Associations Between Neonatal Brain Structure and Neurodevelopmental Outcomes Following Very Preterm Birth

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Counsell, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7059614/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Apr, 2026 Read the published version in Journal of Perinatology → Version 1 posted 9 You are reading this latest preprint version Abstract Background Very preterm (VPT) children have high risks of neurodevelopmental delays, yet early predictors for specific impairments are poorly understood. This study investigated how neonatal brain structure relates to neurodevelopmental delays in VPT toddlers. Methods We analyzed T2-weighted MRI scans at term from 352 VPT children. Neurodevelopmental outcomes were assessed at 18–24 months using the Bayley Scales of Infant and Toddler Development-III. We used tensor-based morphometry to compare voxel-wise whole-brain volumes between delayed and non-delayed groups. Results Toddlers with motor delays showed significantly reduced volume in the left posterior cerebellum at term compared to those without, even after accounting for other delays. No significant volumetric differences were found for cognitive or language delays. Conclusion Reduced cerebellar volume at term may indicate motor delay in VPT children. These findings highlight the cerebellum's crucial role in early motor development and the value of structural MRI for early risk stratification. Health sciences/Medical research/Biomarkers/Predictive markers Health sciences/Risk factors Health sciences/Health care/Medical imaging Health sciences/Health care/Paediatrics preterm birth neurodevelopment cerebellum tensor-based morphometry Bayley Scales of Infant and Toddler Development–III Figures Figure 1 Introduction Children born very preterm (≤32 weeks' gestation) are at greater risk of neurodevelopmental delays, including cognitive, language, and motor impairments, as well as behavioural problems (1, 2). These delays, which may persist into adolescence and even adulthood, could limit individuals’ ability to engage in both structured and informal learning and social opportunities, thereby affecting their overall life outcomes (3, 4). Although various screening tools have been developed to detect neurodevelopmental delays following very preterm birth (5, 6), reliable early predictors of non-optimal outcomes remain poorly understood, representing a significant ongoing clinical challenge. Cognitive, language, and motor delays associated with very preterm birth may be partly explained by underlying structural and functional brain alterations. Since very preterm birth occurs during the third trimester of gestation, which represents a critical stage of brain growth, it may disrupt key neurodevelopmental processes, thereby increasing the risk of later developmental delays. Numerous studies have explored the associations between neonatal brain features and subsequent neurodevelopmental outcomes in very preterm children (7). Larger cortical surface area and more optimal white matter microstructural characteristics at term have been linked to enhanced cognitive outcomes at two; while reduced volume in basal ganglia and thalamus have been associated with unfavourable motor development (8). Recent studies also revealed an association between stronger structural cortico-striatal and thalamo-striatal connectivity at term and improved cognitive and language developmental outcomes at 18 months (9), whereas we previously showed that larger neonatal insular and orbitofrontal volumes characterised very preterm children with more favourable neurocognitive outcomes at 4 (7). Furthermore, prior studies have tended to investigate how brain structure and function relate to individual developmental outcomes (e.g., cognition, language or motor skills) (10), or to study older children (11). Consequently, the potential associations between neonatal brain alterations and the co-occurrence of multiple developmental delays (e.g., cognitive, language, motor) in the very first years of life following very preterm birth remain poorly understood. Using tensor-based morphometry, this study aimed to explore the shared and unique regional neonatal brain alterations at term associated with cognitive, language and motor developmental delays in very preterm toddlers. We hypothesised that very preterm toddlers with developmental delays would display structural brain alterations at term compared to those without developmental delays. We further hypothesised that multiple domains of neurodevelopmental delays would share structural brain alterations and explored whether there were specific brain regions which were uniquely associated with delay in one developmental domain. Methods Study design and population Participants were 511 very preterm infants enrolled in the Evaluation of Preterm Imaging study (ePrime, EudraCT: 2009-011602-42) (12). Infants were recruited at birth between April 2010 and July 2013 from 14 hospitals within the North and South-West London Perinatal Network. Infants recruited into ePrime had the following inclusion criteria: birth before 33 weeks of gestation, maternal age above 16 years, and mothers not being hospital inpatients. Exclusion criteria were major congenital malformations, contraindications to magnetic resonance imaging, parents not being able to speak English, or being subject to child protection proceedings. Parents of 485 infants consented their offspring to undertake magnetic resonance imaging (MRI) at term-equivalent age (38–44 PMA) and follow-up neurodevelopment assessments at 18-24 months of age. Qualitative MRI classification was performed by a senior radiographer, resulting in three categories: major lesions, defined as cystic periventricular leukomalacia, more than ten punctate white matter lesions, and/or grade 3 or 4 germinal matrix hemorrhage; minor lesions, defined as any other lesions; and no lesions (13). Our analyses included a subsample of 352 participants whose neonatal MRI showed no major lesions and who completed follow-up neurodevelopmental assessments. The ePrime study was conducted under the ethical standards of the 1964 Helsinki Declaration and was approved by the Hammersmith and Queen Charlotte’s Research Ethics Committee (09/H0707/98). MRI Acquisition Infants underwent MRI at term-equivalent age using a 3-Tesla system (Philips Medical Systems, Best, The Netherlands) with an 8-channel phased array head coil. During MRI, infant care was supervised by a paediatrician and included continuous monitoring of pulse oximetry, temperature, and electrocardiography data. Ear protection was provided with silicone-based putty (President Putty, Coltene Whaledent, Mahwah, NJ, USA) and neonatal earmuffs (MiniMuffs, Natus Medical Inc., San Carlos, CA, USA). Oral chloral hydrate (25–50 mg kg − 1 ) was administered to infants whose parents chose sedation for the procedure (87%). High-resolution anatomical images were obtained by T2-weighted fast spin echo sequences (repetition time=8,670 ms; echo time=160 ms; flip angle=90°, slice thickness=1 mm, field of view=220*220 mm 2 , voxel size=0.86*0.86*1 mm 3 ). Structural data processing Following the methods described in (14) and (15), T2-weighted images were registered to a study-specific template using ANTS software Symmetric Normalisation algorithms (16). Following rigid and affine image transformations, nonlinear transformations were used to generate deformation tensor fields within the template space and eliminate global volume differences. The resulting tensor fields describing the voxel-wise shape and volume changes from the template to each subject image were used to calculate log-transformed scalar Jacobian determinants. Smoothing with 4 mm full-width half-maximum Gaussian filter was applied. Neurodevelopmental measures Psychomotor development in toddlers was assessed using the Bayley Scales of Infant and Toddler Development–Third Edition (BSID-III) (17) at 18-24 months of age. Scores from its three subscales (cognitive, language, and motor development) were used for analysis. Socio-demographic and clinical measures The following socio-demographic and clinical measures were collected as part of ePRIME: assigned sex at birth, maternal education (categorised as "low" if she left full-time education before the age of 19, otherwise as "high") (18), birth weight, gestational age at birth (in weeks), infant's PMA at MRI scanning and age at follow-up assessment. We also included relative social deprivation, indexed by the 2010 Index of Multiple Deprivation (IMD), which was calculated based on maternal postcode at recruitment (19). Statistical Analysis Statistical analysis was performed using R-4.3.1 (R Project for Statistical Computing). Descriptive results for categorical variables were presented as n (%) and continuous variables as median [interquartile range]. Participants without major brain lesions on neonatal MRI (n=352) were compared to those with major brain lesions (n=37) to ensure the representativeness of the sample. Participants without major brain lesions had longer gestational age than those with major brain lesions (W= 8155.5, p=0.01). However, there were no statistically significant differences between lesion groups in terms of sex distribution (χ= 0.33, p=0.56), PMA at scan (W=6316, p=0.76) and IMD (W=6414, p=0.72). According to the BSID-III scoring criteria, scores below 85 indicate developmental delay in the corresponding domain (20). Therefore, participants were categorised into three pairs of groups: cognitive delay/non-delay, language delay/non-delay, and motor delay/non-delay. Clinical, demographic, and neurodevelopmental measures were compared between each pair of delayed and non-delayed groups using the Mann-Whitney U and Chi-Square tests. For TBM analysis, the 352 infants were subdivided into non-delayed and delayed groups on each subscale of the BSID-III (cognitive, language and motor). We compared voxel-wise whole-brain T2 images between the two groups using FSL Randomise (FSL, version 6.01) (21, 22) random permutation tests with 5000 permutations and threshold-free cluster enhancement, based on a General Linear Model (GLM) matrix (21, 23) with PMA, sex, and IMD as covariates of no interest. Three additional binary nuisance variables (0: non-delay, 1: delay) were generated, representing delay in each subscale of BSID-III scales to account for potential shared structural correlates among the three types of developmental delay. A family-wise-error-corrected p-value of less than 0.008 was considered significant, to account for 6 comparisons: two contrasts (i.e. non-delayed > delayed and non-delayed < delayed) and three subscales. All the analyses were performed with FSL Randomise toolkit (21). Results Characteristics of the study participants Sample characteristics are presented in Table 1. Table 1: Sample Characteristics of Participants (N=352) Variable Characteristics Sex n (%) Male 177 (50.28) Female 175 (49.72) Maternal education Low 104 (29.55) High 248 (70.45) Median [IQR] PMA at Scan, Weeks 42.57 [41.29, 43.43] GA at Birth, Weeks 30.29 [28.14, 31.86] Birth weight, Gram 1300.00 [1010.00, 1622.00] Age at assessment, Month 20.04 [20.00, 20.16] IMD rank 15422 [9310, 22772] BSID-III cognitive development 95.00 [85.00, 105.00] BSID-III language development 91.00 [79.00, 103.00] BSID-III motor development 97.00 [91.00, 103.00] a: “Low” indicates exiting full-time education by 19 years old, “High” indicates exiting full-time education later than 19 years old or still in full-time education. IQR: Interquartile. Comparisons of demographic information between groups with and without developmental delay As shown in Table 2, participants with cognitive delay had significantly lower gestational age and were more likely to live in more deprived neighbourhoods. Participants exhibiting language delays were predominantly male and were also more likely to live in more deprived neighbourhoods. Participants with motor delay had significantly lower gestational age. Participants with developmental delays in one dimension were significantly more likely to have additional delays in the other two dimensions. Comparisons of brain volumes between groups with and without developmental delay Firstly, we found no significant difference in brain volume at term between toddlers with and without delayed cognitive and language development in whole-brain comparisons, after accounting for sex, PMA, and IMD. Toddlers with delayed motor development showed significantly reduced volumes in the cerebellum at term compared to those without delayed motor development (Fig. 1a). Subsequently, given the high degree of overlap between participants with cognitive, language and motor delays, we repeated the analyses accounting for selective BSID-III sub-scores. For instance, when investigating volumetric differences at term between toddlers with and without motor delay, we adjusted for sex, PMA, IMD, BSID-III cognitive and language sub-scores. Toddlers with delayed motor development displayed significantly reduced regional volumes in the left posterior lobe of cerebellum at term compared to those without delayed motor development (Fig. 1b). There was no significant difference in brain volumes at term between toddlers with and without delayed language development as well as between those with and without delayed cognitive development. Table 2: Clinical, socio-demographic and behavioural features of participants with delayed and non-delayed development (continued next page) Variable Cognitive development Language development Delay group (n=68) Typical group (n=284) p-value Delay group (n=123) Typical group (n=229) p-value Sex 0.37 <0.001 Male, n (%) 38 (55.88) 139 (48.94) 78 (63.41) 99 (43.23) Female, n (%) 30 (44.12) 145 (51.06) 45 (36.59) 130 (56.77) Maternal education 0.48 0.44 Low, n (%) 23 (33.82) 81 (28.52) 40 (32.52) 64 (27.95) High, n (%) 45 (66.18) 203 (71.48) 83 (67.48) 165 (72.05) PMA at Scan, Weeks, Median [IQR] 42.64 [41.57, 43.86] 42.57 [41.14, 43.18] 0.14 42.43 [41.22, 43.57] 42.57 [41.29, 43.29] 0.96 GA at Birth, Weeks, Median [IQR] 28.78 [27.25, 30.97] 30.57 [28.43, 32.00] <0.001 30.57 [27.93, 32.00] 30.29 [28.29, 31.86] 0.93 Birth weight, Gram, Median [IQR] 1150.00 [912.50, 1402.75] 1325.00 [1055.00, 1663.75] <0.001 1270.00 [1000.00, 1620.00] 1300.00 [1020.00, 1630.00] 0.59 Age at assessment, Month, Median [IQR] 20.03 [20.00, 20.14] 20.05 [20.00, 20.16] 0.21 20.02 [20.00, 20.12] 20.06 [20.00, 20.16] 0.03 IMD rank, Median [IQR] 10378.00 [6703.50, 18240.00] 16188.00 [9695.00, 23084.50] <0.001 12758.00 [7241.00, 18810.00] 16898.00 [10823.00, 24590.00] <0.001 Cognitive development <0.001 Delay, n(%) 53 (43.09) 15 (6.55) Typical, n(%) 70 (56.91) 214 (93.45) Language development <0.001 Delay, n(%) 53 (77.94) 70 (24.65) Typical, n(%) 15 (22.06) 214 (75.35) Motor development <0.001 <0.001 Delay, n(%) 27 (39.71) 9 (3.17) 30 (24.39) 8 (3.49) Typical, n(%) 41 (60.29) 273 (96.13) 93 (75.61) 221 (96.51) Mann–Whitney U test was used for continuous variables and Chi-squared test was used for categorical variables. IQR: Interquartile range. Table 2: Clinical, socio-demographic and behavioural features of participants with delayed and non-delayed development (continued) Variable Motor development Delay group (n=38) Typical group (n=314) p-value Sex 0.24 Male, n (%) 23 (60.53) 154 (49.04) Female, n (%) 15 (39.47) 160 (50.96) Maternal education 0.39 Low, n (%) 14 (36.84) 90 (28.66) High, n (%) 24 (63.16) 224 (71.34) PMA at Scan, Weeks, Median [IQR] 43.00 [41.89, 43.93] 42.57 [41.14, 43.29] <0.01 GA at Birth, Weeks, Median [IQR] 28.57 [27.18, 29.93] 30.57 [28.29, 31.86] <0.001 Birth weight, Gram, Median [IQR] 1110.00 [773.75, 1323.75] 1315.00 [1021.25, 1646.25] <0.01 Age at assessment, Month, Median [IQR] 20.03 [20.00, 20.11] 20.04 [20.00, 20.17] 0.38 IMD rank, Median [IQR] 14684.50 [8476.00, 22870.00] 15688.00 [9425.75, 22720.00] 0.53 Cognitive development <0.001 Delay, n(%) 27 (71.05) 41 (13.06) Typical, n(%) 11 (28.95) 273 (86.94) Language development <0.001 Delay, n(%) 8 (21.05) 93 (29.62) Typical, n(%) 30 (78.95) 221 (70.38) Motor development Delay, n(%) Typical, n(%) Mann–Whitney U test was used for continuous variables and Chi-squared test was used for categorical variables. IQR: Interquartile range Discussion This study examined structural brain alterations at term in very preterm toddlers with and without selective neurodevelopmental delays. Aligned with our first hypothesis, very preterm toddlers with motor delays displayed reduced bilateral cerebellar volume at term. However, this effect was limited to the left posterior lobe of the cerebellum when accounting for cognitive and language