@inproceedings{4ad4312e413b46bf8602b2097419081f,
title = "Ground Truth for Diffusion MRI in Cancer: A Model-Based Investigation of a Novel Tissue-Mimetic Material",
abstract = "This work presents preliminary results on the development, characterisation, and use of a novel physical phantom designed as a simple mimic of tumour cellular structure, for diffusion-weighted magnetic resonance imaging (DW-MRI) applications. The phantom consists of a collection of roughly spherical, micron-sized core-shell polymer 'cells', providing a system whose ground truth microstructural properties can be determined and compared with those obtained from modelling the DW-MRI signal. A two-compartment analytic model combining restricted diffusion inside a sphere with hindered extracellular diffusion was initially investigated through Monte Carlo diffusion simulations, allowing a comparison between analytic and simulated signals. The model was then fitted to DW-MRI data acquired from the phantom over a range of gradient strengths and diffusion times, yielding estimates of 'cell' size, intracellular volume fraction and the free diffusion coefficient. An initial assessment of the accuracy and precision of these estimates is provided, using independent scanning electron microscope measurements and bootstrap-style simulations. Such phantoms may be useful for testing microstructural models relevant to the characterisation of tumour tissue.",
author = "Damien Mchugh and Fenglei Zhou and Penny Cristinacce and Naish, {Josephine H} and Geoff Parker",
note = "C8742/A18097, Cancer Research UK, United Kingdom, Biotechnology and Biological Sciences Research Council, United Kingdom, Medical Research Council, United Kingdom",
year = "2015",
month = jun,
day = "23",
doi = "10.1007/978-3-319-19992-4_14",
language = "English",
isbn = "978-3-319-19991-7",
volume = "9123",
series = "Lecture Notes in Computer Science (LNCS)",
publisher = "Springer Nature",
pages = "179--190",
booktitle = "International Conference on Information Processing in Medical Imaging",
address = "United States",
}