Evaluating the accuracy and precision of a two-compartment Kärger model using Monte Carlo simulations.

Markus Nilsson, Erik Alerstam, Ronnie Wirestam, Freddy Ståhlberg, Sara Brockstedt, Jimmy Lätt

Research output: Contribution to journalArticlepeer-review

41 Citations (SciVal)

Abstract

Specific parameters of the neuronal tissue microstructure, such as axonal diameters, membrane permeability and intracellular water fractions are assessable using diffusion MRI. These parameters are commonly estimated using analytical models, which may introduce bias in the estimated parameters due to the approximations made when deriving the models. As an alternative to using analytical models, a database of signal curves generated by fast Monte Carlo simulations can be employed. Simulated diffusion MRI measurements were generated and evaluated using the two-compartment Kärger model as well as the simulation model based on a database containing signal curves from approximately 60000 simulations performed with different combinations of microstructural parameters. A protocol based on a pulsed gradient spin echo sequence with diffusion times of 30 and 60ms and with gradient amplitudes obtainable with a clinical MRI scanner was employed for the investigations. When using the analytical model, a major negative bias (up to approximately 25%) in the estimated intracellular volume fraction was observed for short exchange times, while almost no bias was seen for the simulation model. In general, the simulation model improved the accuracy of the estimated parameters as compared to the analytical model, except for the exchange time parameter.
Original languageEnglish
Pages (from-to)59-67
JournalJournal of Magnetic Resonance
Volume206
Issue number1
DOIs
Publication statusPublished - 2010

Subject classification (UKÄ)

  • Radiology, Nuclear Medicine and Medical Imaging

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