2016
DOI: 10.1002/mrm.26469
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Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue

Abstract: PurposeTo investigate the sensitivity of diffusion‐MR signal to microstructural change in muscle tissue associated with pathology, and recommend optimal acquisition parameters.MethodsWe employ Monte‐Carlo simulation of diffusing spins in hierarchical tissue to generate synthetic diffusion‐weighted signal curves over a wide range of scan parameters. Curves are analyzed using entropy—a measure of curve complexity. Entropy change between a baseline and various microstructural scenarios is investigated. We find ac… Show more

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Cited by 22 publications
(51 citation statements)
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References 28 publications
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“…Convergence tests in in Supporting Information Figure S1 show that 10 repetitions per data point using N P = 10 4 and N T = 10 3 is sufficient to reliably compute DT‐CMR parameters while keeping the simulation within an acceptable runtime. These findings are consistent with the observations in simulations of cardiac and brain tissue . The normally‐distributed step lengths aid convergence and a rejection threshold of ±5σ is sufficient for accuracy (Supporting Information Figure S2).…”
Section: Discussionsupporting
confidence: 87%
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“…Convergence tests in in Supporting Information Figure S1 show that 10 repetitions per data point using N P = 10 4 and N T = 10 3 is sufficient to reliably compute DT‐CMR parameters while keeping the simulation within an acceptable runtime. These findings are consistent with the observations in simulations of cardiac and brain tissue . The normally‐distributed step lengths aid convergence and a rejection threshold of ±5σ is sufficient for accuracy (Supporting Information Figure S2).…”
Section: Discussionsupporting
confidence: 87%
“…In the past, other groups have used various methods to synthesise DTI data. The diffusion MRI software package Camino has been used to simulate a wide range of geometries with applications to the brain . However, these studies lack the long diffusion times and microstructural architecture characteristic of DT‐CMR.…”
Section: Discussionmentioning
confidence: 99%
“…With increasing Δ, water diffusion tends to a finite non‐zero value. This is probably a result of the presence of water exchange between intracellular and extracellular spaces because of the finite water permeability of cell membranes . However, at short Δ values, which correspond to diffusion lengths much smaller than the typical separation between barriers, only a very small proportion of spins interact with restricting structure and the overall diffusion behaviour is less restricted.…”
Section: Discussionmentioning
confidence: 99%
“…A change in curvature is indicative of alterations in restriction as a result of the overall permeability of the internal structure between young and mature muscles. It is possible, therefore, that the higher ADC values observed across the studied diffusion time range in young muscle are caused by greater fibre permeability in 7.5‐week‐old animals compared with 22‐ and 44‐week‐old animals, and this effect dominates over ADC differences arising from fibre size …”
Section: Discussionmentioning
confidence: 99%
“…Further, DTI combined with diffusion models is increasingly being used to explore tissue microstructural parameters such as fiber diameter, permeability, or intracellular volume fraction . While most modeling studies have focused on the brain, a few recent studies have extended modeling efforts to the diffusion in skeletal muscle . Recent studies have combined magnetic resonance imaging (MRI) deformation analyses and DTI tractography in the medial gastrocnemius (MG) .…”
mentioning
confidence: 99%