major biological targets of ECM imaging, including the primary imaging target of fibrillar collagen. Then it discusses the imaging methods, describing their current capabilities and limitations. It categorizes the imaging methods into two main categories: organ-scale noninvasive methods and cellular-scale invasive methods. Noninvasive methods can be used on patients, but only a few are clinically available, and others require further development to be used in the clinic. Invasive methods are the most established and can measure a variety of properties, but they cannot be used on live patients. Finally, the chapter concludes with a perspective on future directions and applications of biomedical imaging technologies.

Perspectives, potentials and trends of ex vivo and in vivo optical molecular pathology

It is pivotal for medical applications, such as noninvasive histopathologic characterization of tissue, to realize label-free and molecule-specific representation of morphologic and biochemical composition in real-time with subcellular spatial resolution. This unmet clinical need requires new approaches for rapid and reliable real-time assessment of pathologies to complement established diagnostic tools. Photonic imaging combined with digitalization offers the potential to provide the clinician the requested information both under in vivo and ex vivo conditions. This report summarizes photonic approaches and their use in combination with image processing, machine learning and augmented virtual reality that might solve current challenges in modern medicine. Details are given for pathology, intraoperative diagnosis in head and neck cancer and endoscopic diagnosis in gastroenterology.

Review of quantitative multiscale imaging of breast cancer

Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.