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Standard templates are widely used in human neuroimaging processing pipelines to facilitate group-level analyses and comparisons across subjects/populations. MNI-ICBM152 template is the most commonly used standard template, representing an average of 152 healthy young adult brains. However, in patients with neurodegenerative diseases such as frontotemporal dementia (FTD), high atrophy levels lead to significant differences between individuals' brain shapes and MNI-ICBM152 template. Such differences might inevitably lead to registration errors or subtle biases in downstream analyses and results. Disease-specific templates are therefore desirable to reflect the anatomical characteristics of the populations of interest and reduce potential registration errors. Here, we present MNI-FTD136, MNI-bvFTD70, MNI-svFTD36, and MNI-pnfaFTD30, four unbiased average templates of 136 FTD patients, 70 behavioural variant (bv), 36 semantic variant (sv), and 30 progressive nonfluent aphasia (pnfa) variant FTD patients and a corresponding age-matched template of 133 controls (MNI-CN133), along with probabilistic tissue maps for each template. Public availability of these templates will facilitate analyses of FTD cohorts and enable comparisons between different studies in an appropriate common standardized space., (© 2021. The Author(s).)

Children with congenital heart defects (CHDs) have increased risk of cognitive disabilities for reasons not fully understood. Previous studies have indicated signs of disrupted fetal brain growth from mid-gestation measured with ultrasound and magnetic resonance imaging (MRI) and infants with CHDs have decreased brain volumes at birth. We measured the total and regional brain volumes of infants with and without CHDs using MRI to investigate, if certain areas of the brain are at particular risk of disrupted growth. MRI brain volumetry analyses were performed on 20 infants; 10 with- (postmenstrual age 39-54 weeks, mean 44 weeks + 5 days) and 10 without CHDs (postmenstrual age 39-52 weeks, mean 43 weeks + 5 days). In six infants with- and eight infants without CHDs grey and white matter were also differentiated. Infants with CHDs had smaller brains (48 ml smaller; 95% CI, 6.1-90; p = 0.03), cerebrums (37.8 ml smaller; 95% CI, 0.8-74.8; p = 0.04), and cerebral grey matter (25.8 ml smaller; 95% CI, 3.5-48; p = 0.03) than infants without CHD. Brain volume differences observed within weeks after birth in children with CHDs confirm that the brain impact, which increase the risk of cognitive disabilities, may begin during pregnancy.

Brain enlargement has been observed in children with autism spectrum disorder (ASD), but the timing of this phenomenon, and the relationship between ASD and the appearance of behavioural symptoms, are unknown. Retrospective head circumference and longitudinal brain volume studies of two-year olds followed up at four years of age have provided evidence that increased brain volume may emerge early in development. Studies of infants at high familial risk of autism can provide insight into the early development of autism and have shown that characteristic social deficits in ASD emerge during the latter part of the first and in the second year of life. These observations suggest that prospective brain-imaging studies of infants at high familial risk of ASD might identify early postnatal changes in brain volume that occur before an ASD diagnosis. In this prospective neuroimaging study of 106 infants at high familial risk of ASD and 42 low-risk infants, we show that hyperexpansion of the cortical surface area between 6 and 12 months of age precedes brain volume overgrowth observed between 12 and 24 months in 15 high-risk infants who were diagnosed with autism at 24 months. Brain volume overgrowth was linked to the emergence and severity of autistic social deficits. A deep-learning algorithm that primarily uses surface area information from magnetic resonance imaging of the brain of 6-12-month-old individuals predicted the diagnosis of autism in individual high-risk children at 24 months (with a positive predictive value of 81% and a sensitivity of 88%). These findings demonstrate that early brain changes occur during the period in which autistic behaviours are first emerging.