Toward faster inference of micron-scale axon diameters using Monte Carlo simulations

Magma (New York, N.Y.)(2018)

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摘要
Object Recent advances have allowed oscillating gradient (OG) diffusion MRI to infer the sizes of micron-scale axon diameters. Here the effects on the precision of the inferred diameters are studied when reducing the number of images collected to reduce imaging time for clinical feasibility. Materials and methods Monte Carlo simulations of cosine OG sequences (50–1000 Hz) using a two-compartment model on a parallel cylinder (diameters 1–5 μm) geometry were conducted. Temporal diffusion spectroscopy was used to infer axon diameters. Three different gradient sets were simulated with different combinations of gradient strengths. Results Five frequencies were adequate for d = 3–5 μm with single-sized cylinders and for effective mean axon diameters greater than 2 μm for cylinders with a distributions of diameters. There was some improvement in precision for d = 1–2 μm with 10 frequencies. It is better to repeat measurements at higher gradient strengths than to use a range of gradient strengths. The improvement tended to be greatest when using fewer frequencies and was especially noticeable at very high gradient strengths. Conclusion Images can be collected with fewer gradient strengths and frequencies without sacrificing the precision of the measurements. This could be useful in reducing imaging time so that OG techniques can be used in clinical settings.
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关键词
Diffusion magnetic resonance imaging,Computer simulation,Neuroanatomy
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