developmental delays. These findings suggest that: ( 1 ) motor developmental delays in very preterm toddlers can be detected as early as the neonatal period using T2-weighted structural brain imaging, offering opportunities for earlier intervention; and ( 2 ) cognitive, language, and motor developmental delays may be associated with, albeit limited, overlapping structural brain alterations, hence the importance of treating outcomes as non-independent in statistical analyses. Previous studies have extensively investigated the relationships between brain volume at term and later developmental outcomes in very preterm children and have shown, for instance, that altered volumes in sensorimotor and premotor regions were associated with poorer cognitive and motor outcomes ( 8 , 11 ). Our previous research identified an association between brain lesions and motor impairments ( 24 ), and linked reduced neonatal volume in salience network to poorer cognitive outcomes in childhood ( 15 ). Expanding on these works, the current study explored how neonatal brain volume alterations related to neurodevelopmental outcomes in toddlerhood. Building upon prior studies focusing on individual developmental domains, we examined the unique association between each single domain and brain volumes, accounting for the potential neurostructural overlaps among the three domains. Our findings of reduced left cerebellar volume at term in those toddlers with motor developmental delay can be interpreted in the context of previous literature showing altered cerebellar volume in preterm-born neonates compared to term-born controls ( 25 , 26 ). The third trimester of gestation, i.e. 24–40 weeks post-conceptual, is the most rapid and sensitive window for cerebellar development ( 27 , 28 ). The identification of reduced cerebellar volume associated with very preterm birth could be explained by impaired granule cell proliferation ( 29 ) or exposure to perinatal stressors ( 30 ). Our findings further support the growing evidence that the cerebellum is susceptible to early extra-uterine influence and might be implicated in the aetiology of neurodevelopmental delay in toddlerhood ( 31 ). Our findings of reduced left cerebellar volume at term in those toddlers with motor developmental delay are also consistent with previous literature showing that decreased cerebellar volume was associated with worse motor functioning in neonates and children with cerebellar malformation and motor disorders ( 32 , 33 ). The potential mechanisms underlying the influence of altered cerebellar volume might include disrupted cerebro-cerebellar circuits essential for motor coordination, particularly the cortical-ponto-cerebellar loops modulated by cerebellar output ( 34 , 35 ) and impaired olivocerebellar pathway development, potentially hindering the neural plasticity required for motor skill acquisition ( 36 ). Our results further highlighted that reduced cerebellar volume was associated with toddler neurodevelopmental delay even in neonates without cerebellar injury. Vanes et al also identified an association between reduced cerebellar volume at term and poorer psychomotor functioning in toddlerhood ( 37 ). As such, altered cerebellar volume at term might be a potential biomarker for later motor delay and could be used to guide targeted, mechanism-based interventions. In contrast, we found no volumetric differences at term between toddlers with and without cognitive or language delays. These findings may be due to heterochronicity in developmental trajectories in brain areas underpinning these different dimensions. Cognitive and language functions are primarily supported by later maturing cortices, predominantly prefrontal and temporal regions, where alterations may not be sufficiently evident at term to correlate with subsequent outcomes ( 38 , 39 ). However, after accounting for language and cognitive delays, the differences between toddlers with and without motor delays in cerebellar volume at term became less extensive. These findings suggest that cerebellar spatial compartments may be engaged across multiple behavioural domains, reflecting its function as a central integrative structure (40), but also highlight the role of the posterior cerebellar lobe in supporting motor function during early human development ( 41 ). By leveraging various dimensions of neurodevelopment in toddlerhood, we were able to further explore the early structural underpinnings of delayed motor, cognitive and language development in very preterm children. Future research can further explore other factors (including parenting, environmental, and genetic information) that might influence the relation between brain structure at term and developmental outcome in toddlerhood. While the BSID-III is a widely recognised assessment tool for early development, evidence supporting its ability to accurately identify developmental delays in high-risk populations more specifically, is still scarce. Recent studies indicate that this tool may underestimate developmental delays in very preterm infants ( 42 , 43 ). Future studies should incorporate a broader range of biological, genetic and perinatal risk factors to more thoroughly elucidate the potential mechanisms underlying brain structure and neurodevelopmental trajectories. Further subscales of the BSID-III, including those for fine and gross motor skills, can be employed to delve deeper into the relationship between brain structure and these specific facets of neurodevelopment. Moreover, research has highlighted the significant influence of sex on neurodevelopment ( 44 ) and future studies may investigate the sex-specific brain structural underpinnings of neurodevelopment in males and females, rather than treating sex as a confounding variable. To summarise, this study identified volumetric alterations in the cerebellum, a critical region for motor processing, in very preterm infants with delayed motor development in toddlerhood compared to those without. While advancing our understanding of neonatal structural alterations and their association with different aspects of early development, it helps pinpoint early screening for developmental delays, which can contribute to the development of targeted early interventions to improve children’s outcomes. Declarations Conflict of Interest None. Availability of Data and Materials Available to referees at submission and to readers promptly upon request. Funding This work was financially supported by: The Medical Research Council, UK [Grant numbers: MR/K006355/1 and MR/S026460/1] and Action Medical Research and Dangoor Education [Grant number: GN2606]. Data analysed in this study were collected during independent research funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research Programme [Grant number: RP-PG-0707-10154]. The study was part funded by the infrastructure of the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and Kings College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Author Contributions All authors contributed greatly to this paper and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. SC, JH, DE, PD, DB and CN made substantial contributions to the conception and the design of the work; ML and AC contributed to the acquisition of the data, while ZS, YG, DB and CN made much effort for analysis and interpretation of data. ZS, YG, ML, DB and CN contributed in drafting the first manuscript, and all authors participated in reviewing it critically before our final approval of the version to be published. Acknowledgements The authors would like to thank the participating families of the ePrime study, and all research, radiography and clinical staff involved in the study. References Johnson S. Cognitive and behavioural outcomes following very preterm birth. Semin Fetal Neonatal Med. 2007;12(5):363-73. Linsell L, Malouf R, Morris J, Kurinczuk JJ, Marlow N. Prognostic Factors for Poor Cognitive Development in Children Born Very Preterm or With Very Low Birth Weight: A Systematic Review. JAMA Pediatr. 2015;169(12):1162-72. 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Predictive Value of the BSID-II and the Bayley-III for Early School Age Cognitive Function in Very Preterm Infants. Glob Pediatr Health. 