Abstract #0863

Enhanced Quantitative Susceptibility Mapping of Preterm Infant Brains via Nonlinear Total Field Inversion and Multi-parameter Regularization

Junying Cheng¹, Zhongbiao Xu², Changqing Wang³, Man Xu¹, Li Zhu¹, Liangjie Lin⁴, Yong Zhang¹, Yanqiu Feng⁵, and Jingliang Cheng¹

¹Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, ²Department of Radiotherapy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China, ³School of Biomedical Engineering, Anhui Medical University, Hefei, China, ⁴Clinical and Technical Support, Philips Healthcare, Beijing, China, ⁵School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China

Synopsis

Keywords: Neonatal, Quantitative Susceptibility mapping, Preterm infant

Motivation: Preterm birth is a leading cause of neurodevelopmental disorders.

Goal(s): Quantitative Susceptibility Mapping (QSM) is a valuable tool for studying brain development in preterm infants, but its reconstruction is susceptible to artifacts.

Approach: To address these limitations, we propose a novel nonlinear preconditioned total field inversion (TFI) method, incorporating prior information from magnitude and R2* data.

Results: Our method effectively mitigates noise and phase wrapping, leading to more accurate and robust QSM reconstructions. This enables the investigation of the spatiotemporal evolution of iron and myelin in specific brain regions of preterm infants, facilitating early identification of developmental abnormalities.

Impact: Preliminary applications in preterm infants indicate that proposed approach can successfully model the essential spatiotemporal evolution of susceptibility. This advancement holds promise for establishing a framework for tracking brain maturation in preterm-populations, setting a new way in early neurodevelopmental assessment.

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