Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Clinical Research Article
  • Published:

Novel metrics to characterize temporal lobe of very preterm infants on term-equivalent brain MRI

Pediatric Research volume 94, pages 979–986 (2023)Cite this article

Abstract

Background

Preterm birth adversely impacts brain development and contributes to neurodevelopmental impairment; the temporal lobe may be particularly vulnerable to the impact of very preterm (VP) birth. Yet, no prior magnetic resonance imaging (MRI) scoring system incorporated a method to quantify temporal lobe size in VP infants.

Methods

We developed and applied three metrics (temporal lobe length, extra-axial space, and temporal horn width) to quantify temporal lobe structure on term-equivalent brain MRIs obtained from 74 VP and 16 term infants. We compared metrics between VP and term infants and explored associations of each metric with perinatal risk factors.

Results

All metrics had excellent reliability (intra-class correlation coefficient 0.62–0.98). VP infants had lower mean temporal lobe length (76.8 mm versus 79.2 mm, p = 0.02); however, the difference attenuated after correction for postmenstrual age. VP infants had larger temporal horn widths compared with term infants (2.6 mm versus 1.8 mm, p < 0.001). Temporal lobe length was positively associated with gestational age, birth weight, and male sex, and negatively associated with the duration of parenteral nutrition.

Conclusions

The proposed metrics are reliable and sensitive in distinguishing differences in temporal lobe development between VP and full-term infants.

Impact

  • We developed a novel method for quantifying temporal lobe size among very preterm infants at term equivalent using simple metrics performed on brain MRI.

  • Temporal lobe metrics were reliable, correlated with brain volume from volumetric analysis, and were sensitive in identifying differences in temporal lobe development among preterm compared with term infants, specifically larger temporal horn size in preterm infants.

  • This temporal lobe metric system will enable future work to delineate the perinatal and postnatal factors that impact temporal lobe growth, and better understand the relationship between temporal lobe disturbance and neurodevelopment in very preterm infants.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Temporal lobe metrics on term-equivalent MRI scan of a VP infant.
Fig. 2: Population pyramid histograms for metrics of very preterm (gray bars, on left) and term (black bars, on right) infants.

Similar content being viewed by others

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Cheong, J. L. Y., Spittle, A. J., Burnett, A. C., Anderson, P. J. & Doyle, L. W. Have outcomes following extremely preterm birth improved over time. Semin. Fetal Neonatal Med. 25, 101114 (2020).

    PubMed  Google Scholar 

  2. Marlow, N. et al. No change in neurodevelopment at 11 years after extremely preterm birth. Arch. Dis. Child. Fetal Neonatal Ed. 106, 418–424 (2021).

    PubMed  Google Scholar 

  3. Anderson, P., Doyle, L. W. & Victorian Infant Collaborative Study Group. Neurobehavioral outcomes of school-age children born extremely low birth weight or very preterm in the 1990s. JAMA 289, 3264 (2003).

    PubMed  Google Scholar 

  4. Hack, M. et al. Chronic conditions, functional limitations, and special health care needs of school-aged children born with extremely low-birth-weight in the 1990s. JAMA 294, 318 (2005).

    CAS  PubMed  Google Scholar 

  5. Erdei, C., Austin, N. C., Cherkerzian, S., Morris, A. R. & Woodward, L. J. Predicting school-aged cognitive impairment in children born very preterm. Pediatrics 145, e20191982 (2020).

    PubMed  Google Scholar 

  6. Woodward, L. J., Horwood, L. J., Darlow, B. A. & Bora, S. Visuospatial working memory of children and adults born very preterm and/or very low birth weight. Pediatr. Res. 91, 1436–1444 (2022).

    PubMed  Google Scholar 

  7. Eves, R. et al. Association of very preterm birth or very low birth weight with intelligence in adulthood: an individual participant data meta-analysis. JAMA Pediatr. 175, e211058 (2021).

