High b-value diffusion tensor imaging of the neonatal brain at 3T

Machine-learning based prediction of future outcome using multimodal MRI during early childhood

The human brain undergoes rapid changes from the fetal stage to two years postnatally, during which proper structural and functional maturation lays the foundation for later cognitive and behavioral development. Multimodal magnetic resonance imaging (MRI) techniques, especially structural MRI (sMRI), diffusion MRI (dMRI), functional MRI (fMRI), and perfusion MRI (pMRI), provide unprecedented opportunities to non-invasively quantify these early brain changes at whole brain and regional levels. Each modality offers unique insights into the complex processes of both typical neurodevelopment and the pathological mechanisms underlying psychiatric and neurological disorders. Compared to a single modality, multimodal MRI enhances discriminative power and provides more comprehensive insights for understanding and improving neurodevelopmental and mental health outcomes, particularly in high-risk populations. Machine learning- and deep learning-based methods have demonstrated significant potential for predicting future outcomes using multimodal brain MRI acquired during early childhood. Here, we review the unique characteristics of various MRI techniques for imaging early brain development and describe the common approaches to analyze these modalities. We then discuss machine learning approaches in predicting future neurodevelopmental and clinical outcomes using multimodal MRI information during early childhood, highlighting the potential of identifying biomarkers for early detection and personalized interventions in atypical development.

Diffusion MRI harmonization via personalized template mapping

One fundamental challenge in diffusion magnetic resonance imaging (dMRI) harmonization is to disentangle the contributions of scanner-related effects from the variable brain anatomy for the observed imaging signals. Conventional harmonization methods rely on establishing an atlas space to resolve anatomical variability and generate a unified inter-site mapping function. However, this approach is limited in accounting for the misalignment of neuroanatomy that still widely persists even after registration, especially in regions close to cortical boundaries. To overcome this challenge, we propose a personalized framework in this paper to more effectively address the confounding from the misalignment of neuroanatomy in dMRI harmonization. Instead of using a common template representing site-effects for all subjects, the main novelty of our method is the adaptive computation of personalized templates for both source and target scanning sites to estimate the inter-site mapping function. We integrate our method with the rotation invariant spherical harmonics (RISH) features to achieve the harmonization of dMRI signals between sites. In our experiments, the proposed approach is applied to harmonize the dMRI data acquired from two scanning platforms: Siemens Prisma and GE MR750 from the Adolescent Brain Cognitive Development dataset and compared with a state-of-the-art method based on RISH features. Our results indicate that the proposed harmonization framework achieves superior performance not only in reducing inter-site variations due to scanner differences but also in preserving sex-related biological variability in original cohorts. Moreover, we assess the impact of harmonization on the estimation of fiber orientation distributions and show the robustness of the personalized harmonization procedure in preserving the fiber orientation of original dMRI signals.

Anesthetic modulation of water diffusion: Insights from a diffusion tensor imaging study

Diffusion tensor imaging (DTI) in animal models are essential for translational neuroscience studies. A critical step in animal studies is the use of anesthetics. Understanding the influence of specific anesthesia regimes on DTI-derived parameters, such as fractional anisotropy (FA) and mean diffusivity (MD), is imperative when comparing results between animal studies using different anesthetics. Here, the quantification of FA and MD under different anesthetic regimes, alpha-chloralose and isoflurane, is discussed. We also used a range of b-values to determine whether the anesthetic effect was b-value dependent. The first group of rats (n = 6) was anesthetized with alpha-chloralose (80 mg/kg), whereas the second group of rats (n = 7) was anesthetized with isoflurane (1.5%). DTI was performed with b-values of 500, 1500, and 1500s/mm2, and the MD and FA were assessed individually. Anesthesia-specific differences in MD were apparent, as manifested by the higher estimated MD under isoflurane anesthesia than that under alpha-chloralose anesthesia (P < 0.001). MD values increased with decreasing b-value in all regions studied, and the degree of increase when rats were anesthetized with isoflurane was more pronounced than that associated with alpha-chloralose (P < 0.05). FA quantitation was also influenced by anesthesia regimens to varying extents, depending on the brain regions and b-values. In conclusion, both scanning parameters and the anesthesia regimens significantly impacted the quantification of DTI indices.

Magnetic resonance imaging of the monkey fetal brain in utero

Non-human primates (NHPs) are the closest living relatives of the human and play a critical role in investigating the effects of maternal viral infection and consumption of medicines, drugs, and alcohol on fetal development. With the advance of contemporary fast MRI techniques with parallel imaging, fetal MRI is becoming a robust tool increasingly used in clinical practice and preclinical studies to examine congenital abnormalities including placental dysfunction, congenital heart disease (CHD), and brain abnormalities non-invasively. Because NHPs are usually scanned under anesthesia, the motion artifact is reduced substantially, allowing multi-parameter MRI techniques to be used intensively to examine the fetal development in a single scanning session or longitudinal studies. In this paper, the MRI techniques for scanning monkey fetal brains in utero in biomedical research are summarized. Also, a fast imaging protocol including T2-weighted imaging, diffusion MRI, resting-state functional MRI (rsfMRI) to examine rhesus monkey fetal brains in utero on a clinical 3T scanner is introduced.

High B-value diffusion tensor imaging for early detection of hippocampal microstructural alteration in a mouse model of multiple sclerosis

Several studies have highlighted the value of diffusion tensor imaging (DTI) with strong diffusion weighting to reveal white matter microstructural lesions, but data in gray matter (GM) remains scarce. Herein, the effects of b-values combined with different numbers of diffusion-encoding directions (NDIRs) on DTI metrics to capture the normal hippocampal microstructure and its early alterations were investigated in a mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis [EAE]). Two initial DTI datasets (B2700-43Dir acquired with b = 2700 s.mm⁻² and NDIR = 43; B1000-22Dir acquired with b = 1000 s.mm⁻² and NDIR = 22) were collected from 18 normal and 18 EAE mice at 4.7 T. Three additional datasets (B2700-22Dir, B2700-12Dir and B1000-12Dir) were extracted from the initial datasets. In healthy mice, we found a significant influence of b-values and NDIR on all DTI metrics. Confronting unsupervised hippocampal layers classification to the true anatomical classification highlighted the remarkable discrimination of the molecular layer with B2700-43Dir compared with the other datasets. Only DTI from the B2700 datasets captured the dendritic loss occurring in the molecular layer of EAE mice. Our findings stress the needs for both high b-values and sufficient NDIR to achieve a GM DTI with more biologically meaningful correlations, though DTI-metrics should be interpreted with caution in these settings.