2020;7:2333794X20973146. Hanamsagar R, Bilbo SD. Sex differences in neurodevelopmental and neurodegenerative disorders: Focus on microglial function and neuroinflammation during development. J Steroid Biochem Mol Biol. 2016;160:127-33. Additional Declarations There is NO conflict of interest to disclose. Cite Share Download PDF Status: Published Journal Publication published 15 Apr, 2026 Read the published version in Journal of Perinatology → Version 1 posted Editorial decision: revise 01 Oct, 2025 Review # 1 received at journal 30 Sep, 2025 Review # 2 received at journal 06 Aug, 2025 Reviewer # 2 agreed at journal 25 Jul, 2025 Reviewer # 1 agreed at journal 10 Jul, 2025 Reviewers invited by journal 09 Jul, 2025 Submission checks completed at journal 07 Jul, 2025 Editor assigned by journal 06 Jul, 2025 First submitted to journal 06 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7059614","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":483177500,"identity":"a96e4eee-2498-43f0-a453-92c8689ce0f2","order_by":0,"name":"Zeyuan SUN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYHAD5sMMDAUQFrFa2JIZGAxI08JjTJwW+fYeM4mfOxjsDW73fDb4YcAgz9/AY2yATwtjzxkzyd4zDIkb7pzdnNhjwGA44wCPcQI+LcwSOWYSvG0MCQY3cjcfBjqMcQPQhQfwaWGTf2Mm+bcN6LAbOY9BWuwJauGR4DGTBtrCuOFGDnMyUEsiSAteh0nwpBVby7ZJJM68kWZs2GMgkTzjMFsxXu/Ltx/eePNtm409343kxxI/Kmxs+9ubN0vg08LAwAEyEq5GgpiIZH9AUMkoGAWjYBSMcAAAajA9NOe74sEAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-2309-8149","institution":"Institute of Psychiatry, Psychology and Neuroscience, King’s College London","correspondingAuthor":true,"prefix":"","firstName":"Zeyuan","middleName":"","lastName":"SUN","suffix":""},{"id":483177501,"identity":"0c108d64-605a-4d32-9edc-b2d7b1adcea9","order_by":1,"name":"Yan Ge","email":"","orcid":"","institution":"School of Biomedical Engineering \u0026 Imaging Science, King’s College London","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Ge","suffix":""},{"id":483177502,"identity":"57a8d105-ab07-42a2-ac74-6397be75073d","order_by":2,"name":"Marguerite Leoni","email":"","orcid":"https://orcid.org/0000-0003-1078-0533","institution":"Institute of Psychiatry, Psychology and Neuroscience, King's College London","correspondingAuthor":false,"prefix":"","firstName":"Marguerite","middleName":"","lastName":"Leoni","suffix":""},{"id":483177503,"identity":"931e5129-889b-4171-a6c0-2448f67b9dbe","order_by":3,"name":"Andrew Chew","email":"","orcid":"","institution":"School of Biomedical Engineering \u0026 Imaging Science, King's College London, London, United Kingdom","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Chew","suffix":""},{"id":483177504,"identity":"f74e23d7-ff39-47c6-b260-8212cea2fda5","order_by":4,"name":"Serena J. Counsell","email":"","orcid":"","institution":"School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom","correspondingAuthor":false,"prefix":"","firstName":"Serena","middleName":"J.","lastName":"Counsell","suffix":""},{"id":483177505,"identity":"d2f28764-2fef-4dea-af81-a9b97666e687","order_by":5,"name":"Joseph Hajnal","email":"","orcid":"","institution":"School of Biomedical Engineering \u0026 Imaging Science, King's College London, London, United Kingdom","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Hajnal","suffix":""},{"id":483177506,"identity":"cd30226d-2dc1-438f-9a30-f45c7c3028d4","order_by":6,"name":"Anthony Edwards","email":"","orcid":"https://orcid.org/0000-0003-4801-7066","institution":"King's College London","correspondingAuthor":false,"prefix":"","firstName":"Anthony","middleName":"","lastName":"Edwards","suffix":""},{"id":483177507,"identity":"a58583a2-93ce-4f3c-8613-fa0c945c6b0a","order_by":7,"name":"Paola Dazzan","email":"","orcid":"","institution":"Institute of Psychiatry, Psychology, and Neuroscience, King's College London, United Kingdom","correspondingAuthor":false,"prefix":"","firstName":"Paola","middleName":"","lastName":"Dazzan","suffix":""},{"id":483177508,"identity":"df20d9bd-6e8a-476b-b375-a7e6305182f7","order_by":8,"name":"Dafnis Batalle","email":"","orcid":"","institution":"Institute of Psychiatry, Psychology, and Neuroscience, King's College London, United Kingdom","correspondingAuthor":false,"prefix":"","firstName":"Dafnis","middleName":"","lastName":"Batalle","suffix":""},{"id":483177509,"identity":"feeb560f-0e84-421b-953d-b2beb17a6054","order_by":9,"name":"Chiara Nosarti","email":"","orcid":"https://orcid.org/0000-0001-6305-9710","institution":"Kings College London, UK","correspondingAuthor":false,"prefix":"","firstName":"Chiara","middleName":"","lastName":"Nosarti","suffix":""}],"badges":[],"createdAt":"2025-07-06 19:35:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7059614/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7059614/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41372-026-02672-3","type":"published","date":"2026-04-15T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86758102,"identity":"e1e19d57-7abe-4724-acd5-ac63cdac4152","added_by":"auto","created_at":"2025-07-15 09:47:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":290858,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolume difference at term between toddlers with and without delayed motor development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMap of T-statistic values of areas of significant reductions (blue-green) in volumes at term in toddlers with motor delayed development compared to non-delayed development (family-wise-error-corrected p \u0026lt; 0.008) overlaid on study-specific brain template. Panel a adjusted for sex, PMA and IMD; Panel b adjusted for sex, PMA, IMD, cognitive development and language development. T-statistic range is shown on the colour bars. Anterior (A)-Posterior (P) and Left (L)-right (R) orientation follows radiological convention\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7059614/v1/9447a679c9ca688742fd781d.png"},{"id":107045232,"identity":"edd8f429-6cdd-470f-a9c1-ca36275cb997","added_by":"auto","created_at":"2026-04-16 07:13:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1607802,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7059614/v1/564c620b-15f0-4fc6-ba23-410f26e33a7f.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Associations Between Neonatal Brain Structure and Neurodevelopmental Outcomes Following Very Preterm Birth","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChildren born very preterm (\u0026le;32 weeks\u0026apos; gestation) are at greater risk of neurodevelopmental delays, including cognitive, language, and motor impairments, as well as behavioural problems (1, 2). These delays, which may persist into adolescence and even adulthood, could limit individuals\u0026rsquo; ability to engage in both structured and informal learning and social opportunities, thereby affecting their overall life outcomes (3, 4). Although various screening tools have been developed to detect neurodevelopmental delays following very preterm birth (5, 6), reliable early predictors of non-optimal outcomes remain poorly understood, representing a significant ongoing clinical challenge.\u003c/p\u003e\n\u003cp\u003eCognitive, language, and motor delays associated with very preterm birth may be partly explained by underlying structural and functional brain alterations. Since very preterm birth occurs during the third trimester of gestation, which represents a critical stage of brain growth, it may disrupt key neurodevelopmental processes, thereby increasing the risk of later developmental delays. Numerous studies have explored the associations between neonatal brain features and subsequent neurodevelopmental outcomes in very preterm children (7). Larger cortical surface area and more optimal white matter microstructural characteristics at term have been linked to enhanced cognitive outcomes at two; while reduced volume in basal ganglia and thalamus have been associated with unfavourable motor development (8). Recent studies also revealed an association between stronger structural cortico-striatal and thalamo-striatal connectivity at term and improved cognitive and language developmental outcomes at 18 months (9), whereas we previously showed that larger neonatal insular and orbitofrontal volumes characterised very preterm children with more favourable neurocognitive outcomes at 4 (7). Furthermore, prior studies have tended to investigate how brain structure and function relate to individual developmental outcomes (e.g., cognition, language or motor skills) (10), or to study older children (11). Consequently, the potential associations between neonatal brain alterations and the co-occurrence of multiple developmental delays (e.g., cognitive, language, motor) in the very first years of life following very preterm birth remain poorly understood.