Neuroimaging brain growth charts: A road to mental health

Abstract

Mental disorders are common health concerns and contribute to a heavy global burden on our modern society. It is challenging to identify and treat them timely. Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function. The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier, perhaps even prior to onset, and treat them more precisely. An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population. The brain growth charts can offer a series of standard references on typical neurodevelopment, representing an important resource for the scientific and medical communities. In the present paper, we review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.

Functional connectome through the human life span

“…Disruption of these normative connectome patterns, especially during specific time windows, can predispose individuals to a spectrum of neurodevelopmental [10][11][12] , neurodegenerative 13 , and psychiatric disorders [14][15][16] . The growth chart framework offers an invaluable tool for charting normative reference curves in the human brain [17][18][19][20] . Very recently, Bethlehem et al 18 delineated the life-cycle growth curves of brain morphometry by aggregating the largest multi-site structural MRI dataset to date (123,984 scans from 101,457 human participants), marking a significant stride toward reproducible and generalizable brain charts.…”

Predicting depression risk in early adolescence via multimodal brain imaging

“…In addition, these studies were limited by relatively small sample sizes and/or, importantly, the lack of longitudinal designs. Longitudinal designs are a fundamental tool to describe prospective lifespan changes at the individual level (Chen et al, 2021;Gracia-Tabuenca et al, 2021). Considering the importance of predicting the onset of depression, more research is needed in early or pre-adolescent groups from large community-based samples which better represent the population.…”

Normative models for neuroimaging markers: Impact of model selection, sample size and evaluation criteria

“…While they are well established in some clinical contexts (e.g. paediatric growth charts (GROUP and de Onis, 2006;Borghi et al, 2006)), neuroimaging has started to adopt them only recently, where they have already been beneficial for the assessment of brain development (Erus et al, 2015;Chen et al, 2021;Dimitrova et al, 2021), ageing (Bethlehem et al, 2022;Rutherford et al, 2022) and in various clinical conditions related to psychiatry (Wolfers et al, 2018;Marquand et al, 2019;Zabihi et al, 2019;Wolfers et al, 2020) and dementia (Pinaya et al, 2021). Moving away from group-level studies, normative modelling incorporates heterogeneity in clinical cohorts, allowing predictions at an individual subject level (Marquand et al, 2016).…”