structural connectivity analysis in children with segmental callosal agenesis

BACKGROUND AND PURPOSE: Segmental callosal agenesis is characterized by the absence of the intermediate callosal portion. We aimed to evaluate the structural connectivity of segmental callosal agenesis by using constrained spherical deconvolution tractography and connectome analysis. MATERIALS AND METHODS: We reviewed the clinical-radiologic features of 8 patients (5 males; mean age, 3.9 years). Spherical deconvolution and probabilistic tractography were performed on diffusion data. Structural connectivity analysis, including summary network metrics, modularity analysis, and network consistency measures, was applied in 5 patients and 10 age-/sex-matched controls. RESULTS: We identified 3 subtypes based on the position of the hippocampal commissure: beneath the anterior callosal remnant in 3 patients (type I), beneath the posterior callosal remnant in 3 patients (type II), and between the anterior and posterior callosal remnants in 2 patients (type III). In all patients, the agenetic segment corresponded to fibers projecting to the parietal lobe, and segmental Probst bundles were found at that level. Ectopic callosal bundles were identified in 3 patients. Topology analysis revealed reduced global connectivity in patients compared with controls. The network topology of segmental callosal agenesis was more variable across patients than that of the control connectomes. Modularity analysis revealed disruption of the structural core organization in the patients. CONCLUSIONS: Three malformative subtypes of segmental callosal agenesis were identified. Even the absence of a small callosal segment may impact global brain connectivity and modularity organization. The presence of ectopic callosal bundles may explain the greater interindividual variation in the connectomes of patients with segmental callosal agenesis

In utero diffusion tensor imaging of the fetal brain: a reproducibility study

Our purpose was to evaluate the within-subject reproducibility of in utero diffusion tensor imaging (DTI) metrics and the visibility of major white matter structures. Images for 30 fetuses (20-33. postmenstrual weeks, normal neurodevelopment: 6 cases, cerebral pathology: 24 cases) were acquired on 1.5 T or 3.0 T MRI. DTI with 15 diffusion-weighting directions was repeated three times for each case, TR/TE: 2200/63 ms, voxel size: 1 ∗ 1 mm, slice thickness: 3-5 mm, b-factor: 700 s/mm(2). Reproducibility was evaluated from structure detectability, variability of DTI measures using the coefficient of variation (CV), image correlation and structural similarity across repeated scans for six selected structures. The effect of age, scanner type, presence of pathology was determined using Wilcoxon rank sum test. White matter structures were detectable in the following percentage of fetuses in at least two of the three repeated scans: corpus callosum genu 76%, splenium 64%, internal capsule, posterior limb 60%, brainstem fibers 40% and temporooccipital association pathways 60%. The mean CV of DTI metrics ranged between 3% and 14.6% and we measured higher reproducibility in fetuses with normal brain development. Head motion was negatively correlated with reproducibility, this effect was partially ameliorated by motion-correction algorithm using image registration. Structures on 3.0 T had higher variability both with- and without motion correction. Fetal DTI is reproducible for projection and commissural bundles during mid-gestation, however, in 16-30% of the cases, data were corrupted by artifacts, resulting in impaired detection of white matter structures. To achieve robust results for the quantitative analysis of diffusivity and anisotropy values, fetal-specific image processing is recommended and repeated DTI is needed to ensure the detectability of fiber pathways

Scoping Review of the Prenatal Diagnosis of Agenesis of the Corpus Callosum

Objective: To map and summarize the literature related to the prenatal diagnosis of agenesis of the corpus callosum (ACC) to inform nursing practice. Data Sources: We searched MEDLINE, CINAHL, PyscINFO, and Academic Search Complete with the use of strings of curated terms to cover the broad ACC nomenclature. Documents were published in English between 2009 and June 1, 2020. We also hand searched the reference lists of included documents. Study Selection: We screened 582 abstracts and retrieved the full texts of primary research articles, reviews, discussion papers, and peer-reviewed book chapters if the abstracts specifically mentioned ACC and the prenatal period. We excluded case reports, conference and poster abstracts, papers on broader anomalies, and animal studies. We reviewed 84 full-text documents and identified 61 for inclusion. Data Extraction: We charted the data through an iterative process under headings for location, article type, study design, participant age, ACC type, recruitment, method, tools/assessments, results, key recommendations, gestational age at diagnosis, termination of pregnancy rate, the definition of isolated ACC, and our notes of critique of the document. Data Synthesis: We constructed a narrative synthesis from thematically arranged data. In the included documents, ACC was diagnosed between 17 and 38 weeks gestation and was frequently described as heterogeneous because of different causes, presentations, and outcomes. Whether the ACC was isolated as the only anomaly or present with other anomalies was considered the key factor for prenatal counseling. However, the definition of isolated ACC was inconsistent. Conclusion: The inconsistent nomenclature and definitions of an isolated presentation of ACC increase the ambiguity in the prenatal diagnosis and must be considered when the outcome and diagnostic efficacy studies are interpreted. There is an absence of research on parents’ experiences of prenatal diagnoses of ACC to inform holistic nursing interventions and the provision of psychosocial support