    PubMed  PubMed Central  Google Scholar 

  8. Robinson R. et al. ADHD symptoms and diagnosis in adult preterms: systematic review, IPD meta-analysis, and register-linkage study. Pediatr. Res. https://doi.org/10.1038/s41390-021-01929-1 (2022).

  9. Woodward, L. J., Clark, C. A. C., Bora, S. & Inder, T. E. Neonatal white matter abnormalities an important predictor of neurocognitive outcome for very preterm children. PLoS ONE 7, e51879 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Woodward, L. J., Anderson, P. J., Austin, N. C., Howard, K. & Inder, T. E. Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. N. Engl. J. Med. 355, 685–694 (2006).

    CAS  PubMed  Google Scholar 

  11. Belfort, M. B. et al. Infant growth before and after term: effects on neurodevelopment in preterm infants. Pediatrics 128, e899–e906 (2011).

    PubMed  PubMed Central  Google Scholar 

  12. Logan, J. W. et al. Adverse effects of perinatal illness severity on neurodevelopment are partially mediated by early brain abnormalities in infants born very preterm. J. Perinatol. 41, 519–527 (2021).

    CAS  PubMed  Google Scholar 

  13. Tierney, A. L. & Nelson, C. A. Brain development and the role of experience in the early years. Zero Three 30, 9–13 (2009).

    PubMed  PubMed Central  Google Scholar 

  14. Pineda, R. G. et al. Alterations in brain structure and neurodevelopmental outcome in preterm infants hospitalized in different neonatal intensive care unit environments. J. Pediatr. 164, 52.e2–60.e2 (2014).

    Google Scholar 

  15. Pineda, R. G. et al. Enhancing sensory experiences for very preterm infants in the NICU: an integrative review. J. Perinatol. 37, 323–332 (2017).

    CAS  PubMed  Google Scholar 

  16. Peterson, B. S. et al. Regional brain volumes and their later neurodevelopmental correlates in term and preterm infants. Pediatrics 111, 939–948 (2003).

    PubMed  Google Scholar 

  17. Tich S. N. T. et al. Neurodevelopmental and perinatal correlates of simple brain metrics in very preterm infants. Arch. Pediatr. Adolesc. Med. 165, 216–222 (2011).

  18. Cheong, J. L. Y. et al. Brain volumes at term-equivalent age are associated with 2-year neurodevelopment in moderate and late preterm children. J. Pediatr. 174, 91.e1–97.e1 (2016).

    Google Scholar 

  19. Rogers, C. E. et al. Regional cerebral development at term relates to school-age social-emotional development in very preterm children. J. Am. Acad. Child Adolesc. Psychiatry 51, 181–191 (2012).

    PubMed  PubMed Central  Google Scholar 

  20. Inder, T. E. et al. Neuroimaging of the preterm brain: review and recommendations. J. Pediatr. 237, 276.e4–287.e4 (2021).

    Google Scholar 

  21. Kesler, S. R. et al. Increased temporal lobe gyrification in preterm children. Neuropsychologia 44, 445–453 (2006).

    PubMed  Google Scholar 

  22. Peterson, B. S. et al. Regional brain volume abnormalities and long-term cognitive outcome in preterm infants. JAMA 284, 1939 (2000).

    CAS  PubMed  Google Scholar 

  23. Kesler, S. R. et al. Volumetric analysis of regional cerebral development in preterm children. Pediatr. Neurol. 31, 318–325 (2004).

    PubMed  PubMed Central  Google Scholar 

  24. Thompson, D. K. et al. Neonate hippocampal volumes: prematurity, perinatal predictors, and 2-year outcome. Ann. Neurol. 63, 642–651 (2008).

    PubMed  Google Scholar 

  25. Thompson, D. K. et al. Hippocampal shape variations at term equivalent age in very preterm infants compared with term controls: perinatal predictors and functional significance at age 7. Neuroimage 70, 278–287 (2013).

