Precise neonatal arterial ischemic stroke classification with a three-dimensional map of the arterial territories of the neonatal brain

Massive Neonatal Arterial Ischemic Stroke

BACKGROUND

Massive infarction in adults is a devastating entity characterized by signs of extreme swelling of the brain's parenchyma. We explored whether a similar entity exists in neonates, which we call massive neonatal arterial ischemic stroke (M-NAIS), and assess its potential clinical implications.

METHODS

Prospective multicenter cohort study comprising 48 neonates with gestational age ≥35 weeks with middle cerebral artery (MCA) NAIS was performed. Diagnosis with magnetic resonance imaging (MRI) was performed within the first three days after symptom onset. The presence of signs of a space-occupying mass, such as brain midline shift and/or ventricular and/or extra-axial space collapse, was recorded. The volume of the infarct and brain midline shift were determined with semiautomatic procedures. Neurodevelopment was assessed at age 24 months.

RESULTS

Fifteen (31%) neonates presented MRI signs of a space-occupying mass effect and were considered to have an M-NAIS. The relative volume (infarct volume/total brain volume) of the infarct was on average significantly greater in the M-NAIS subgroup (29% vs 4.9%, P < 0.001). Patients with M-NAIS consistently presented lesions involving the M1 arterial territory of the MCA and showed more apneic and tonic seizures, which had an earlier onset and lasted longer. Moderate to severe adverse neurodevelopmental outcomes were present in most M-NAIS cases (79% vs 6%, P < 0.001).

CONCLUSIONS

M-NAIS appears to be a distinctive subtype of neonatal infarction, defined by characteristic neuroimaging signs. Neonates with M-NAIS frequently present a moderate to severe adverse outcome. Early M-NAIS identification would allow for prompt, specific rehabilitation interventions and would provide more accurate prognostic information to families.

Language lateralization and outcome in perinatal stroke patients with different vascular types

Perinatal stroke affects child's language development and can change language lateralization. Language generation and comprehension tasks in functional magnetic resonance imaging were used to determine language lateralization in term born children with perinatal left-side arterial ischemic stroke (AIS) (n = 9, mean age (SD) 13.4 (3.1) y.) and periventricular venous infarction (PVI) (n = 12, 11.8 (2.8) y.), and in healthy right-handed controls (n = 30, 11.6 (2.6) y.). Lateralization index was calculated for the Broca and Wernicke areas and correlated with language and cognitive outcomes measured by the Kaufman Assessment Battery for Children II ed. Language outcome in children with perinatal stroke is poorer compared to healthy controls. Children with small AIS lesions and most children with PVI showed left-side language activation. Most children with large AIS lesions and one child with large PVI had language activation reorganized to the right hemisphere. Language reorganization to the unlesioned right hemisphere did not ensure normal language outcome.

Signatures of brain plasticity supporting language recovery after perinatal arterial ischemic stroke

Brain imaging methods such as functional Magnetic Resonance Imaging (fMRI) and Diffusion Tensor Imaging (DTI) have already been used to decipher the functional and structural brain changes occurring during normal language development. However, little is known about the differentiation of the language network after an early lesion. While in adults, stroke over the left hemisphere generally induces post-stroke aphasia, it is not always the case when a stroke occurs in the perinatal period, thus revealing a remarkable plastic power of the language network during early development. In particular, the role of perilesional tissues, as opposed to undamaged brain areas in the functional recovery of language functions after an early insult, remains unclear. In this review article, we provide an overview of the extant literature using functional and structural neuroimaging data revealing the signatures of brain plasticity underlying near-normal language development.

Structural and functional connectivity of motor circuits after perinatal stroke: A machine learning study

Developmental neuroplasticity allows young brains to adapt via experiences early in life and also to compensate after injury. Why certain individuals are more adaptable remains underexplored. Perinatal stroke is an ideal human model of neuroplasticity with focal lesions acquired near birth in a healthy brain. Machine learning can identify complex patterns in multi-dimensional datasets. We used machine learning to identify structural and functional connectivity biomarkers most predictive of motor function. Forty-nine children with perinatal stroke and 27 controls were studied. Functional connectivity was quantified by fluctuations in blood oxygen-level dependent (BOLD) signal between regions. White matter tractography of corticospinal tracts quantified structural connectivity. Motor function was assessed using validated bimanual and unimanual tests. RELIEFF feature selection and random forest regression models identified predictors of each motor outcome using neuroimaging and demographic features. Unilateral motor outcomes were predicted with highest accuracy (8/54 features r = 0.58, 11/54 features, r = 0.34) but bimanual function required more features (51/54 features, r = 0.38). Connectivity of both hemispheres had important roles as did cortical and subcortical regions. Lesion size, age at scan, and type of stroke were predictive but not highly ranked. Machine learning regression models may represent a powerful tool in identifying neuroimaging biomarkers associated with clinical motor function in perinatal stroke and may inform personalized targets for neuromodulation.