T2 at MR Imaging Is an Objective Quantitative Measure of Cerebral White Matter Signal Intensity Abnormality in Preterm Infants at Term-equivalent Age

In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences

PURPOSE

We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements.

METHODS

Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system.

RESULTS

The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies.

CONCLUSION

The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.

A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation.

Three-Dimensional Magnetic Resonance Fingerprinting in Neonates: Quantifying Regional Difference and Maturation in the Brain

OBJECTIVES

Magnetic resonance fingerprinting (MRF) allows the simultaneous measurement of multiple tissue properties in a single acquisition. Three-dimensional (3D) MRF with high spatial resolution can be used for neonatal brain imaging. The aim of this study is to apply 3D MRF to neonates and show regional differences and maturation in the brain.

MATERIALS AND METHODS

In this prospective study, 3D MRF using hybrid radial-interleaved acquisition was performed on phantoms and neonates from December 2019 to October 2020. For the reconstruction of 3D MRF, singular value decomposition was applied to reduce reconstruction time, and the iterative reconstruction technique was applied to improve image quality. The accuracies of T1 and T2 values derived from 3D MRF were evaluated in a phantom experiment. Regional T1 and T2 values were obtained from neonates' brain T1 and T2 maps derived from 3D MRF. Regional T1 and T2 values were compared, and their changes according to corrected gestational age were evaluated.

RESULTS

The acquisition time for 3D MRF with a spatial resolution of 0.7 × 0.7 × 2 mm3 was less than 5 minutes. The phantom study showed high correlation between T1 and T2 values derived from 3D MRF and those from conventional spin echo sequences (T1, R2 = 0.998, P < 0.001; T2, R2 = 0.998, P < 0.001). Three-dimensional MRF was performed in 25 neonates (15 boys, 10 girls; median corrected gestational age, 263 days; interquartile range, 10 days). In neonates, T1 and T2 values differed in the frontal (median [interquartile range], 2785 [2684-2888] milliseconds and 189.8 [176.7-222.9] milliseconds), parietal (2849 [2741-2950] milliseconds and 191.6 [167.5-232.9] milliseconds), and occipital white matter (2621 [2513-2722] milliseconds and 162.9 [143.5-186.1] milliseconds), showing lower values in occipital white matter (P < 0.001). Regional T1 values showed a negative relationship with corrected gestational age (coefficient, -0.775 to -0.480; P < 0.05).

CONCLUSIONS

Fast and high spatial resolution 3D MRF was applied to neonates. T1 and T2 maps derived from 3D MRF enabled the quantification of regional differences and maturation in the neonatal brain.

Automatic Segmentation of Diffuse White Matter Abnormality on T2-weighted Brain MR Images Using Deep Learning in Very Preterm Infants

About 50%-80% of very preterm infants (VPIs) (≤ 32 weeks gestational age) exhibit diffuse white matter abnormality (DWMA) on their MR images at term-equivalent age. It remains unknown if DWMA is associated with developmental impairments, and further study is warranted. To aid in the assessment of DWMA, a deep learning model for DWMA quantification on T2-weighted MR images was developed. This secondary analysis of prospective data was performed with an internal cohort of 98 VPIs (data collected from December 2014 to April 2016) and an external cohort of 28 VPIs (data collected from January 2012 to August 2014) who had already undergone MRI at term-equivalent age. Ground truth DWMA regions were manually annotated by two human experts with the guidance of a prior published semiautomated algorithm. In a twofold cross-validation experiment using the internal cohort of 98 infants, the three-dimensional (3D) ResU-Net model accurately segmented DWMA with a Dice similarity coefficient of 0.907 ± 0.041 (standard deviation) and balanced accuracy of 96.0% ± 2.1, outperforming multiple peer deep learning models. The 3D ResU-Net model that was trained with the whole internal cohort (n = 98) was further tested on an independent external test cohort (n = 28) and achieved a Dice similarity coefficient of 0.877 ± 0.059 and balanced accuracy of 92.3% ± 3.9. The externally validated 3D ResU-Net deep learning model for accurately segmenting DWMA may facilitate the clinical diagnosis of DWMA in VPIs. Supplemental material is available for this article. Keywords: Brain/Brain Stem, Convolutional Neural Network (CNN), MR-Imaging, Pediatrics, Segmentation, Supervised learning © RSNA, 2021.

Synthetic MRI demonstrates prolonged regional relaxation times in the brain of preterm born neonates with severe postnatal morbidity

BACKGROUND

To identify preterm infants at risk for neurodevelopment impairment that might benefit from early neurorehabilitation, early prognostic biomarkers of future outcomes are needed.

OBJECTIVE

To determine whether synthetic MRI is sensitive to age-related changes in regional tissue relaxation times in the brain of preterm born neonates when scanned at term equivalent age (TEA, 37-42 weeks), and to investigate whether severe postnatal morbidity results in prolonged regional tissue relaxation times.

MATERIALS AND METHODS

This retrospective study included 70 very preterm born infants scanned with conventional and synthetic MRI between January 2017 and June 2019 at TEA. Infants with severe postnatal morbidity were allocated to a high-risk group (n = 22). All other neonates were allocated to a low-risk group (n = 48). Linear regression analysis was performed to determine the relationship between relaxation times and postmenstrual age (PMA) at scan. Analysis of covariance was used to evaluate the impact of severe postnatal morbidity in the high-risk group on T1 and T2 relaxation times. Receiver operating characteristic (ROC) curves were plotted and analysed with area under the ROC curve (AUC) to evaluate the accuracy of classifying high-risk patients based on regional relaxation times.

