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Abstract #1606

Structural Network Efficiency as an Early Predictor of Cognitive Delay in Premature Infants with Mild PWML: A Longitudinal Cohort Study

Miaomiao Wang1,2,3, Congcong Liu1,2,3, Xianjun Li1, Pengxuan Bai1, Xiaoyu Wang1, Chenyue Liu1, Chunxu Da1, Shuai Wang1, Xinyi Huang1, Zhujun Li1, and Jian Yang1,2,3
1Department of Diagnostic Radiology, the First Affiliated Hospital of Xi’an Jiaotong University, Xi'an, China, 2Shaanxi Engineering Research Center of Computational Imaging and Medical Intelligence, Xi'an, China, 3Xi’an Key Laboratory of Medical Computational Imaging, Xi'an, China

Synopsis

Keywords: White Matter, Diagnosis/Prediction

Motivation: Punctate white matter lesions (PWML) are common in the preterm. Since previous studies have primarily concentrated on severe cases, the neurodevelopmental outcomes and its structural connectivity alterations associated with mild lesions require further clarification.

Goal(s): This study aims to investigate the relationship between DTI network parameters and the outcome at a corrected age of 6 months of mild PWML.

Approach: The DTI network characteristics among groups were analyzed.

Results: PWML mainly associated with delayed cognitive development, and decreased local efficiency in left inferior parietal lobule and right supplementary motor area can serve as early diagnostic markers for this adverse outcome.

Impact: This result can offer an early screening plan for identifying preterm infants with mild PWML who are at risk of poor cognitive prognosis, which is beneficial for early intervention and improving outcomes.

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Keywords