Effects of Tissue Temperature and Injury on ADC during Therapeutic Hypothermia in Newborn Hypoxic-Ischemic Encephalopathy

BACKGROUND AND PURPOSE

ADC changes are useful in detecting ischemic brain injury, but mechanisms other than tissue pathology may affect the kinetic movement and diffusion of water molecules. We aimed to determine the effects of brain temperature on the corresponding ADC in infants undergoing therapeutic hypothermia.

MATERIALS AND METHODS

Brain temperature and ADC values in the basal ganglia, thalamus, cortical GM, and WM were analyzed during and after therapeutic hypothermia. The study cohort was categorized as having no-injury or injury. Among infants without injury, the correlation between ADC values and temperature was analyzed using the Pearson correlation. Intrasubject comparison of ADC changes during and after therapeutic hypothermia were analyzed, excluding patients who had an MR image interval of >5 days to minimize the effects of injury evolution.

RESULTS

Thirty-nine infants with hypoxic-ischemic encephalopathy were enrolled (23 no-injury; 16 injury). The median ADC was significantly lower during therapeutic hypothermia (837; interquartile range, 771-928, versus 906; interquartile range, 844-1032 ×10^-6mm²/s; P < .001). There was no difference in the ADC between the no-injury and injury groups during therapeutic hypothermia (823; interquartile range, 782-868, versus 842; interquartile range, 770-1008 ×10^-6mm²/s; P  = .4). In the no-injury group, in which ADC is presumed least affected by the evolution of injury, the median ADC was significantly lower during therapeutic hypothermia (826; interquartile range, 771-866, versus 897; interquartile range, 846-936 ×10^-6mm²/s; P  < .001). There was a moderate correlation between temperature and ADC in the no-injury group (during therapeutic hypothermia: Spearman ρ, 0.48; P  < .001; after therapeutic hypothermia: ρ, 0.4; P  < .001).

CONCLUSIONS

Aside from brain injury, reduced tissue temperature may also contribute to diffusion restriction on MR imaging in infants undergoing therapeutic hypothermia.

Structural Brain Network Reproducibility: Influence of Different Diffusion Acquisition and Tractography Reconstruction Schemes on Graph Metrics

Background: Graph metrics of structural brain networks demonstrate to be a powerful tool for investigating brain topology at a large scale. However, the variability of the results related to applying different magnetic resonance acquisition schemes and tractography reconstruction techniques is not fully characterized. Materials and Methods: The present work aims to evaluate the influence of different combinations of diffusion acquisition schemes (single and multishell), diffusion models (tensor and spherical deconvolution), and tractography reconstruction approaches (deterministic and probabilistic) on the reproducibility of graph metrics derived from structural connectome on test/retest (TRT) data released by the Human Connectome Project. From each implemented experimental setup, both global and local graph metrics were evaluated and their reproducibility was estimated by the intraclass correlation coefficient (ICC). Moreover, the percentage relative standard deviation (pRSD) from the ICC values of local graph metrics was calculated to quantify how much the reproducibility varied across nodes within each experimental setup. Results: The presented results show that different combinations of diffusion acquisition schemes, diffusion models, and tractography algorithms can strongly affect the reproducibility of global and local graph metrics. The combination of constrained spherical deconvolution (CSD) and deterministic tractography gave generally high reproducibility (ICCs >0.75) and lowest pRSD for the considered graph metrics, meanwhile probabilistic CSD with a high b-value returned the highest reproducibility. Notably, the introduction of streamline selection filters on CSD can substantially affect the reproducibility. Discussion: This work demonstrates that the TRT reproducibility of graph metrics is generally high but can vary substantially with different combinations of acquisition and reconstruction schemes. Impact statement This work demonstrates the influence of different diffusion acquisition schemes, diffusion models, and tractography reconstruction approaches on the reproducibility of graph metrics derived from structural connectome. The presented findings impact on the choice of both acquisition protocol and processing pipeline for topological analyses to produce reproducible measurements for brain network studies.

Comparison of Predictive Values of Magnetic Resonance Biomarkers Based on Scan Timing in Neonatal Encephalopathy Following Therapeutic Hypothermia

OBJECTIVE

To determine the optimal quantitative magnetic resonance (MR) biomarker in neonatal encephalopathy following therapeutic hypothermia based on scan timing.

STUDY DESIGN

This retrospective study included 98 neonates (35-41 weeks of gestation) with neonatal encephalopathy, who underwent therapeutic hypothermia; diffusion-weighted imaging and proton MR spectroscopy were performed at 24-96 hours (n = 56) and 7-14 days (n = 92) after birth, respectively, to estimate apparent diffusion coefficient (ADC) values, N-acetylaspartate and N-acetylaspartylglutamate (tNAA), lactate, and choline concentrations, and lactate/tNAA, tNAA/choline ratios in the deep gray matter. Adverse outcomes included death or neurodevelopmental impairment at 18-22 months of age. We used receiver operating characteristic curves to examine the prognostic accuracy of each MR biomarker.

RESULTS

Deep gray matter tNAA concentrations showed the best prognostic value, with an area under the curve (AUC) of 0.97 and 1.00 at 24-96 hours and 7-14 days after birth, respectively. At 24-96 hours of age, ADC values, lactate concentrations, and lactate/tNAA ratios showed prognostic value with AUCs of 0.90, 0.95, and 0.97, respectively. At 7-14 days of age, the AUCs of ADC values, lactate, and lactate/tNAA ratios were 0.61, 0.67, and 0.80, respectively; these were lower than those at 24-96 hours of age.

