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ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI.

ABSTRACT: Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.

SUBMITTER: Moia S

PROVIDER: S-EPMC8351526 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired BOLD signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example in a chronic stroke cohort with varying stroke location and degree of tissue damage.

Project description:Cerebrovascular reactivity (CVR), an index of brain vessel's dilatory capacity, is typically measured using hypercapnic gas inhalation or breath-holding as a vasoactive challenge. However, these methods require considerable subject cooperation and could be challenging in clinical studies. More recently, there have been attempts to use resting-state BOLD data to map CVR by utilizing spontaneous changes in breathing pattern. However, in subjects who have small fluctuations in their spontaneous breathing pattern, the CVR results could be noisy and unreliable. In this study, we aim to develop a new method for CVR mapping that does not require gas-inhalation yet provides substantially higher sensitivity than resting-state CVR mapping. This new method is largely based on resting-state scan, but introduces intermittent modulation of breathing pattern in the subject to enhance fluctuations in their end-tidal CO2 (EtCO2) level. Here we examined the comfort level, sensitivity, and accuracy of this method in two studies. First, in 8 healthy young subjects, we developed the intermittent breath-modulation method using two different modulation frequencies, 6 s per breath and 12 s per breath, respectively, and compared the results to three existing CVR methods, specifically hypercapnic gas inhalation, breath-holding, and resting-state. Our results showed that the comfort level of the 6-s breath-modulation method was significantly higher than breath-holding (p = 0.007) and CO2-inhalation (p = 0.015) methods, while not different from the resting-state, i.e. free breathing method (p = 0.52). When comparing the sensitivity of CVR methods, the breath-modulation methods revealed higher Z-statistics compared to the resting-state scan (p < 0.008) and was comparable to breath-holding results. Next, we tested the feasibility of breath-modulation CVR mapping (6 s per breath) in 21 cognitively normal elderly participants and compared quantitative CVR values to that obtained with the CO2-inhalation method. Whole-brain CVR was found to be 0.150 ± 0.055 and 0.154 ± 0.032 %ΔBOLD/mmHg for the breath-modulation and CO2-inhalation method, respectively, with a significant correlation between them (y = 0.97x, p = 0.007). CVR mapping with intermittent breath modulation may be a useful method that combines the advantages of resting-state and CO2-inhalation based approaches.

Project description:Age and apolipoprotein E (APOE) e4 genotype are two of the strongest known risk factors for sporadic Alzheimer's disease (AD). Neuroimaging has shown hemodynamic response changes with age, in asymptomatic carriers of the APOE e4 allele, and in AD. In this study, we aimed to characterize and differentiate age- and APOE gene-specific hemodynamic changes to breath-hold and visual stimulation. A further aim was to study whether these responses were modulated by 3-day intake of nitrate, a nitric oxide (NO) source. The study was designed as a randomized, double-blinded, placebo-controlled crossover study, and the study cohort comprised 41 APOE e4 carriers (e3/e4 or e4/e4 genotype) and 40 non-carriers (e3/e3 genotype) aged 30-70?years at enrollment. The participants underwent two scanning sessions, each preceded by ingestion of sodium nitrate or sodium chloride (control). During functional magnetic resonance imaging (fMRI) sessions, participants performed two concurrent tasks; a breath-hold task to probe cerebrovascular reactivity and a visual stimulation task to evoke functional hyperemia, respectively. We found that the blood oxygenation level dependent (BOLD) hemodynamic response to breath-hold was altered in APOE e4 carriers relative to non-carriers. Mid-aged (50-60?years of age) e4 carriers exhibited a significantly increased peak time relative to mid-aged e3 carriers, and peak time for younger (30-40?years of age) e4 carriers was significantly shorter than that of mid-aged e4 carriers. The response width was significantly increased for e4 carriers. The response peak magnitude significantly decreased with age. For the visual stimulation task, we found age-related changes, with reduced response magnitude with age but no significant effect of APOE allele type. We found no effect of nitrate ingestion on BOLD responses evoked by the breath-hold and visual stimulation tasks. The APOE gene-dependent response to breath-hold may reflect NO-independent differences in vascular function.

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ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI.

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