The Value of Diffusion Kurtosis Imaging in Detecting Delayed Brain Development of Premature Infants

Zhao, Xin; Zhang, Chunxiang; Yan, Jiayue; Wang, Kaiyu; Zhu, Zhang; Zhang, Xiaoan

doi:10.3389/fneur.2021.789254

Cited by 5 publications

(7 citation statements)

References 26 publications

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“…In (Zhao et al, 2021), kurtosis-related parameters, especially MK, showed to sensitively reflect the brain maturity of premature infants. Decreased MK values were registered in the preterm cohort due to the decreased density of cells and axon membranes associated with impaired brain development.…”

Section: Discussionmentioning

confidence: 99%

“…Most recent studies show how higher-order diffusion models (e.g., Diffusion Kurtosis Imaging (DKI) (Zhao et al, 2021;Ouyang et al, 2019b;Shi et al, 2016), Neurite Orientation Dispersion and Density Imaging (NODDI) (Kelly et al, 2016) or Constrained Spherical Deconvolution (CSD) (Pannek et al, 2018)) may offer unique insight into the postnatal neurological development associated with differential degrees of preterm birth, thanks to their improved sensitivity to microstructural changes. Indeed, by relating the diffusion signal more directly and specifically to underlying cellular microstructural properties, these HARDI methods allow to investigate WM microstructure with higher levels of detail and to potentially give access to richer microstructural properties, thus increasing the diagnostic values of their derived measures.…”

Section: Introductionmentioning

confidence: 99%

“…If examination of WM development in preterm neonates by using DTI is by then recognized as a trusted tool to identify neonates at high risk of neurodevelopmental impairment, the recent advent of High Angular Resolution Diffusion Imaging (HARDI) represents a promising implementation for enhancing our understanding of WM maturation compared with standard DTI metrics alone (Kunz et al, 2014). Most recent studies show how higher-order diffusion models (e.g., Diffusion Kurtosis Imaging (DKI) (Zhao et al, 2021; Ouyang et al, 2019b; Shi et al, 2016), Neurite Orientation Dispersion and Density Imaging (NODDI) (Kelly et al, 2016) or Constrained Spherical Deconvolution (CSD) (Pannek et al, 2018)) may offer unique insight into the postnatal neurological development associated with differential degrees of preterm birth, thanks to their improved sensitivity to microstructural changes.…”

Section: Introductionmentioning

confidence: 99%

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Data-driven characterization of Preterm Birth through intramodal Diffusion MRI

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Tortora

et al. 2023

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Preterm birth still represents a concrete emergency to be managed and addressed globally. Since cerebral white matter injury is the major form of brain impairment in survivors of premature birth, the identification of reliable, non-invasive markers of altered white matter development is of utmost importance in diagnostics. Diffusion MRI has recently emerged as a valuable tool to investigate these kinds of alterations. In this work, rather than focusing on a single MRI modality, we worked on a compound of beyond-DTI High Angular Resolution Diffusion Imaging (HARDI) techniques in a group of 46 preterm babies studied on a 3T scanner at term equivalent age and in 23 control neonates born at term. After extracting relevant derived parameters, we examined discriminative patterns of preterm birth through (i) a traditional voxel-wise statistical method such as the Tract-Based Spatial Statistics approach (TBSS); (ii) an advanced Machine Learning approach such as the Support Vector Machine (SVM) classification; (iii) establishing the degree of association between the two methods in voting white matter most discriminating areas. Finally, we applied a multi-set Canonical Correlation Analysis (CCA) in search for sources of linked alterations across modalities. TBSS analysis showed significant differences between preterm and term cohorts in several white matter areas for multiple HARDI features. SVM classification performed on skeletonized HARDI measures produced satisfactory accuracy rates, especially as for highly informative parameters about fibers directionality. Assessment of the degree of overlap between the relevant measures identified by the two methods exhibited a good, though parameter-dependent rate of agreement. Finally, CCA analysis identified joint changes precisely for those features exhibiting less correspondence between TBSS and SVM. Our results suggest that a data-driven intramodal imaging approach is crucial to extract deep and complementary information that cannot be extracted from a single modality.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Data-driven characterization of Preterm Birth through intramodal Diffusion MRI

Trò

Roascio

Tortora

et al. 2023

Preprint

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“…It is based on the assumption that water molecules diffuse freely and that diffusion only reflects the Gaussian distribution. It is unable to completely characterize tissue microstructure ( 10 , 11 ).…”

Section: Introductionmentioning

confidence: 99%

“…As a novel diffusion-weighted technique of MRI, DKI may provide sensitive and comprehensive measures for the quantitative evaluation of microstructural changes of brain white matter ( 10 – 12 ). DKI exhibited improved specificity in detecting pathological changes in the developing brain ( 10 , 11 ). DKI may provide both diffusion metrics, such as fractional anisotropy (FA), as well as kurtosis parameters, including mean kurtosis (MK), which is specific parameter that cannot be expressed by DTI.…”

Section: Introductionmentioning

confidence: 99%

Microstructural changes of white matter assessed with diffusional kurtosis imaging in extremely preterm infants with severe intraventricular hemorrhage

et al. 2022

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ObjectiveIntraventricular hemorrhage (IVH) is a serious neurological complication in premature infants. This study aimed to investigate the white matter impairments and neurodevelopmental outcomes of severe IVH in extremely preterm infants with gestation age less than 28 weeks.MethodsWe retrospectively evaluated the extremely preterm infants between 2017 and 2020. Neurodevelopmental outcomes were evaluated with the Bayley Scales of Infant and Toddler Development-III at 2 years of corrected age. Diffusional kurtosis imaging (DKI) was employed to evaluate the microstructural changes in white matter tracts. Mean kurtosis (MK) and fractional anisotropy (FA) values of DKI were measured in the brain regions including posterior limbs of the internal capsule (PLIC) and the corpus callosum at term equivalent age.ResultsOf 32 extremely preterm infants with severe IVH during the follow-up period, 18 cases were identified as neurodevelopmental impairments. The delay rates of motor and language were 58.4% and 52.7%. The cases with neurodevelopmental impairments had lower MK and FA values in both bilateral PLIC and the corpus callosum. The analysis of multivariable regression models predicting motor and language outcomes at 2 years of corrected age, showed that the decreases of MK values in both PLIC and the corpus callosum at the term equivalent age contributed to a significantly increased risk of neurodevelopmental impairments (all p < 0.05). During follow-up period, obvious loss of nerve fiber bundles was observed with DKI tractography.ConclusionMotor and language abilities at age 2 years were associated with MK values of DKI at the term equivalent age in both PLIC and the corpus callosum of extremely preterm infants with severe IVH. The evaluation of white matter microstructural changes with MK values might provide feasible indicators of neurodevelopmental outcomes of extremely preterm infants with severe intraventricular hemorrhage.

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