CONCLUSIONS

During the first 2 weeks of life, the deep gray matter tNAA concentration was the most accurate quantitative MR biomarker. Although ADC values, lactate levels, and lactate/tNAA ratios also showed high prognostic value during 24-96 hours of life, only tNAA retained high prognostic value in the second week of life.

Brain Development From Newborn to Adolescence: Evaluation by Neurite Orientation Dispersion and Density Imaging

Neurite orientation dispersion and density imaging (NODDI) is a diffusion model specifically designed for brain magnetic resonance imaging. Despite recent studies suggesting that NODDI modeling might be more sensitive to brain development than diffusion tensor imaging (DTI), these studies were limited to a relatively small age range and mainly based on the manually operated region of interest analysis. Therefore, this study applied NODDI to investigate brain development in a large sample size of 214 subjects ranging in ages from 0 to 14. The whole brain was automatically segmented into 122 regions. The maturation trajectory of each region was characterized by the time course of diffusion metrics and further quantified using nonlinear regression. The NODDI-derived metrics, neurite density index (NDI) and orientation dispersion index (ODI), increased with age. And these two metrics were superior to the DTI-derived metrics in SVM regression models of age. The NDI in white matter exhibited a more rapid growth than that in gray matter (including the cortex and deep nucleus). These diffusion indicators experienced conspicuous increases during early childhood and the growth speed slowed down in adolescence. Region-specific maturation patterns were described throughout the brain, including white matter, cortical and deep gray matter. These development patterns were evaluated and discussed on the basis of NODDI's model assumptions. To summarize, this study verified the high sensitivity of NODDI to age over a crucial developmental period from newborn to adolescence. Moreover, the existing knowledge of brain development has been complemented, suggesting that NODDI has a potential capability in the investigation of brain development.

Effect of b Value on Imaging Quality for Diffusion Tensor Imaging of the Spinal Cord at Ultrahigh Field Strength

Objective

To explore the optimal b value setting for diffusion tensor imaging of rats' spinal cord at ultrahigh field strength (7 T).

Methods

Spinal cord diffusion tensor imaging data were collected from 14 rats (5 healthy, 9 spinal cord injured) with a series of b values (200, 300, 400, 500, 600, 700, 800, 900, and 1000 s/mm²) under the condition that other scanning parameters were consistent. The image quality (including image signal-to-noise ratio and image distortion degree) and data quality (i.e., the stability and consistency of the DTI-derived parameters, referred to as data stability and data consistency) were quantitatively evaluated. The min-max normalization method was used to process the calculation results of the four indicators. Finally, the image and data quality under each b value were synthesized to determine the optimal b value.

Results

b = 200 s/mm² and b = 900 s/mm² ranked in the top two of the comprehensive evaluation, with the best image quality at b = 200 s/mm² and the best data quality at b = 900 s/mm².

Conclusion

Considering the shortcomings of the ability of low b values to reflect the microstructure, b = 900 s/mm² can be used as the optimal b value for 7 T spinal cord diffusion tensor scanning.

Higher b-values improve the correlation between diffusion MRI and the cortical microarchitecture

PURPOSE

In diffusion MRI (dMRI), it remains unclear to know how much increase of b-value is conveying additional biological meaning. We tested the correlations between cortical microarchitecture and diffusion metrics computed from standard (1000 s/mm²), high (3000 s/mm²), to very high (5000 s/mm²) b-value dMRI.

METHODS

Healthy volunteers were scanned with a dMRI pulse sequence that was first optimized together with a T1-WI and T2-WI. Averaged cortical surface map of estimated myelin (T1-WI/T2-WI) was compared with surface maps of mean diffusivity (MD) computed from each b-value (MD₁₀₀₀, MD₃₀₀₀, and MD₅₀₀₀) and to surface map of mean kurtosis (MK computed from the 0-, 1000-, to 3000-s/mm² shells) in 360 cortical parcels using Spearman correlations, multiple linear regressions, and Akaike information criteria (AIC).

RESULTS

Surface map from MD₁₀₀₀ showed variations not related to myelin but the MD₃₀₀₀ and MD₅₀₀₀ maps inversely mirrored estimated myelin map; lower MD values being observed in more myelinated cortical areas. MK mirrored myelinated cortical areas. Quantitatively, Spearman correlations between myelin and MD became more and more negative as long as b-values increased while the correlation was positive between myelin and MK. Multiple regression models confirmed negative associations between myelin and MD that were significantly better from MD₁₀₀₀ to MD₃₀₀₀ and MD₅₀₀₀ (R² = 0.33, p < 0.001; R² = 0.43, p < 0.001; and R² = 0.50, p < 0.001) and positive association between myelin and MK (R² = 0.53, p < 0.001). Comparisons of the 3 statistical models showed the best performances with MK and MD₅₀₀₀ (AIC_MK < AIC_MD5000 < AIC_MD3000 < AIC_MD1000).

CONCLUSION

Higher b-values are more closely related to subtle cellular variations of the cortical microarchitecture.

Longitudinal structural connectomic and rich-club analysis in adolescent mTBI reveals persistent, distributed brain alterations acutely through to one year post-injury

The diffuse nature of mild traumatic brain injury (mTBI) impacts brain white-matter pathways with potentially long-term consequences, even after initial symptoms have resolved. To understand post-mTBI recovery in adolescents, longitudinal studies are needed to determine the interplay between highly individualised recovery trajectories and ongoing development. To capture the distributed nature of mTBI and recovery, we employ connectomes to probe the brain’s structural organisation. We present a diffusion MRI study on adolescent mTBI subjects scanned one day, two weeks and one year after injury with controls. Longitudinal global network changes over time suggests an altered and more ‘diffuse’ network topology post-injury (specifically lower transitivity and global efficiency). Stratifying the connectome by its back-bone, known as the ‘rich-club’, these network changes were driven by the ‘peripheral’ local subnetwork by way of increased network density, fractional anisotropy and decreased diffusivities. This increased structural integrity of the local subnetwork may be to compensate for an injured network, or it may be robust to mTBI and is exhibiting a normal developmental trend. The rich-club also revealed lower diffusivities over time with controls, potentially indicative of longer-term structural ramifications. Our results show evolving, diffuse alterations in adolescent mTBI connectomes beginning acutely and continuing to one year.