    PubMed  Google Scholar 

  26. Thompson, D. K. et al. Longitudinal growth and morphology of the hippocampus through childhood: Impact of prematurity and implications for memory and learning. Hum. Brain Mapp. 35, 4129–4139 (2014).

    PubMed  PubMed Central  Google Scholar 

  27. Jansen, L. et al. Associations between neonatal magnetic resonance imaging and short- and long-term neurodevelopmental outcomes in a longitudinal cohort of very preterm Children. J. Pediatr. 234, 46.e2–53.e2 (2021).

    Google Scholar 

  28. Kidokoro, H. et al. Brain injury and altered brain growth in preterm infants: predictors and prognosis. Pediatrics 134, e444–e453 (2014).

    PubMed  Google Scholar 

  29. Kidokoro, H., Neil, J. J. & Inder, T. E. New MR imaging assessment tool to define brain abnormalities in very preterm infants at term. AJNR Am. J. Neuroradiol. 34, 2208–2214 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Nguyen The Tich, S. et al. A novel quantitative simple brain metric using MR imaging for preterm infants. AJNR Am. J. Neuroradiol. 30, 125–131 (2009).

    CAS  PubMed  Google Scholar 

  31. Bell, K. A. et al. Associations of body composition with regional brain volumes and white matter microstructure in very preterm infants. Arch. Dis. Child. Fetal Neonatal Ed. 107, 533–538 (2022).

    PubMed  Google Scholar 

  32. Fedorov, A. et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn. Reson. Imaging 30, 1323–1341 (2012).

    PubMed  PubMed Central  Google Scholar 

  33. Yushkevich, P. A. et al. User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage 31, 1116–1128 (2006).

    PubMed  Google Scholar 

  34. Beare R. J. et al. Neonatal brain tissue classification with morphological adaptation and unified segmentation. Front. Neuroinform. 10, 12 (2016).

  35. Vermont Oxford Network. 2019 Vermont Oxford Network Manual of Operations, Part 2, Release 23.2. https://vtoxford.zendesk.com/hc/en-us/articles/360013115393-2019-Manual-of-Operations-Part-2-Release-23-2-PDF (2019).

  36. Koo, T. K. & Li, M. Y. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J. Chiropr. Med. 15, 155–163 (2016).

    PubMed  PubMed Central  Google Scholar 

  37. Isaacs, E. B. et al. Hippocampal volume and everyday memory in children of very low birth weight. Pediatr. Res. 47, 713–720 (2000).

    CAS  PubMed  Google Scholar 

  38. Cheong et al. Contribution of brain size to IQ and educational underperformance in extremely preterm adolescents. PLoS ONE 8, e77475 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Keunen, K. et al. Brain tissue volumes in preterm infants: prematurity, perinatal risk factors and neurodevelopmental outcome: a systematic review. J. Matern. Fetal Neonatal Med. 25, 89–100 (2012).

    PubMed  Google Scholar 

  40. Volpe, J. J. Dysmaturation of premature brain: importance, cellular mechanisms, and potential interventions. Pediatr. Neurol. 95, 42–66 (2019).

    PubMed  Google Scholar 

  41. Utsunomiya, H., Takano, K., Okazaki, M. & Mitsudome, A. Development of the temporal lobe in infants and children: analysis by MR-based volumetry. AJNR Am. J. Neuroradiol. 20, 717–723 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Bell, B., Lin, J. J., Seidenberg, M. & Hermann, B. The neurobiology of cognitive disorders in temporal lobe epilepsy. Nat. Rev. Neurol. 7, 154–164 (2011).

    PubMed  Google Scholar 

  43. Ramos-Escobar, N. et al. Hippocampal and auditory contributions to speech segmentation. Cortex 150, 1–11 (2022).

    PubMed  Google Scholar 

  44. Dien, J. et al. fMRI characterization of the language formulation area. Brain Res. 1229, 179–192 (2008).

    CAS  PubMed  Google Scholar 

  45. Gallagher, M. & Chiba, A. A. The amygdala and emotion. Curr. Opin. Neurobiol. 6, 221–227 (1996).

    CAS  PubMed  Google Scholar 

  46. Phelps, E. A. Human emotion and memory: interactions of the amygdala and hippocampal complex. Curr. Opin. Neurobiol. 14, 198–202 (2004).

