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Updated: Jul 2, 2025
Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury
Published on: August 14, 2019
Impact of truncating diffusion MRI scans on diffusional kurtosis imaging
Ana R Fouto1, Rafael N Henriques2, Marc Golub3
1Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal. anafouto@tecnico.ulisboa.pt.
Objective:
Diffusional kurtosis imaging (DKI) extends diffusion tensor imaging (DTI), characterizing non-Gaussian diffusion effects but requires longer acquisition times. To ensure the robustness of DKI parameters, data acquisition ordering should be optimized allowing for scan interruptions or shortening. Three methodologies were used to examine how reduced diffusion MRI scans impact DKI histogram-metrics: 1) the electrostatic repulsion model (OptEEM); 2) spherical codes (OptSC); 3) random (RandomTRUNC).
Materials And Methods:
Pre-acquired diffusion multi-shell data from 14 female healthy volunteers (29±5 years) were used to generate reordered data. For each strategy, subsets containing different amounts of the full dataset were generated. The subsampling effects were assessed on histogram-based DKI metrics from tract-based spatial statistics (TBSS) skeletonized maps. To evaluate each subsampling method on simulated data at different SNRs and the influence of subsampling on in vivo data, we used a 3-way and 2-way repeated measures ANOVA, respectively.
Results:
Simulations showed that subsampling had different effects depending on DKI parameter, with fractional anisotropy the most stable (up to 5% error) and radial kurtosis the least stable (up to 26% error). RandomTRUNC performed the worst while the others showed comparable results. Furthermore, the impact of subsampling varied across distinct histogram characteristics, the peak value the least affected (OptEEM: up to 5% error; OptSC: up to 7% error) and peak height (OptEEM: up to 8% error; OptSC: up to 11% error) the most affected.
Conclusion:
The impact of truncation depends on specific histogram-based DKI metrics. The use of a strategy for optimizing the acquisition order is advisable to improve DKI robustness to exam interruptions.
Insights
Optimizing diffusion MRI scan order improves robustness of diffusion kurtosis imaging (DKI) metrics. Strategies like electrostatic repulsion and spherical codes are better than random truncation for shorter scans.
Area of Science:
- Neuroimaging
- Quantitative MRI
Background:
- Diffusional kurtosis imaging (DKI) offers advanced characterization of diffusion compared to diffusion tensor imaging (DTI).
- DKI requires longer acquisition times, posing challenges for scan robustness and interruptions.
- Optimizing data acquisition order is crucial for reliable DKI parameter estimation.
Purpose of the Study:
- To evaluate the impact of reduced diffusion MRI scan durations on histogram-based DKI metrics.
- To compare the effectiveness of different data acquisition ordering strategies: electrostatic repulsion model (OptEEM), spherical codes (OptSC), and random truncation (RandomTRUNC).
Main Methods:
- Diffusion multi-shell data from 14 healthy volunteers were reordered using OptEEM, OptSC, and RandomTRUNC strategies.
- Subsets of varying sizes were generated to simulate shortened scans.
- Effects on histogram-based DKI metrics were assessed using tract-based spatial statistics (TBSS) skeletonized maps.
- Simulations and repeated measures ANOVA were used to evaluate subsampling effects on data with varying signal-to-noise ratios (SNRs) and in vivo data.
Main Results:
- Subsampling effects varied by DKI parameter; fractional anisotropy was most stable (up to 5% error), while radial kurtosis was least stable (up to 26% error).
- RandomTRUNC performed worst, while OptEEM and OptSC showed comparable results.
- Histogram peak value was least affected (up to 7% error), while peak height was most affected (up to 11% error).
Conclusions:
- The impact of scan shortening on DKI metrics depends on the specific metric and histogram characteristic.
- Employing optimized acquisition order strategies enhances DKI robustness against scan interruptions or shortening.
- This optimization is advisable for clinical applications requiring efficient MRI acquisition.