Arterial stiffness cut-off value and white matter integrity in the elderly

Objective

Central artery stiffness is a confirmed predictor of cardiovascular health status that has been consistently associated with cognitive dysfunction and dementia. The European Society of Hypertension has established a threshold of arterial stiffness above which a cardiovascular event is likely to occur. However, the threshold at which arterial stiffness alters brain integrity has never been established.

Methods

The aim of this study is to determine the arterial stiffness cut-off value at which there is an impact on the white matter microstructure. This study has been conducted with 53 cognitively elderly without dementia. The integrity of the white matter was assessed using diffusion tensor metrics. Central artery stiffness was evaluated by measuring the carotid-femoral pulse wave velocity (cfPWV). The statistical analyses included 4 regions previously denoted vulnerable to increased central arterial stiffness (the corpus callosum, the internal capsule, the corona radiata and the superior longitudinal fasciculus).

Results

The results of this study call into question the threshold value of 10 m/s cfPWV established by the European Society of Hypertension to classify patients in neuro-cardiovascular risk groups. Our results suggest that the cfPWV threshold value would be approximately 8.5 m/s when the microstructure of the white matter is taken as a basis for comparison.

Conclusions

Adjustment of the cfPWV value may be necessary for a more accurate distinction between lower and higher risk group of patients for white matter microstructural injury related to arterial stiffness. Targeting the highest risk group for prevention methods may, in turn, help preserve brain health and cognitive functions.

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DTI (FA, RD) analysis of white matter microstructure reveals that the cfPWV cut-off value (10 m/s) may be too high

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This study rather suggests a value of cfPWV cut-off of 8.5 m/s to separate lower and higher neurovascular risk groups

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Better executive function performance is correlated with higher FA and lower RD in participants with a cfPWV above 8.5 m/s.

Diffusion Tensor Model links to Neurite Orientation Dispersion and Density Imaging at high b-value in Cerebral Cortical Gray Matter

Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value = 3000 sec/mm²). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture.

The Diffusion Tensor Imaging Properties of the Normal Testicles at 3 Tesla Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

The testicles are structured in a well-defined microtubular network formation, which is expected to be reflected in high anisotropic diffusivity. However, preliminary studies reported on low values of fractional-anisotropy (FA) in the normal testicles. Our aim was to design and apply a diffusion-tensor imaging (DTI) protocol in order to elucidate the diffusivity properties of the testicles and their determining factors.

MATERIALS AND METHODS

16 healthy volunteers were prospectively scanned at 3T. The protocol included T₂-weighted and DTI sequences, the latter using 24 directional diffusion gradients and 3 b-values (0, 100, and 700 s/mm²) that were separated for analysis based on the reference b-value of 0 or 100 s/mm². Image processing of the two DTI datasets yielded the diffusion vector maps and parametric maps of their corresponding principal diffusion coefficients λ₁, λ₂, λ₃, mean diffusivity and FA.

RESULTS

The results demonstrated the feasibility of DTI to provide parametric maps of the testicles. The diffusion tensor parameters obtained using the pair of 0 and 700 s/mm² b-values, exhibited relatively low diffusivity, with mean λ₁ values of 1.36 ± 0.21 × 10^-3 mm²/s and low anisotropy, with mean FA values of 0.13 ± 0.05. Analysis of DTI using the 100 and 700 s/mm² b-values yielded a slight decrease in the diffusivity of 4%-5%, whereas FA remained similar.

CONCLUSION

The diffusivity of the normal testicles is relatively slow, closed-to isotropic and hardly affected by the low b-values regime exclusion. Thus, DTI parameters of the normal testicles are neither dictated by the underlying architectural anisotropy nor microperfusion effects.

Probabilistic tractography-based thalamic parcellation in healthy newborns and newborns with congenital heart disease

BACKGROUND

Given the central role of the thalamus in motor, sensory, and cognitive development, methods to study emerging thalamocortical connectivity in early infancy are of great interest.

PURPOSE

To determine the feasibility of performing probabilistic tractography-based thalamic parcellation (PTbTP) in typically developing (TD) neonates and to compare the results with a pilot sample of neonates with congenital heart disease (CHD).

STUDY TYPE

Institutional Review Board (IRB)-approved cross-sectional study.

MODEL

We prospectively recruited 20 TD neonates and five CHD neonates (imaged preoperatively).

FIELD STRENGTH/SEQUENCE

MRI was performed at 3.0T including diffusion-weighted imaging (DWI) and 3D magnetization prepared rapid gradient-echo (MPRAGE).

ASSESSMENT

A radiologist and trained research assistants segmented the thalamus and seven cortical targets for each hemisphere. Using the thalami as seeds and the cortical labels as targets, FSL library tools were used to generate probabilistic tracts. A Hierarchical Dirichlet Process algorithm was then used for clustering analysis. A radiologist qualitatively assessed the results of clustering. Quantitative analyses were also performed.

STATISTICAL TESTS

We summarized the demographic data and results of clustering with descriptive statistics. Linear regressions covarying for gestational age were used to compare groups.

RESULTS

In 17 of 20 TD neonates, we identified five connectivity-determined clusters, which correlate with known thalamic nuclei and subnuclei. In four neonates with CHD we observed a spectrum of abnormalities including fewer and disorganized clusters or small supernumerary clusters (up to seven per thalamus). After covarying for differences in corrected gestational age (cGA), the fractional anisotropy (FA), volume, and normalized thalamic volume were significantly lower in CHD neonates (P < 0.01).

DATA CONCLUSIONS

Using PTbTP clusters, correlating well with the location and connectivity of known thalamic nuclei, were identified in TD neonates. Differences in thalamic clustering outputs were identified in four neonates with CHD, raising concern for disordered thalamic connectivity. PTbTP is feasible in TD and CHD neonates. Preliminary findings suggest the prenatal origins of altered connectivity in CHD.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;47:1626-1637.

