Identification of neonatal white matter on DTI: influence of more inclusive thresholds for atlas segmentation

Early micro- and macrostructure of sensorimotor tracts and development of cerebral palsy in high risk infants

Infants born very preterm (VPT) are at high risk of motor impairments such as cerebral palsy (CP), and diagnosis can take 2 years. Identifying in vivo determinants of CP could facilitate presymptomatic detection and targeted intervention. Our objectives were to derive micro‐ and macrostructural measures of sensorimotor white matter tract integrity from diffusion MRI at term‐equivalent age, and determine their association with early diagnosis of CP. We enrolled 263 VPT infants (≤32 weeks gestational age) as part of a large prospective cohort study. Diffusion and structural MRI were acquired at term. Following consensus guidelines, we defined early diagnosis of CP based on abnormal structural MRI at term and abnormal neuromotor exam at 3–4 months corrected age. Using Constrained Spherical Deconvolution, we derived a white matter fiber orientation distribution (fOD) for subjects, performed probabilistic whole‐brain tractography, and segmented nine sensorimotor tracts of interest. We used the recently developed fixel‐based (FB) analysis to compute fiber density (FD), fiber‐bundle cross‐section (FC), and combined fiber density and cross‐section (FDC) for each tract. Of 223 VPT infants with high‐quality diffusion MRI data, 14 (6.3%) received an early diagnosis of CP. The cohort's mean (SD) gestational age was 29.4 (2.4) weeks and postmenstrual age at MRI scan was 42.8 (1.3) weeks. FD, FC, and FDC for each sensorimotor tract were significantly associated with early CP diagnosis, with and without adjustment for confounders. Measures of sensorimotor tract integrity enhance our understanding of white matter changes that antecede and potentially contribute to the development of CP in VPT infants.

White Matter Segmentation Algorithm for DTI Images Based on Super-Pixel Full Convolutional Network

Diffusion tensor imaging (DTI) is a new imaging method that can be used to non-invasively measure the diffusion coefficient of water molecules in biological tissue structures in recent years. Since the DTI data is a tensor space, its segmentation is different from ordinary MRI images. Based on the existing deep learning model, an improved image semantic segmentation method based on super-pixels and conditional random field is proposed. Firstly, this paper uses the existing feature extraction model based on deep learning to obtain rough semantic segmentation results, including high-level semantic information of the image but lacking details of the image. In addition, the super-pixel segmentation algorithm is implemented to obtain super-pixels that carries more low-level information. Secondly, due to the lack of image details in rough segmentation results, the segmentation of the edge of the image is inaccurate. In this paper, a boundary optimization algorithm is proposed to optimize the edge segmentation accuracy of the rough results. Finally, the use of super-pixels for local boundary optimization can improve the segmentation accuracy. Experiments results show that this segment is a practical and effective method.

Early assessment of lateralization and sex influences on the microstructure of the white matter corticospinal tract in healthy term neonates

We assessed the sex and the lateralization differences in the corticospinal tract (CST) during the early postnatal period. Twenty-five healthy term neonates (13 girls, aged 39.2 ± 1.2 weeks, and 12 boys aged 38.6 ± 3.0 weeks) underwent Diffusion Tensor Imaging (DTI). Fiber tracking was performed to extract bilaterally the CST pathways and to quantify the parallel (E₁ ) and perpendicular (E₂₃ ) diffusions, the apparent diffusion coefficient (ADC), and fractional anisotropy (FA). The measurements were performed on the entire CST fibers and on four segments: base of the pons (CST-Po), cerebral peduncles (CST-CP), posterior limb of the internal capsule (CST-PLIC), and corona-radiata (CST-CR). Significantly higher E₁ , lower E_23, and higher FA in the right compared to the left were noted in the CST-PLIC of the girls. Significantly lower E₂₃ and lower ADC with higher FA in the right compared to left were observed in the CST-CP of the boys. Moreover, the CST-PLIC of the boys had significantly higher E₁ in the right compared to the left. There was a significant increase in left CST E₁ of boys when compared with girls. Girls had a significantly lower E₁ , lower E₂₃ and, lower ADC in the left CST-CP compared with boys. In addition, girls had a significantly lower E₂₃ and higher FA in the right CST-PLIC compared with boys. Sex differences and lateralization in structure-based segments of the CST were found in healthy term infants during early postnatal period. These findings are vital to understanding motor development of healthy term born neonates to better interpret newborn infants with abnormal neurodevelopment.

