Dual-energy computed tomography in acute ischemic stroke: state-of-the-art.

Dual-energy computed tomography (DECT) allows distinguishing between tissues with similar X-ray attenuation but different atomic numbers. Recent studies demonstrated that this technique has several areas of application in patients with ischemic stroke and a potential impact on patient management. After endovascular stroke therapy (EST), hyperdense areas can represent either hemorrhage or contrast staining due to blood-brain barrier disruption, which can be differentiated reliably by DECT. Further applications are improved visualization of early infarctions, compared to single-energy computed tomography, and prediction of transformation into infarction or hemorrhage in contrast-enhancing areas. In addition, DECT allows detection and evaluation of the material composition of intra-arterial clots after EST. This review summarizes the clinical state-of-the-art of DECT in patients with stroke, and features some prospects for future developments. KEY POINTS: • Dual-energy computed tomography (DECT) allows differentiation between tissues with similar X-ray attenuation but differentatomic numbers. • DECT has several areas of application in patients with ischemic stroke and a potential impact on patient management. • Prospects for future developments in DECT may improve treatment decision-making.

Magnetic Resonance Spectroscopy in Diagnosis and Follow-Up of Gliomas: State-of-the-Art.

Preoperative grade prediction is important in diagnostics of glioma. Even more important can be follow-up after chemotherapy and radiotherapy of high grade gliomas. In this review we provide an overview of MR-spectroscopy (MRS), technical aspects, and different clinical scenarios in the diagnostics and follow-up of gliomas in pediatric and adult populations. Furthermore, we provide a recap of the current research utility and possible future strategies regarding proton- and phosphorous-MRS in glioma research.

A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates.

Segmentation of specific brain tissue from MRI volumes is of great significance for brain disease diagnosis, progression assessment, and monitoring of neurological conditions. Manual segmentation is time-consuming, laborious, and subjective, which significantly amplifies the need for automated processes. Over the last decades, the active development in the field of deep learning, especially convolutional neural networks (CNNs), and the associated performance improvements have increased the demand for the application of CNN-based methods to provide consistent measurements and quantitative analyses. In this paper, we present an efficient deep learning approach for the segmentation of brain tissue. More specifically, we address the problem of segmentation of the posterior limb of the internal capsule (PLIC) in preterm neonates. To this end, we propose a CNN-based pipeline comprised of slice-selection modules and a multi-view segmentation model, which exploits the 3D information contained in the MRI volumes to improve segmentation performance. One special feature of the proposed method is its ability to identify one desired slice out of the whole image volume, which is relevant for pediatricians in terms of prognosis. To increase computational efficiency, we apply a strategy that automatically reduces the information contained in the MRI volumes to its relevant parts. Finally, we conduct an expert rating alongside standard evaluation metrics, such as dice score, to evaluate the performance of the proposed framework. We demonstrate the benefit of the multi-view technique by comparing it with its single-view counterparts, which reveals that the proposed method strikes a good balance between exploiting the available image information and reducing the required computing power compared to 3D segmentation networks. Standard evaluation metrics as, well as expert-based assessment, confirm the good performance of the proposed framework, with the latter being more relevant in terms of clinical applicability. We demonstrate that the proposed deep learning pipeline can compete with the experts in terms of accuracy. To prove the generalisability of the proposed method, we additionally assess our deep learning pipeline to data from the Developing Human Connectome Project (dHCP).

Prophylactic Low-Dose Paracetamol Administration for Ductal Closure and Microstructural Brain Development in Preterm Infants.

