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Background: Delayed Post-Hypoxic Leukoencephalopathy (DPHL), or Grinker’s myelinopathy, is a syndrome in which extensive changes are seen in the white matter of the cerebral hemispheres with MRI weeks or months after a hypoxic episode. T2-weighted spin echo (T2-wSE) and/or T2-Fluid Attenuated Inversion Recovery (T2-FLAIR) images classically show diffuse hyperintensities in white matter which are thought to be near pathognomonic of the condition. The clinical features include Parkinsonism and akinetic mutism. DPHL is generally regarded as a rare condition. Methods and Results: Two cases of DPHL imaged with MRI nine months and two years after probable hypoxic episodes are described. No abnormalities were seen on the T2-FLAIR images with MRI, but very extensive changes were seen in the white matter of the cerebral and cerebellar hemisphere on divided Subtraction Inversion Recovery (dSIR) images. dSIR sequences may produce ten times the contrast of conventional inversion recovery (IR) sequences from small changes in T1. The clinical findings in both cases were of cognitive impairment without Parkinsonism or akinetic mutism. Conclusion: The classic features of DPHL may only represent the severe end of a spectrum of diseases in white matter following global hypoxic injury to the brain. The condition may be much more common than is generally thought but may not be recognized using conventional clinical and MRI criteria for diagnosis. Reappraisal of the syndrome of DPHL to include clinically less severe cases and to encompass recent advances in MRI is advocated.

Our study methodology is motivated from three disparate needs: one, imaging studies have existed in silo and study organs but not across organ systems; two, there are gaps in our understanding of paediatric structure and function; three, lack of representative data in New Zealand. Our research aims to address these issues in part, through the combination of magnetic resonance imaging, advanced image processing algorithms and computational modelling. Our study demonstrated the need to take an organ-system approach and scan multiple organs on the same child. We have pilot tested an imaging protocol to be minimally disruptive to the children and demonstrated state-of-the-art image processing and personalized computational models using the imaging data. Our imaging protocol spans brain, lungs, heart, muscle, bones, abdominal and vascular systems. Our initial set of results demonstrated child-specific measurements on one dataset. This work is novel and interesting as we have run multiple computational physiology workflows to generate personalized computational models. Our proposed work is the first step towards achieving the integration of imaging and modelling improving our understanding of the human body in paediatric health and disease.