Mapping White Matter Microstructure in the One Month Human Brain

White matter microstructure, essential for efficient and coordinated transmission of neural communications, undergoes pronounced development during the first years of life, while deviations to this neurodevelopmental trajectory likely result in alterations of brain connectivity relevant to behavior. Hence, systematic evaluation of white matter microstructure in the normative brain is critical for a neuroscientific approach to both typical and atypical early behavioral development. However, few studies have examined the infant brain in detail, particularly in infants under 3 months of age. Here, we utilize quantitative techniques of diffusion tensor imaging and neurite orientation dispersion and density imaging to investigate neonatal white matter microstructure in 104 infants. An optimized multiple b-value diffusion protocol was developed to allow for successful acquisition during non-sedated sleep. Associations between white matter microstructure measures and gestation corrected age, regional asymmetries, infant sex, as well as newborn growth measures were assessed. Results highlight changes of white matter microstructure during the earliest periods of development and demonstrate differential timing of developing regions and regional asymmetries. Our results contribute to a growing body of research investigating the neurobiological changes associated with neurodevelopment and suggest that characteristics of white matter microstructure are already underway in the weeks immediately following birth.

Pediatric brain MRI, Part 2: Advanced techniques

Pediatric neuroimaging is a complex and specialized field that uses magnetic resonance (MR) imaging as the workhorse for diagnosis. MR protocols should be tailored to the specific indication and reviewed by the supervising radiologist in real time. Targeted advanced imaging sequences can be added to provide information regarding tissue microstructure, perfusion, metabolism and function. In part 2 of this review, we highlight the utility of advanced imaging techniques for superior evaluation of pediatric neurologic disease. We focus on the following techniques, with clinical examples: phase-contrast imaging, perfusion-weighted imaging, vessel wall imaging, diffusion tensor imaging, task-based functional MRI and MR spectroscopy.

Therapeutic hypothermia modifies perinatal asphyxia-induced changes of the corpus callosum and outcome in neonates

What Is Known about this Subject?

Diffusion-weighted MRI has demonstrated changes in the corpus callosum of term neonates with perinatal asphyxia. The severity of cerebral changes demonstrated using diffusion-weighted MRI is difficult to assess without measuring values of the Apparent Diffusion Coefficient (ADC).

What Is New?

ADC values of the anterior part of the corpus callosum are slightly higher than of the posterior part in full term infants with perinatal asphyxia. Low ADC values of the corpus callosum were associated with an adverse outcome in infants with perinatal asphyxia. In infants treated with hypothermia lower ADC values than with normothermia were associated with a poor outcome, supporting neuroprotective effects of hypothermia

Background

Using MRI, changes can be detected in the corpus callosum (CC) following perinatal asphyxia which are associated with later neurodevelopmental outcome.

Aim

To study the association between the apparent diffusion coefficient of water (ADC) in the CC on MRI in neonates with perinatal asphyxia and neurodevelopmental outcome at 18 months of age.

Subjects, Methods

Of 121 infants 32 (26%) died and 13 (11%) survived with an adverse neurological outcome. Sixty-five (54%) received therapeutic hypothermia. MRI was performed within 7 days after birth using a 1.5 T or 3.0 T system, and ADC values were measured in the anterior and posterior CC. The association between ADC and composite outcome (death or abnormal neurodevelopment) was analyzed for both normothermia and hypothermia cases using receiver operating characteristics.

Results

ADC values of the posterior CC were lower than of the anterior part (mean difference 0.050 x 10^-3 mm²/s, p<0.001). Field strength did not affect ADC values. ADC values of the posterior part of the CC were significantly lower in infants with basal ganglia/thalamus or near total brain injury (p<0.001). Lower ADC values were associated with an adverse outcome, but cut-off levels were lower after hypothermia (1.024 x 10^-3 mm²/s vs 0.969 x 10^-3 mm²/s)

Conclusion

Low ADC values of the posterior part of the corpus callosum are associated with an adverse outcome in term or near term neonates with perinatal asphyxia. Therapeutic hypothermia slightly modifies this association, showing that lower values were needed for an adverse outcome.

Recent advancements in diffusion MRI for investigating cortical development after preterm birth-potential and pitfalls

Preterm infants are born during a critical period of brain maturation, in which even subtle events can result in substantial behavioral, motor and cognitive deficits, as well as psychiatric diseases. Recent evidence shows that the main source for these devastating disabilities is not necessarily white matter (WM) damage but could also be disruptions of cortical microstructure. Animal studies showed how moderate hypoxic-ischemic conditions did not result in significant neuronal loss in the developing brain, but did cause significantly impaired dendritic growth and synapse formation alongside a disturbed development of neuronal connectivity as measured using diffusion magnetic resonance imaging (dMRI). When using more advanced acquisition settings such as high-angular resolution diffusion imaging (HARDI), more advanced reconstruction methods can be applied to investigate the cortical microstructure with higher levels of detail. Recent advances in dMRI acquisition and analysis have great potential to contribute to a better understanding of neuronal connectivity impairment in preterm birth. We will review the current understanding of abnormal preterm cortical development, novel approaches in dMRI, and the pitfalls in scanning vulnerable preterm infants.

Data quality in diffusion tensor imaging studies of the preterm brain: a systematic review

BACKGROUND

To study early neurodevelopment in preterm infants, evaluation of brain maturation and injury is increasingly performed using diffusion tensor imaging, for which the reliability of underlying data is paramount.

OBJECTIVE

To review the literature to evaluate acquisition and processing methodology in diffusion tensor imaging studies of preterm infants.

MATERIALS AND METHODS

We searched the Embase, Medline, Web of Science and Cochrane databases for relevant papers published between 2003 and 2013. The following keywords were included in our search: prematurity, neuroimaging, brain, and diffusion tensor imaging.

RESULTS

We found 74 diffusion tensor imaging studies in preterm infants meeting our inclusion criteria. There was wide variation in acquisition and processing methodology, and we found incomplete reporting of these settings. Nineteen studies (26%) reported the use of neonatal hardware. Data quality assessment was not reported in 13 (18%) studies. Artefacts-correction and data-exclusion was not reported in 33 (45%) and 18 (24%) studies, respectively. Tensor estimation algorithms were reported in 56 (76%) studies but were often suboptimal.