INTRODUCTION: Prophylactic low-dose paracetamol administration is used to induce closure of the ductus arteriosus. Effects on the neurological outcome in preterm infants remain unknown. We compared microstructural brain development in very preterm infants with and without exposure to prophylactic paracetamol by using MR-based diffusion tensor imaging. MATERIALS AND METHODS: Infants aged <32 gestational weeks born between October 2014 and December 2018 received prophylactic paracetamol (10 mg/kg intravenously every 8 h until echocardiography after at least 72 h) and form the paracetamol group; infants born between February 2011 and September 2014 form the control group. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) at term-equivalent age were measured in 14 defined cerebral regions and compared between the groups. RESULTS: Included in the study were 340 infants, of whom 217 received prophylactic paracetamol, and 123 formed the control group. The paracetamol group showed significantly higher FA values and lower ADC values in the splenium of the corpus callosum, as well as higher FA values in the pons bilaterally, the left middle cerebellar peduncle, the right occipital white matter, and the right posterior limb of the internal capsule (p ≤ 0.02). CONCLUSION: The perceived safety of prenatal paracetamol exposure has been questioned in recent years. We found no impairment on microstructural maturation processes in the brain of preterm infants at term-equivalent age following early paracetamol administration. The clinical relevance of these imaging findings has to be determined in long-term follow-up studies on neurodevelopmental outcome.

Characteristic facial features and cortical blindness distinguish the DOCK7-related epileptic encephalopathy.

BACKGROUND: The epileptic encephalopathies display extensive locus and allelic heterogeneity. Biallelic truncating DOCK7 variants were recently reported in five children with early-onset epilepsy, intellectual disability, and cortical blindness, indicating that DOCK7 deficiency causes a specific type of epileptic encephalopathy. METHODS: We identified 23- and 27-year-old siblings with the clinical pattern reported for DOCK7 deficiency, and conducted genome-wide linkage analysis and WES. The consequences of a DOCK7 variant were analyzed on the transcript and protein level in patients' fibroblasts. RESULTS: We identified a novel homozygous DOCK7 frameshift variant, an intragenic tandem duplication of 124-kb, previously missed by CGH array, in adult patients. Patients display atrophy in the occipital lobe and pontine hypoplasia with marked pontobulbar sulcus, and focal atrophy of occasional cerebellar folia is a novel finding. Recognizable dysmorphic features include normo-brachycephaly, narrow forehead, low anterior and posterior hairlines, prominent ears, full cheeks, and long eyelashes. Our patients function on the level of 4-year-old children, never showed signs of regression, and seizures are largely controlled with multi-pharmacotherapy. Studies of patients' fibroblasts showed nonsense-mediated RNA decay and lack of DOCK7 protein. CONCLUSION: DOCK7 deficiency causes a definable clinical entity, a recognizable type of epileptic encephalopathy.

Reduced Cerebellar Size at Term-Equivalent Age Is Related to a 17% Lower Mental Developmental Index in Very Preterm Infants without Brain Injury.

INTRODUCTION: Cerebellar injury is increasingly recognized as a relevant complication of premature birth. However, the prevalence of reduced cerebellar growth and its consequences for neurodevelopmental outcome in preterm infants without overt brain injury remain to be defined in detail. The aim of this study was to assess the transcerebellar diameter (TCD) at term-equivalent age (TEA) in very preterm infants without brain injury and to evaluate whether TCD is related to neurodevelopmental outcome in this population. METHODS: Very preterm infants underwent magnetic resonance imaging at TEA. Infants with any grade of supra- or infratentorial brain injury were excluded. TCD was measured and categorized using existing cut-off values as normal TCD and mild or severe TCD reduction. Psychomotor Developmental index (PDI) and Mental Developmental index (MDI) were assessed using Bayley Scales of Infant Development II and III at a corrected age of 2 years. RESULTS: A total of 166 infants with a mean gestational age of 29.9 ± 1.8 weeks and a mean birth weight of 1,317 ± 393 g were included. Mean TCD of girls was significantly lower compared to the mean TCD of boys (p = 0.004). TCD reduction was present in 8 infants (4.8%). Infants with a mild TCD reduction achieved lower mean MDI than infants with normal TCD (p = 0.021). DISCUSSION: We found that reduced TCD was associated with a 17% lower mean MDI at a corrected age of 2 years. Thus, TCD at TEA may be used as an imaging marker for adverse cognitive outcome in the apparently low-risk group of preterm infants without brain injury.