\u003c/p\u003e\n\u003cp\u003eUsing tensor-based morphometry, this study aimed to explore the shared and unique regional neonatal brain alterations at term associated with cognitive, language and motor developmental delays in very preterm toddlers. We hypothesised that very preterm toddlers with developmental delays would display structural brain alterations at term compared to those without developmental delays. We further hypothesised that multiple domains of neurodevelopmental delays would share structural brain alterations and explored whether there were specific brain regions which were uniquely associated with delay in one developmental domain.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were 511 very preterm infants enrolled in the Evaluation of Preterm Imaging study (ePrime, EudraCT: 2009-011602-42) (12). Infants were recruited at birth between April 2010 and July 2013 from 14 hospitals within the North and South-West London Perinatal Network. Infants recruited into ePrime had the following inclusion criteria: birth before 33 weeks of gestation, maternal age above 16 years, and mothers not being hospital inpatients. Exclusion criteria were major congenital malformations, contraindications to magnetic resonance imaging, parents not being able to speak English, or being subject to child protection proceedings. Parents of 485 infants consented their offspring to undertake magnetic resonance imaging (MRI) at term-equivalent age (38\u0026ndash;44 PMA) and follow-up neurodevelopment assessments at 18-24 months of age. Qualitative MRI classification was performed by a senior radiographer, resulting in three categories: major lesions, defined as cystic periventricular leukomalacia, more than ten punctate white matter lesions, and/or grade 3 or 4 germinal matrix hemorrhage; minor lesions, defined as any other lesions; and no lesions (13). Our analyses included a subsample of 352 participants whose neonatal MRI showed no major lesions and who completed follow-up neurodevelopmental assessments. The ePrime study was conducted under the ethical standards of the 1964 Helsinki Declaration and was approved by the Hammersmith and Queen Charlotte\u0026rsquo;s Research Ethics Committee (09/H0707/98).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMRI Acquisition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInfants underwent MRI at term-equivalent age using a 3-Tesla system (Philips Medical Systems, Best, The Netherlands) with an 8-channel phased array head coil. During MRI, infant care was supervised by a paediatrician and included continuous monitoring of pulse oximetry, temperature, and electrocardiography data. Ear protection was provided with silicone-based putty (President Putty, Coltene Whaledent, Mahwah, NJ, USA) and neonatal earmuffs (MiniMuffs, Natus Medical Inc., San Carlos, CA, USA). Oral chloral hydrate (25\u0026ndash;50 mg kg\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003csup\u003e1\u003c/sup\u003e) was administered to infants whose parents chose sedation for the procedure (87%). High-resolution anatomical images were obtained by T2-weighted fast spin echo sequences (repetition time=8,670 ms; echo time=160 ms; flip angle=90\u0026deg;, slice thickness=1 mm, field of view=220*220 mm\u003csup\u003e2\u003c/sup\u003e, voxel size=0.86*0.86*1 mm\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructural data processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the methods described in (14) and (15), T2-weighted images were registered to a study-specific template using ANTS software Symmetric Normalisation algorithms (16). Following rigid and affine image transformations, nonlinear transformations were used to generate deformation tensor fields within the template space and eliminate global volume differences. The resulting tensor fields describing the voxel-wise shape and volume changes from the template to each subject image were used to calculate log-transformed scalar Jacobian determinants. Smoothing with 4 mm full-width half-maximum Gaussian filter was applied.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeurodevelopmental measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePsychomotor development in toddlers was assessed using the Bayley Scales of Infant and Toddler Development\u0026ndash;Third Edition (BSID-III) (17) at 18-24 months of age. Scores from its three subscales (cognitive, language, and motor development) were used for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSocio-demographic and clinical measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following socio-demographic and clinical measures were collected as part of ePRIME: assigned sex at birth, maternal education (categorised as \u0026quot;low\u0026quot; if she left full-time education before the age of 19, otherwise as \u0026quot;high\u0026quot;) (18), birth weight, gestational age at birth (in weeks), infant\u0026apos;s PMA at MRI scanning and age at follow-up assessment. We also included relative social deprivation, indexed by the 2010 Index of Multiple Deprivation (IMD), which was calculated based on maternal postcode at recruitment (19).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using R-4.3.1 (R Project for Statistical Computing). Descriptive results for categorical variables were presented as n (%) and continuous variables as median [interquartile range]. Participants without major brain lesions on neonatal MRI (n=352) were compared to those with major brain lesions (n=37) to ensure the representativeness of the sample. Participants without major brain lesions had longer gestational age than those with major brain lesions (W= 8155.5, p=0.01). However, there were no statistically significant differences between lesion groups in terms of sex distribution (\u0026chi;= 0.33, p=0.56), PMA at scan (W=6316, p=0.76) and IMD (W=6414, p=0.72). According to the BSID-III scoring criteria, scores below 85 indicate\u0026nbsp;developmental delay in the corresponding domain (20).\u0026nbsp;Therefore, participants were categorised into three pairs of groups: cognitive delay/non-delay, language delay/non-delay, and motor delay/non-delay. Clinical, demographic, and neurodevelopmental measures were compared between each pair of delayed and non-delayed groups using the Mann-Whitney U and Chi-Square tests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor TBM analysis, the 352 infants were subdivided into non-delayed and delayed groups on each subscale of the BSID-III (cognitive, language and motor). We compared voxel-wise whole-brain T2 images between the two groups using FSL Randomise (FSL, version 6.01) (21, 22) random permutation tests with 5000 permutations and threshold-free cluster enhancement, based on a General Linear Model (GLM) matrix (21, 23) \u0026nbsp;with \u0026nbsp; PMA, sex, and IMD as covariates of no interest. Three additional binary nuisance variables (0: non-delay, 1: delay) were generated, representing delay in each subscale of BSID-III scales to account for potential shared structural correlates among the three types of developmental delay. A family-wise-error-corrected p-value of less than 0.008 was considered significant, to account for 6 comparisons: two contrasts (i.e. non-delayed \u0026gt; delayed and non-delayed \u0026lt; delayed) and three subscales. All the analyses were performed with FSL Randomise toolkit (21).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCharacteristics of the study participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSample characteristics are presented in Table 1. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1: Sample Characteristics of Participants (N=352)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"529\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSex\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e177 (50.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e175 (49.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eMaternal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e104 (29.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e248 (70.