RESULTS

A linear age-related decrease of T1 and T2 relaxation times correlating with PMA at scan (between 37 and 42 weeks) was found in the deep gray matter, the cerebellum, the cortex, and the posterior limb of the internal capsule (PLIC) (p < .005 each), but not in the global, frontal, parietal, or central white matter. Analysis of covariance for both risk groups, adjusted for PMA, revealed significantly prolonged regional tissue relaxation times in neonates with severe postnatal morbidity, which was best illustrated in the central white matter of the centrum semiovale (T1 Δ = 11.5%, T2 Δ = 13.4%, p < .001) and in the PLIC (T1 Δ = 9.2%, T2 Δ = 6.9%, p < .001). The relaxation times in the PLIC and the central white matter predicted high-risk status with excellent accuracy (AUC range 0.82-0.86).

CONCLUSION

Synthetic MRI-based relaxometry in the brain of preterm born neonates is sensitive to age-related maturational changes close to TEA. Severe postnatal morbidity correlated with a significant delay in tissue relaxation. Synthetic MRI may provide early prognostic biomarkers for neurodevelopment impairment.

Objective and Automated Detection of Diffuse White Matter Abnormality in Preterm Infants Using Deep Convolutional Neural Networks

Diffuse white matter abnormality (DWMA), or diffuse excessive high signal intensity is observed in 50-80% of very preterm infants at term-equivalent age. It is subjectively defined as higher than normal signal intensity in periventricular and subcortical white matter in comparison to normal unmyelinated white matter on T2-weighted MRI images. Despite the well-documented presence of DWMA, it remains debatable whether DWMA represents pathological tissue injury or a transient developmental phenomenon. Manual tracing of DWMA exhibits poor reliability and reproducibility and unduly increases image processing time. Thus, objective and ideally automatic assessment is critical to accurately elucidate the biologic nature of DWMA. We propose a deep learning approach to automatically identify DWMA regions on T2-weighted MRI images. Specifically, we formulated DWMA detection as an image voxel classification task; that is, the voxels on T2-weighted images are treated as samples and exclusively assigned as DWMA or normal white matter voxel classes. To utilize the spatial information of individual voxels, small image patches centered on the given voxels are retrieved. A deep convolutional neural networks (CNN) model was developed to differentiate DWMA and normal voxels. We tested our deep CNN in multiple validation experiments. First, we examined DWMA detection accuracy of our CNN model using computer simulations. This was followed by in vivo assessments in a cohort of very preterm infants (N = 95) using cross-validation and holdout validation. Finally, we tested our approach on an independent preterm cohort (N = 28) to externally validate our model. Our deep CNN model achieved Dice similarity index values ranging from 0.85 to 0.99 for DWMA detection in the aforementioned validation experiments. Our proposed deep CNN model exhibited significantly better performance than other popular machine learning models. We present an objective and automated approach for accurately identifying DWMA that may facilitate the clinical diagnosis of DWMA in very preterm infants.

T2 Relaxometry MRI Predicts Cerebral Palsy in Preterm Infants

BACKGROUND AND PURPOSE

T2-relaxometry brain MR imaging enables objective measurement of brain maturation based on the water-macromolecule ratio in white matter, but the outcome correlation is not established in preterm infants. Our study aimed to predict neurodevelopment with T2-relaxation values of brain MR imaging among preterm infants.

MATERIALS AND METHODS

From January 1, 2012, to May 31, 2015, preterm infants who underwent both T2-relaxometry brain MR imaging and neurodevelopmental follow-up were retrospectively reviewed. T2-relaxation values were measured over the periventricular white matter, including sections through the frontal horns, midbody of the lateral ventricles, and centrum semiovale. Periventricular T2 relaxometry in relation to corrected age was analyzed with restricted cubic spline regression. Prediction of cerebral palsy was examined with the receiver operating characteristic curve.

RESULTS

Thirty-eight preterm infants were enrolled for analysis. Twenty patients (52.6%) had neurodevelopmental abnormalities, including 8 (21%) with developmental delay without cerebral palsy and 12 (31.6%) with cerebral palsy. The periventricular T2-relaxation values in relation to age were curvilinear in preterm infants with normal development, linear in those with developmental delay without cerebral palsy, and flat in those with cerebral palsy. When MR imaging was performed at >1 month corrected age, cerebral palsy could be predicted with T2 relaxometry of the periventricular white matter on sections through the midbody of the lateral ventricles (area under the receiver operating characteristic curve = 0.738; cutoff value of >217.4 with 63.6% sensitivity and 100.0% specificity).

CONCLUSIONS

T2-relaxometry brain MR imaging could provide prognostic prediction of neurodevelopmental outcomes in premature infants. Age-dependent and area-selective interpretation in preterm brains should be emphasized.

Cerebral White Matter Maturation Patterns in Preterm Infants: An MRI T2 Relaxation Anisotropy and Diffusion Tensor Imaging Study

BACKGROUND AND PURPOSE

Preterm birth is associated with worse neurodevelopmental outcome, but brain maturation in preterm infants is poorly characterized with standard methods. We evaluated white matter (WM) of infant brains at term-equivalent age, as a function of gestational age at birth, using multimodal magnetic resonance imaging (MRI).

