Data-science ready, multisite, human diffusion MRI white-matter-tract statistics

Tractometry of the Human Connectome Project: resources and insights

Introduction

The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data.

Methods

We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines.

Results

We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry-"Tractoscope" (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.

Early, low-dose hydrocortisone and near-term brain connectivity in extremely preterm infants

BACKGROUND

Postnatal steroids are used to prevent bronchopulmonary dysplasia in extremely preterm infants but may have adverse effects on brain development. We assessed connectivity metrics of major cerebral and cerebellar white matter pathways at near-term gestational age among infants who did or did not receive a standardized regimen of hydrocortisone during the first 10 days of life.

METHODS

Retrospective cohort study.

PARTICIPANTS

Infants born <28 weeks: Protocol group (n = 33) received at least 50% and not more than 150% of an intended standard dose of 0.5 mg/kg hydrocortisone twice daily for 7 days, then 0.5 mg/kg per day for 3 days; Non-Protocol group (n = 22), did not receive protocol hydrocortisone or completed <50% of the protocol dose. We assessed group differences in near-term diffusion MRI mean fractional anisotropy (FA) and mean diffusivity (MD) across the corticospinal tract, inferior longitudinal fasciculus, corpus callosum and superior cerebellar peduncle.

RESULTS

Groups were comparable in gestational age, post-menstrual age at scan, medical complications, bronchopulmonary dysplasia, and necrotizing enterocolitis. No significant large effect group differences were identified in mean FA or MD in any cerebral or cerebellar tract.

CONCLUSION(S)

Low dose, early, postnatal hydrocortisone was not associated with significant differences in white matter tract microstructure at near-term gestational age.

IMPACT

This study compared brain microstructural connectivity as a primary outcome among extremely preterm infants who did or did not receive early postnatal hydrocortisone. Low dose hydrocortisone in the first 10 days of life was not associated with significant differences in white matter microstructure in major cerebral and cerebellar pathways. Hydrocortisone did not have a significant effect on early brain white matter circuits.

Reproducible Tract Profiles 2 (RTP2) suite, from diffusion MRI acquisition to clinical practice and research

Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In the present work we introduce Reproducible Tract Profiles 2 (RTP2), a set of flexible and automated methods to analyze anatomical MRI and diffusion weighted imaging (DWI) data for reproducible tractography. RTP2 reads structural MRI data and processes them through a succession of serialized containerized analyses. We describe the DWI algorithms used to identify white-matter tracts and their summary metrics, the flexible architecture of the platform, and the tools to programmatically access and control the computations. The combination of these three components provides an easy-to-use automatized tool developed and tested over 20 years, to obtain usable and reliable state-of-the-art diffusion metrics at the individual and group levels for basic research and clinical practice.

Reproducible protocol to obtain and measure first-order relay human thalamic white-matter tracts

The "primary" or "first-order relay" nuclei of the thalamus feed the cerebral cortex with information about ongoing activity in the environment or the subcortical motor systems. Because of the small size of these nuclei and the high specificity of their input and output pathways, new imaging protocols are required to investigate thalamocortical interactions in human perception, cognition and language. The goal of the present study was twofold: I) to develop a reconstruction protocol based on in vivo diffusion MRI to extract and measure the axonal fiber tracts that originate or terminate specifically in individual first-order relay nuclei; and, II) to test the reliability of this reconstruction protocol. In left and right hemispheres, we investigated the thalamocortical/corticothalamic axon bundles linking each of the first-order relay nuclei and their main cortical target areas, namely, the lateral geniculate nucleus (optic radiation), the medial geniculate nucleus (acoustic radiation), the ventral posterior nucleus (somatosensory radiation) and the ventral lateral nucleus (motor radiation). In addition, we examined the main subcortical input pathway to the ventral lateral posterior nucleus, which originates in the dentate nucleus of the cerebellum. Our protocol comprised three components: defining regions-of-interest; preprocessing diffusion data; and modeling white-matter tracts and tractometry. We then used computation and test-retest methods to check whether our protocol could reliably reconstruct these tracts of interest and their profiles. Our results demonstrated that the protocol had nearly perfect computational reproducibility and good-to-excellent test-retest reproducibility. This new protocol may be of interest for both basic human brain neuroscience and clinical studies and has been made publicly available to the scientific community.

What's new and what's next in diffusion MRI preprocessing

Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the analysis of results and their interpretability if not appropriately accounted for. This review will cover dMRI artifacts and preprocessing steps, some of which have not typically been considered in existing pipelines or reviews, or have only gained attention in recent years: brain/skull extraction, B-matrix incompatibilities w.r.t the imaging data, signal drift, Gibbs ringing, noise distribution bias, denoising, between- and within-volumes motion, eddy currents, outliers, susceptibility distortions, EPI Nyquist ghosts, gradient deviations, B1 bias fields, and spatial normalization. The focus will be on "what's new" since the notable advances prior to and brought by the Human Connectome Project (HCP), as presented in the predecessing issue on "Mapping the Connectome" in 2013. In addition to the development of novel strategies for dMRI preprocessing, exciting progress has been made in the availability of open source tools and reproducible pipelines, databases and simulation tools for the evaluation of preprocessing steps, and automated quality control frameworks, amongst others. Finally, this review will consider practical considerations and our view on "what's next" in dMRI preprocessing.

Age dependency and lateralization in the three branches of the human superior longitudinal fasciculus

The superior longitudinal fascicle/fasciculus (SLF) is a major white matter tract connecting the frontal and parietal cortices in humans. Although the SLF has often been analyzed as a single entity, several studies have reported that the SLF is segregated into three distinct branches (SLF I, II, and III). They have also reported the right lateralization of the SLF III volume and discussed its relationship with lateralized cortical functions in the fronto-parietal network. However, to date, the homogeneity or heterogeneity of the age dependency and lateralization properties of SLF branches have not been fully clarified. Through this study, we aimed to clarify the age dependency and lateralization of SLF I-III by analyzing diffusion-weighted MRI (dMRI) and quantitative R1 (qR1) map datasets collected from a wide range of age groups, mostly comprising right-handed children, adolescents, adults, and seniors (6 to 81 years old). The age dependency in dMRI measurement (fractional anisotropy, FA) was heterogeneous among the three SLF branches, suggesting that these branches are regulated by distinct developmental and aging processes. Lateralization analysis on SLF branches revealed that the right SLF III was larger than the left SLF III in adults, replicating previous reports. FA measurement also suggested that, in addition to SLF III, SLF II was lateralized to the right hemisphere in adolescents and adults. We further found a left lateralization of SLF I in qR1 data, a microstructural measurement sensitive to myelin levels, in adults. These findings suggest that the SLF sub-bundles are distinct entities in terms of age dependency and lateralization.

Evaluating the Reliability of Human Brain White Matter Tractometry

The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on the reliability of analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability, and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to establish the reliability of computational analysis pipelines in neuroimaging.