Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project

Bastiani, Matteo; Andersson, Jesper; Cordero‐Grande, Lucilio; Murgasova, Maria; Hutter, Jana; Price, Anthony N.; Makropoulos, Antonios; Fitzgibbon, Sean P.; Hughes, Emer; Rueckert, Daniel; Victor, Suresh; Rutherford, Mary; Edwards, A. David; Smith, Stephen M.; Tournier, Jacques‐Donald; Hajnal, Joseph V.; Jbabdi, Saâd; Sotiropoulos, Stamatios N.

doi:10.1016/j.neuroimage.2018.05.064

Cited by 160 publications

(174 citation statements)

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“…In both the nociception-paradigm and dHCP datasets, infants with larger noxious-response amplitudes (or for the dHCP data, larger predicted values) had smaller MD and larger FA values throughout the brain (Supplementary Figure 7). White matter MD decreases and FA increases throughout development into adulthood 26 , and similar to the functional measures, these developmental trends are discernible within the perinatal period 27 . The combination of negative MD and positive FA correlations suggest specific structural maturational influences, such as increasing white matter myelination, or fibre packing density, or both.…”

Section: Discussionsupporting

confidence: 53%

Functional and diffusion MRI reveal the functional and structural basis of infants’ noxious-evoked brain activity

Baxter¹,

Moultrie²,

Fitzgibbon³

et al. 2020

Preprint

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Understanding the neurophysiology underlying pain perception in infants is central to improving early life pain management. In this multimodal MRI study, we use resting-state functional and white matter diffusion MRI to investigate individual variability in infants' noxious-evoked brain activity. In an 18-infant nociception-paradigm dataset, we show it is possible to predict infants' cerebral haemodynamic responses to experimental noxious stimulation using their resting-state activity across nine networks from a separate stimulusfree scan. In an independent 215-infant Developing Human Connectome Project dataset, we use this resting-state-based prediction model to generate noxious responses. We identify a significant correlation between these predicted noxious responses and infants' white matter mean diffusivity, and this relationship is subsequently confirmed within our nociceptionparadigm dataset. These findings reveal that a newborn infant's pain-related brain activity is tightly coupled to both their spontaneous resting-state activity and underlying white matter microstructure. This work provides proof-of-concept that knowledge of an infant's functional and structural brain architecture could be used to predict pain responses, informing infant pain management strategies and facilitating evidence-based personalisation of care.

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Section: Discussionsupporting

confidence: 53%

Functional and diffusion MRI reveal the functional and structural basis of infants’ noxious-evoked brain activity

Baxter¹,

Moultrie²,

Fitzgibbon³

et al. 2020

Preprint

Self Cite

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“…Standard neuroimaging techniques do not provide quantifiable data on brain microstructural architecture, however this study has demonstrated a reproducible and reliable method for obtaining whole brain maps with quantifiable estimates of brain microstructure. This measure is stable enough to be used in longitudinal studies lasting at least up to three months; and provides information on a voxel-or region-wise basis for analysis of subcortical structures, lesions, or developing brains (Dhollander et al, 2017;Mito et al, 2018;Mito et al, 2019;Bastiani et al, 2019). Related microstructural analysis of free water signal fractions has been performed in the context of Parkinson's disease (Ofori et al, 2015;Burciu et al, 2016), Schizophrenia (Pasternak et al, 2012;Mandl et al, 2015), and concussion (Pasternak et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

“…This was followed by utilizing the FSL package ( "topup" and "eddy" ) to correct for susceptibility induced (EPI) distortions, eddy currents, and subject motion (Smith et al, 2004;Andersson et al, 2003;. Finally, we upsampled the preprocessed data to 1.3⨉1.3⨉1.3mm 3 isotropic voxels (Greenspan, 2008;Kuklisova-Murgasova et al, 2012;Bastiani et al, 2019). These preprocessing steps are largely similar to those used in other recently published works (Bastiani et al, 2019;Pietsch et al, 2019;Mito et al, 2019;Aerts et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

“…Finally, we upsampled the preprocessed data to 1.3⨉1.3⨉1.3mm 3 isotropic voxels (Greenspan, 2008;Kuklisova-Murgasova et al, 2012;Bastiani et al, 2019). These preprocessing steps are largely similar to those used in other recently published works (Bastiani et al, 2019;Pietsch et al, 2019;Mito et al, 2019;Aerts et al, 2019). Brain masks were obtained for all subjects by performing a recursive application of the Brain Extraction Tool (Avants et al, 2014).…”