Alien Hand, Restless Brain: Salience Network and Interhemispheric Connectivity Disruption Parallel Emergence and Extinction of Diagonistic Dyspraxia

International audienceDiagonistic dyspraxia (DD) is by far the most spectacular manifestation reported by sufferers of acute corpus callosum (CC) injury (so-called "split-brain"). In this form of alien hand syndrome, one hand acts at cross purposes with the other "against the patient's will". Although recent models view DD as a disorder of motor control, there is still little information regarding its neural underpinnings, due to widespread connectivity changes produced by CC insult, and the obstacle that non-volitional movements represent for task-based functional neuroimaging studies. Here, we studied patient AM, the first report of DD in patient with complete developmental CC agenesis. This unique case also offers the opportunity to study the resting-state connectomics of DD in the absence of diffuse changes subsequent to CC injury or surgery. AM developed DD following status epilepticus (SE) which resolved over a 2-year period. Whole brain functional connectivity (FC) was compared (Crawford-Howell [CH]) to 16 controls during the period of acute DD symptoms (Time 1) and after remission (Time 2). Whole brain graph theoretical models were also constructed and topological efficiency examined. At Time 1, disrupted FC was observed in inter-hemispheric and intra-hemispheric right edges, involving frontal superior and midline structures. Graph analysis indicated disruption of the efficiency of salience and right frontoparietal (FP) networks. At Time 2, after remission of diagnostic dyspraxia symptoms, FC and salience network changes had resolved. In sum, longitudinal analysis of connectivity in AM indicates that DD behaviors could result from disruption of systems that support the experience and control of volitional movements and the ability to generate appropriate behavioral responses to salient stimuli. This also raises the possibility that changes to large-scale functional architecture revealed by resting-state functional magnetic resonance imaging (fMRI) (rs-fMRI) may provide relevant information on the evolution of behavioral syndromes in addition to that provided by structural and task-based functional imaging

Brain plasticity following corpus callosum agenesis or loss: a review of the Probst bundles

The corpus callosum is the largest axonal tract in the human brain, connecting the left and right cortical hemipheres. This structure is affected in myriad human neurodevelopmental disorders, and can be entirely absent as a result of congenital or surgical causes. The age when callosal loss occurs, for example via surgical section in cases of refractory epilepsy, correlates with resulting brain morphology and neuropsychological outcomes, whereby an earlier loss generally produces relatively improved interhemispheric connectivity compared to a loss in adulthood (known as the “Sperry’s paradox”). However, the mechanisms behind these age-dependent differences remain unclear. Perhaps the best documented and most striking of the plastic changes that occur due to developmental, but not adult, callosal loss is the formation of large, bilateral, longitudinal ectopic tracts termed Probst bundles. Despite over 100 years of research into these ectopic tracts, which are the largest and best described stereotypical ectopic brain tracts in humans, much remains unclear about them. Here, we review the anatomy of the Probst bundles, along with evidence for their faciliatory or detrimental function, the required conditions for their formation, patterns of etiology, and mechanisms of development. We provide hypotheses for many of the remaining mysteries of the Probst bundles, including their possible relationship to preserved interhemispheric communication following corpus callosum absence. Future research into naturally occurring plastic tracts such as Probst bundles will help to inform the general rules governing axon plasticity and disorders of brain miswiring

Relationship between large-scale structural and functional brain connectivity in the human lifespan