METHODS

Infants born very preterm (<32 weeks gestation) and late preterm (33-36 weeks gestation) were scanned at 3 T at term-equivalent age using diffusion tensor imaging (DTI) and T2 relaxometry. MRI data were analyzed using tract-based spatial statistics, and anisotropy of T2 relaxation was also determined. Principal component analysis and linear discriminant analysis were applied to seek the variables best distinguishing very preterm and late preterm groups.

RESULTS

Across widespread regions of WM, T2 is longer in very preterm infants than in late preterm ones. These effects are more prevalent in regions of WM that myelinate earlier and faster. Similar effects are obtained from DTI, showing that fractional anisotropy (FA) is lower and radial diffusivity higher in the very preterm group, with a bias toward earlier myelinating regions. Discriminant analysis shows high sensitivity and specificity of combined T2 relaxometry and DTI for the detection of a distinct WM development pathway in very preterm infants. T2 relaxation is anisotropic, depending on the angle between WM fiber and magnetic field, and this effect is modulated by FA.

CONCLUSIONS

Combined T2 relaxometry and DTI characterizes specific patterns of retarded WM maturation, at term equivalent age, in infants born very preterm relative to late preterm.

Detection and assessment of brain injury in the growth-restricted fetus and neonate

Fetal growth restriction (FGR) is a common complication of pregnancy and, in severe cases, is associated with elevated rates of perinatal mortality, neonatal morbidity, and poor neurodevelopmental outcomes. The leading cause of FGR is placental insufficiency, with the placenta failing to adequately meet the increasing oxygen and nutritional needs of the growing fetus with advancing gestation. The resultant chronic fetal hypoxia induces a decrease in fetal growth, and a redistribution of blood flow preferentially to the brain. However, this adaptation does not ensure normal brain development. Early detection of brain injury in FGR, allowing for the prediction of short- and long-term neurodevelopmental consequences, remains a significant challenge. Furthermore, in FGR infants the detection and diagnosis of neuropathology is complicated by preterm birth, the etiological heterogeneity of FGR, timing of onset of growth restriction, its severity, and coexisting complications. In this review, we examine existing and emerging diagnostic tools from human and preclinical studies for the detection and assessment of brain injury in FGR fetuses and neonates. Increased detection rates, and early detection of brain injury associated with FGR, will offer opportunities for developing and assessing interventions to improve long-term outcomes.

Differentiating T2 hyperintensity in neonatal white matter by two-compartment model of diffusional kurtosis imaging

In conventional neonatal MRI, the T2 hyperintensity (T2h) in cerebral white matter (WM) at term-equivalent age due to immaturity or impairment is still difficult to identify. To clarify such issue, this study used the metrics derived from a two-compartment WM model of diffusional kurtosis imaging (WM-DKI), including intra-axonal, extra-axonal axial and radial diffusivities (D_a, D_e,// and D_e,⊥), to compare WM differences between the simple T2h and normal control for both preterm and full-term neonates, and between simple T2h and complex T2h with hypoxic-ischemic encephalopathy (HIE). Results indicated that compared with control, the simple T2h showed significantly increased D_e,// and D_e,⊥, but no significant change in D_a in multiple premyelination regions, indicative of expanding extra-axonal diffusion microenvironment; while myelinated regions showed no changes. However, compared with simple T2h, the complex T2h with HIE had decreased D_a, increased D_e,⊥ in both premyelination and myelinated regions, indicative of both intra- and extra-axonal diffusion alterations. While diffusion tensor imaging (DTI) failed to distinguish simple T2h from complex T2h with HIE. In conclusion, superior to DTI-metrics, WM-DKI metrics showed more specificity for WM microstructural changes to distinguish simple T2h from complex T2h with HIE.

Longitudinal development in the preterm thalamus and posterior white matter: MRI correlations between diffusion weighted imaging and T2 relaxometry

Infants born prematurely are at increased risk of adverse neurodevelopmental outcome. The measurement of white matter tissue composition and structure can help predict functional performance. Specifically, measurements of myelination and indicators of myelination status in the preterm brain could be predictive of later neurological outcome. Quantitative imaging of myelin could thus serve to develop biomarkers for prognosis or therapeutic intervention; however, accurate estimation of myelin content is difficult. This work combines diffusion MRI and multi-component T2 relaxation measurements in a group of 37 infants born very preterm and scanned between 27 and 58 weeks equivalent gestational age. Seven infants have longitudinal data at two time points that we analyze in detail. Our aim is to show that measurement of the myelin water fraction is achievable using widely available pulse sequences and state-of-the-art algorithmic modeling of the MR imaging procedure and that a multi-component fitting routine to multi-shell diffusion weighted data can show differences in neurite density and local spatial arrangement in grey and white matter. Inference on the myelin water fraction allows us to demonstrate that the change in diffusion properties of the preterm thalamus is not solely due to myelination (that increase in myelin content accounts for about a third of the observed changes) whilst the decrease in the posterior white matter T2 has no significant component that is due to myelin water content. This work applies multi-modal advanced quantitative neuroimaging to investigate changing tissue properties in the longitudinal setting. Hum Brain Mapp 37:2479-2492, 2016. © 2016 Wiley Periodicals, Inc.