Section: Methodsmentioning

confidence: 99%

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Test-retest reliability and long-term stability of 3-tissue constrained spherical deconvolution methods for analyzing diffusion MRI data

Newman

Dhollander

Reynier

et al. 2019

Preprint

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Purpose : Several recent studies have utilized a 3-tissue constrained spherical deconvolution pipeline to obtain quantitative metrics of brain tissue microstructure from diffusion-weighted MRI data. The three tissue compartments, comprising white matter-, grey matter-, and CSF-like (free water) signals, are potentially useful in the evaluation of brain microstructure in a range of pathologies. However, the reliability and long-term stability of these metrics has not yet been evaluated. Methods : This study examined estimates of whole brain microstructure for the three tissue compartments, in three separate test-retest cohorts. Each cohort has different lengths of time between baseline and retest, ranging from within the same scanning session in the shortest interval to three months in the longest interval. Each cohort was also collected with different acquisition parameters. Results : The CSF-like compartment displayed the greatest reliability across all cohorts, with intraclass correlation coefficient (ICC) values being above 0.95 in each cohort. White matter-like and grey matter-like compartments both demonstrated very high reliability in the immediate cohort (both ICC>0.90), however this declined in the 3 month interval cohort to both compartments having ICC>0.80. Regional CSF-like signal fraction was examined in bilateral hippocampus and had an ICC>0.80 in each cohort. Conclusion : The 3-tissue CSD techniques provide reliable and stable estimates of tissue microstructure composition, up to 3 months longitudinally in a control population. This forms an important basis for further investigations utilizing 3-tissue CSD techniques to track changes in microstructure across a variety of brain pathologies.

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“…We used 40 subjects from the developing HCP project (Hughes et al, 2017;Bastiani et al, 2019). The data was acquired using TR=3800 ms and TE=90 ms.…”

Section: Real Datamentioning

confidence: 99%

Evaluation of six phase encoding based susceptibility distortion correction methods for diffusion MRI

Eklund

2019

Preprint

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ITEA3 / VINNOVA funded project "Intelligence based iMprovement of Personalized treatment And Clinical workflow supporT" (IMPACT) Purpose: Susceptibility distortion impacts diffusion MRI data analysis and is typically corrected during preprocessing. Correction strategies involve three classes of methods: registration to a structural image, the use of a fieldmap or the use of images acquired with opposing phase encoding directions. It has been demonstrated that phase encoding based methods outperform the other two classes but unfortunately, the choice of which phase encoding based method to use is still an open question due to the absence of any systematic comparisons. Methods:In this paper we quantitatively evaluated six popular phase encoding based methods for correcting susceptibility distortions in diffusion MRI data. We employed a framework that allows for the simulation of realistic diffusion MRI data with susceptibility distortions. We evaluated the ability for methods to correct distortions by comparing the corrected data with the ground truth. Four diffusion tensor metrics (FA, MD, eigenvalues and eigenvectors) were calculated from the corrected data and compared with the ground truth. We also validated two popular indirect metrics using both simulated data and real data. The two indirect metrics are the difference between the corrected LR and AP data, and the FA standard deviation over the corrected LR, RL, AP and PA data. 1 2 XUAN GU ET AL. Results:We found that TOPUP offered the most accurate and robust correction than the other five methods when evaluating using both direct and indirect metrics. EPIC and HySCO performed well in correcting b 0 images but produced poor corrections for diffusion weighted volumes and they produced large errors for the four diffusion tensor metrics.We also demonstrated that the indirect metric gave a different ordering of correction quality than the direct metric. Conclusion:We suggest researchers to use TOPUP for susceptibility distortion correction. We also suggest that indirect metrics must be interpreted cautiously when evaluating methods for correcting susceptibility distortions in diffusion MRI data.

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Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project

Cited by 160 publications

References 82 publications

Functional and diffusion MRI reveal the functional and structural basis of infants’ noxious-evoked brain activity

Functional and diffusion MRI reveal the functional and structural basis of infants’ noxious-evoked brain activity

Test-retest reliability and long-term stability of 3-tissue constrained spherical deconvolution methods for analyzing diffusion MRI data

Evaluation of six phase encoding based susceptibility distortion correction methods for diffusion MRI

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