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Updated: Sep 25, 2026
A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
Published on: September 16, 2017
Temporal relation between the ADC and DC potential responses to transient focal ischemia in the rat: a Markov chain
Martin D King1, Martin J Crowder, David J Hand
1RCS Unit of Biophysics, Institute of Child Health, University College, London, UK. M.King@inc.ucl.ac.uk
Insights
Markov chain Monte Carlo simulation revealed distinct temporal patterns in direct current (DC) potential and apparent diffusion coefficient (ADC) responses to focal ischemia. These findings indicate separate underlying processes, not a common driving mechanism.
Area of Science:
- Biomedical research
- Neuroscience
- Medical imaging analysis
Background:
- Focal ischemia studies often involve analyzing longitudinal data on direct current (DC) potential and apparent diffusion coefficient (ADC).
- Understanding the temporal relationship between DC and ADC responses is crucial for stroke research.
- Previous analyses may not have formally assessed a common latent process driving both responses.
Purpose of the Study:
- To formally analyze the temporal relationship between apparent diffusion coefficient (ADC) and direct current (DC) potential responses to focal ischemia.
- To investigate the potential involvement of a common latent process influencing both DC and ADC changes.
- To apply advanced statistical modeling to longitudinal biomedical data.
Main Methods:
- Reanalysis of longitudinal data using Markov chain Monte Carlo (MCMC) simulation.
- Application of a Bayesian nonlinear hierarchical random coefficients model.
- Generation of posterior probability distributions for DC and ADC transition parameters via Metropolis algorithm with three parallel Markov chains.
Main Results:
- The direct current (DC) potential response to focal ischemia was found to be biphasic.
- The apparent diffusion coefficient (ADC) response exhibited monophasic behavior.
- Distinct temporal dependencies were observed between the two DC components and the ADC response, refuting a common latent driving process.
Conclusions:
- The DC and ADC changes in response to focal ischemia are not driven by a single common latent process.
- This study demonstrates a robust analytical approach for multivariate, longitudinal data in stroke and biomedical research.
- The distinct temporal characteristics of DC and ADC responses offer new insights into ischemic pathophysiology.
Abstract:
Markov chain Monte Carlo simulation was used in a reanalysis of the longitudinal data obtained by Harris et al. (J Cereb Blood Flow Metab 20:28-36) in a study of the direct current (DC) potential and apparent diffusion coefficient (ADC) responses to focal ischemia. The main purpose was to provide a formal analysis of the temporal relationship between the ADC and DC responses, to explore the possible involvement of a common latent (driving) process. A Bayesian nonlinear hierarchical random coefficients model was adopted. DC and ADC transition parameter posterior probability distributions were generated using three parallel Markov chains created using the Metropolis algorithm. Particular attention was paid to the within-subject differences between the DC and ADC time course characteristics. The results show that the DC response is biphasic, whereas the ADC exhibits monophasic behavior, and that the two DC components are each distinguishable from the ADC response in their time dependencies. The DC and ADC changes are not, therefore, driven by a common latent process. This work demonstrates a general analytical approach to the multivariate, longitudinal data-processing problem that commonly arises in stroke and other biomedical research.
