Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

IntroductionWe conducted a phase 1 clinical trial in nine patients with mild-to-moderate Alzheimer's disease to evaluate the safety and dose-limiting toxicity of stereotactic brain injection of human umbilical cord blood–derived mesenchymal stem cells (hUCB-MSCs).MethodsThe low- (n = 3) and high-dose (n = 6) groups received a total of 3.0 × 106 cells/60 μL and 6.0 × 106 cells/60 μL, respectively, into the bilateral hippocampi and right precuneus.ResultsNo patient showed serious adverse events including fever during the 24-month follow-up period. During the 12-week follow-up period, the most common acute adverse event was wound pain from the surgical procedure (n = 9), followed by headache (n = 4), dizziness (n = 3), and postoperative delirium (n = 3). There was no dose-limiting toxicity.DiscussionAdministration of hUCB-MSCs into the hippocampus and precuneus by stereotactic injection was feasible, safe, and well tolerated. Further trials are warranted to test the efficacy.Clinical Trial RegistrationClinicalTrial.gov identifier NCT01297218 and NCT01696591.

Sulcal depth that is one of the quantitative measures of cerebral cortex has been widely used as an important marker for brain morphological studies. Several studies have employed Euclidean (EUD) or geodesic (GED) algorithms to measure sulcal depth, which have limitations that ignore sulcal geometry in highly convoluted regions and result in under or overestimated depth. In this study, we proposed an automated measurement for sulcal depth on cortical surface reflecting geometrical properties of sulci, which named the adaptive distance transform (ADT). We first defined the volume region of cerebrospinal fluid between the 3D convex hull and the cortical surface, and constructed local coordinates for that restricted region. Dijkstra’s algorithm was then used to compute the shortest paths from the convex hull to the vertices of the cortical surface based on the local coordinates, which may be the most proper approach for defining sulcal depth. We applied our algorithm to both a clinical dataset including patients with mild Alzheimer’s disease (AD) and 25 normal controls and a simulated dataset whose shape was similar to a single sulcus. The mean sulcal depth in the mild AD group was significantly lower than controls (p = 0.007, normal [mean±SD]: 7.29±0.23 mm, AD: 7.11±0.29) and the area under the receiver operating characteristic curve was relatively high, showing the value of 0.818. Results from clinical dataset that were consistent with former studies using EUD or GED demonstrated that ADT was sensitive to cortical atrophy. The robustness against inter-individual variability of ADT was highlighted through simulation dataset. ADT showed a low and constant normalized difference between the depth of the simulated data and the calculated depth, whereas EUD and GED had high and variable differences. We suggest that ADT is more robust than EUD or GED and might be a useful alternative algorithm for measuring sulcal depth.

Down syndrome (DS) is the most common liveborn autosomal chromosomal anomaly and is a major cause of developmental disability. Atypical brain development and the resulting intellectual disability originate during the fetal period. Perinatal interventions to correct such aberrant development are on the horizon in preclinical studies. However, we lack tools to sensitively measure aberrant structural brain development in living human fetuses with DS. In this study, we aimed to develop safe and precise neuroimaging measures to monitor fetal brain development in DS. We measured growth patterns of regional brain structures in 10 fetal brains with DS (29.1 ± 4.2, weeks of gestation, mean ± SD, range 21.7~35.1) and 12 control fetuses (25.2 ± 5.0, range 18.6~33.3) using regional volumetric analysis of fetal brain MRI. All cases with DS had confirmed karyotypes. We performed non-linear regression models to compare fitted regional growth curves between DS and controls. We found decreased growth trajectories of the cortical plate (P = 0.033), the subcortical parenchyma (P = 0.010), and the cerebellar hemispheres (P < 0.0001) in DS compared to controls. This study provides proof of principle that regional volumetric analysis of fetal brain MRI facilitates successful evaluation of brain development in living fetuses with DS.