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Allam, N.

Publications and source records attributed to Allam, N..

2 recordsLinked to original sources

Low-Cost 3D-Printed Tools Towards Robust Longitudinal Multi-Modal Pre-Clinical Imaging

1Window chamber models enable a range of preclinical in-vivo optical studies with high spatial resolution and contrast, most notably probing the tumour microenvironment (TME). However, there are multiple sources of experimental variability that can affect the quality of the resultant data, especially in the context of longitudinal data acquisition, where accurate registration between images acquired at different times is crucial to understanding changes to the spatially heterogeneous TME. Further, it is challenging to correlate the findings of these models to clinical imaging modalities such as magnetic resonance imaging (MRI), which typically have much lower resolution and derive contrast from different physical mechanisms; yet such correlations may assist in the translation of window-chamber-derived basic preclinical insights into the clinic. Here, we describe the development and construction of a low-cost 3D-printable window chambers and compatible toolset to improve the accuracy, precision, and repeatability of longitudinal pre-clinical imaging and inter-modality co-registration at different spatial resolution scales. Such improvements in our novel multi-modal experimental pipeline may assist researchers in the acquisition and translation of TME biomarkers and other pre-clinical measurements from the window chamber model into the clinic.

biophysics↗

Differentiation of semi-transparent tissue phantom inclusions using optical coherence tomography towards label-free neurography and lymphography

SignificanceLymphatic and peripheral nervous system imaging is of prime importance for monitoring various important pathologic processes including cancer development, metastasis, and response to therapy. AimOptical coherence tomography (OCT) is a promising approach for this imaging task but is challenged by the near-transparent nature of these structures. Our aim is to detect and differentiate semi-transparent materials using OCT texture analysis, towards label-free neurography and lymphography. ApproachWe have recently demonstrated a novel OCT texture analysis-based approach that used speckle statistics to image lymphatics and nerves in-vivo that does not rely on negative contrast. However, these two near-transparent structures could not be differentiated from each other easily in the texture analysis parameter space. Here we perform a rigorous follow-up study to improve upon this differentiation in controlled phantoms mimicking the optical properties of these tissues. ResultsThe results of the three-parameter Rayleigh distribution fit to the OCT images of six types of tissue-mimicking materials varying in transparency and biophysical properties demonstrate clear differences between them, suggesting routes for improved lymphatics-nerves differentiation. ConclusionsWe demonstrate a novel OCT texture analysis based lymphatics-nerves differentiation methodology in tissue-simulating phantoms. Future work will focus on in-vivo lymphangiography and neurography studies of longitudinal treatment monitoring for therapy feedback and optimization.

cancer biology↗