Supratentorial Brain Metrics Predict Neurodevelopmental Outcome in Very Preterm Infants without Brain Injury at Age 2 Years.

INTRODUCTION: Very preterm infants are at risk for adverse neurodevelopmental outcome. To better identify children without brain injury at risk for developmental sequelae, we assessed predictive values of supratentorial brain metrics in relation to outcome. METHODS: Very preterm infants underwent magnetic resonance imaging (MRI) at term-equivalent age. Infants with any grade of supra- or infratentorial brain injury according to Kidokoro et al. [Pediatrics 2014;134:e444-53] were excluded. Supratentorial brain metrics (biparietal width, extracerebral space, interhemispheric distance) were measured and categorised using existing cut-off values. The Psychomotor Developmental Index (PDI) and Mental Developmental Index (MDI) were assessed using the Bayley Scales of Infant Development, second and third edition, at 2 years of age. Developmental delay was defined as a score <85. Positive and negative predictive values for developmental delay were calculated. RESULTS: A total of 237 very preterm infants were enrolled. Of all infants, 59 (21.2%) showed developmental delay. Infants with z-scores less than -0.5 for biparietal width had significantly lower PDI (p = 0.039) and MDI (p = 0.042) than infants with normal z-scores. Enlargement of extracerebral spaces was also related to lower PDI (p = 0.047) and MDI (p = 0.036). Negative predictive value was highest when all brain metrics were within the normal range (PDI <85: 96.6%, MDI <85: 90.0%). Combining the biparietal width and the interhemispheric distance showed highest positive predictive values for developmental delay (MDI or PDI <85: 58.3%). DISCUSSION: Supratentorial brain metrics are predictive for neurodevelopmental outcome in infants with ostensibly normal MRI. A combination of supratentorial brain metrics is most meaningful for identifying infants at risk for long-term sequelae.

Developmental patterns of Ki-67, Oct-4 and α-tubulin proteins expression in the human spinal cord.

The aim of this study was to analyze immunohistochemically the relationships between factors involved in processes of cell proliferation (Ki-67), differentiation (Oct-4) and primary cilia formation (α-tubulin) in the two parts of the developing human spinal cord (SC) of different origin in 11 human concepti (developmental weeks 5-10). Proliferation was highest in weeks 7-8 in the dorsal ventricular zones of the cranial (85.5%) and caudal (12.1%) SC. In the ventricular (VZ), intermediate (IZ) and marginal zones (MZ) of the cranial SC, α-tubulin and Oct-4 were moderately to strongly expressed. During weeks 5-6, moderate expression of α-tubulin and Oct-4 characterized the ventral part, with mild expression in the dorsal part of the caudal SC. In weeks 7-8, their expression increased in the VZ and IZ, and decreased in the MZ. In both parts of the SC Ki-67 and α-tubulin co-localized in the VZ. Oct-4 and Ki-67 co-localized only in the ependymal cells. In the cranial SC α-tubulin and Oct-4 co-localized (VZ and IZ), while the MZ expressed only α-tubulin. In the caudal SC, α-tubulin and Oct-4 co-localized in the VZ, while in the IZ some cells were only α-tubulin-positive. We suggest the importance of temporal-spatial expression of Ki-67 for the thickening of the cranial SC lateral wall. While in the cranial part of the SC, proliferation followed a ventral-dorsal direction, the caudal SC had a more irregular pattern. α-Tubulin was associated with cilia formation (ependymal cells) and axonic elongation of neuroblasts (MZ). Primary cilia signaling are important in control of SC proliferation and differentiation. Oct-4 expression in the SC coincided with presence of dividing neuroepithelial cells in the VZ and neuroblasts in the IZ, and could control the level of SC differentiation.