    CAS  PubMed  Google Scholar 

  47. Rogers, C. E. et al. Regional cerebral development at term relates to school-age social-emotional development in very preterm children. J. Am. Acad. Child Adolesc. Psychiatry 51, 181–191 (2012).

    PubMed  PubMed Central  Google Scholar 

  48. Kersbergen et al. Longitudinal regional brain development and clinical risk factors in extremely preterm infants. J. Pediatr. 178, 93.e6–100.e6 (2016).

    Google Scholar 

  49. Belfort, M. B. & Ramel, S. E. NICU diet, physical growth and nutrient accretion, and preterm infant brain development. Neoreviews 20, e385–e396 (2019).

    PubMed  Google Scholar 

  50. Alexander, B. et al. Changes in neonatal regional brain volume associated with preterm birth and perinatal factors. Neuroimage 185, 654–663 (2019).

    PubMed  Google Scholar 

  51. Maitre, N. L. et al. The dual nature of early-life experience on somatosensory processing in the human infant brain. Curr. Biol. 27, 1048–1054 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Pineda, R. G. et al. Alterations in brain structure and neurodevelopmental outcome in preterm infants hospitalized in different neonatal intensive care unit environments. J. Pediatr. 164, 52.e2–60.e2 (2014).

    Google Scholar 

Download references

Acknowledgements

We thank the infants and their families who participated in this study.

Funding

Portions of this study were supported by a Marshall Klaus Perinatal Research Award from the American Academy of Pediatrics (KAB); Brigham and Women’s Hospital Department of Pediatric Newborn Medicine and Stork Fund, and the Brigham Research Institute Fund to Sustain Research Excellence (MBB); and the Harvard Clinical and Translational Science Center (National Center for Advancing Translational Science, grants 1UL1TR001102 and 1UL1TR002541-01). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

Author information

Author notes

  1. These authors contributed equally: Carmina Erdei, Katherine A. Bell.

Authors and Affiliations

  1. Department of Pediatric Newborn Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    Carmina Erdei, Katherine A. Bell, Aisling A. Garvey, Clementine Blaschke, Mandy B. Belfort & Terrie E. Inder

  2. Harvard Medical School, Boston, MA, USA

    Carmina Erdei, Katherine A. Bell, Aisling A. Garvey, Mandy B. Belfort & Terrie E. Inder

  3. INFANT Research Centre, University College Cork, Cork, Ireland

    Aisling A. Garvey

  4. Neonatology, University of California Irvine, Irvine, CA, USA

    Terrie E. Inder

Authors
  1. Carmina Erdei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katherine A. Bell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aisling A. Garvey
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Clementine Blaschke
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mandy B. Belfort
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Terrie E. Inder
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

C.E. and T.E.I. conceptualized the study; T.E. and M.B.B. contributed to data acquisition; C.E., K.A.B., A.G., and C.B. analyzed the data; all authors contributed to data interpretation; C.E., K.A.B., A.A.G., and C.B. wrote the initial manuscript draft; all authors provided critical review and editing of the manuscript and approved the final draft.

Corresponding author

Correspondence to Carmina Erdei.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

The parents of all infants participating in this study provided written informed consent to undergo brain magnetic resonance imaging for research purposes, under protocols approved by the Mass General Brigham Institutional Review Board.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Erdei, C., Bell, K.A., Garvey, A.A. et al. Novel metrics to characterize temporal lobe of very preterm infants on term-equivalent brain MRI. Pediatr Res 94, 979–986 (2023). https://doi.org/10.1038/s41390-023-02567-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41390-023-02567-5

This article is cited by

Search

Advanced search

Quick links