MRI-neuropathological correlations in type 1 lissencephaly

An integrated finite element method and machine learning algorithm for brain morphology prediction

The human brain development experiences a complex evolving cortical folding from a smooth surface to a convoluted ensemble of folds. Computational modeling of brain development has played an essential role in better understanding the process of cortical folding, but still leaves many questions to be answered. A major challenge faced by computational models is how to create massive brain developmental simulations with affordable computational sources to complement neuroimaging data and provide reliable predictions for brain folding. In this study, we leveraged the power of machine learning in data augmentation and prediction to develop a machine-learning-based finite element surrogate model to expedite brain computational simulations, predict brain folding morphology, and explore the underlying folding mechanism. To do so, massive finite element method (FEM) mechanical models were run to simulate brain development using the predefined brain patch growth models with adjustable surface curvature. Then, a GAN-based machine learning model was trained and validated with these produced computational data to predict brain folding morphology given a predefined initial configuration. The results indicate that the machine learning models can predict the complex morphology of folding patterns, including 3-hinge gyral folds. The close agreement between the folding patterns observed in FEM results and those predicted by machine learning models validate the feasibility of the proposed approach, offering a promising avenue to predict the brain development with given fetal brain configurations.

Cortex2vector: anatomical embedding of cortical folding patterns

Current brain mapping methods highly depend on the regularity, or commonality, of anatomical structure, by forcing the same atlas to be matched to different brains. As a result, individualized structural information can be overlooked. Recently, we conceptualized a new type of cortical folding pattern called the 3-hinge gyrus (3HG), which is defined as the conjunction of gyri coming from three directions. Many studies have confirmed that 3HGs are not only widely existing on different brains, but also possess both common and individual patterns. In this work, we put further effort, based on the identified 3HGs, to establish the correspondences of individual 3HGs. We developed a learning-based embedding framework to encode individual cortical folding patterns into a group of anatomically meaningful embedding vectors (cortex2vector). Each 3HG can be represented as a combination of these embedding vectors via a set of individual specific combining coefficients. In this way, the regularity of folding pattern is encoded into the embedding vectors, while the individual variations are preserved by the multi-hop combination coefficients. Results show that the learned embeddings can simultaneously encode the commonality and individuality of cortical folding patterns, as well as robustly infer the complicated many-to-many anatomical correspondences among different brains.

NAS-optimized topology-preserving transfer learning for differentiating cortical folding patterns

Increasing evidence suggests that cortical folding patterns of human cerebral cortex manifest overt structural and functional differences. However, for interpretability, few studies leverage advanced techniques (e.g., deep learning) to investigate the difference among cortical folds, resulting in more differences yet to be extensively explored. To this end, we proposed an effective topology-preserving transfer learning framework to differentiate cortical fMRI time series extracted from cortical folds. Our framework consists of three main parts: (1) Neural architecture search (NAS), which is used to devise a well-performing network structure based on an initialized hand-designed super-graph in an image dataset; (2) Topology-preserving transfer, which takes the model searched by NAS as the source network, keeping the topological connectivity in the network unchanged, while transforming all 2D operations including convolution and pooling into 1D, therefore resulting in a topology-preserving network, named TPNAS-Net; (3) Classification and correlation analysis, which involves using the TPNAS-Net to classify 1D cortical fMRI time series for each individual brain, and performing a group difference analysis between autism spectrum disorder (ASD) and healthy control (HC) and correlation analysis with clinical information (i.e., age). Extensive experiments on two ASD datasets obtain consistent results, demonstrating that the TPNAS-Net not only discriminates cortical folding patterns at high classification accuracy, but also captures subtle differences between ASD and HC (p-value = 0.042). In addition, we discover that there is a positive correlation between the classification accuracy and age in ASD (r = 0.39, p-value = 0.04). These findings together suggest that structural and functional differences in cortical folding patterns between ASD and HC may provide a potentially useful biomarker for the diagnosis of ASD.

An inverse modelling study on the local volume changes during early morphoelastic growth of the fetal human brain

We take a data-driven approach to deducing the local volume changes accompanying early development of the fetal human brain. Our approach uses fetal brain atlas MRI data for the geometric changes in representative cases. Using a nonlinear continuum mechanics model of morphoelastic growth, we invert the deformation obtained from MRI registration to arrive at a field for the growth deformation gradient tensor. Our field inversion uses a combination of direct and adjoint methods for computing gradients of the objective function while constraining the optimization by the physics of morphoelastic growth. We thus infer a growth deformation gradient field that obeys the laws of morphoelastic growth. The errors between the MRI data and the forward displacement solution driven by the inverted growth deformation gradient field are found to be smaller than the reference displacement by well over an order of magnitude, and can be driven even lower. The results thus reproduce the three-dimensional growth during the early development of the fetal brain with controllable error. Our findings confirm that early growth is dominated by in plane cortical expansion rather than thickness increase.