CONCLUSION

Diffusion tensor imaging acquisition and processing settings are incompletely described in current literature, vary considerably, and frequently do not meet the highest standards.

Identification and interpretation of microstructural abnormalities in motor pathways in adolescents born preterm

There has been extensive interest in assessing the long-term effects of preterm birth on brain white matter microstructure using diffusion MRI. Our aim in this study is to explore diffusion MRI differences between adolescents born preterm and term born controls, with a specific interest in characterising how such differences are manifested in white matter regions containing predominantly single or crossing fibre populations. Probabilistic high angular resolution tractography together with large deformation spatial normalisation were used to objectively investigate diffusion tensor parameters at regular intervals along fibre tracts of 45 adolescents born before 33 weeks of gestation and 30 term-born typically developing adolescents. Diffusion parameters were significantly different between preterms and controls at several levels along the cortico-spinal, thalamo-cortical and transcallosal pathways. Within the predominantly single fibre regions of the corpus callosum and internal capsule, in the preterms mean diffusivity (MD) was found to be increased while fractional anisotropy (FA) was decreased compared to controls. In contrast, however, where these pathways traversed the centrum semiovale, FA and MD were both significantly increased. The major contributor to reduced FA in preterms in predominantly single fibre regions was the increased radial eigenvalue (i.e. increased radial diffusivity). In predominantly crossing-fibre regions, the tensor eigenvalues are not meaningful, and the observed increase in FA is likely to be due to a decrease in anisotropy in one of the contributing fibre bundles. Similar differences (although less pronounced) were observed after excluding preterms with radiological signs of preterm brain injury from the sample. In summary, white matter microstructure was found to be altered in motor pathways in adolescents born preterm. Disruption of white matter (WM) microstructure in a single fibre region with resulting higher radial diffusivity leads to lower FA, whereas selective disruption of one fibre population in a crossing fibre region is observed to lead to higher FA. These findings challenge the common simplistic interpretation of FA as a measure of WM tract integrity.

Diffusion tensor parameters and principal eigenvector coherence: relation to b-value intervals and field strength

Diffusion-weighted MRI images acquired at b-value greater than 1000 s mm(-2) measure the diffusion of a restricted pool of water molecules. High b-value images are accompanied by a reduction in signal-to-noise ratio (SNR) due to the application of large diffusion gradients. By fitting the diffusion tensor model to data acquired at incremental b-value intervals, we determined the effect of SNR on tensor parameters in normal human brains, in vivo. In addition, we also investigated the impact of field strength on the diffusion tensor model. Data were acquired at 1.5 and 3T, at b-values 0, 1000, 2000 and 3000 s mm(-2) in twenty diffusion-sensitised directions. Fractional anisotropy (FA), mean diffusivity (MD) and principal eigenvector coherence (κ) were calculated from diffusion tensors fitted between datasets with b-values 0-1000, 0-2000, 0-3000, 1000-2000 and 2000-3000 s mm(-2). Field strength and b-value effects on diffusion parameters were analysed in white and grey matter regions of interest. Decreases in FA, κ and MD were found with increasing b-value in white matter. Univariate analysis showed a significant increase in FA with increasing field strength in highly organised white matter. These results suggest there are significant differences in diffusion parameters at 1.5 and 3T and that the optimal results, in terms of the highest values of FA in white matter, are obtained at 3T with a maximum b=1000 s mm(-2).

A decade of DTI in traumatic brain injury: 10 years and 100 articles later

SUMMARY

The past decade has seen an increase in the number of articles reporting the use of DTI to detect brain abnormalities in patients with traumatic brain injury. DTI is well-suited to the interrogation of white matter microstructure, the most important location of pathology in TBI. Additionally, studies in animal models have demonstrated the correlation of DTI findings and TBI pathology. One hundred articles met the inclusion criteria for this quantitative literature review. Despite significant variability in sample characteristics, technical aspects of imaging, and analysis approaches, the consensus is that DTI effectively differentiates patients with TBI and controls, regardless of the severity and timeframe following injury. Furthermore, many have established a relationship between DTI measures and TBI outcomes. However, the heterogeneity of specific outcome measures used limits interpretation of the literature. Similarly, few longitudinal studies have been performed, limiting inferences regarding the long-term predictive utility of DTI. Larger longitudinal studies, using standardized imaging, analysis approaches, and outcome measures will help realize the promise of DTI as a prognostic tool in the care of patients with TBI.

Diffusion MRI of the neonate brain: acquisition, processing and analysis techniques

Diffusion MRI (dMRI) is a popular noninvasive imaging modality for the investigation of the neonate brain. It enables the assessment of white matter integrity, and is particularly suited for studying white matter maturation in the preterm and term neonate brain. Diffusion tractography allows the delineation of white matter pathways and assessment of connectivity in vivo. In this review, we address the challenges of performing and analysing neonate dMRI. Of particular importance in dMRI analysis is adequate data preprocessing to reduce image distortions inherent to the acquisition technique, as well as artefacts caused by head movement. We present a summary of techniques that should be used in the preprocessing of neonate dMRI data, and demonstrate the effect of these important correction steps. Furthermore, we give an overview of available analysis techniques, ranging from voxel-based analysis of anisotropy metrics including tract-based spatial statistics (TBSS) to recently developed methods of statistical analysis addressing issues of resolving complex white matter architecture. We highlight the importance of resolving crossing fibres for tractography and outline several tractography-based techniques, including connectivity-based segmentation, the connectome and tractography mapping. These techniques provide powerful tools for the investigation of brain development and maturation.

Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer

PURPOSE

To extend the intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) model to restricted diffusion and to simultaneously quantify the perfusion and restricted diffusion parameters in neck nodal metastases.