Clinical Implications of Diffuse Excessive High Signal Intensity (DEHSI) on Neonatal MRI in School Age Children Born Extremely Preterm

OBJECTIVE

Magnetic resonance imaging (MRI) of the brain carried out during the neonatal period shows that 55-80% of extremely preterm infants display white matter diffuse excessive high signal intensity (DEHSI). Our aim was to study differences in developmental outcome at the age of 6.5 years in children born extremely preterm with and without DEHSI.

STUDY DESIGN

This was a prospective cohort study of 83 children who were born in Stockholm, Sweden, between 2004 and 2007, born at gestational age of < 27 weeks + 0 days and who underwent an MRI scan of their brain at term equivalent age. The outcome measures at 6.5 years included testing 66 children with the modified Touwen neurology examination, the Movement Assessment Battery for Children 2, the Wechsler Intelligence Scale for Children-Fourth Edition, Beery Visual-motor Integration test-Sixth Edition, and the Strengths and Difficulties Questionnaire. Group-wise comparisons were done between children with and without DEHSI using Student t-test, Mann Whitney U test, Chi square test and regression analysis.

RESULTS

DEHSI was detected in 39 (59%) of the 66 children who were assessed at 6.5 years. The presence of DEHSI was not associated with mild neurological dysfunction, scores on M-ABC assessment, cognition, visual-motor integration, or behavior at 6.5 years.

CONCLUSION

The presence of qualitatively defined DEHSI on neonatal MRI did not prove to be a useful predictor of long-term impairment in children born extremely preterm.

T2 relaxometry in the extremely-preterm brain at adolescence

Survival following very preterm birth is associated with cognitive and behavioral sequelae, which may have identifiable neural correlates. Many survivors of modern neonatal care in the 1990s are now young adults and the evolution of MRI findings into adult life has rarely been evaluated. We have investigated a cohort of 19-year-old adolescents without severe impairments born between 22 and 26 weeks of gestation in 1995 (extremely preterm: EP). Using T2 data derived from magnetic resonance imaging we investigate differences between the brains of 46 EP participants (n = 46) and the brains of a group of term-born controls (n = 20). Despite EP adolescents having significantly reduced gray and white matter volumes, the composition of these tissues, assessed by both single and multi-component relaxometry, appears to be unrelated to either preterm status or gender. This may represent either insensitivity of the imaging technique or reflect that there are only subtle differences between EP subjects and their term-born peers.

T2* relaxometry of fetal brain at 1.5 Tesla using a motion tolerant method

PURPOSE

The aim of this study was to determine T2* values for the fetal brain in utero and to compare them with previously reported values in preterm and term neonates. Knowledge of T2* may be useful for assessing brain development, brain abnormalities, and for optimizing functional imaging studies.

METHODS

Maternal respiration and unpredictable fetal motion mean that conventional multishot acquisition techniques used in adult T2* relaxometry studies are not practical. Single shot multiecho echo planar imaging was used as a rapid method for measuring fetal T2* by effectively freezing intra-slice motion.

RESULTS

T2* determined from a sample of 24 subjects correlated negatively with gestational age with mean values of 220 ms (±45) for frontal white matter, 159 ms (±32) for thalamic gray matter, and 236 ms (±45) for occipital white matter.

CONCLUSION

Fetal T2* values are higher than those previously reported for preterm neonates and decline with a consistent trend across gestational age. The data suggest that longer than usual echo times or direct T2* measurement should be considered when performing fetal fMRI to reach optimal BOLD sensitivity.

Neurodevelopmental outcome at 36 months in very low birth weight premature infants with MR diffuse excessive high signal intensity (DEHSI) of cerebral white matter

PURPOSE

To understand the meaning of diffuse excessive high signal intensity (DEHSI) of white matter (WM), a frequently observed finding on MR in VLBW infants at a corrected term age.

METHODS

This is a retrospective study. Qualitative visual assessment of cerebral WM signal intensity on T2WI was performed by two readers on 78 VLBW infants, scanned on a 1.5 T-MRI at term equivalent age. ADC values were then measured in six regions of interest: four in frontal and parietal periventricular and two in parietal subcortical WM. Mean ADC values were then compared with qualitative visual assessment and with mean ADC values obtained ten term healthy babies. Both periventricular and subcortical mean ADC values were correlated with the neurological follow-up, evaluated with the Griffith's mental developmental scale at 36 months.

RESULTS

There was no agreement between the visual qualitative assessment of white matter DEHSI and corresponding ADC values (P values = 0.42 for periventricular WM; P values = 0.18 for subcortical WM). Mean ADC values were higher in preterms than in term babies (P values <0.001). No significant correlation was found between ADC values and the developmental quotient at 36 months (P values >0.05).

CONCLUSIONS

DEHSI in VLBW infants is a MR finding poorly defined with conventional T2 MRI. The presence of T2 hyperintensities weakly correlates with ADC, and ADC values are not associated with the neurological long-term outcome at 3 years, demonstrating that DEHSI should not be considered as a WM disease.

Isolated mild white matter signal changes in preterm infants: a regional approach for comparison of cranial ultrasound and MRI findings

OBJECTIVE

To compare echogenicity detected using cranial ultrasound (cUS) and diffuse excessive high signal intensity (DEHSI) detected using magnetic resonance imaging (MRI) by identical region-based scoring criteria in preterm infants. To explore the association between these white matter (WM) signal changes with early neurobehavior.

STUDY DESIGN

Forty-nine pre-selected premature infants with only echogenicity on a first routine cUS1 underwent MRI and a repeated cUS2 at term equivalent age. Echogenicity and DEHSI were graded in various brain areas and diffusivity values were calculated. Neurobehavior was assessed using the Rapid Neonatal Neurobehavioral Assessment Procedure.