Definitions and classification of malformations of cortical development: practical guidelines

Malformations of cortical development are a group of rare disorders commonly manifesting with developmental delay, cerebral palsy or seizures. The neurological outcome is extremely variable depending on the type, extent and severity of the malformation and the involved genetic pathways of brain development. Neuroimaging plays an essential role in the diagnosis of these malformations, but several issues regarding malformations of cortical development definitions and classification remain unclear. The purpose of this consensus statement is to provide standardized malformations of cortical development terminology and classification for neuroradiological pattern interpretation. A committee of international experts in paediatric neuroradiology prepared systematic literature reviews and formulated neuroimaging recommendations in collaboration with geneticists, paediatric neurologists and pathologists during consensus meetings in the context of the European Network Neuro-MIG initiative on Brain Malformations (https://www.neuro-mig.org/). Malformations of cortical development neuroimaging features and practical recommendations are provided to aid both expert and non-expert radiologists and neurologists who may encounter patients with malformations of cortical development in their practice, with the aim of improving malformations of cortical development diagnosis and imaging interpretation worldwide.

A mechanical method of cerebral cortical folding development based on thermal expansion

Cortical folding malformations are associated with several severe neurological disorders, including epilepsy, schizophrenia and autism. However, the mechanism behind cerebral cortical folding development is not yet clear. In this paper, we propose a mechanical method based on thermal expansion to simulate the development of human cerebral cortical folding. The influences of stiffness ratio, growth rate ratio, and initial cortical plate thickness on cortical folding are discussed. The results of our thermal expansion model are consistent with previous studies, indicating that abnormal values of the aforementioned three factors could directly lead to cortical folding malformation in a generally fixed pattern.

Mechanism of Consistent Gyrus Formation: an Experimental and Computational Study

As a significant type of cerebral cortical convolution pattern, the gyrus is widely preserved across species. Although many hypotheses have been proposed to study the underlying mechanisms of gyrus formation, it is currently still far from clear which factors contribute to the regulation of consistent gyrus formation. In this paper, we employ a joint analysis scheme of experimental data and computational modeling to investigate the fundamental mechanism of gyrus formation. Experimental data on mature human brains and fetal brains show that thicker cortices are consistently found in gyral regions and gyral cortices have higher growth rates. We hypothesize that gyral convolution patterns might stem from heterogeneous regional growth in the cortex. Our computational simulations show that gyral convex patterns may occur in locations where the cortical plate grows faster than the cortex of the brain. Global differential growth can only produce a random gyrification pattern, but it cannot guarantee gyrus formation at certain locations. Based on extensive computational modeling and simulations, it is suggested that a special area in the cerebral cortex with a relatively faster growth speed could consistently engender gyri.

Commonly preserved and species-specific gyral folding patterns across primate brains

Cortical folding pattern analysis is very important to understand brain organization and development. Since previous studies mostly focus on human brain cortex, the regularity and variability of cortical folding patterns across primate brains (macaques, chimpanzees and human) remain largely unknown. This paper presents a novel computational framework to identify common or unique gyral folding patterns in macaque, chimpanzee and human brains using magnetic resonance imaging (MRI) data. We quantitatively characterize gyral folding patterns via hinge numbers with cortical surfaces constructed from MRI data, and identify 6 common three-hinge gyral folds that exhibit consistent anatomical locations across these three species as well as 2 unique three hinges in macaque, 6 ones in chimpanzee and 14 ones in human. A novel morphology descriptor is then applied to classify three-hinge gyral folds, and the increasing complexity is identified among the species analyzed. This study may provide novel insights into the regularity and variability of the cerebral cortex from developmental perspective and may potentially facilitate novel neuroimage analyses such as cortical parcellation with correspondences across species in the future.