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003ePMA at Scan, Weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e42.57 [41.29, 43.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eGA at Birth, Weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e30.29 [28.14, 31.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eBirth weight, Gram\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e1300.00 [1010.00, 1622.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eAge at assessment, Month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e20.04 [20.00, 20.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eIMD rank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e15422 [9310, 22772]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eBSID-III cognitive development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e95.00 [85.00, 105.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eBSID-III language development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e91.00 [79.00, 103.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eBSID-III motor development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e97.00 [91.00, 103.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea: \u0026ldquo;Low\u0026rdquo; indicates exiting full-time education by 19 years old, \u0026ldquo;High\u0026rdquo; indicates exiting full-time education later than 19 years old or still in full-time education. IQR: Interquartile.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparisons of demographic information between groups with and without developmental delay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 2, participants with cognitive delay had significantly lower gestational age and were more likely to live in more deprived neighbourhoods. Participants exhibiting language delays were predominantly male and were also more likely to live in more deprived neighbourhoods. Participants with motor delay had significantly lower gestational age. Participants with developmental delays in one dimension were significantly more likely to have additional delays in the other two dimensions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparisons of brain volumes between groups with and without developmental delay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirstly, we found no significant difference in brain volume at term between toddlers with and without delayed cognitive and language development in whole-brain comparisons, after accounting for sex, PMA, and IMD. Toddlers with delayed motor development showed significantly reduced volumes in the cerebellum at term compared to those without delayed motor development (Fig. 1a).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubsequently, given the high degree of overlap between participants with cognitive, language and motor delays, we repeated the analyses accounting for selective BSID-III sub-scores. For instance, when investigating volumetric differences at term between toddlers with and without motor delay, we adjusted for sex, PMA, IMD, BSID-III cognitive and language sub-scores. Toddlers with delayed motor development displayed significantly reduced regional volumes in the left posterior lobe of cerebellum at term compared to those without delayed motor development (Fig. 1b). There was no significant difference in brain volumes at term between toddlers with and without delayed language development as well as between those with and without delayed cognitive development.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Clinical, socio-demographic and behavioural features of participants with delayed and non-delayed development (continued next page)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1399\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 558px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCognitive development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 548px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLanguage development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay group (n=68)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical group (n=284)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay group (n=123)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical group (n=229)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.37\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e38 (55.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e139 (48.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e78 (63.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e99 (43.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e30 (44.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e145 (51.06) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e45 (36.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e130 (56.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.48\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.44\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e23 (33.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e81 (28.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e40 (32.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e64 (27.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e45 (66.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e203 (71.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e83 (67.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e165 (72.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePMA at Scan, Weeks, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e42.64 [41.57, 43.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e42.57 [41.14, 43.18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e42.43 [41.22, 43.57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e42.57 [41.29, 43.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.96\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGA at Birth, Weeks, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e28.78 [27.25, 30.97]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e30.57 [28.43, 32.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e30.57 [27.93, 32.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e30.29 [28.29, 31.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.93\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth weight, Gram, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e1150.00 [912.50, 1402.75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e1325.00 [1055.00, 1663.75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e1270.00 [1000.00, 1620.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e1300.00 [1020.00, 1630.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.59\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at assessment, Month, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e20.03 [20.00, 20.14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e20.05 [20.00, 20.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.21\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e20.02 [20.00, 20.12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e20.06 [20.00, 20.16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMD rank, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e10378.00 [6703.50, 18240.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e16188.00 [9695.00, 23084.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e12758.00 [7241.00, 18810.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e16898.00 [10823.00, 24590.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCognitive development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e53 (43.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e15 (6.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e70 (56.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e214 (93.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLanguage development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e53 (77.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e70 (24.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e15 (22.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e214 (75.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMotor development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e27 (39.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e9 (3.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e30 (24.