RESULT

WM signal changes were significantly higher on cUS1 than cUS2; and higher in MRI than cUS2 in posterior regions. Infants with DEHSI demonstrated reduced tissue integrity. Imaging findings were not correlated with early neurobehavior.

CONCLUSION

Echogenicity and DEHSI likely represent the same phenomenon. Reduction of over-interpretation of WM signal changes may help define criteria for the judicious use of imaging in routine follow-up of premature infants.

Measurement of myelin in the preterm brain: multi-compartment diffusion imaging and multi-component T2 relaxometry

Measurements of myelination and indicators of myelination status in the preterm brain could be predictive of later neurological outcome. Quantitative imaging of myelin could thus serve to develop predictive biomarkers; however, accurate estimation of myelin content is difficult. In this work we show that measurement of the myelin water fraction (MWF) is achievable using widely available pulse sequences and state-of-the-art algorithmic modelling of the MR imaging. We show results of myelin water fraction measurement at both 30 (4 infants) and 40 (2 infants) weeks equivalent gestational age (EGA) and show that the spatial pattern of myelin is different between these ages. Furthermore we apply a multi-component fitting routine to multi-shell diffusion weighted data to show differences in neurite density and local spatial arrangement in grey and white matter. Finally we combine these results to investigate the relationships between the diffusion and myelin measurements to show that MWF in the preterm brain may be measured alongside multi-component diffusion characteristics using clinically feasible MR sequences.

Definition and quantification of acute inflammatory white matter injury in the immature brain by MRI/MRS at high magnetic field

BACKGROUND

Lipopolysaccharide (LPS) injection in the corpus callosum (CC) of rat pups results in diffuse white matter injury similar to the main neuropathology of preterm infants. The aim of this study was to characterize the structural and metabolic markers of acute inflammatory injury by high-field magnetic resonance imaging (MRI) magnetic resonance spectroscopy (MRS) in vivo.

METHODS

Twenty-four hours after a 1-mg/kg injection of LPS in postnatal day 3 rat pups, diffusion tensor imaging and proton nuclear magnetic spectroscopy ((1)H NMR) were analyzed in conjunction to determine markers of cell death and inflammation using immunohistochemistry and gene expression.

RESULTS

MRI and MRS in the CC revealed an increase in lactate and free lipids and a decrease of the apparent diffusion coefficient. Detailed evaluation of the CC showed a marked apoptotic response assessed by fractin expression. Interestingly, the degree of reduction in the apparent diffusion coefficient correlated strongly with the natural logarithm of fractin expression, in the same region of interest. LPS injection further resulted in increased activated microglia clustered in the cingulum, widespread astrogliosis, and increased expression of genes for interleukin (IL)-1, IL-6, and tumor necrosis factor.

CONCLUSION

This model was able to reproduce the typical MRI hallmarks of acute diffuse white matter injury seen in preterm infants and allowed the evaluation of in vivo biomarkers of acute neuropathology after inflammatory challenge.

Atlas-guided quantification of white matter signal abnormalities on term-equivalent age MRI in very preterm infants: findings predict language and cognitive development at two years of age

The developmental significance of the frequently encountered white matter signal abnormality (WMSA) findings on MRI around term-equivalent age (TEA) in very preterm infants, remains in question. The use of conventional qualitative analysis methods is subjective, lacks sufficient reliability for producing accurate and reproducible WMSA diagnosis, and possibly contributes to suboptimal neurodevelopmental outcome prediction. The advantages of quantitative over qualitative diagnostic approaches have been widely acknowledged and demonstrated. The purpose of this study is to objectively and accurately quantify WMSA on TEA T2-weighted MRI in very preterm infants and to assess whether such quantifications predict 2-year language and cognitive developmental outcomes. To this end, we constructed a probabilistic brain atlas, exclusively for very preterm infants to embed tissue distributions (i.e. to encode shapes, locations and geometrical proportion of anatomical structures). Guided with this atlas, we then developed a fully automated method for WMSA detection and quantification using T2-weighted images. Computer simulations and experiments using in vivo very preterm data showed very high detection accuracy. WMSA volume, particularly in the centrum semiovale, on TEA MRI was a significant predictor of standardized language and cognitive scores at 2 years of age. Independent validation of our automated WMSA detection algorithm and school age follow-up are important next steps.

Automatic segmentation of eight tissue classes in neonatal brain MRI

Purpose

Volumetric measurements of neonatal brain tissues may be used as a biomarker for later neurodevelopmental outcome. We propose an automatic method for probabilistic brain segmentation in neonatal MRIs.

Materials and Methods

In an IRB-approved study axial T1- and T2-weighted MR images were acquired at term-equivalent age for a preterm cohort of 108 neonates. A method for automatic probabilistic segmentation of the images into eight cerebral tissue classes was developed: cortical and central grey matter, unmyelinated and myelinated white matter, cerebrospinal fluid in the ventricles and in the extra cerebral space, brainstem and cerebellum. Segmentation is based on supervised pixel classification using intensity values and spatial positions of the image voxels. The method was trained and evaluated using leave-one-out experiments on seven images, for which an expert had set a reference standard manually. Subsequently, the method was applied to the remaining 101 scans, and the resulting segmentations were evaluated visually by three experts. Finally, volumes of the eight segmented tissue classes were determined for each patient.

