Towards pixel-dependent spatial frequency domain imaging modelling and recovery

Spatial frequency domain imaging (SFDI) is an imaging modality that projects spatially modulated light patterns to determine optical property maps for absorption and reduced scattering of biological tissue via a pixel-by-pixel data acquisition and analysis procedure. The light interaction theory behind SFDI is based upon homogenous properties, with forward models calculated via analytical solutions or Monte-Carlo, also used for the optical property recovery, using only a pixel-independent nature. This is known to be limited for samples with high heterogeneity, with an increased error observed for varying optical property boundaries. NIRFAST is an image modelling and reconstruction tool based upon FEM of the diffusion model that simulates complex heterogenic tissue interactions from single and multi-wavelength systems and is routinely used in a variety of clinical and pre-clinical applications. NIRFAST has been adapted for SFDI, allowing for pixel-dependent heterogenic simulations. Image reconstruction using existing methodologies is compared to data generated from complex models with NIRFAST to quantify the optical property reconstruction accuracy, whilst heterogenous models of varying optical property values and depths further demonstrate SFDIs parameter recovery capabilities. It is shown that pixel-dependent light interaction in tissue plays an important part of accurate optical map recovery and can affect quantitative accuracy. This work demonstrates full raw image SFDI simulations for heterogenous samples working towards the use of model-based image reconstruction to allow a coupled, pixel-dependent SFDI image modelling and parameter recovery.</p

Application of numerical methods for heterogenic spatial frequency domain imaging simulations

A numerical simulation tool for spatial frequency domain imaging (SFDI) has been developed. Validation against current methods for parameter recovery is presented including heterogenic models demonstrating a complex light propagation tool for SFDI.</p

Cell trauma detection using infra-red live cell imaging

Infra-red (IR) spectroscopic imaging of live cells is greatly affected by the presence of water, which is a strong absorber of IR radiation. In order to overcome this, a variety of methods have been developed using complex microfluidic devices to reduce the liquid sample path length. However, these devices are often custom made needing both specialised equipment and detailed fabrication steps. Here we show the novel utilisation of a liquid-air interface configuration and a negative contrast imaging device (NCI) reflectance imaging system for the collection of spectral data from live cells within an in vitro environment. Spectral differences were observed between two different cell densities, both in the presence and absence of cell culture media. Additionally, differences were observed between control and test cultures exposed to dimethyl sulfoxide (DMSO) to induce cell apoptosis. The NCI system acquired data in the 2.5 – 3.5 µm spectral region, at a spectral sampling interval of 10 nm. This method will allow further investigation of spectral bio-markers within cell cultures to augment understanding of specific cell contributions to wound healing in vivo.</p

Mid-infrared spectroscopic imaging to assess wounded tissue health

Modern traumatic injuries, as encountered in battlefield conflicts, are often characterised by extensive soft tissue damage from blasts and high energy projectiles. This situation has created a challenge for wound stabilisation and repair, with surgical intervention common, via wound debridement procedures. These are often complex surgeries where necrotic and infected tissue is removed, usually with multiple remedial surgeries, designed to aid the natural healing process and to reduce the likelihood of infection. With extensive injuries, the preservation of viable tissue is paramount to functional recovery. Additionally, identifying wounds which are likely to heal without intervention, as well as those that exhibit precursors for impaired healing or infection, would assist in informing the appropriate medical care. Technologies that utilise concepts of non-contact imaging, such as optical imaging and spectroscopy can be used to obtain spatial and spectral maps of biomarkers, which provide valuable information on the wound (e.g. precursors to improper healing or delineate viable and necrotic tissue). A negative contrast imaging device (NCI) has been shown to characterise wound biopsies, through mid-IR (2.6 - 4 μm) non-invasive spectroscopic imaging. To better demonstrate the applicability of this technique, wound relevant cell cultures, subjected to induced trauma, are used to identify spectral changes between healthy and traumatised cells. This work highlights the available contrast in spectroscopic mid-IR signals and demonstrates the utility of spatially and spectrally derived maps as an assessment tool for wound diagnostics.</p

Compressive sensing based spatial frequency domain imaging reconstruction

Compressive sensing methods demonstrate the ability to collect large data sets using a reduced number of observations. Here we present advantages of compressive sensing applied to Spatial Frequency Domain Imaging.</p