The role of mechanics during brain development

Convolutions are a classical hallmark of most mammalian brains. Brain surface morphology is often associated with intelligence and closely correlated to neurological dysfunction. Yet, we know surprisingly little about the underlying mechanisms of cortical folding. Here we identify the role of the key anatomic players during the folding process: cortical thickness, stiffness, and growth. To establish estimates for the critical time, pressure, and the wavelength at the onset of folding, we derive an analytical model using the Föppl-von-Kármán theory. Analytical modeling provides a quick first insight into the critical conditions at the onset of folding, yet it fails to predict the evolution of complex instability patterns in the post-critical regime. To predict realistic surface morphologies, we establish a computational model using the continuum theory of finite growth. Computational modeling not only confirms our analytical estimates, but is also capable of predicting the formation of complex surface morphologies with asymmetric patterns and secondary folds. Taken together, our analytical and computational models explain why larger mammalian brains tend to be more convoluted than smaller brains. Both models provide mechanistic interpretations of the classical malformations of lissencephaly and polymicrogyria. Understanding the process of cortical folding in the mammalian brain has direct implications on the diagnostics of neurological disorders including severe retardation, epilepsy, schizophrenia, and autism.

A mechanical model predicts morphological abnormalities in the developing human brain

The developing human brain remains one of the few unsolved mysteries of science. Advancements in developmental biology, neuroscience, and medical imaging have brought us closer than ever to understand brain development in health and disease. However, the precise role of mechanics throughout this process remains underestimated and poorly understood. Here we show that mechanical stretch plays a crucial role in brain development. Using the nonlinear field theories of mechanics supplemented by the theory of finite growth, we model the human brain as a living system with a morphogenetically growing outer surface and a stretch-driven growing inner core. This approach seamlessly integrates the two popular but competing hypotheses for cortical folding: axonal tension and differential growth. We calibrate our model using magnetic resonance images from very preterm neonates. Our model predicts that deviations in cortical growth and thickness induce morphological abnormalities. Using the gyrification index, the ratio between the total and exposed surface area, we demonstrate that these abnormalities agree with the classical pathologies of lissencephaly and polymicrogyria. Understanding the mechanisms of cortical folding in the developing human brain has direct implications in the diagnostics and treatment of neurological disorders, including epilepsy, schizophrenia, and autism.

Sonographic assessment of normal and abnormal patterns of fetal cerebral lamination

OBJECTIVES

Prenatal development of the brain is characterized by gestational age-specific changes in the laminar structure of the brain parenchyma before 30 gestational weeks. Cerebral lamination patterns of normal fetal brain development have been described histologically, by postmortem in-vitro magnetic resonance imaging (MRI) and by in-vivo fetal MRI. The purpose of this study was to evaluate the sonographic appearance of laminar organization of the cerebral wall in normal and abnormal brain development.

METHODS

This was a retrospective study of ultrasound findings in 92 normal fetuses and 68 fetuses with abnormal cerebral lamination patterns for gestational age, at 17-38 weeks' gestation. We investigated the visibility of the subplate zone relative to the intermediate zone and correlated characteristic sonographic findings of cerebral lamination with gestational age in order to evaluate transient structures.

RESULTS

In the normal cohort, the subplate zone-intermediate zone interface was identified as early as 17 weeks, and in all 57 fetuses examined up to 28 weeks. In all of these fetuses, the subplate zone appeared anechoic and the intermediate zone appeared homogeneously more echogenic than did the subplate zone. In the 22 fetuses between 28 and 34 weeks, there was a transition period when lamination disappeared in a variable fashion. The subplate zone-intermediate zone interface was not identified in any fetus after 34 weeks (n=13). There were three patterns of abnormal cerebral lamination: (1) no normal laminar pattern before 28 weeks (n=32), in association with severe ventriculomegaly, diffuse ischemia, microcephaly, teratogen exposure or lissencephaly; (2) focal disruption of lamination before 28 weeks (n=24), associated with hemorrhage, porencephaly, stroke, migrational abnormalities, thanatophoric dysplasia, meningomyelocele or encephalocele; (3) increased prominence and echogenicity of the intermediate zone before 28 weeks and/or persistence of a laminar pattern beyond 33 weeks (n=10), associated with Type 1 lissencephaly or CMV infection. There was a mixed focal/diffuse pattern in two fetuses. In CMV infection, the earliest indication of the infection was focal heterogeneity and increased echogenicity of the intermediate zone, which predated the development of microcephaly, ventriculomegaly and intracranial calcification.

CONCLUSIONS

The fetal subplate and intermediate zones can be demonstrated reliably on routine sonography before 28 weeks and disappear after 34 weeks. These findings represent normal gestational age-dependent transient laminar patterns of cerebral development and are consistent with histological studies. Abnormal fetal cerebral lamination patterns for gestational age are also visible on sonography, and may indicate abnormal brain development.