White Matter Associations With Performance Validity Testing in Veterans With Mild Traumatic Brain Injury: The Utility of Biomarkers in Complicated Assessment

OBJECTIVE

Failure on performance validity tests (PVTs) is common in Veterans with histories of mild traumatic brain injury (mTBI), leading to questionable validity of clinical presentations.

PARTICIPANTS

Using diffusion tensor imaging, we investigated white matter (WM) integrity and cognition in 79 Veterans with history of mTBI who passed PVTs (n = 43; traumatic brain injury [TBI]-passed), history of mTBI who failed at least 1 PVT (n = 13; TBI-failed), and military controls (n = 23; MCs) with no history of TBI.

RESULTS

The TBI-failed group demonstrated significantly lower cognitive scores relative to MCs and the TBI-passed group; however, no such differences were observed between MCs and the TBI-passed group. On a global measure of WM integrity (ie, WM burden), the TBI-failed group showed more overall WM abnormalities than the other groups. However, no differences were observed between the MCs and TBI-passed group on WM burden. Interestingly, regional WM analyses revealed abnormalities in the anterior internal capsule and cingulum of both TBI subgroups relative to MCs. Moreover, compared with the TBI-passed group, the TBI-failed group demonstrated significantly decreased WM integrity in the corpus callosum.

CONCLUSIONS

Findings revealed that, within our sample, WM abnormalities are evident in those who fail PVTs. This study adds to the burgeoning PVT literature by suggesting that poor PVT performance does not negate the possibility of underlying WM abnormalities in military personnel with history of mTBI.

Combined Diffusion Tensor and Magnetic Resonance Spectroscopic Imaging Methodology for Automated Regional Brain Analysis: Application in a Normal Pediatric Population

During human brain development, anatomic regions mature at different rates. Quantitative anatomy-specific analysis of longitudinal diffusion tensor imaging (DTI) and magnetic resonance spectroscopic imaging (MRSI) data may improve our ability to quantify and categorize these maturational changes. Computational tools designed to quickly fuse and analyze imaging information from multiple, technically different datasets would facilitate research on changes during normal brain maturation and for comparison to disease states. In the current study, we developed a complete battery of computational tools to execute such data analyses that include data preprocessing, tract-based statistical analysis from DTI data, automated brain anatomy parsing from T1-weighted MR images, assignment of metabolite information from MRSI data, and co-alignment of these multimodality data streams for reporting of region-specific indices. We present statistical analyses of regional DTI and MRSI data in a cohort of normal pediatric subjects (n = 72; age range: 5-18 years; mean 12.7 ± 3.3 years) to establish normative data and evaluate maturational trends. Several regions showed significant maturational changes for several DTI parameters and MRSI ratios, but the percent change over the age range tended to be small. In the subcortical region (combined basal ganglia [BG], thalami [TH], and corpus callosum [CC]), the largest combined percent change was a 10% increase in fractional anisotropy (FA) primarily due to increases in the BG (12.7%) and TH (9%). The largest significant percent increase in N-acetylaspartate (NAA)/creatine (Cr) ratio was seen in the brain stem (BS) (18.8%) followed by the subcortical regions in the BG (11.9%), CC (8.9%), and TH (6.0%). We found consistent, significant (p < 0.01), but weakly positive correlations (r = 0.228-0.329) between NAA/Cr ratios and mean FA in the BS, BG, and CC regions. Age- and region-specific normative MR diffusion and spectroscopic metabolite ranges show brain maturation changes and are requisite for detecting abnormalities in an injured or diseased population.

