Brain Structure and Function

, Volume 221, Issue 1, pp 487–506 | Cite as

Thalamic alterations in preterm neonates and their relation to ventral striatum disturbances revealed by a combined shape and pose analysis

  • Yi Lao
  • Yalin Wang
  • Jie Shi
  • Rafael Ceschin
  • Marvin D. Nelson
  • Ashok Panigrahy
  • Natasha LeporéEmail author
Original Article


Finding the neuroanatomical correlates of prematurity is vital to understanding which structures are affected, and to designing efficient prevention and treatment strategies. Converging results reveal that thalamic abnormalities are important indicators of prematurity. However, little is known about the localization of the abnormalities within the subnuclei of the thalamus, or on the association of altered thalamic development with other deep gray matter disturbances. Here, we aim to investigate the effect of prematurity on the thalamus and the putamen in the neonatal brain, and further investigate the associated abnormalities between these two structures. Using brain structural magnetic resonance imaging, we perform a novel combined shape and pose analysis of the thalamus and putamen between 17 preterm (41.12 ± 5.08 weeks) and 19 term-born (45.51 ± 5.40 weeks) neonates at term equivalent age. We also perform a set of correlation analyses between the thalamus and the putamen, based on the surface and pose results. We locate significant alterations on specific surface regions such as the anterior and ventral anterior (VA) thalamic nuclei, and significant relative pose changes of the left thalamus and the right putamen. In addition, we detect significant association between the thalamus and the putamen for both surface and pose parameters. The regions that are significantly associated include the VA, and the anterior and inferior putamen. We detect statistically significant surface deformations and pose changes on the thalamus and putamen, and for the first time, demonstrate the feasibility of using relative pose parameters as indicators for prematurity in neonates. Our methods show that regional abnormalities of the thalamus are associated with alterations of the putamen, possibly due to disturbed development of shared pre-frontal connectivity. More specifically, the significantly correlated regions in these two structures point to frontal-subcortical pathways including the dorsolateral prefrontal-subcortical circuit, the lateral orbitofrontal-subcortical circuit, the motor circuit, and the oculomotor circuit. These findings reveal new insight into potential subcortical structural covariates for poor neurodevelopmental outcomes in the preterm population.


Frontal-subcortical circuits Pose Prematurity Subcortical structures Tensor-based morphometry 



Attentional deficit/hyperactivity disorder


Autism spectrum disorders


Dorsolateral prefrontal circuit


The lateral orbitofrontal circuit


Periventricular leukomalacia


Magnetic resonance imaging


Multivariate surface tensor-based morphometry


Point distribution model


Medial axis distance


Left thalamus


Right thalamus


Left putamen


Right putamen


Ventral anterior


Centrum medianum




The globus pallidus interna


The globus pallidus externa


The subthalamic nucleus




Autism spectrum disorders


Very preterm birth



We thank for the participation of families from Children’s Hospital Los Angeles and Children’s Hospital of Pittsburgh UPMC. This work was supported by the National Institutes of Health through NIH grant 5K23-NS063371 and grants R21EB012177 and R21AG043760. For more question, please address correspondence to: Dr. Natasha Leporé PhD, Department of Radiology, University of Southern California and Children’s Hospital Los Angeles, 4650 Sunset Blvd, MS#81, Los Angeles, CA 90027, USA, Phone:(323) 361–6276, E-mail:


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Yi Lao
    • 1
  • Yalin Wang
    • 2
  • Jie Shi
    • 2
  • Rafael Ceschin
    • 3
  • Marvin D. Nelson
    • 1
  • Ashok Panigrahy
    • 1
    • 3
  • Natasha Leporé
    • 1
    Email author
  1. 1.Department of RadiologyUniversity of Southern California and Children’s HospitalLos AngelesUSA
  2. 2.School of Computing, Informatics, and Decision Systems EngineeringArizona State UniversityTempeUSA
  3. 3.Department of RadiologyChildren’s Hospital of Pittsburgh UPMCPittsburghUSA

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