Quantitative Apparent Diffusion Coefficient Mapping May Predict Seizure Onset in Children With Sturge-Weber Syndrome

BOston Neonatal Brain Injury Dataset for Hypoxic Ischemic Encephalopathy (BONBID-HIE): Part I. MRI and Manual Lesion Annotation

Hypoxic ischemic encephalopathy (HIE) is a brain injury that occurs in 1 ~ 5/1000 term neonates. Accurate identification and segmentation of HIE-related lesions in neonatal brain magnetic resonance images (MRIs) is the first step toward predicting prognosis, identifying high-risk patients, and evaluating treatment effects. It will lead to a more accurate estimation of prognosis, a better understanding of neurological symptoms, and a timely prediction of response to therapy. We release the first public dataset containing neonatal brain diffusion MRI and expert annotation of lesions from 133 patients diagnosed with HIE. HIE-related lesions in brain MRI are often diffuse (i.e., multi-focal), and small (over half the patients in our data having lesions occupying <1% of brain volume). Segmentation for HIE MRI data is remarkably different from, and arguably more challenging than, other segmentation tasks such as brain tumors with focal and relatively large lesions. We hope that this dataset can help fuel the development of MRI lesion segmentation methods for HIE and small diffuse lesions in general.

Deep Medullary Vein Thrombosis in Newborns: A Systematic Literature Review

BACKGROUND

Deep medullary vein (DMV) thrombosis is a rare cause of brain damage in both preterm and full-term neonates. In this study, we aimed to collect data on clinical and radiological presentation, treatment, and outcome of neonatal DMV thrombosis.

METHODS

Systematic literature review on neonatal DMV thrombosis was carried out in PubMed, ClinicalTrial.gov, Scopus, and Web of Science up to December 2022.

RESULTS

Seventy-five published cases of DMV thrombosis were identified and analysed (preterm newborns were 46%). Neonatal distress, respiratory resuscitation, or need for inotropes were present in 34/75 (45%) of patients. Signs and symptoms at presentation included seizures (38/75, 48%), apnoea (27/75, 36%), lethargy or irritability (26/75, 35%). At magnetic resonance imaging (MRI), fan-shaped linear T2 hypointense lesions were documented in all cases. All had ischaemic injuries, most often involving the frontal (62/74, 84%) and parietal lobes (56/74, 76%). Signs of haemorrhagic infarction were present in 53/54 (98%). Antithrombotic treatment was not mentioned in any of the studies included. Although mortality was low (2/75, 2.6%), a large proportion of patients developed neurological sequelae (intellectual disability in 19/51 [37%] and epilepsy in 9/51 [18%] cases).

CONCLUSIONS

DMV thrombosis is rarely identified in the literature, even if it is possibly under-recognized or under-reported. Presentation in neonatal age is with seizures and non-specific systemic signs/symptoms that often cause diagnostic delay, despite the pathognomonic MRI picture. The high rate of morbidity, which determines significant social and health costs, requires further in-depth studies aimed at earlier diagnosis and evidence-based prevention and therapeutic strategies.

Study protocol: retrospectively mining multisite clinical data to presymptomatically predict seizure onset for individual patients with Sturge-Weber

INTRODUCTION

Secondary analysis of hospital-hosted clinical data can save time and cost compared with prospective clinical trials for neuroimaging biomarker development. We present such a study for Sturge-Weber syndrome (SWS), a rare neurovascular disorder that affects 1 in 20 000-50 000 newborns. Children with SWS are at risk for developing neurocognitive deficit by school age. A critical period for early intervention is before 2 years of age, but early diagnostic and prognostic biomarkers are lacking. We aim to retrospectively mine clinical data for SWS at two national centres to develop presymptomatic biomarkers.

METHODS AND ANALYSIS

We will retrospectively collect clinical, MRI and neurocognitive outcome data for patients with SWS who underwent brain MRI before 2 years of age at two national SWS care centres. Expert review of clinical records and MRI quality control will be used to refine the cohort. The merged multisite data will be used to develop algorithms for abnormality detection, lesion-symptom mapping to identify neural substrate and machine learning to predict individual outcomes (presence or absence of seizures) by 2 years of age. Presymptomatic treatment in 0-2 years and before seizure onset may delay or prevent the onset of seizures by 2 years of age, and thereby improve neurocognitive outcomes. The proposed work, if successful, will be one of the largest and most comprehensive multisite databases for the presymptomatic phase of this rare disease.

