Harmonization of multi-center diffusion tensor tractography in neonates with congenital heart disease: Optimizing post-processing and application of ComBat

Meyers, Benjamin; Lee, Vince; Dennis, Lauren; Wallace, Julia; Schmithorst, Vanessa; Votava‐Smith, Jodie K.; Rajagopalan, Vidya; Herrup, Elizabeth; Baust, Tracy; Tran, Nhu; Hunter, Jill V.; Licht, Daniel J.; Gaynor, J. William; Andropoulos, Dean B.; Panigrahy, Ashok; Ceschin, Rafael

doi:10.1016/j.ynirp.2022.100114

Cited by 12 publications

(11 citation statements)

References 44 publications

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“…When combining data from multiple sites, standardizing preprocessing and quality control strategies can reduce variation between sites, however differences related to data acquisition are likely to impact extracted metrics (Galdi et al, 2024). ComBat has been used to harmonize DTI metric maps from very preterm infants imaged with different sequences on the same MRI system (Parikh et al, 2021), region of interest measures in term and preterm infants (Galdi et al, 2018), and DTI metrics along white matter tractography reconstruction in infants with congenital heart disease (Meyers et al, 2022). We add to this literature by demonstrating that ComBat successfully harmonizes voxel-wise DTI metrics as well as mean values and histogram widths from the white matter skeleton.…”

Section: Discussionmentioning

confidence: 99%

Harmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience

Bonthrone,

Blesa Cábez,

Edwards

et al. 2024

Preprint

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Large diffusion-weighted brain MRI (dMRI) studies in neonates are crucial for developmental neuroscience. Our aim was to investigate the utility of ComBat, and empirical Bayes tool for multisite harmonization, for removing site effects from white matter (WM) dMRI measures in healthy infants born 37-42+6 weeks from the Theirworld Edinburgh Birth Cohort (n=86) and Developing Human Connectome Project (n=287). Skeletonized fractional anisotropy (FA), mean, axial and radial diffusivity (MD, AD, RD) maps were harmonized. The differences between voxel-wise metrics, skeleton means and histogram widths (5th-95th percentile) were assessed before and after harmonization, as well as variance associated with gestational age at birth. Before harmonization, large cohort differences were observed in all measures. Harmonization removed all voxel-wise differences from MD maps and all metric means and histogram widths, however small voxel-wise differences (<1.5% of voxels) remained in FA, AD and RD. We detected significant relationships between GA at birth and all metrics. When comparing single site and multi-site harmonized datasets of equal sample sizes, harmonized data resulted in smaller standardized regression coefficients. ComBat will enable unprecedented sample sizes in developmental neuroscience, offering new horizons for biomarker discovery and validation, understanding typical and atypical brain development, and assessment of neuroprotective therapies.

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Section: Discussionmentioning

confidence: 99%

Harmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience

Bonthrone,

Blesa Cábez,

Edwards

et al. 2024

Preprint

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“…Structural white matter features were generated using our previously developed automated tractography pipeline. 22 Initially developed for group analysis of neonatal diffusion imaging, we have since generalized it to use with population and age-appropriate region of interest templates for tracking. We generated along-tract diffusivity measures – fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) – of 18 inter-hemispheric and cortico-association fibers.…”

Section: Methodsmentioning

confidence: 99%

Cerebral Spinal Fluid Volumetrics and Paralimbic Predictors of Executive Dysfunction in Congenital Heart Disease: A Machine Learning Approach Informing Mechanistic Insights

