Background Large-scale longitudinal and multi-centre studies are used to explore neuroimaging markers of normal ageing, and neurodegenerative and mental health disorders. Longitudinal changes in brain structure are typically small, therefore the reliability of automated techniques is crucial. Determining the effects of different factors on reliability allows investigators to control those adversely affecting reliability, calculate statistical power, or even avoid particular brain measures with low reliability. This study examined the impact of several image acquisition and processing factors and documented the test-retest reliability of structural MRI measurements. Methods In Phase I, 20 healthy adults (11 females; aged 20–30 years) were scanned on two occasions three weeks apart on the same scanner using the ADNI-3 protocol. On each occasion, individuals were scanned twice (repetition), after re-entering the scanner (reposition) and after tilting their head forward. At one year follow-up, nine returning individuals and 11 new volunteers were recruited for Phase II (11 females; aged 22–31 years). Scans were acquired on two different scanners using the ADNI-2 and ADNI-3 protocols. Structural images were processed using FreeSurfer (v5.3.0, 6.0.0 and 7.1.0) to provide subcortical and cortical volume, cortical surface area and thickness measurements. Intra-class correlation coefficients (ICC) were calculated to estimate test-retest reliability. We examined the effect of repetition, reposition, head tilt, time between scans, MRI sequence and scanner on reliability of structural brain measurements. Mean percentage differences were also calculated in supplementary analyses. Results Using the FreeSurfer v7.1.0 longitudinal pipeline, we observed high reliability for subcortical and cortical volumes, and cortical surface areas at repetition, reposition, three weeks and one year (mean ICCs>0.97). Cortical thickness reliability was lower (mean ICCs>0.82). Head tilt had the greatest adverse impact on ICC estimates, for example reducing mean right cortical thickness to ICC=0.74. In contrast, changes in ADNI sequence or MRI scanner had a minimal effect. We observed an increase in reliability for updated FreeSurfer versions, with the longitudinal pipeline consistently having a higher reliability than the cross-sectional pipeline. Discussion Longitudinal studies should monitor or control head tilt to maximise reliability. We provided the ICC estimates and mean percentage differences for all FreeSurfer brain regions, which may inform power analyses for clinical studies and have implications for the design of future longitudinal studies.

Background Cognitive impairments in childhood are associated with increased risk of schizophrenia in later life, but the extent to which poor academic achievement is associated with the disorder is unclear. Methods Major databases were searched for articles published in English up to 31 December 2019. We conducted random-effects meta-analyses to: (1) compare general academic and mathematics achievement in youth who later developed schizophrenia and those who did not; (2) to examine the association between education level achieved and adult-onset schizophrenia; and, (3) compare general academic achievement in youth at-risk for schizophrenia and typically developing peers. Meta-regression models examined the effects of type of academic assessment, educational system, age at assessment, measurement of educational level attained, school leaving age, and study quality on academic achievement and education level among individuals with schizophrenia. Results Meta-analyses, comprising data of over four million individuals, found that: (1) by age 16 years, those who later developed schizophrenia had poorer general academic (Cohen's d = −0.29, p ⩽ 0.0001) and mathematics achievement (d = −0.23, p = 0.01) than those who did not; (2) individuals with schizophrenia were less likely to enter higher education (odds ratio = 0.49, p ⩽ 0.0001); and, (3) youth reporting psychotic-like experiences and youth with a family history of schizophrenia had lower general academic achievement (d = −0.54, p ⩽ 0.0001; d = −0.39, p ⩽ 0.0001, respectively). Meta-regression analyses determined no effect modifiers. Discussion Despite significant heterogeneity across studies, various routinely collected indices of academic achievement can identify premorbid cognitive dysfunction among individuals who are vulnerable for schizophrenia, potentially aiding the early identification of risk in the population.

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Persons at clinical high-risk for psychosis (CHR) are characterised by specific neurocognitive deficits. However, the course of neurocognitive performance during the prodromal period and over the onset of psychosis remains unclear. The aim of this meta-analysis was to synthesise results from follow-up studies of CHR individuals to examine longitudinal changes in neurocognitive performance. Three electronic databases were systematically searched to identify articles published up to 31 December 2021. Thirteen studies met inclusion criteria. Study effect sizes (Hedges' g) were calculated and pooled for each neurocognitive task using random-effects meta-analyses. We examined whether changes in performance between baseline and follow-up assessments differed between: (1) CHR and healthy control (HC) individuals, and (2) CHR who did (CHR-T) and did not transition to psychosis (CHR-NT). Meta-analyses found that HC individuals had greater improvements in performance over time compared to CHR for letter fluency (g = −0.32, p = 0.029) and digit span (g = −0.30, p = 0.011) tasks. Second, there were differences in longitudinal performance of CHR-T and CHR-NT in trail making test A (TMT-A) (g = 0.24, p = 0.014) and symbol coding (g = −0.51, p = 0.011). Whilst CHR-NT improved in performance on both tasks, CHR-T improved to a lesser extent in TMT-A and had worsened performance in symbol coding over time. Together, neurocognitive performance generally improved in all groups at follow-up. Yet, evidence suggested that improvements were less pronounced for an overall CHR group, and specifically for CHR-T, in processing speed tasks which may be a relevant domain for interventions aimed to enhance neurocognition in CHR populations.