Cardiorespiratory noise correction improves the ASL signal

ASL MRI informs blood flow to chronic stroke lesions in patients with aphasia

Introduction: Response to post-stroke aphasia language rehabilitation is difficult to anticipate, mainly because few predictors can help identify optimal, individualized treatment options. Imaging techniques, such as Voxel-based Lesion Symptom Mapping have been useful in linking specific brain areas to language behavior; however, further development is required to optimize the use of structural and physiological information in guiding individualized treatment for persons with aphasia (PWA). In this study, we will determine if cerebral blood flow (CBF) mapped in patients with chronic strokes can be further used to understand stroke-related factors and behavior. Methods: We collected perfusion MRI data using pseudo-Continuous Arterial Spin Labeling (pCASL) using a single post-labeling delay of 2,200 ms in 14 chronic PWA, along with high-resolution structural MRI to compute maps of tissue damage using Tissue Integrity Gradation via T2w T1w Ratio (TIGR). To quantify the CBF in chronic stroke lesions, we tested at what point spatial smoothing should be applied in the ASL analysis pipeline. We then related CBF to tissue damage, time since stroke, age, sex, and their respective cross-terms to further understand the variability in lesion CBF. Finally, we assessed the feasibility of computing multivariate brain-behavior maps using CBF and compared them to brain-behavior maps extracted with TIGR MRI. Results: We found that the CBF in chronic stroke lesions is significantly reduced compared to its homologue grey and white matter regions. However, a reliable CBF signal (although smaller than expected) was detected to reveal a negative relationship between CBF and increasing tissue damage. Further, the relationship between the lesion CBF and age, sex, time since stroke, and tissue damage and cross-terms suggested an aging-by-disease interaction. This relationship was strongest when smoothing was applied in the template space. Finally, we show that whole-brain CBF relates to domain-general visuospatial functioning in PWA. The CBF-based brain-behavior maps provide unique and complementary information to structural (lesion-based) brain-behavior maps. Discussion: Therefore, CBF can be detected in chronic stroke lesions using a standard pCASL MRI acquisition and is informative at the whole-brain level in identifying stroke rehabilitation targets in PWAs due to its relationship with demographic factors, stroke-related factors, and behavior.

The Hybrid Excess and Decay (HED) model: an automated approach to characterising changes in the photoplethysmography pulse waveform

Photoplethysmography offers a widely used, convenient and non-invasive approach to monitoring basic indices of cardiovascular function, such as heart rate and blood oxygenation. Systematic analysis of the shape of the waveform generated by photoplethysmography might be useful to extract estimates of several physiological and psychological factors influencing the waveform. Here, we developed a robust and automated method for such a systematic analysis across individuals and across different physiological and psychological contexts. We describe a psychophysiologically-relevant model, the Hybrid Excess and Decay (HED) model, which characterises pulse wave morphology in terms of three underlying pressure waves and a decay function. We present the theoretical and practical basis for the model and demonstrate its performance when applied to a pharmacological dataset of 105 participants receiving intravenous administrations of the sympathomimetic drug isoproterenol (isoprenaline). We show that these parameters capture photoplethysmography data with a high degree of precision and, moreover, are sensitive to experimentally-induced changes in interoceptive arousal within individuals. We conclude by discussing the possible value in using the HED model as a complement to standard measures of photoplethysmography signals.

Influence of the cardiac cycle on velocity selective and acceleration selective arterial spin labeling

Purpose

In this study, the influence of the cardiac cycle on the amount of label produced by a velocity‐selective (VSASL) and acceleration‐selective arterial spin labeling (AccASL) module was investigated.

Methods

A short‐PLD sequence was developed where a single VSASL‐ or AccASL‐module was preceded by pCASL labeling to isolate the arterial blood pool. ASL subtraction was performed with label/control images with similar cardiac phase and time‐of‐measurement, followed by retrospective binning in 10 cardiac phase bins. ASL signal variation over the heart cycle was evaluated and tested for significance using a permutation test.

Results

VSASL and AccASL showed significant arterial signal fluctuations over the cardiac cycle of up to ~36% and ~64%, respectively, mainly in areas containing large arteries. pCASL also showed significant signal fluctuations, of up to ~25% in arteries. Raw label/control images confirmed that the observed signal fluctuations were caused by the amount of label produced during the cardiac cycle, rather than inflow‐effects, because the raw images did not all show equal cardiac phase dependence.

No significant effects of the cardiac cycle were found on the gray matter ASL‐signal.

Conclusion

Significant influence of the cardiac cycle on the generated label was found for spatially nonselective ASL‐sequences. Hence, to become independent of the cardiac cycle, sufficient averages need to be taken. Alternatively, these findings could be highly interesting for the purpose of quantifying pulsatility more distally in the vascular tree.

Cardiorespiratory noise correction improves the ASL signal

Cardiorespiratory fluctuations such as changes in heart rate or respiration volume influence the temporal dynamics of cerebral blood flow (CBF) measurements during arterial spin labeling (ASL) fMRI. This "physiological noise" can confound estimates of resting state network activity, and it may lower the signal-to-noise ratio of ASL during task-related experiments. In this study we examined several methods for minimizing the contributions of both synchronized and non-synchronized physiological noise in ASL measures of CBF, by combining the RETROICOR approach with different linear deconvolution models. We evaluated the amount of variance in CBF that could be explained by each method during physiological rest, in both resting state and task performance conditions. To further demonstrate the feasibility of this approach, we induced low-frequency cardiorespiratory deviations via peripheral adrenergic stimulation with isoproterenol, and determined how these fluctuations influenced CBF, before and after applying noise correction. By suppressing physiological noise, we observed substantial improvements in the signal-to-noise ratio at the individual and group activation levels. Our results suggest that variations in cardiac and respiratory parameters can account for a large proportion of the variance in resting and task-based CBF, and indicate that regressing out these non-neuronal signal variations improves the intrinsically low signal-to-noise ratio of ASL. This approach may help to better identify and control physiologically driven activations in ASL resting state and task-based analyses.