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e8 (3.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 246px;\"\u003e\n \u003cp\u003e41 (60.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e273 (96.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e93 (75.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 236px;\"\u003e\n \u003cp\u003e221 (96.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMann\u0026ndash;Whitney U test was used for continuous variables and Chi-squared test was used for categorical variables. IQR: Interquartile range.\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Clinical, socio-demographic and behavioural features of participants with delayed and non-delayed development (continued)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"803\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 510px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMotor development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay group (n=38)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical group (n=314)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e23 (60.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e154 (49.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e15 (39.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e160 (50.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.39\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e14 (36.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e90 (28.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e24 (63.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e224 (71.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePMA at Scan, Weeks, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e43.00 [41.89, 43.93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e42.57 [41.14, 43.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGA at Birth, Weeks, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e28.57 [27.18, 29.93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e30.57 [28.29, 31.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth weight, Gram, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e1110.00 [773.75, 1323.75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e1315.00 [1021.25, 1646.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at assessment, Month, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e20.03 [20.00, 20.11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e20.04 [20.00, 20.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.38\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMD rank, Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e14684.50 [8476.00, 22870.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e15688.00 [9425.75, 22720.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.53\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCognitive development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e27 (71.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e41 (13.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e11 (28.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e273 (86.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLanguage development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e8 (21.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e93 (29.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e30 (78.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e221 (70.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMotor development\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTypical, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMann\u0026ndash;Whitney U test was used for continuous variables and Chi-squared test was used for categorical variables. IQR: Interquartile range\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined structural brain alterations at term in very preterm toddlers with and without selective neurodevelopmental delays. Aligned with our first hypothesis, very preterm toddlers with motor delays displayed reduced bilateral cerebellar volume at term. However, this effect was limited to the left posterior lobe of the cerebellum when accounting for cognitive and language developmental delays. These findings suggest that: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) motor developmental delays in very preterm toddlers can be detected as early as the neonatal period using T2-weighted structural brain imaging, offering opportunities for earlier intervention; and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) cognitive, language, and motor developmental delays may be associated with, albeit limited, overlapping structural brain alterations, hence the importance of treating outcomes as non-independent in statistical analyses.\u003c/p\u003e\u003cp\u003ePrevious studies have extensively investigated the relationships between brain volume at term and later developmental outcomes in very preterm children and have shown, for instance, that altered volumes in sensorimotor and premotor regions were associated with poorer cognitive and motor outcomes (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Our previous research identified an association between brain lesions and motor impairments (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), and linked reduced neonatal volume in salience network to poorer cognitive outcomes in childhood (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Expanding on these works, the current study explored how neonatal brain volume alterations related to neurodevelopmental outcomes in toddlerhood. Building upon prior studies focusing on individual developmental domains, we examined the unique association between each single domain and brain volumes, accounting for the potential neurostructural overlaps among the three domains.\u003c/p\u003e\u003cp\u003eOur findings of reduced left cerebellar volume at term in those toddlers with motor developmental delay can be interpreted in the context of previous literature showing altered cerebellar volume in preterm-born neonates compared to term-born controls (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The third trimester of gestation, i.e. 24\u0026ndash;40 weeks post-conceptual, is the most rapid and sensitive window for cerebellar development (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The identification of reduced cerebellar volume associated with very preterm birth could be explained by impaired granule cell proliferation (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) or exposure to perinatal stressors (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Our findings further support the growing evidence that the cerebellum is susceptible to early extra-uterine influence and might be implicated in the aetiology of neurodevelopmental delay in toddlerhood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur findings of reduced left cerebellar volume at term in those toddlers with motor developmental delay are also consistent with previous literature showing that decreased cerebellar volume was associated with worse motor functioning in neonates and children with cerebellar malformation and motor disorders (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). The potential mechanisms underlying the influence of altered cerebellar volume might include disrupted cerebro-cerebellar circuits essential for motor coordination, particularly the cortical-ponto-cerebellar loops modulated by cerebellar output (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and impaired olivocerebellar pathway development, potentially hindering the neural plasticity required for motor skill acquisition (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Our results further highlighted that reduced cerebellar volume was associated with toddler neurodevelopmental delay even in neonates without cerebellar injury. Vanes et al also identified an association between reduced cerebellar volume at term and poorer psychomotor functioning in toddlerhood (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). As such, altered cerebellar volume at term might be a potential biomarker for later motor delay and could be used to guide targeted, mechanism-based interventions.