Results

The Dice similarity coefficients of the segmented tissue classes, except myelinated white matter, ranged from 0.75 to 0.92. Myelinated white matter was difficult to segment and the achieved Dice coefficient was 0.47. Visual analysis of the results demonstrated accurate segmentations of the eight tissue classes. The probabilistic segmentation method produced volumes that compared favorably with the reference standard.

Conclusion

The proposed method provides accurate segmentation of neonatal brain MR images into all given tissue classes, except myelinated white matter. This is the one of the first methods that distinguishes cerebrospinal fluid in the ventricles from cerebrospinal fluid in the extracerebral space. This method might be helpful in predicting neurodevelopmental outcome and useful for evaluating neuroprotective clinical trials in neonates.

Preterm birth affects the developmental synergy between cortical folding and cortical connectivity observed on multimodal MRI

The survival rates of infants born prematurely have improved as a result of advances in neonatal care, although there remains an increased risk of subsequent disability. Accurate measurement of the shape and appearance of the very preterm brain at term-equivalent age may guide the development of predictive biomarkers of neurological outcome. We demonstrate in 92 preterm infants (born at an average gestational age of 27.0±2.7weeks) scanned at term equivalent age (scanned at 40.4±1.74weeks) that the cortical sulcation ratio varies spatially over the cortical surface at term equivalent age and correlates significantly with gestational age at birth (r=0.49,p<0.0001). In the underlying white matter, fractional anisotropy of local white matter regions correlated significantly with gestational age at birth at term equivalent age (for the genu of the corpus callosum r=0.26,p=0.02 and for the splenium r=0.52,p<0.001) and in addition the fractional anisotropy in these local regions varies according to location. Finally, we demonstrate that connectivity measurements from tractography correlate significantly and specifically with the sulcation ratio of the overlying cortical surface at term equivalent age in a subgroup of 20 infants (r={0.67,0.61,0.86}, p={0.004,0.01,0.00002}) for tract systems emanating from the left and right corticospinal tracts and the corpus callosum respectively). Combined, these results suggest a close relationship between the cortical surface phenotype and underlying white matter structure assessed by diffusion weighted MRI. The spatial surface pattern may allow inference on the connectivity and developmental trajectory of the underlying white matter complementary to diffusion imaging and this result may guide the development of biomarkers of functional outcome.

White matter NAA/Cho and Cho/Cr ratios at MR spectroscopy are predictive of motor outcome in preterm infants

PURPOSE

To determine (a) whether diffuse white matter injury of prematurity is associated with an increased choline (Cho)-to-creatine (Cr) ratio and a reduced N-acetylaspartate (NAA)-to-Cho ratio and whether these measures can be used as biomarkers of outcome and (b) if changes in peak area metabolite ratios at magnetic resonance (MR) spectroscopy are associated with changes in T2 and fractional anisotropy (FA) at MR imaging.

MATERIALS AND METHODS

The local ethics committee approved this study, and informed parental consent was obtained for each infant. At term-equivalent age, 43 infants born at less than 32 weeks gestation underwent conventional and quantitative diffusion-tensor and T2-weighted MR imaging. Single-voxel point-resolved proton (hydrogen 1) MR spectroscopy was performed from a 2-cm(3) voxel centered in the posterior periventricular white matter. Outcome was evaluated by using Bayley scales at a corrected age of 1 year. Associations were investigated with Pearson product moment or Spearman rank order correlation. Differences in ratios in infants with and infants without impairment were tested by using t tests.

RESULTS

NAA/Cho and Cho/Cr ratios correlated with the scaled gross motor score and the composite motor score, independent of gestational age (P < .05). FA at diffusion-tensor MR imaging and T2 at MR imaging correlated with the NAA/Cho ratio (P < .05 for both) but not with the Cho/Cr ratio. Infants with motor scores of less than 85 (impaired) had an increased Cho/Cr ratio (P < .03) and a reduced NAA/Cho ratio (P < .01) compared to those without impairment. A combination of increased Cho/Cr ratio and decreased NAA/Cho ratio predicted impaired motor outcome at a corrected age of 1 year with a sensitivity of 0.80 (95% confidence interval [CI]: 0.57, 0.94) and a specificity of 0.80 (95% CI: 0.66, 0.88).

CONCLUSION

The combination of Cho/Cr and NAA/Cho ratios measured in the posterior periventricular white matter at term-equivalent age is predictive of motor outcome at 1 year in infants born at less than 32 weeks gestation.

Prospective evaluation of term neonate brain damage following preceding hypoxic sentinel events using enhanced T₂* weighted angiography (eSWAN)

PURPOSE

To evaluate the brain damage of term neonates with evidence of a preceding hypoxic sentinel event using eSWAN prospectively.

METHODS

The study was approved by the institutional research ethics committee. Among the neonates who were examined during the first 8 days after birth with conventional magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI) and eSWAN, 39 neonates with a preceding acute hypoxic sentinel event were divided into two groups: the hypoxic ischaemic encephalopathy (HIE) group and the high-risk group. Twenty-five neonates were normal control subjects. Conventional MRI, DWI, and T₂* and R₂* maps from eSWAN were assessed. T₂* and R₂* values from T₂* and R₂* maps were calculated in predefined regions in the HIE and high-risk groups and then compared with those in control subjects.