The relationship between the anatomical structure of the brain and its functional organization is not straightforward and has not been elucidated yet, despite the growing interest this topic has received in the last decade. In particular, a new area of research has been defined in these years, called \u2019connectomics\u2019: this is the study of the different kinds of \u2019connections\u2019 existing among micro- and macro-areas of the brain, from structural connectivity \u2014 described by white matter fibre tracts physically linking cortical areas \u2014 to functional connectivity \u2014 defined as temporal correlation between electrical activity of different brain regions \u2014 to effective connectivity\u2014defining causal relationships between functional activity of different brain areas. Cortical areas of the brain physically linked by tracts of white matter fibres are known to exhibit a more coherent functional synchronization than areas which are not anatomically linked, but the absence of physical links between two areas does not imply a similar absence of functional correspondence. Development and ageing, but also structural modifications brought on by malformations or pathology, can modify the relation between structure and function. The aim of my PhD work has been to further investigate the existing relationship between structural and functional connectivity in the human brain at different ages of the human lifespan, in particular in healthy adults and both healthy and pathological neonates and children. These two \u2019categories\u2019 of subjects are very different in terms of the analysis techniques which can be applied for their study, due to the different characteristics of the data obtainable from them: in particular, while healthy adult data can be studied with the most advanced state-of-the-art methods, paediatric and neonatal subjects pose hard constraints to the acquisition methods applicable, and thus to the quality of the data which can be analysed. During this PhD I have studied this relation in healthy adult subjects by comparing structural connectivity from DWI data with functional connectivity from stereo-EEG recordings of epileptic patients implanted with intra-cerebral electrodes. I have then focused on the paediatric age, and in particular on the challenges posed by the paediatric clinical environment to the analysis of structural connectivity. In collaboration with the Neuroradiology Unit of the Giannina Gaslini Hospital in Genova, I have adapted and tested advanced DWI analysis methods for neonatal and paediatric data, which is commonly studied with less effective methods. We applied the same methods to the study of the effects of a specific brain malformation on the structural connectivity in 5 paediatric patients. While diffusion weighted imaging (DWI) is recognised as the best method to compute structural connectivity in the human brain, the most common methods for estimating functional connectivity data \u2014 functional MRI (fMRI) and electroencephalography (EEG) \u2014 suffer from different limitations: fMRI has good spatial resolution but low temporal resolution, while EEG has a better temporal resolution but the localisation of each signal\u2019s originating area is difficult and not always precise. Stereo-EEG (SEEG) combines strong spatial and temporal resolution with a high signal-to-noise ratio and allows to identify the source of each signal with precision, but is not used for studies on healthy subjects because of its invasiveness. Functional connectivity in children can be computed with either fMRI, EEG or SEEG, as in adult subjects. On the other hand, the study of structural connectivity in the paediatric age is met with obstacles posed by the specificity of this data, especially for the application of the advanced DWI analysis techniques commonly used in the adult age. Moreover, the clinical environment introduces even more constraints on the quality of the available data, both in children and adults, further limiting the possibility of applying advanced analysis methods for the investigation of connectivity in the paediatric age. Our results on adult subjects showed a positive correlation between structural and functional connectivity at different granularity levels, from global networks to community structures to single nodes, suggesting a correspondence between structural and functional organization which is maintained at different aggregation levels of brain units. In neonatal and paediatric subjects, we successfully adapted and applied the same advanced DWI analysis method used for the investigation in adults, obtaining white matter reconstructions more precise and anatomically plausible than with methods commonly used in paediatric clinical environments, and we were able to study the effects of a specific type of brain malformation on structural connectivity, explaining the different physical and functional manifestation of this malformation with respect to similar pathologies. This work further elucidates the relationship between structural and functional connectivity in the adult subject, and poses the basis for a corresponding work in the neonatal and paediatric subject in the clinical environment, allowing to study structural connectivity in the healthy and pathological child with clinical data

A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth.

Longitudinal characterization of early brain growth in-utero has been limited by a number of challenges in fetal imaging, the rapid change in size, shape and volume of the developing brain, and the consequent lack of suitable algorithms for fetal brain image analysis. There is a need for an improved digital brain atlas of the spatiotemporal maturation of the fetal brain extending over the key developmental periods. We have developed an algorithm for construction of an unbiased four-dimensional atlas of the developing fetal brain by integrating symmetric diffeomorphic deformable registration in space with kernel regression in age. We applied this new algorithm to construct a spatiotemporal atlas from MRI of 81 normal fetuses scanned between 19 and 39 weeks of gestation and labeled the structures of the developing brain. We evaluated the use of this atlas and additional individual fetal brain MRI atlases for completely automatic multi-atlas segmentation of fetal brain MRI. The atlas is available online as a reference for anatomy and for registration and segmentation, to aid in connectivity analysis, and for groupwise and longitudinal analysis of early brain growth

Development of functional organization within the sensorimotor network across the perinatal period

In the mature human brain, the neural processing related to different body parts is reflected in patterns of functional connectivity, which is strongest between functional homologs in opposite cortical hemispheres. To understand how this organization is first established, we investigated functional connectivity between limb regions in the sensorimotor cortex in 400 preterm and term infants aged across the equivalent period to the third trimester of gestation (32–45 weeks postmenstrual age). Masks were obtained from empirically derived functional responses in neonates from an independent data set. We demonstrate the early presence of a crude but spatially organized functional connectivity, that rapidly matures across the preterm period to achieve an adult-like configuration by the normal time of birth. Specifically, connectivity was strongest between homolog regions, followed by connectivity between adjacent regions (different limbs but same hemisphere) already in the preterm brain, and increased with age. These changes were specific to the sensorimotor network. Crucially, these trajectories were strongly dependent on age more than age of birth. This demonstrates that during the perinatal period the sensorimotor cortex undergoes preprogrammed changes determining the functional movement organization that are not altered by preterm birth in absence of brain injury