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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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Edwards, Rueckert, Smith, Abo Seada, Alansary, Almalbis, Allsop, Andersson, Arichi, Arulkumaran, Bastiani, Batalle, Baxter, Bozek, Braithwaite, Brandon, Carney, Chew, Christiaens, Chung, Colford, Cordero-Grande, Counsell, Cullen, Cupitt, Curtis, Davidson, Deprez, Dillon, Dimitrakopoulou, Dimitrova, Duff, Falconer, Farahibozorg, Fitzgibbon, Gao, Gaspar, Harper, Harrison, Hughes, Hutter, Jenkinson, Jbabdi, Jones, Karolis, Kyriakopoulou, Lenz, Makropoulos, Malik, Mason, Mortari, Nosarti, Nunes, O’Keeffe, O’Muircheartaigh, Patel, Passerat-Palmbach, Pietsch, Price, Robinson, Rutherford, Schuh, Sotiropoulos, Steinweg, Teixeira, Tenev, Tournier, Tusor, Uus, Vecchiato, Williams, Wright, Wurie and Hajnal.)

Background: We tested the hypothesis that routine MRI would improve the care and well-being of preterm infants and their families., Design: Parallel-group randomised trial (1.1 allocation; intention-to-treat) with nested diagnostic and cost evaluations (EudraCT 2009-011602-42)., Setting: Participants from 14 London hospitals, imaged at a single centre., Patients: 511 infants born before 33 weeks gestation underwent both MRI and ultrasound around term. 255 were randomly allocated (siblings together) to receive only MRI results and 255 only ultrasound from a paediatrician unaware of unallocated results; one withdrew before allocation., Main Outcome Measures: Maternal anxiety, measured by the State-Trait Anxiety inventory (STAI) assessed in 206/214 mothers receiving MRI and 217/220 receiving ultrasound. Secondary outcomes included: prediction of neurodevelopment, health-related costs and quality of life., Results: After MRI, STAI fell from 36.81 (95% CI 35.18 to 38.44) to 32.77 (95% CI 31.54 to 34.01), 31.87 (95% CI 30.63 to 33.12) and 31.82 (95% CI 30.65 to 33.00) at 14 days, 12 and 20 months, respectively. STAI fell less after ultrasound: from 37.59 (95% CI 36.00 to 39.18) to 33.97 (95% CI 32.78 to 35.17), 33.43 (95% CI 32.22 to 34.63) and 33.63 (95% CI 32.49 to 34.77), p=0.02. There were no differences in health-related quality of life. MRI predicted moderate or severe functional motor impairment at 20 months slightly better than ultrasound (area under the receiver operator characteristic curve (CI) 0.74; 0.66 to 0.83 vs 0.64; 0.56 to 0.72, p=0.01) but cost £315 (CI £295-£336) more per infant., Conclusions: MRI increased costs and provided only modest benefits., Trial Registration: ClinicalTrials.gov NCT01049594 https://clinicaltrials.gov/ct2/show/NCT01049594. EudraCT: EudraCT: 2009-011602-42 (https://www.clinicaltrialsregister.eu/)., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Diffusion-weighted imaging (DWI) is becoming an increasingly important tool for studying brain development. DWI analyses relying on manually-drawn regions of interest and tractography using manually-placed waypoints are considered to provide the most accurate characterisation of the underlying brain structure. However, these methods are labour-intensive and become impractical for studies with large cohorts and numerous white matter (WM) tracts. Tract-specific analysis (TSA) is an alternative WM analysis method applicable to large-scale studies that offers potential benefits. TSA produces a skeleton representation of WM tracts and projects the group's diffusion data onto the skeleton for statistical analysis. In this work we evaluate the performance of TSA in analysing preterm infant data against results obtained from native space tractography and tract-based spatial statistics. We evaluate TSA's registration accuracy of WM tracts and assess the agreement between native space data and template space data projected onto WM skeletons, in 12 tracts across 48 preterm neonates. We show that TSA registration provides better WM tract alignment than a previous protocol optimised for neonatal spatial normalisation, and that TSA projects FA values that match well with values derived from native space tractography. We apply TSA for the first time to a preterm neonatal population to study the effects of age at scan on WM tracts around term equivalent age. We demonstrate the effects of age at scan on DTI metrics in commissural, projection and association fibres. We demonstrate the potential of TSA for WM analysis and its suitability for infant studies involving multiple tracts., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: The goal of the Developing Human Connectome Project is to acquire MRI in 1000 neonates to create a dynamic map of human brain connectivity during early development. High-quality imaging in this cohort without sedation presents a number of technical and practical challenges., Methods: We designed a neonatal brain imaging system (NBIS) consisting of a dedicated 32-channel receive array coil and a positioning device that allows placement of the infant's head deep into the coil for maximum signal-to-noise ratio (SNR). Disturbance to the infant was minimized by using an MRI-compatible trolley to prepare and transport the infant and by employing a slow ramp-up and continuation of gradient noise during scanning. Scan repeats were minimized by using a restart capability for diffusion MRI and retrospective motion correction. We measured the 1) SNR gain, 2) number of infants with a completed scan protocol, and 3) number of anatomical images with no motion artifact using NBIS compared with using an adult 32-channel head coil., Results: The NBIS has 2.4 times the SNR of the adult coil and 90% protocol completion rate., Conclusion: The NBIS allows advanced neonatal brain imaging techniques to be employed in neonatal brain imaging with high protocol completion rates. Magn Reson Med 78:794-804, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made., (© 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)