RESULTS

The neonates in the HIE and high-risk groups showed a high percentage of cerebral oedema and periventricular white-matter (PWM) lesions. Cerebral oedema and haemorrhagic lesions of PWM were more highly visible on the T₂* map compared with conventional MRI: cerebral oedema was illustrated as a high T₂* area and haemorrhagic lesions had a significantly lower T₂* on the T₂* map. Lower R₂* values of lentiform nuclei (LN) and a higher T₂* and lower R₂* of frontal white matter (FWM) were found in neonates in the HIE group relative to those of normal controls. The T₂* value of LN in the high-risk group was higher than that of the normal controls.

CONCLUSIONS

The T₂* map from eSWAN is useful in detecting cerebral oedema and haemorrhagic lesions of PWM in neonates. The measurement of T₂* and R₂* values is helpful in assessing the LN and FWM damage in neonates following a hypoxic sentinel event.

Optimal timing of cerebral MRI in preterm infants to predict long-term neurodevelopmental outcome: a systematic review

SUMMARY

Advances in neonatal neuroimaging have improved detection of preterm brain injury responsible for abnormal neuromotor and cognitive development. Increasingly sophisticated MR imaging setups allow scanning during early preterm life. In this review, we investigated how brain MR imaging in preterm infants should be timed to best predict long-term outcome. Given the strong evidence that structural brain abnormalities are related to long-term neurodevelopment, MR imaging should preferably be performed at term-equivalent age. Early MR imaging is promising because it can guide early intervention studies and is indispensable in research on preterm brain injury.

Automated detection of white matter signal abnormality using T2 relaxometry: application to brain segmentation on term MRI in very preterm infants

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.

Neuroanatomical assessment of biological maturity

Structural MRI allows unparalleled in vivo study of the anatomy of the developing human brain. For more than two decades, MRI research has revealed many new aspects of this multifaceted maturation process, significantly augmenting scientific knowledge gathered from postmortem studies. Postnatal brain development is notably protracted and involves considerable changes in cerebral cortical, subcortical, and cerebellar structures, as well as significant architectural changes in white matter fiber tracts (see [12]). Although much work has described isolated features of neuroanatomical development, it remains a critical challenge to characterize the multidimensional nature of brain anatomy, capturing different phases of development among individuals. Capitalizing on key advances in multisite, multimodal MRI, and using cross-validated nonlinear modeling, we demonstrate that developmental brain phase can be assessed with much greater precision than has been possible using other biological measures, accounting for more than 92% of the variance in age. Further, our composite metric of morphology, diffusivity, and signal intensity shows that the average difference in phase among children of the same age is only about 1 year, revealing for the first time a latent phenotype in the human brain for which maturation timing is tightly controlled.

Neuro-developmental outcome at 18 months in premature infants with diffuse excessive high signal intensity on MR imaging of the brain

BACKGROUND

Diffuse excessive high signal intensity (DEHSI) may represent damage to the white matter in preterm infants, but may be best studied alongside quantitative markers. Limited published data exists on its neuro-developmental implications.

OBJECTIVE

The purpose of this study was to assess whether preterm children with DEHSI at term-corrected age have abnormal neuro-developmental outcome.

MATERIALS AND METHODS

This was a prospective observational study of 67 preterm infants with MRI of the brain around term-equivalent age, including diffusion-weighted imaging (DWI). Images were reported as being normal, overtly abnormal or to show DEHSI. A single observer placed six regions of interest in the periventricular white matter and calculated the apparent diffusion coefficients (ADC). DEHSI was defined as (1) high signal on T2-weighted images alone, (2) high signal with raised ADC values or (3) raised ADC values independent of visual appearances. The neuro-development was assessed around 18 months' corrected age using the Bayley Scales of Infant and Toddler Development (3rd Edition). Standard t tests compared outcome scores between imaging groups.

RESULTS

No statistically significant difference in neuro-developmental outcome scores was seen between participants with normal MRI and DEHSI, regardless of which definition was used.

CONCLUSION

Preterm children with DEHSI have similar neuro-developmental outcome to those with normal brain MRI, even if the definition includes objective markers alongside visual appearances.

High signal intensity on T2-weighted MR imaging at term-equivalent age in preterm infants does not predict 2-year neurodevelopmental outcomes

BACKGROUND AND PURPOSE

DEHSI on T2-weighted MR imaging in preterm infants at term-equivalent age has been regarded as an unfavorable marker for neurodevelopmental outcome. The aim of this study was to examine the relationship between the presence and extent of DEHSI and neurodevelopmental outcomes.

MATERIALS AND METHODS

We evaluated the MR images of 160 preterm infants at term-equivalent age. The presence of DEHSI was evaluated in separate regions and classified into 5 grades based on the extent of DEHSI. We also examined within those infants with DEHSI, whether typical signal-intensity characteristics of the posterior periventricular crossroads region were visible. Finally, ADC and FA values within the white matter were analyzed. Neurodevelopmental outcomes were assessed at 2-year corrected age with a standardized neurologic examination and the BSID-II.

RESULTS

The grade of DEHSI had significant linear trends with increasing ADC and a trend toward lower FA values. However, there was no relationship between the degree of DEHSI and 2-year neurodevelopmental outcomes. In contrast, 13 infants with DEHSI who did not have visible posterior crossroads had poorer neurodevelopmental outcomes compared with infants with visible posterior crossroads.