ETHICS AND DISSEMINATION

This study involves human participants and was approved by Boston Children's Hospital Institutional Review Board: IRB-P00014482 and IRB-P00025916 Johns Hopkins School of Medicine Institutional Review Board: NA_00043846. Participants gave informed consent to participate in the study before taking part. The Institutional Review Boards at Kennedy Krieger Institute and Boston Children's Hospital approval have been obtained at each site to retrospectively study this data. Results will be disseminated by presentations, publication and sharing of algorithms generated.

How Machine Learning is Powering Neuroimaging to Improve Brain Health

This report presents an overview of how machine learning is rapidly advancing clinical translational imaging in ways that will aid in the early detection, prediction, and treatment of diseases that threaten brain health. Towards this goal, we aresharing the information presented at a symposium, "Neuroimaging Indicators of Brain Structure and Function - Closing the Gap Between Research and Clinical Application", co-hosted by the McCance Center for Brain Health at Mass General Hospital and the MIT HST Neuroimaging Training Program on February 12, 2021. The symposium focused on the potential for machine learning approaches, applied to increasingly large-scale neuroimaging datasets, to transform healthcare delivery and change the trajectory of brain health by addressing brain care earlier in the lifespan. While not exhaustive, this overview uniquely addresses many of the technical challenges from image formation, to analysis and visualization, to synthesis and incorporation into the clinical workflow. Some of the ethical challenges inherent to this work are also explored, as are some of the regulatory requirements for implementation. We seek to educate, motivate, and inspire graduate students, postdoctoral fellows, and early career investigators to contribute to a future where neuroimaging meaningfully contributes to the maintenance of brain health.

Deep medullary vein engorgement and superficial medullary vein engorgement: two patterns of perinatal venous stroke

Perinatal venous stroke has classically been attributed to cerebral sinovenous thrombosis with resultant congestion or thrombosis of the small veins draining the cerebrum. Advances in brain MRI, in particular susceptibility-weighted imaging, have enabled the visualization of the engorged small intracerebral veins, and the spectrum of perinatal venous stroke has expanded to include isolated congestion or thrombosis of the deep medullary veins and the superficial intracerebral veins. Congestion or thrombosis of the deep medullary veins or the superficial intracerebral veins can result in vasogenic edema, cytotoxic edema or hemorrhage in the territory of disrupted venous flow. Deep medullary vein engorgement and superficial medullary vein engorgement have characteristic findings on MRI and should be differentiated from neonatal hemorrhagic stroke.

Extent of Leptomeningeal Capillary Malformation is Associated With Severity of Epilepsy in Sturge-Weber Syndrome

BACKGROUND

Individuals with Sturge-Weber syndrome (SWS) often expereince intractable epilepsy and cognitive decline. We hypothesized that the extent of the leptomeningeal capillary malformation (LCM) may correlate with the severity of neurological impairment due to SWS. We tested the hypothesis in a cross-sectional study of seizure severity and electroencephalographic (EEG) findings and a retrospective cohort study for surgical indications related to the extent of the LCM.

METHODS

We enrolled 112 patients and classified them according to LCM distribution: (1) bilateral, (2) hemispheric, (3) multilobar, and (4) single lobe. Age at seizure onset, seizure semiology and frequency, and EEG findings were compared. Surgical indications were evaluated for each group by Fisher exact test, and predictors for surgery were evaluated by univariate and multivariate analyses. Therapeutic efficacy was evaluated by the SWS-Neurological Score (SWS-NS).

RESULTS

The bilateral and hemispheric groups had early seizure onset (4.0 months old and 3.0 months old), frequent seizures (88.9% and 80.6% had more than one per month), focal-to-bilateral tonic-clonic seizures (88.9% and 74.2%), and status epilepticus (100% and 87.1%). The groups' EEG findings did not differ substantially. Surgical indications were present in 77.8% of the bilateral, 88.1% of the hemispheric, and 46.8% of the multilobar groups. Seizure more than once per month was a predictor of surgical treatment. Seizure subscore improved postoperatively in the hemispheric and multilobar groups. Even after surgical treatment, the bilateral and hemispheric groups exhibited higher SWS-NSs than members of the other groups.

