Evaluation of multi-echo ICA denoising for task based fMRI studies: Block designs, rapid event-related designs, and cardiac-gated fMRI.

Multi-echo fMRI, particularly the multi-echo independent component analysis (ME-ICA) algorithm, has previously proven useful for increasing the sensitivity and reducing false positives for functional MRI (fMRI) based resting state connectivity studies. Less is known about its efficacy for task-based fMRI, especially at the single subject level. This work, which focuses exclusively on individual subject results, compares ME-ICA to single-echo fMRI and a voxel-wise T2(⁎) weighted combination of multi-echo data for task-based fMRI under the following scenarios: cardiac-gated block designs, constant repetition time (TR) block designs, and constant TR rapid event-related designs. Performance is evaluated primarily in terms of sensitivity (i.e., activation extent, activation magnitude, percent detected trials and effect size estimates) using five different tasks expected to evoke neuronal activity in a distributed set of regions. The ME-ICA algorithm significantly outperformed all other evaluated processing alternatives in all scenarios. Largest improvements were observed for the cardiac-gated dataset, where ME-ICA was able to reliably detect and remove non-neural T1 signal fluctuations caused by non-constant repetition times. Although ME-ICA also outperformed the other options in terms of percent detection of individual trials for rapid event-related experiments, only 46% of all events were detected after ME-ICA; suggesting additional improvements in sensitivity are required to reliably detect individual short event occurrences. We conclude the manuscript with a detailed evaluation of ME-ICA outcomes and a discussion of how the ME-ICA algorithm could be further improved. Overall, our results suggest that ME-ICA constitutes a versatile, powerful approach for advanced denoising of task-based fMRI, not just resting-state data.

Quantitative ischemia detection during cardiac magnetic resonance stress testing by use of FastHARP.

BACKGROUND: Because ECG alterations caused by ischemia cannot be reliably detected in the high-field MRI environment, detection of wall motion abnormalities is often used to ensure patient safety during stress testing. However, an experienced observer is needed to detect these abnormalities. In this study, we investigate the use of fast harmonic phase (FastHARP) MRI for the quantitative, operator-independent detection of the onset of ischemia during acute coronary occlusion. METHODS AND RESULTS: Eight mongrel dogs underwent an acute 2-minute closed-chest coronary artery occlusion while continuous FastHARP images were acquired. Full regional wall strain was determined every other heartbeat in a single short-axis imaging slice. After 5 minutes of reperfusion, a second 2-minute ischemic episode was induced during the acquisition of conventional cine wall-motion images. The time at which ECG alterations were observed during the first ischemic period was recorded. The time from occlusion to the detection of ischemia, based on a consensus of 2 blinded observers, was determined for MRI. No significant ischemia was present in 2 animals. In the remaining animals, the onset of ischemia was detected significantly earlier by FastHARP than by cine MRI (9.5+/-5 versus 33+/-14 seconds, P<0.01). HARP ischemia detection preceded ECG changes, on average, by 54 seconds. CONCLUSIONS: The rapid acquisition and detection of induced ischemia with FastHARP MRI shows promise as a nonsubjective method to diagnose significant coronary lesions during MR stress testing.