CONCLUSIONS

Although DEHSI may represent disturbances in white matter structure, as illustrated by its relationship to altered ADC and FA values, there is no relationship to short-term neurodevelopment outcome unless there are invisible posterior crossroads, representing a severe form of global high T2 signal intensity.

Post-mortem cerebral magnetic resonance imaging T1 and T2 in fetuses, newborns and infants

Post-mortem magnetic resonance imaging (PM MRI) of brain is increasingly used in clinical practice; understanding of normal PM contrast to noise ratio (CNR), T1 and T2 values relaxation times is important for optimisation and accurate interpretation of PM MRI.

METHODS

We obtained T1- and T2-weighted images at 1.5 T. In the first phase of the study, we calculated CNR in twelve brain regions in 5 newborn infants after death and compared this with CNR from 5 infants during life. In the second phase, we measured deep grey matter (GM) and white matter (WM) T1 post-mortem in 18 fetuses and T1 and T2 post-mortem 6 infants prior to autopsy.

RESULTS

Phase I: post-mortem T1- and T2-weighted CNRs were lower in most brain regions than during life. Phase II: compared with in vivo, all post-mortem images lacked GM-WM contrast and had high T2-weighted WM signal intensity. Mean (SD) post-mortem T1 in white and deep gray matter were respectively 1898 (327)ms and 1514 (202)ms in fetuses (p>0.05) and 1234 (180)ms and 1016 (161)ms in infants and newborns (p>0.05). Mean (SD) post-mortem T2 was 283 (11)ms in WM and 182 (18)ms in deep GM in infants and newborns (p<0.001).

CONCLUSIONS

Post-mortem T1 and T2 values are higher than those reported from live cases. The difference between T1 values in GM and WM reduce after death.

Early versus late MRI in asphyxiated newborns treated with hypothermia

OBJECTIVE

The purposes of this feasibility study were to assess: (1) the potential utility of early brain MRI in asphyxiated newborns treated with hypothermia; (2) whether early MRI predicts later brain injury observed in these newborns after hypothermia has been completed; and (3) whether early MRI indicators of brain injury in these newborns represent reversible changes.

PATIENTS AND METHODS

All consecutive asphyxiated term newborns meeting the criteria for therapeutic hypothermia were enrolled prospectively. Each newborn underwent one or two early MRI scans while receiving hypothermia, on day of life (DOL) 1 and DOL 2-3 and also one or two late MRI scans on DOL 8-13 and at 1 month of age.

RESULTS

37 MRI scans were obtained in 12 asphyxiated neonates treated with induced hypothermia. Four newborns developed MRI evidence of brain injury, already visible on early MRI scans. The remaining eight newborns did not develop significant MRI evidence of brain injury on any of the MRI scans. In addition, two patients displayed unexpected findings on early MRIs, leading to early termination of hypothermia treatment.

CONCLUSIONS

MRI scans obtained on DOL 2-3 during hypothermia seem to predict later brain injuries in asphyxiated newborns. Brain injuries identified during this early time appear to represent irreversible changes. Early MRI scans might also be useful to demonstrate unexpected findings not related to hypoxic-ischaemic encephalopathy, which could potentially be exacerbated by induced hypothermia. Additional studies with larger numbers of patients will be useful to confirm these results.

In vivo MRI analysis of an inflammatory injury in the developing brain

Cerebral periventricular white matter injury stands as a leading cause of cognitive, behavioral and motor impairment in preterm infants. There is epidemiological and histopathological evidence demonstrating the role of prenatal or neonatal inflammation in brain injury in preterm infants. In order to define the effect of an inflammatory insult in the developing brain on magnetic resonance (MR) imaging, we obtained high resolution conventional and diffusion MR images of the brain of rat pups after an inflammatory injury. Rat pups were subjected on postnatal day 5 (P5) to a stereotaxic injection of lipopolysaccharide in the corpus callosum and then imaged at 11.7 T on days 0, 2 and 4 following the injury. They were subsequently sacrificed for immunohistochemistry. Diffusion tensor imaging (DTI) acquired at high spatial resolution showed an initial reduction of the apparent diffusion coefficient (ADC) in the white matter. This was followed by an increase in ADC value and in T2 relaxation time constant in the white matter, with an associated increase of radial diffusivity of the corpus callosum, and a 10-fold increase in ventricular size. On histology, these MR changes corresponded to widespread astrogliosis, and decreased proportion of the section areas containing cresyl violet positive stain. The increase in radial diffusivity, typically attributed to myelin loss, occurred in this case despite the absence of myelin at this developmental stage.

Imaging biomarkers of outcome in the developing preterm brain

The neurodevelopmental disabilities of those who were born prematurely have been well described, yet the underlying alterations in brain development that lead to these changes remain poorly understood. Processes that are vulnerable to injury in the developing brain include maturation of oligodendrocyte precursors and genetically programmed changes in cortical connectivity; recent data have indicated that diffuse injury of the white matter accompanied by neuronal and axonal disruption is common in prematurely born infants. Recent advances in MRI include diffusion tensor imaging and sophisticated image analysis tools, such as functional connectivity, voxel-based morphometry, and mathematical morphology-based cortical folding strategies. These advanced techniques have shown that white matter structure is dependent on gestational age and have started to provide important information about the dynamic interactions between development, injury, and functional recovery in the preterm brain. Identification of early biomarkers for outcome could enable physicians and scientists to develop targeted pharmacological and behavioural therapies to restore functional connectivity.