CONCLUSION

Our study demonstrated a strong association between extensive LCM and epilepsy severity. Surgical intervention improved seizure outcome in patients with SWS with large LCMs.

Voxelwise and Regional Brain Apparent Diffusion Coefficient Changes on MRI from Birth to 6 Years of Age

Background A framework for understanding rapid diffusion changes from 0 to 6 years of age is important in the detection of neurodevelopmental disorders. Purpose To quantify patterns of normal apparent diffusion coefficient (ADC) development from 0 to 6 years of age. Materials and Methods Previously constructed age-specific ADC atlases from 201 healthy full-term children (108 male; age range, 0-6 years) with MRI scans acquired from 2006 to 2013 at one large academic hospital were analyzed to quantify four patterns: ADC trajectory, rate of ADC change, age of ADC maturation, and hemispheric asymmetries of maturation ages. Patterns were quantified in whole-brain, segmented regional, and voxelwise levels by fitting a two-term exponential model. Hemispheric asymmetries in ADC maturation ages were assessed using t tests with Bonferroni correction. Results The posterior limb of the internal capsule (mean ADC: left hemisphere, 1.18 ×10³μm²/sec; right hemisphere, 1.17 ×10³μm²/sec), anterior limb of the internal capsule (left, 1.11 ×10³μm²/sec; right, 1.09 ×10³μm²/sec), vermis (1.26 ×10³μm²/sec), thalami (left, 1.17 ×10³μm²/sec; right, 1.15 ×10³μm²/sec), and basal ganglia (left, 1.26 ×10³μm²/sec; right, 1.23 ×10³μm²/sec) demonstrate low initial ADC values, indicating an earlier prenatal time course of development. ADC maturation was completed between 1.3 and 2.4 years of age, depending on the region. The vermis and left thalamus matured earliest (1.3 years). The frontolateral gray matter matured latest (right, 2.3 years; left, 2.4 years). ADC maturation occurred earlier in the left hemisphere (P < .001) in several regions, including the frontal (mean ± standard deviation) (left, 2.16 years ± 0.29; right, 2.19 years ± 0.31), temporal (left, 1.93 years ± 0.22; right, 1.99 years ± 0.22), and parietal (left, 1.92 years ± 0.30; right, 2.03 years ± 0.28) white matter. Maturation occurred earlier in the right hemisphere (P < .001) in several regions, including the thalami (left, 1.63 years ± 0.32; right, 1.45 years ± 0.33), basal ganglia (left, 1.79 years ± 0.31; right, 1.70 years ± 0.37), and hippocampi (left, 1.93 years ± 0.34; right, 1.78 years ± 0.33). Conclusion Normative apparent diffusion coefficient developmental patterns on diffusion-weighted MRI scans were quantified in children aged 0 to 6 years. This work provides knowledge about early brain development and may guide the detection of abnormal patterns of maturation. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Rollins in this issue.

A somatic missense mutation in GNAQ causes capillary malformation

PURPOSE OF REVIEW

Capillary malformations, the most common type of vascular malformation, are caused by a somatic mosaic mutation in GNAQ, which encodes the Gαq subunit of heterotrimeric G-proteins. How the single amino acid change - predicted to activate Gαq - causes capillary malformations is not known but recent advances are helping to unravel the mechanisms.

RECENT FINDINGS

The GNAQ R183Q mutation is present not only in endothelial cells isolated from skin and brain capillary malformations but also in brain tissue underlying the capillary malformation, raising questions about the origin of capillary malformation-causing cells. Insights from computational analyses shed light on the mechanisms of constitutive activation and new basic science shows Gαq plays roles in sensing shear stress and in regulating cerebral blood flow.

SUMMARY

Several studies confirm the GNAQ R183Q mutation in 90% of nonsyndromic and Sturge-Weber syndrome (SWS) capillary malformations. The mutation is enriched in endothelial cells and blood vessels isolated from skin, brain, and choroidal capillary malformations, but whether the mutation resides in other cell types must be determined. Further, the mechanisms by which the R183Q mutation alters microvascular architecture and blood flow must be uncovered to develop new treatment strategies for SWS in particular, a devastating disease for which there is no cure.

