RT journal article
T1 An innovative method for assessing the relationship between longitudinal brain volume measurements and neurodevelopmental outcomes in preterm infants
A1 Ortega León, Arantxa Mireya
A1 Urda Muñoz, Daniel
A1 Turias Domínguez, Ignacio José
A1 Lubián López, Simón Pedro
A1 Benavente Fernández, Isabel
A1 Zhao, Qingyu
A1 Jafrasteh, Bahram
A2 Ingeniería Informática
A2 Materno-Infantil y Radiología
K1 Very preterm infants
K1 Gaussian processes
K1 3D ultrasound
K1 Neurodevelopmental outcomes
K1 Total brain volume
AB Predicting neurodevelopmental outcomes in very preterm infants is critical, but clinically-acquired data like longitudinal total brain volume (TBV), as macroscopic index of brain growth, are often sparse and irregular, hindering accurate prognosis. We studied 294 very preterm infants with TBV measured longitudinally and neurodevelopmental outcomes assessed at 2 years (Bayley-III) and 8 years (WISC-V). To handle missingness and irregular sampling, we compared six imputation strategies (mean, MissForest, MICE, GP, MGP, and MGP (initGP)) and trained a semi-supervised classifier on the imputed TBV trajectories. Performance was evaluated using multiple classification metrics, and results were summarized by averaging across outcomes and ages of study. Across analyses, a novel variant of Missing Gaussian Process (MGP) initialized with a GP fit (MGP (initGP)), which leverages individual patient trajectories to stabilize estimates, achieved the best average performance. Its advantages were most consistent and significant for 8-year outcomes, highlighting its strength in modeling longer developmental trajectories. While performance at 2 years was more modest, this likely reflects the intrinsic challenges of early-term prediction from TBV alone. We therefore recommend MGP (initGP) as a strong default for imputing longitudinal TBV for prognostic studies.
PB Elsevier
SN 1879-0534
YR 2025
FD 2025-10
LK http://hdl.handle.net/10498/39076
UL http://hdl.handle.net/10498/39076
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 07-nov-2026