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Bunce, E. V.

Publications and source records attributed to Bunce, E. V..

2 recordsLinked to original sources

The in vitro dynamics of pseudo-vascular network formation.

Pseudo-vascular network formation capacity in vitro is considered a key characteristic of vasculogenic mimicry. While many cancer cell lines are known to form pseudo-vascular networks, little is known about the spatiotemporal dynamics of these formations. Here, we present a framework for monitoring and characterising the dynamic formation and dissolution of pseudo-vascular networks in vitro. The framework combines time-resolved optical microscopy with open-source image analysis for network feature extraction and statistical modelling. The framework is demonstrated by comparing diverse cancer cell lines associated with vasculogenic mimicry, then in detecting response to drug compounds proposed to affect formation of vasculogenic mimics. Dynamic datasets collected were analysed morphometrically and a descriptive statistical analysis model was developed in order to measure stability and dissimilarity characteristics of the pseudo-vascular networks formed. Melanoma cells formed the most stable pseudo-vascular networks and were selected to evaluate the response of their pseudo-vascular networks to treatment with axitinib, brucine and tivantinib. Our framework is shown to enable quantitative analysis of both the capacity for network formation, linked vasculogenic mimicry, as well as dynamic responses to treatment.

cancer biology↗

The effects of skin tone on photoacoustic imaging and oximetry

SignificancePhotoacoustic imaging (PAI) provides contrast based on the concentration of optical absorbers in tissue, enabling the assessment of functional physiological parameters such as blood oxygen saturation (sO2). Recent evidence suggests that variation in melanin levels in the epidermis leads to measurement biases in optical technologies, which could potentially limit the application of these biomarkers in diverse populations. AimTo examine the effects of skin melanin pigmentation on photoacoustic imaging and oximetry. ApproachWe evaluated the effects of skin tone in PAI using a computational skin model, two-layer melanin-containing tissue-mimicking phantoms, and mice of a consistent genetic background with varying pigmentations. The computational skin model was validated by simulating the diffuse reflectance spectrum using the adding-doubling method, allowing us to assign our simulation parameters to approximate Fitzpatrick skin types. Monte Carlo simulations and acoustic simulations were run to obtain idealised photoacoustic images of our skin model. Photoacoustic images of the phantoms and mice were acquired using a commercial instrument. Reconstructed images were processed with linear spectral unmixing to estimate blood oxygenation. Linear unmixing results were compared with a learned unmixing approach based on gradient-boosted regression. ResultsOur computational skin model was consistent with representative literature for in vivo skin reflectance measurements. We observed consistent spectral colouring effects across all model systems, with an overestimation of sO2 and more image artefacts observed with increasing melanin concentration. The learned unmixing approach reduced the measurement bias, but predictions made at lower blood sO2 still suffered from a skin tone-dependent effect. ConclusionPAI demonstrates measurement bias, including an overestimation of blood sO2, in higher Fitzpatrick skin types. Future research should aim to characterise this effect in humans to ensure equitable application of the technology.

bioengineering↗