Maternal Dietary Intake of Omega-3 Fatty Acids Correlates Positively with Regional Brain Volumes in 1-Month-Old Term Infants

Maternal nutrition is an important factor for infant neurodevelopment. However, prior magnetic resonance imaging (MRI) studies on maternal nutrients and infant brain have focused mostly on preterm infants or on few specific nutrients and few specific brain regions. We present a first study in term-born infants, comprehensively correlating 73 maternal nutrients with infant brain morphometry at the regional (61 regions) and voxel (over 300 000 voxel) levels. Both maternal nutrition intake diaries and infant MRI were collected at 1 month of life (0.9 ± 0.5 months) for 92 term-born infants (among them, 54 infants were purely breastfed and 19 were breastfed most of the time). Intake of nutrients was assessed via standardized food frequency questionnaire. No nutrient was significantly correlated with any of the volumes of the 61 autosegmented brain regions. However, increased volumes within subregions of the frontal cortex and corpus callosum at the voxel level were positively correlated with maternal intake of omega-3 fatty acids, retinol (vitamin A) and vitamin B12, both with and without correction for postmenstrual age and sex (P < 0.05, q < 0.05 after false discovery rate correction). Omega-3 fatty acids remained significantly correlated with infant brain volumes after subsetting to the 54 infants who were exclusively breastfed, but retinol and vitamin B12 did not. This provides an impetus for future larger studies to better characterize the effect size of dietary variation and correlation with neurodevelopmental outcomes, which can lead to improved nutritional guidance during pregnancy and lactation.

Mining multi-site clinical data to develop machine learning MRI biomarkers: application to neonatal hypoxic ischemic encephalopathy

BACKGROUND

Secondary and retrospective use of hospital-hosted clinical data provides a time- and cost-efficient alternative to prospective clinical trials for biomarker development. This study aims to create a retrospective clinical dataset of Magnetic Resonance Images (MRI) and clinical records of neonatal hypoxic ischemic encephalopathy (HIE), from which clinically-relevant analytic algorithms can be developed for MRI-based HIE lesion detection and outcome prediction.

METHODS

This retrospective study will use clinical registries and big data informatics tools to build a multi-site dataset that contains structural and diffusion MRI, clinical information including hospital course, short-term outcomes (during infancy), and long-term outcomes (~ 2 years of age) for at least 300 patients from multiple hospitals.

DISCUSSION

Within machine learning frameworks, we will test whether the quantified deviation from our recently-developed normative brain atlases can detect abnormal regions and predict outcomes for individual patients as accurately as, or even more accurately, than human experts. Trial Registration Not applicable. This study protocol mines existing clinical data thus does not meet the ICMJE definition of a clinical trial that requires registration.

Neurological Complications of Sturge-Weber Syndrome: Current Status and Unmet Needs

OBJECTIVE

We aimed to identify the current status and major unmet needs in the management of neurological complications in Sturge-Weber syndrome.

METHODS

An expert panel consisting of neurologists convened during the Sturge-Weber Foundation Clinical Care Network conference in September 2018. Literature regarding current treatment strategies for neurological complications was reviewed.

RESULTS

Although strong evidence-based standards are lacking, the implementation of consensus-based standards of care and outcome measures to be shared across all Sturge-Weber Foundation Clinical Care Network Centers are needed. Each patient with Sturge-Weber syndrome should have an individualized seizure action plan. There is a need to determine the appropriate abortive and preventive treatment of migraine headaches in Sturge-Weber syndrome. Likewise, a better understanding and better diagnostic modalities and treatments are needed for stroke-like episodes. As behavioral problems are common, the appropriate screening tools for mental illnesses and the timing for screening should be established. Brain magnetic resonance imaging (MRI) preferably done after age one year is the primary imaging modality of choice to establish the diagnosis, although advances in MRI techniques can improve presymptomatic diagnosis to identify patients eligible for preventive drug trials.

CONCLUSION

We identified the unmet needs in the management of neurological complications in Sturge-Weber syndrome. We define a minimum standard brain MRI protocol to be used by Sturge-Weber syndrome centers. Future multicenter clinical trials on specific treatments of Sturge-Weber syndrome-associated neurological complications are needed. An improved national clinical database is critically needed to understand its natural course, and for retrospective and prospective measures of treatment efficacy.