The evolving MR imaging appearance of lissencephaly: a case report

MR imaging of a patient with epilepsy and psychomotor retardation at 5 months revealed parieto-occipital pachygyria with almost normal cortical appearance and thickness in the frontal region; this appearance evolved into diffuse pachygyria at 7 years. The change of the MR imaging findings may have resulted from myelination in the intracortical and subcortical fibers. It is important for clinicians to be aware of the longitudinal changes of the cerebral cortex in lissencephaly.

Ocular findings in lissencephaly

PURPOSE

To report our retrospective study of 20 cases with lissencephaly and describe ocular and visual abnormalities associated with this disorder.

METHODS

Patients with lissencephaly were identified and classified into classic (type I) or cobblestone (type 2) lissencephaly on the basis of a review of clinical records and neuroimaging studies. Only patients examined by an ophthalmologist were included in the study.

RESULTS

Only 1 patient had a normal ocular examination. Ocular abnormalities included optic nerve hypoplasia and atrophy, retinal dysplasia, retinal nonattachment, macular hypoplasia, anterior segment malformation, and strabismus.

CONCLUSIONS

Ocular abnormalities in classic (type 1) lissencephaly are less severe. Central, steady, and maintained fixation may be present despite the presence of optic nerve hypoplasia, optic atrophy, macular hypoplasia, strabismus, or refractive errors. Retinal and anterior segment abnormalities were observed only in cobblestone (type 2) lissencephaly. These patients often have severe visual impairment because of retinal or cortical disease.

Magnetic resonance imaging features of lissencephaly in 2 Lhasa Apsos

Two Lhasa Apsos were diagnosed with lissencephaly based on MR imaging and clinical findings. Histologic confirmation of the diagnosis was obtained in one dog. The MR imaging appearance of the brain in 2 Lhasa Apsos with lissencephaly was of a smooth cerebral surface and a thick neocortex with an absence of the corona radiata. This correlated very well with the histopathologic findings in the dog. Our findings, together with the histopathologic features reported previously, are most consistent with Lhasa Apsos having the canine equivalent of human classical lissencephaly. MR is the imaging modality of choice for antemortem diagnosis of canine lissencephaly.

Reproductive status in long-term bone marrow transplant survivors receiving busulfan-cyclophosphamide (120 mg/kg)

There are few published data on the recovery of fertility after 'little' Bu-Cy (busulfan 16 mg/kg, cyclophosphamide 120 mg/kg) conditioning for BMT. To address this, we identified 19 females aged less than 40 years at transplant and 47 males from a single centre who were alive a minimum of 2 years after BMT with little Bu-Cy as conditioning and who were evaluable for testing. FSH, LH, testosterone and inhibin B levels were measured in males. Twenty-six also had semen analysis, a median of 5 years post transplant; 21 had detectable sperm, with 11 having counts >20 x 10(6)/ml. There was an association between prolonged chronic graft-versus-host disease and low sperm counts. FSH and inhibin B levels correlated with sperm counts but not to the extent that they could reliably predict counts in individual patients. An additional six of seven males attempting to father children did so, a median of 3.2 years post transplant. Low testosterone levels were noted in 12% of males, most of whom had symptoms consistent with androgen deficiency. FSH, LH and oestradiol levels in the absence of hormone replacement therapy were measured in females; all remained amenorrheic with endocrine evidence of ovarian failure. These results have implications for fertility counselling and hormone replacement therapy both pre- and post BMT.

[What is new in pediatric neurology?]

Some significant advances in the field of pediatric neurology are reviewed. For many constitutional disorders, concepts and diagnostic procedures have progressed from various genetic techniques or from protein labeling in situ. Many neurodegenerative disorders, some poorly-defined metabolic diseases, and several syndromes associating mental retardation with neurologic or extraneurologic malformations have been characterized. In addition, for many disorders viewed as 'poorly specific' (mental retardation, epilepsy, migraine), familial forms have permitted us to define the first genes involved. In 'acquired' disorders, new data come from clinical trials (antiepileptic, anti-inflammatory drugs) rather than definite conceptual advances. Finally, clinics and biology are no longer the only approaches to brain functions, and clinical neurophysiology could encounter a second wind thanks to the techniques of functional imaging, especially in the fields of developmental neuropsychology.