Spectral imaging in preclinical research and clinical pathology.

Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, pre-clinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings

Imaging of plasmonic nanoparticles for biomedical applications

Plasmonic nanoparticles show potential for numerous different biomedical applications, including diagnostic applications such as targeted labelling and therapeutic applications such as drug delivery and therapeutic hyperthermia. In order to support the development of these applications, imaging techniques are required for imaging and characterising nanoparticles both in isolation and in the cellular environment.The work presented in this thesis relates to the use and development of two different optical techniques for imaging and measuring the localised surface plasmon resonanceof plasmonic nanoparticles, both for isolated particles and for particles in a cellular environment.The two techniques that have been used in this project are hyperspectral darkfield microscopy and spatial modulation microscopy.Hyperspectral darkfield microscopy is a darkfield technique in which a supercontinuum light source and an acousto-optic tuneable filter are used to collect darkfield images whichinclude spectral information. This technique has been used to measure the spectra of single nanoparticles of different shapes and sizes, and nanoparticle clusters. The resultsof some of these measurements have also been correlated with finite element method simulations and transmission electron microscope images.The hyperspectral darkfield technique has also been used to image cells that have been incubated with nanoparticles, demonstrating that this technique may also be used tomeasure the spectra of nanoparticle clusters on a cellular background.Spatial modulation microscopy is based on fast modulation of the position of a nanoparticle in the focus of an optical beam. This modulation results in a variation in transmittedintensity, which can be detected with very high sensitivity using a lock-in amplifier. Since, for biological imaging applications it is desirable to be able to image, for example whole cells in real time, a fast scanning version of this technique has been implemented, which increases the applicability of the technique to imaging of nanoparticles in cell

Imaging White Blood Cells using a Snapshot Hyper-Spectral Imaging System

Automated white blood cell (WBC) counting systems process an extracted whole blood sample and provide a cell count. A step that would not be ideal for onsite screening of individuals in triage or at a security gate. Snapshot Hyper-Spectral imaging systems are capable of capturing several spectral bands simultaneously, offering co-registered images of a target. With appropriate optics, these systems are potentially able to image blood cells in vivo as they flow through a vessel, eliminating the need for a blood draw and sample staining. Our group has evaluated the capability of a commercial Snapshot Hyper-Spectral imaging system, specifically the Arrow system from Rebellion Photonics, in differentiating between white and red blood cells on unstained and sealed blood smear slides. We evaluated the imaging capabilities of this hyperspectral camera as a platform to build an automated blood cell counting system. Hyperspectral data consisting of 25, 443x313 hyperspectral bands with ~3nm spacing were captured over the range of 419 to 494nm. Open-source hyperspectral datacube analysis tools, used primarily in Geographic Information Systems (GIS) applications, indicate that white blood cells\u27 features are most prominent in the 428-442nm band for blood samples viewed under 20x and 50x magnification over a varying range of illumination intensities. The system has shown to successfully segment blood cells based on their spectral-spatial information. These images could potentially be used in subsequent automated white blood cell segmentation and counting algorithms for performing in vivo white blood cell counting

Surgical spectral imaging

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

Hyperspectral imaging of the haemodynamic and metabolic states of the exposed cortex

A hyperspectral imaging (HSI) system to measure and quantify in vivo haemodynamic and metabolic signals from the exposed cerebral cortex of small animals was designed, developed and investigated in this thesis. Imaging brain tissue at multiple narrow wavelength bands in the visible and near-infrared (NIR) range allows one not only to monitor cerebral oxygenation and haemodynamics via mapping of haemoglobin concentration changes, but also to directly target the spatial quantification of cerebral metabolic activity via measurement of the redox states of mitochondrial cytochrome-c-oxidase (CCO). Having both these sets of information in vivo at high resolution on the exposed cortex can provide impactful insight on brain physiology and can help validate corresponding data acquired non-invasively using broadband near-infrared spectroscopy (bNIRS). Several designs and HSI configurations were assessed and compared, including different customised benchtop setups. In the end, a bespoke spectral-scanning HSI system called hNIR, using a supercontinuum laser coupled with a rotating Pellin-Broca prism and a scientific complementary metal-oxide semiconductor (sCMOS) camera, was built, characterised and validated on liquid optical phantoms. In addition, an in-house Monte Carlo (MC) framework for simulating HSI of the haemodynamic and metabolic states of the exposed cortex was also developed using an open-source MC code package (Mesh-based Monte Carlo) and integrated with hNIR, for aiding image reconstruction and enhance quantification, as well as to run computational investigations on the performances of HSI for brain haemodynamic and metabolic monitoring. hNIR was finally applied in vivo on the exposed cerebral cortex of three mice during different levels of hyperoxic and hypoxic stimulation, demonstrating its capability to retrieve high resolution and accurate maps of the relative changes in the concentrations of oxyhaemoglobin (HbO₂), deoxyhaemoglobin (HHb) and the oxidative state of CCO (oxCCO)

Hyperspectral microscope imaging methods for multiplex detection of Campylobacter

Campylobacter is an emerging zoonotic bacterial threat in the poultry industry. The current methods for the isolation and detection of Campylobacter are culture-based techniques with several selective agars designed to isolate Campylobacter colonies, which is time-consuming, labour intensive and has low sensitivity. Several immunological and molecular techniques such as enzyme-linked immunosorbent assay (ELISA) and Latex agglutination are commercially available for the detection and identification of Campylobacter. However, these methods demand more advanced instruments as well as specially trained experts. A hyperspectral microscope imaging (HMI) technique with the fluorescence in situ hybridisation (FISH) technique has the potential for multiplex foodborne pathogen detection. Using Alexa488 and Cy3 fluorophores, the HMI (450–800 nm) technique was able to identify Campylobacter jejuni stains with high sensitivity and specificity. In addition, HMI was able to classify six bacteria using scattering intensity from their spectra without a FISH fluorophore. Overall classification accuracy of quadratic discriminant analysis (QDA) method for six bacteria including Bifidobacter longum, Campylobacter jejuni, Clostridium perfringens, Enterobacter cloacae, Lactobacillus salivarius and Shigella flexneri using the HMI technique without fluorescent markers was approximately 88.6 % with pixel-wise classification

Remote sensing of strong emotions using electro-optical imaging technique

©Cranfield UniversityThis thesis reports a summary of the PhD programme for the assessment of person‘s emotional anxiety using Electro-optical technology. The thesis focuses mainly on the understanding of fundamental properties of physiological responses to emotional anxiety and how they can be captured by using Electro-optical (EO) imaging methods such as hyperspectral imaging (HSI) and thermal imaging (TI) techniques. The thesis summarises three main areas of work that have been undertaken by the author in the programme: (a) Experimental set up including HSI system and data acquisition software design and implementation, (b) fundamental understanding of physiological responses to emotional anxiety from the EO perspective and (c) the development of a novel remote sensing technique for the assessment of emotions without the requirement of base line information. One of our main results is to provide evidence to prove that the mean temperature in the periorbital region remains the same within 0.2°C during emotional anxiety. Furthermore, we have shown that it is the high temperature pixels within the periorbital, which increases in numbers by a huge amount after 2 minutes of the onset of anxiety. We have also developed techniques to allow the assessment anxiety without the need of base line information. The method has been tested using a sample size of about 40 subjects, and achieved promising result. Technologies for the remote sensing of heart beat rate has been in great demand, this study also involves the development of heart beat detection using TI system. Moreover, we have also attempted for the first time to sense glucose concentration from the blood sample in-vivo using HSI technique remotely