MATERIALS AND METHODS

The non-gaussian (NG)-IVIM model was developed and tested on diffusion-weighted MRI data collected on a 1.5-Tesla MRI scanner from eight patients with head and neck cancer. Voxel-wise parameter quantification was performed by using a noise-rectified least-square fitting method. The NG-IVIM, IVIM, Kurtosis, and ADC (apparent diffusion coefficient) models were used for comparison. For each voxel, within the metastatic node, the optimal model was determined using the Bayesian Information Criterion. The voxel percentage preferred by each model was calculated and the optimal model map was generated. Monte Carlo simulations were performed to evaluate the accuracy and precision dependency of the new model.

RESULTS

For the eight neck nodes, the range of voxel percentage preferred by the NG-IVIM model was 2.3-79.3%. The optimal modal maps showed heterogeneities within the tumors. The Monte Carlo simulations demonstrated that the accuracy and precision of the NG-IVIM model improved by increasing signal-to-noise ratio and b value.

CONCLUSION

The NG-IVIM model characterizes perfusion and restricted diffusion simultaneously in neck nodal metastases.

In vivo assessment of ductal carcinoma in situ grade: a model incorporating dynamic contrast-enhanced and diffusion-weighted breast MR imaging parameters

PURPOSE

To develop a model incorporating dynamic contrast material-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging features to differentiate high-nuclear-grade (HNG) from non-HNG ductal carcinoma in situ (DCIS) in vivo.

MATERIALS AND METHODS

This HIPAA-compliant study was approved by the institutional review board and requirement for informed consent was waived. A total of 55 pure DCIS lesions (19 HNG, 36 non-HNG) in 52 women who underwent breast MR imaging at 1.5 T with both DCE and DW imaging (b = 0 and 600 sec/mm(2)) were retrospectively reviewed. The following lesion characteristics were recorded or measured: DCE morphology, DCE maximum lesion size, peak initial enhancement at 90 seconds, worst-curve delayed enhancement kinetics, apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR) at DW imaging with b values of 0 and 600 sec/mm(2), and T2 signal effects (measured with CNR at b = 0 sec/mm(2)). Univariate and stepwise multivariate logistic regression modeling was performed to identify MR imaging features that optimally discriminated HNG from non-HNG DCIS. Discriminative abilities of models were compared by using the area under the receiver operating characteristic curve (AUC).

RESULTS

HNG lesions exhibited larger mean maximum lesion size (P = .02) and lower mean CNR for images with b value of 600 sec/mm(2) (P = .004), allowing discrimination of HNG from non-HNG DCIS (AUC = 0.71 for maximum lesion size, AUC = 0.70 for CNR at b = 600 sec/mm(2)). Differences in CNR for images with b value of 0 sec/mm(2) (P = .025) without corresponding differences in ADC values were observed between HNG and non-HNG lesions. Peak initial enhancement was the only kinetic variable to approach significance (P = .05). No differences in lesion morphology (P = .11) or worst-curve delayed enhancement kinetics (P = .97) were observed. A multivariate model combining CNR for images with b value of 600 sec/mm(2) and maximum lesion size most significantly discriminated HNG from non-HNG (AUC = 0.81).

CONCLUSION

The preliminary findings suggest that DCE and DW MR imaging features may aid in identifying patients with high-risk DCIS. Further study may yield a model combining MR characteristics with histopathologic data to facilitate lesion-specific targeted therapies. © RSNA, 2012.

White matter maturation of normal human fetal brain. An in vivo diffusion tensor tractography study

We demonstrate for the first time the ability to determine in vivo and in utero the transitions between the main stages of white matter (WM) maturation in normal human fetuses using magnetic resonance diffusion tensor imaging (DTI) tractography. Biophysical characteristics of water motion are used as an indirect probe to evaluate progression of the tissue matrix organization in cortico-spinal tracts (CSTs), optic radiations (OR), and corpus callosum (CC) in 17 normal human fetuses explored between 23 and 38 weeks of gestation (GW) and selected strictly on minimal motion artifacts. Nonlinear polynomial (third order) curve fittings of normalized longitudinal and radial water diffusivities (Z-scores) as a function of age identify three different phases of maturation with specific dynamics for each WM bundle type. These phases may correspond to distinct cellular events such as axonal organization, myelination gliosis, and myelination, previously reported by other groups on post-mortem fetuses using immunostaining methods. According to the DTI parameter dynamics, we suggest that myelination (phase 3) appears early in the CSTs, followed by the OR and by the CC, respectively. DTI tractography provides access to a better understanding of fetal WM maturation.

Diffusion-weighted imaging in neonates

Diffusion-weighted imaging (DWI) has become an important tool in pediatric neuroradiology, helping in the evaluation of the encephalopathic and seizing neonate, and adding conspicuity, specificity, and prognostic value to the conventional magnetic resonance (MR) imaging data. DWI also facilitates understanding the pathophysiology and natural time course of ischemic and nonischemic disorders. When interpreted concurrently with the conventional MR imaging and other advanced MR imaging techniques, such as spectroscopy and arterial spin labeling, DWI can give clues leading to an accurate diagnosis and provide important information about pathophysiology and prognosis of the diseases, as well as guide adequate therapeutic modalities.

Characterization of ductal carcinoma in situ on diffusion weighted breast MRI

OBJECTIVES

To characterize ductal carcinoma in situ (DCIS) and its subtypes on diffusion-weighted imaging (DWI).

METHODS

We retrospectively reviewed 74 pure DCIS lesions in 69 women who underwent DWI at 1.5 T (b = 0 and 600 s/mm(2)). Each lesion was characterized by qualitative DWI intensity, quantitative DWI lesion-to-normal contrast-to-noise ratio (CNR), and quantitative apparent diffusion coefficient (ADC). The detection rate was calculated with predetermined thresholds for each parameter. The effects of lesion size, grade, morphology, and necrosis were assessed.

