Jeonbuk National University (JBNU) College of Medicine student Sehyun Lee (first-year medical student) has attracted attention by publishing research papers as first author consecutively in SCI-indexed international journals on early identification of brain developmental abnormalities in preterm infants. It is considered a highly unusual achievement for an undergraduate medical student prior to clinical training to publish consecutive first-author papers in international journals.

Sehyun Lee recently published a paper titled 'Multimodal Graphical Network Analysis of Small-for-Gestational-Age in Preterm Infants' in the international biomedical engineering journal Annals of Biomedical Engineering. This is the second SCI-indexed achievement following a paper published earlier this March in the leading neuroscience journal Brain Research Bulletin.

Annals of Biomedical Engineering is an authoritative biomedical engineering journal published by the Biomedical Engineering Society (BMES) in the United States. Since its launch in 1972, it has represented the field of biomedical engineering and is an international journal that publishes interdisciplinary medical and engineering research following rigorous peer review.

This research aims to enable early identification of brain developmental abnormalities in preterm infants born small for gestational age (SGA). It proposed a new methodology that overcomes limitations of existing brain imaging analyses.

SGA newborns are at higher risk of cognitive, language, and motor developmental delays, but existing techniques have struggled to detect subtle abnormalities at an early stage.

Under the supervision of Professor Hyunho Kim (Department of Pediatrics, Seoul St. Mary’s Hospital), Lee applied Graph Network Analysis (GNA) to neonatal research for the first time worldwide. Lee analyzed brain MRI data from 186 preterm infants in the neonatal intensive care unit at Hanyang University Hospital, integrating a total of 762 variables including brain volume, white matter microstructure, and structural connectivity.

The key advance was analyzing complex interactions precisely based on conditional dependencies rather than simple correlations between variables, thereby overcoming limitations of prior studies. The analysis identified increased cerebrospinal fluid volume, diffusion abnormalities of the left inferior longitudinal fasciculus (ILFL), and reduced connectivity centrality of the posterior cingulate cortex (PCC) as major biomarkers independently associated with SGA. The model also demonstrated high classification performance with a cross-validated AUC of 0.809.

Notably, microstructural abnormalities of the ILFL were associated with language development delays at 18–24 months of age, suggesting the potential to predict future developmental vulnerability early using neonatal brain imaging alone.

Lee said, "Observing children with developmental disorders motivated me to consider ways to detect and help them as early as possible. Through translational research that connects medicine and engineering, I want to become a physician who realizes bench-to-bedside translation of laboratory discoveries."

Professor Hyunho Kim of Seoul St. Mary’s Hospital, Lee’s advisor, said, "It is very rare for an undergraduate student to take the lead in conducting complex multimodal neuroimaging analyses. We expect this research to make a practical contribution to the early diagnosis and intervention of SGA newborns."