\u003c/p\u003e\u003cp\u003eIn contrast, we found no volumetric differences at term between toddlers with and without cognitive or language delays. These findings may be due to heterochronicity in developmental trajectories in brain areas underpinning these different dimensions. Cognitive and language functions are primarily supported by later maturing cortices, predominantly prefrontal and temporal regions, where alterations may not be sufficiently evident at term to correlate with subsequent outcomes (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). However, after accounting for language and cognitive delays, the differences between toddlers with and without motor delays in cerebellar volume at term became less extensive. These findings suggest that cerebellar spatial compartments may be engaged across multiple behavioural domains, reflecting its function as a central integrative structure (40), but also highlight the role of the posterior cerebellar lobe in supporting motor function during early human development (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBy leveraging various dimensions of neurodevelopment in toddlerhood, we were able to further explore the early structural underpinnings of delayed motor, cognitive and language development in very preterm children. Future research can further explore other factors (including parenting, environmental, and genetic information) that might influence the relation between brain structure at term and developmental outcome in toddlerhood. While the BSID-III is a widely recognised assessment tool for early development, evidence supporting its ability to accurately identify developmental delays in high-risk populations more specifically, is still scarce. Recent studies indicate that this tool may underestimate developmental delays in very preterm infants (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Future studies should incorporate a broader range of biological, genetic and perinatal risk factors to more thoroughly elucidate the potential mechanisms underlying brain structure and neurodevelopmental trajectories. Further subscales of the BSID-III, including those for fine and gross motor skills, can be employed to delve deeper into the relationship between brain structure and these specific facets of neurodevelopment. Moreover, research has highlighted the significant influence of sex on neurodevelopment (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e) and future studies may investigate the sex-specific brain structural underpinnings of neurodevelopment in males and females, rather than treating sex as a confounding variable.\u003c/p\u003e\u003cp\u003eTo summarise, this study identified volumetric alterations in the cerebellum, a critical region for motor processing, in very preterm infants with delayed motor development in toddlerhood compared to those without. While advancing our understanding of neonatal structural alterations and their association with different aspects of early development, it helps pinpoint early screening for developmental delays, which can contribute to the development of targeted early interventions to improve children\u0026rsquo;s outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAvailable to referees at submission and to readers promptly upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by: The Medical Research Council, UK [Grant numbers: MR/K006355/1 and MR/S026460/1] and Action Medical Research and Dangoor Education [Grant number: GN2606]. Data analysed in this study were collected during independent research funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research Programme [Grant number: RP-PG-0707-10154]. The study was part funded by the infrastructure of the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and Kings College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed greatly to this paper and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. SC, JH, DE, PD, DB and CN made substantial contributions to the conception and the design of the work; ML and AC contributed to the acquisition of the data, while ZS, YG, DB and CN made much effort for \u0026nbsp;analysis and interpretation of data. ZS, YG, ML, DB and CN contributed in drafting the first manuscript, and all authors participated in reviewing it critically before our final approval of the version to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the participating families of the ePrime study, and all research, radiography and clinical staff involved in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJohnson S. Cognitive and behavioural outcomes following very preterm birth. Semin Fetal Neonatal Med. 2007;12(5):363-73.\u003c/li\u003e\n\u003cli\u003eLinsell L, Malouf R, Morris J, Kurinczuk JJ, Marlow N. 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Sex differences in neurodevelopmental and neurodegenerative disorders: Focus on microglial function and neuroinflammation during development. J Steroid Biochem Mol Biol. 2016;160:127-33.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"preterm birth, neurodevelopment, cerebellum, tensor-based morphometry, Bayley Scales of Infant and Toddler Development–III","lastPublishedDoi":"10.21203/rs.3.rs-7059614/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7059614/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eVery preterm (VPT) children have high risks of neurodevelopmental delays, yet early predictors for specific impairments are poorly understood. This study investigated how neonatal brain structure relates to neurodevelopmental delays in VPT toddlers.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe analyzed T2-weighted MRI scans at term from 352 VPT children. Neurodevelopmental outcomes were assessed at 18\u0026ndash;24 months using the Bayley Scales of Infant and Toddler Development-III. We used tensor-based morphometry to compare voxel-wise whole-brain volumes between delayed and non-delayed groups.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eToddlers with motor delays showed significantly reduced volume in the left posterior cerebellum at term compared to those without, even after accounting for other delays. No significant volumetric differences were found for cognitive or language delays.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eReduced cerebellar volume at term may indicate motor delay in VPT children. These findings highlight the cerebellum's crucial role in early motor development and the value of structural MRI for early risk stratification.\u003c/p\u003e","manuscriptTitle":"Associations Between Neonatal Brain Structure and Neurodevelopmental Outcomes Following Very Preterm Birth","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 09:47:27","doi":"10.21203/rs.3.rs-7059614/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-10-01T13:31:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-01T03:17:01+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-08-06T17:11:59+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-07-25T12:48:38+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-07-11T02:33:48+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-07-09T22:27:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-07T11:01:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-06T19:32:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Perinatology","date":"2025-07-06T19:32:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e1196092-a244-4af7-a6a3-614a533eed04","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51304231,"name":"Health sciences/Medical research/Biomarkers/Predictive markers"},{"id":51304232,"name":"Health sciences/Risk factors"},{"id":51304233,"name":"Health sciences/Health care/Medical imaging"},{"id":51304234,"name":"Health sciences/Health care/Paediatrics"}],"tags":[],"updatedAt":"2026-04-16T07:13:38+00:00","versionOfRecord":{"articleIdentity":"rs-7059614","link":"https://doi.org/10.1038/s41372-026-02672-3","journal":{"identity":"journal-of-perinatology","isVorOnly":false,"title":"Journal of Perinatology"},"publishedOn":"2026-04-15 04:00:00","publishedOnDateReadable":"April 15th, 2026"},"versionCreatedAt":"2025-07-15 09:47:27","video":"","vorDoi":"10.1038/s41372-026-02672-3","vorDoiUrl":"https://doi.org/10.1038/s41372-026-02672-3","workflowStages":[]},"version":"v1","identity":"rs-7059614","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7059614","identity":"rs-7059614","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}