Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate’s observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants’ voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.

Structural and diffusion MRI provide complimentary anatomical and microstructural characterization of early brain maturation. The existing models of the developing brain in time include only either structural or diffusion channels. Furthermore, there is a lack of tools for combined analysis of structural and diffusion MRI in the same reference space. In this work we propose methodology to generate multi-channel (MC) continuous spatio-temporal parametrized atlas of brain development based on MC registration driven by both T2-weighted and orientation distribution functions (ODF) channels along with the Gompertz model (GM) fitting of the signals and spatial transformations in time. We construct a 4D MC atlas of neonatal brain development during 38 to 44 week PMA range from 170 normal term subjects from developing Human Connectomme Project. The resulting atlas consists of fourteen spatio-temporal microstructural indices and two parcellation maps delineating white matter tracts and neonatal transient structures. We demonstrate applicability of the atlas for quantitative region-specific comparison of 140 term and 40 preterm subjects scanned at the term-equivalent age. We show multi-parametric microstructural differences in multiple white matter regions, including the transient compartments. The atlas and software will be available after publication of the article.