ArticleNeuroImage2013
Automated detection of white matter signal abnormality using T2 relaxometry: application to brain segmentation on term MRI in very preterm infants.
Article in NeuroImage, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 27 citations in OpenAlex.
- Diffuse white matter abnormality is independently predictive of neurodevelopmental outcomes in preterm infants.Archives of disease in childhood. Fetal and neonatal edition · 2026Article
- Duration of mechanical ventilation is more critical for brain growth than postnatal hydrocortisone in extremely preterm infants.European journal of pediatrics · 2021Article
- Perinatal Risk and Protective Factors in the Development of Diffuse White Matter Abnormality on Term-Equivalent Age Magnetic Resonance Imaging in Infants Born Very Preterm.The Journal of pediatrics · 2021Article
- Objectively Diagnosed Diffuse White Matter Abnormality at Term Is an Independent Predictor of Cognitive and Language Outcomes in Infants Born Very Preterm.The Journal of pediatrics · 2020Article
- Antecedents of Objectively Diagnosed Diffuse White Matter Abnormality in Very Preterm Infants.Pediatric neurology · 2020Article
- Thirteen-Year Outcomes in Very Preterm Children Associated with Diffuse Excessive High Signal Intensity on Neonatal Magnetic Resonance Imaging.The Journal of pediatrics · 2019Observational
- Objective and Automated Detection of Diffuse White Matter Abnormality in Preterm Infants Using Deep Convolutional Neural Networks.Frontiers in neuroscience · 2019Article
- Optimization of magnetization-prepared rapid gradient echo (MP-RAGE) sequence for neonatal brain MRI.Pediatric radiology · 2018Article
- T2 Relaxometry MRI Predicts Cerebral Palsy in Preterm Infants.AJNR. American journal of neuroradiology · 2018Article
- Longitudinal development in the preterm thalamus and posterior white matter: MRI correlations between diffusion weighted imaging and T2 relaxometry.Human brain mapping · 2016Article
- Differentiating T2 hyperintensity in neonatal white matter by two-compartment model of diffusional kurtosis imaging.Scientific reports · 2016Article
- Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI.Frontiers in neuroanatomy · 2015Review
- Magnetic resonance spectroscopy markers of axons and astrogliosis in relation to specific features of white matter injury in preterm infants.Neuroradiology · 2014Article
- Integration of sparse multi-modality representation and anatomical constraint for isointense infant brain MR image segmentation.NeuroImage · 2014Article
- Automatically quantified diffuse excessive high signal intensity on MRI predicts cognitive development in preterm infants.Pediatric neurology · 2013Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Hyperintense white matter signal abnormalities, also called diffuse excessive high signal intensity (DEHSI), are observed in up to 80% of very preterm infants on T2-weighted MRI scans at term-equivalent age. DEHSI may represent a developmental stage or diffuse microstructural white matter abnormalities. Automated quantitative assessment of DEHSI severity may help resolve this debate and improve neonatal brain tissue segmentation. For T2-weighted sequence without fluid attenuation, the signal intensity distribution of DEHSI greatly overlaps with that of cerebrospinal fluid (CSF) making its detection difficult. Furthermore, signal intensities of T2-weighted images are susceptible to magnetic field inhomogeneity. Increased signal intensities caused by field inhomogeneity may be confused with DEHSI. To overcome these challenges, we propose an algorithm to detect DEHSI using T2 relaxometry, whose reflection of the rapid changes in free water content provides improved distinction between CSF and DEHSI over that of conventional T2-weighted imaging. Moreover, the parametric transverse relaxation time T2 is invulnerable to magnetic field inhomogeneity. We conducted computer simulations to select an optimal detection parameter and to validate the proposed method. We also demonstrated that brain tissue segmentation is further enhanced by incorporating DEHSI detection for both simulated preterm infant brain images and in vivo in very preterm infants imaged at term-equivalent age.
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Registered trials
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