Diffusion Tensor Imaging Colour Mapping Threshold for Identification of Ventilation-Induced Brain Injury after Intrauterine Inflammation in Preterm Lambs

PURPOSE

The aim of this study is to examine whether advanced magnetic resonance imaging (MRI) techniques can detect early brain injury caused by intrauterine inflammation and inappropriate initial respiratory support in preterm lambs.

HYPOTHESIS

Neuropathology caused by intrauterine inflammation is exacerbated by mechanical ventilation at birth and is detectable with advanced MRI techniques.

METHODS

Pregnant ewes received intra-amniotic lipopolysaccharide (LPS) 7 days prior to delivery at ~125 days of gestation (85% of gestation), whereupon lambs were delivered and randomised to receive an injurious (LPS + INJ, n = 6) or protective (LPS + PROT, n = 6) ventilation strategy. MRI of the brain was conducted 90 min after preterm delivery, using structural, diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS) techniques. A colour map threshold technique was utilised to compare distributions of low diffusivity voxels in the brains of LPS-exposed lambs with those not exposed to LPS (PROT, n = 7 PROT and INJ, n = 10).

RESULTS

No overt cerebral injury was identified on structural MRI images of any lamb. However, on DTI, axial diffusivity, radial diffusivity, and mean diffusivity values were lower and significantly more heterogeneous in specific brain regions of lambs in the LPS + INJ group compared to the LPS + PROT group. Colour mapping revealed lower diffusivity in the thalamus, periventricular white matter, internal capsule, and frontal white matter in the LPS + INJ group compared to LPS + PROT group. The MRS peak area ratios of lactate, relative to those for the metabolites creatine, choline, and N-acetylaspartate, were not different between LPS-exposed groups. Lambs exposed to LPS had lower diffusivity within the white matter regions assessed than non-LPS-treated control lambs.

CONCLUSION

DTI colour map threshold techniques detected early brain injury in preterm lambs exposed to intrauterine inflammation and detected differences between injurious and protective ventilation strategies. DTI mapping approaches are potentially useful for early detection of subtle brain injury in premature infants.

Neonatal brain microstructure correlates of neurodevelopment and gait in preterm children 18-22 mo of age: an MRI and DTI study

BACKGROUND

Near-term brain structure was examined in preterm infants in relation to neurodevelopment. We hypothesized that near-term macrostructural brain abnormalities identified using conventional magnetic resonance imaging (MRI), and white matter (WM) microstructure detected using diffusion tensor imaging (DTI), would correlate with lower cognitive and motor development and slower, less-stable gait at 18-22 mo of age.

METHODS

One hundred and two very-low-birth-weight preterm infants (≤1,500 g birth weight; ≤32 wk gestational age) were recruited prior to routine near-term brain MRI at 36.6 ± 1.8 wk postmenstrual age. Cerebellar and WM macrostructure was assessed on conventional structural MRI. DTI was obtained in 66 out of 102 and WM microstructure was assessed using fractional anisotropy and mean diffusivity (MD) in six subcortical brain regions defined by DiffeoMap neonatal atlas. Neurodevelopment was assessed with Bayley-Scales-of-Infant-Toddler-Development, 3rd-Edition (BSID-III); gait was assessed using an instrumented mat.

RESULTS

Neonates with cerebellar abnormalities identified using MRI demonstrated lower mean BSID-III cognitive composite scores (89.0 ± 10.1 vs. 97.8 ± 12.4; P = 0.002) at 18-22 mo. Neonates with higher DTI-derived left posterior limb of internal capsule (PLIC) MD demonstrated lower cognitive and motor composite scores (r = -0.368; P = 0.004; r = -0.354; P = 0.006) at 18-22 mo; neonates with higher genu MD demonstrated slower gait velocity (r = -0.374; P = 0.007). Multivariate linear regression significantly predicted cognitive (adjusted r(2) = 0.247; P = 0.002) and motor score (adjusted r(2) = 0.131; P = 0.017).

CONCLUSION

Near-term cerebellar macrostructure and PLIC and genu microstructure were predictive of early neurodevelopment and gait.