RESULTS

Ninety-six percent (71/74) of DCIS lesions demonstrated greater qualitative DWI intensity than normal breast tissue. Quantitatively, DCIS lesions demonstrated on average 56% greater signal than normal tissue (mean CNR = 1.83  ±  2.7) and lower ADC values (1.50 ± 0.28 × 10(-3) mm(2)/s) than normal tissue (2.01 ± 0.37 × 10(-3) mm(2)/s, p < 0.0001). A 91% detection rate was achieved utilizing an ADC threshold (<1.81 × 10(-3) mm(2)/s ). Non-high-grade DCIS exhibited greater qualitative DWI intensity (p = 0.02) and quantitative CNR (p = 0.01) than high-grade DCIS but no difference in ADC (p = 0.40). Lesion size, morphology, and necrosis did not affect qualitative or quantitative DWI parameters of DCIS lesions (p > 0.05).

CONCLUSIONS

DCIS lesions have higher DWI signal intensity and lower ADC values than normal breast tissue. DWI warrants further investigation as a potential non-contrast MRI tool for early breast cancer detection.

Improved diagnostic accuracy of breast MRI through combined apparent diffusion coefficients and dynamic contrast-enhanced kinetics

This study investigated the relationship between apparent diffusion coefficient (ADC) measures and dynamic contrast-enhanced magnetic resonance imaging (MRI) kinetics in breast lesions and evaluated the relative diagnostic value of each quantitative parameter. Seventy-seven women with 100 breast lesions (27 malignant and 73 benign) underwent both dynamic contrast-enhanced MRI and diffusion weighted MRI. Dynamic contrast-enhanced MRI kinetic parameters included peak initial enhancement, predominant delayed kinetic curve type (persistent, plateau, or washout), and worst delayed kinetic curve type (washout > plateau > persistent). Associations between ADC and dynamic contrast-enhanced MRI kinetic parameters and predictions of malignancy were evaluated. Results showed that ADC was significantly associated with predominant curve type (ADC was higher for lesions exhibiting predominantly persistent enhancement compared with those exhibiting predominantly washout or plateau, P = 0.006), but was not significantly associated with peak initial enhancement or worst curve type (P > 0.05). Univariate analysis showed significant differences between benign and malignant lesions in both ADC (P < 0.001) and worst curve (P = 0.003). In multivariate analysis, worst curve type and ADC were significant independent predictors of benign versus malignant outcome and in combination produced the highest area under the receiver operating characteristic curve (0.85 and 0.78 with 5-fold cross validation).

Non-gaussian analysis of diffusion-weighted MR imaging in head and neck squamous cell carcinoma: A feasibility study

BACKGROUND AND PURPOSE

Water in biological structures often displays non-Gaussian diffusion behavior. The objective of this study was to test the feasibility of non-Gaussian fitting by using the kurtosis model of the signal intensity decay curves obtained from DWI by using an extended range of b-values in studies of phantoms and HNSCC.

MATERIALS AND METHODS

Seventeen patients with HNSCC underwent DWI by using 6 b-factors (0, 50-1500 s/mm(2)) at 1.5T. Monoexponential (yielding ADC(mono)) and non-Gaussian kurtosis (yielding apparent diffusion coefficient D(app) and apparent kurtosis coefficient K(app)) fits were performed on a voxel-by-voxel basis in selected regions of interest (primary tumors, metastatic lymph nodes, and spinal cord). DWI studies were also performed on phantoms containing either water or homogenized asparagus. To determine whether the kurtosis model provided a significantly better fit than did the monoexponential model, an F test was performed. Spearman correlation coefficients were calculated to assess correlations between K(app) and D(app).

RESULTS

The kurtosis model fit the experimental data points significantly better than did the monoexponential model (P < .05). D(app) was approximately twice the value of ADC(mono) (eg, in neck nodal metastases D(app) was 1.54 and ADC(mono) was 0.84). K(app) showed a weak Spearman correlation with D(app) in a homogenized asparagus phantom and for 44% of tumor lesions.

CONCLUSIONS

The use of kurtosis modeling to fit DWI data acquired by using an extended b-value range in HNSCC is feasible and yields a significantly better fit of the data than does monoexponential modeling. It also provides an additional parameter, K(app), potentially with added value.

Diffusion tensor imaging of the cortical plate and subplate in very-low-birth-weight infants

BACKGROUND

Many intervention studies in preterm infants aim to improve neurodevelopmental outcome, but short-term proxy outcome measurements are lacking. Cortical plate and subplate development could be such a marker.

OBJECTIVE

Our aim was to provide normal DTI reference values for the cortical plate and subplate of preterm infants.

MATERIALS AND METHODS

As part of an ongoing study we analysed diffusion tensor imaging (DTI) images of 19 preterm infants without evidence of injury on conventional MRI, with normal outcome (Bayley-II assessed at age 2), and scanned in the first 4 days of life. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in the frontal and temporal subplate and cortical plate were measured in single and multiple voxel regions of interest (ROI) placed on predefined regions.

RESULTS

Using single-voxel ROIs, statistically significant inverse correlation was found between gestational age (GA) and FA of the frontal (r = -0.5938, P = 0.0058) and temporal (r = -0.4912, P = 0.0327) cortical plate. ADC values had a significant positive correlation with GA in the frontal (r = 0.5427, P = 0.0164) and temporal (r = 0.5540, P = 0.0138) subplate.

CONCLUSION

Diffusion tensor imaging allows in vivo exploration of the evolving cortical plate and subplate. We provide FA and ADC values of the subplate and cortical plate in very-low-birth-weight (VLBW) infants with normal developmental outcome that can be used as reference values.

Magnetic resonance imaging in neonatal stroke

Neonatal stroke occurs in 1 in 2300-5000 live births, the incidence of which is lower than that in adults, but still higher than that in childhood. The higher incidence of perinatal stroke in preterm and term infants compared to stroke in childhood may be partly explained by higher detection rates using routine fetal ultrasound and postnatal cranial sonography. In addition, there is greater availability of magnetic resonance imaging (MRI) for neuroimaging in preterm and full-term infants, which is due in part to the availability of MR-compatible incubators and MR systems at or near the neonatal intensive care unit. In addition, the wide range of MR techniques, such as T2-, diffusion- and susceptibility-weighted imaging allows improved visualization and quantification of neonatal stroke or hypoxic-ischemic injury. This chapter reviews the MR neuroimaging modalities that actually assist the clinician in the detection of neonatal stroke.