Lee,

Wallace,

Meyers

et al. 2023

Preprint

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The relationship between increased cerebral spinal fluid (CSF) ventricular compartments, structural and microstructural dysmaturation, and executive function in patients with congenital heart disease (CHD) is unknown. Here, we leverage a novel machine-learning data-driven technique to delineate interrelationships between CSF ventricular volume, structural and microstructural alterations, clinical risk factors, and sub-domains of executive dysfunction in adolescent CHD patients. We trained random forest regression models to predict measures of executive function (EF) from the NIH Toolbox, the Delis-Kaplan Executive Function System (D-KEFS), and the Behavior Rating Inventory of Executive Function (BRIEF) and across three subdomains of EF - mental flexibility, working memory, and inhibition. We estimated the best parameters for the random forest algorithm via a randomized grid search of parameters using 10-fold cross-validation on the training set only. The best parameters were then used to fit the model on the full training set and validated on the test set. Algorithm performance was measured using root-mean squared-error (RMSE). As predictors, we included patient clinical variables, perioperative clinical measures, microstructural white matter (diffusion tensor imaging- DTI), and structural volumes (volumetric magnetic resonance imaging- MRI). Structural white matter was measured using along-tract diffusivity measures of 13 inter-hemispheric and cortico-association fibers. Structural volumes were measured using FreeSurfer and manual segmentation of key structures. Variable importance was measured by the average Gini-impurity of each feature across all decision trees in which that feature is present in the model, and functional ontology mapping (FOM) was used to measure the degree of overlap in feature importance for each EF subdomain and across subdomains. We found that CSF structural properties (including increased lateral ventricular volume and reduced choroid plexus volumes) in conjunction with proximate cortical projection and paralimbic-related association white matter tracts that straddle the lateral ventricles and distal paralimbic-related subcortical structures (basal ganglia, hippocampus, cerebellum) are predictive of two-specific subdomains of executive dysfunction in CHD patients: cognitive flexibility and inhibition. These findings in conjunction with combined RF models that incorporated clinical risk factors, highlighted important clinical risk factors, including the presence of microbleeds, altered vessel volume, and delayed PDA closure, suggesting that CSF-interstitial fluid clearance, vascular pulsatility, and glymphatic microfluid dynamics may be pathways that are impaired in CHD, providing mechanistic information about the relationship between CSF and executive dysfunction.

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“…COMBAT can also be effective with small sample size and provide regional-specific correction factors for multimodal neuroimaging data [ 128 , 129 , 130 ]. We have recently successfully applied this COMBAT technique to a four-center DTI dataset of n = 763 neonates with CHD [ 131 ].…”

Section: Methods and Designsmentioning

confidence: 99%

Design and Harmonization Approach for the Multi-Institutional Neurocognitive Discovery Study (MINDS) of Adult Congenital Heart Disease (ACHD) Neuroimaging Ancillary Study: A Technical Note

Panigrahy,

Schmithorst,

Ceschin

et al. 2023

JCDD

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Dramatic advances in the management of congenital heart disease (CHD) have improved survival to adulthood from less than 10% in the 1960s to over 90% in the current era, such that adult CHD (ACHD) patients now outnumber their pediatric counterparts. ACHD patients demonstrate domain-specific neurocognitive deficits associated with reduced quality of life that include deficits in educational attainment and social interaction. Our hypothesis is that ACHD patients exhibit vascular brain injury and structural/physiological brain alterations that are predictive of specific neurocognitive deficits modified by behavioral and environmental enrichment proxies of cognitive reserve (e.g., level of education and lifestyle/social habits). This technical note describes an ancillary study to the National Heart, Lung, and Blood Institute (NHLBI)-funded Pediatric Heart Network (PHN) “Multi-Institutional Neurocognitive Discovery Study (MINDS) in Adult Congenital Heart Disease (ACHD)”. Leveraging clinical, neuropsychological, and biospecimen data from the parent study, our study will provide structural–physiological correlates of neurocognitive outcomes, representing the first multi-center neuroimaging initiative to be performed in ACHD patients. Limitations of the study include recruitment challenges inherent to an ancillary study, implantable cardiac devices, and harmonization of neuroimaging biomarkers. Results from this research will help shape the care of ACHD patients and further our understanding of the interplay between brain injury and cognitive reserve.

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Harmonization of multi-center diffusion tensor tractography in neonates with congenital heart disease: Optimizing post-processing and application of ComBat

Cited by 12 publications

References 44 publications

Harmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience

Harmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience

Cerebral Spinal Fluid Volumetrics and Paralimbic Predictors of Executive Dysfunction in Congenital Heart Disease: A Machine Learning Approach Informing Mechanistic Insights

Design and Harmonization Approach for the Multi-Institutional Neurocognitive Discovery Study (MINDS) of Adult Congenital Heart Disease (ACHD) Neuroimaging Ancillary Study: A Technical Note

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