Faculty Bibliography

Models based in differential expansion of elastic material, axonal constraints, directed growth, or multi-phasic combinations have been proposed to explain brain folding. However, the cellular and physical processes present during folding have not been defined. We used the murine cerebellum to challenge folding models with in vivo data. We show that at folding initiation differential expansion is created by the outer layer of proliferating progenitors expanding faster than the core. However, the stiffness differential, compressive forces, and emergent thickness variations required by elastic material models are not present. We find that folding occurs without an obvious cellular pre-pattern, that the outer layer expansion is uniform and fluid-like, and that the cerebellum is under radial and circumferential constraints. Lastly, we find that a multi-phase model incorporating differential expansion of a fluid outer layer and radial and circumferential constraints approximates the in vivo shape evolution observed during initiation of cerebellar folding.

Objective: Granule cell precursors (GCPs) are a sonic hedgehog (SHH)- dependent progenitor population in the developing cerebellum and the main cell of origin for the SHH subgroup of medulloblastoma (MB). Unlike other subgroups of MB, SHH-MBs occur preferentially in the lateral cerebellum (hemispheres) and have four main driver mutations. We studied whether the timing or type of mutation affects tumor location and identified factors influencing SHH-MB progression.
Method(s): We analyzed the association between type of mutation and tumor location in 38 SHH-MB patient samples. To generate sporadic mouse models of SHH-MB, inducible recombinases were used to express a constitutive activate SMO receptor (SmoM2) or delete Ptch1 in only scattered GCPs. Tumor location, expression profiles and GCP behaviors were analyzed in the models.
Result(s): Our analysis of patient data indicates that adult tumors with SMO mutations form more specifically in the hemispheres than those with PTCH1 mutations. Using sporadic mouse models, we found that regardless of the number of GCPs mutated, timing or type of mutation, tumors developed almost exclusively in the hemispheres with SmoM2-mutants showing a stronger specificity. We further uncovered that GCPs in the hemispheres are more susceptible to high level SHH signaling compared to GCPs in the medial cerebellum (vermis), as more mutant cells in the hemisphere remain undifferentiated and show increased tumorigenicity when transplanted. We also identified location-specific gene expression profiles, and found that deletion of the genes most highly expressed in the hemispheres or vermis showed opposing effects on GCP differentiation.
Conclusion(s): We found that GCPs respond differentially to two driver mutations and a subset of GCPs is more susceptible to high level of SHH signaling as well as tumors formation. We redefined themain cell of origin by showing that GCPs are heterogeneous with molecularly distinct populations based on their location

Volumetric analysis of brain ventricle (BV) structure is a key tool in the study of central nervous system development in embryonic mice. High-frequency ultrasound (HFU) is the only non-invasive, real-time modality available for rapid volumetric imaging of embryos in utero. However, manual segmentation of the BV from HFU volumes is tedious, time-consuming, and requires specialized expertise. In this paper, we propose a novel deep learning based BV segmentation system for whole-body HFU images of mouse embryos. Our fully automated system consists of two modules: localization and segmentation. It first applies a volumetric convolutional neural network on a 3D sliding window over the entire volume to identify a 3D bounding box containing the entire BV. It then employs a fully convolutional network to segment the detected bounding box into BV and background. The system achieves a Dice Similarity Coefficient (DSC) of 0.8956 for BV segmentation on an unseen 111 HFU volume test set surpassing the previous state-of-the-art method (DSC of 0.7119) by a margin of 25%.

Sex differences exist in behaviors, disease and neuropsychiatric disorders. Sexual dimorphisms however, have yet to be studied across the whole brain and across a comprehensive time course of postnatal development. Here, we use manganese-enhanced MRI (MEMRI) to longitudinally image male and female C57BL/6J mice across 9 time points, beginning at postnatal day 3. We recapitulate findings on canonically dimorphic areas, demonstrating MEMRI's ability to study neuroanatomical sex differences. We discover, upon whole-brain volume correction, that neuroanatomical regions larger in males develop earlier than those larger in females. Groups of areas with shared sexually dimorphic developmental trajectories reflect behavioral and functional networks, and expression of genes involved with sex processes. Also, post-pubertal neuroanatomy is highly individualized, and individualization occurs earlier in males. Our results demonstrate the ability of MEMRI to reveal comprehensive developmental differences between male and female brains, which will improve our understanding of sex-specific predispositions to various neuropsychiatric disorders.

This paper presents a fully automatic segmentation system for whole-body high-frequency ultrasound (HFU) images of mouse embryos that can simultaneously segment the body contour and the brain ventricles (BVs). Our system first locates a region of interest (ROI), which covers the interior of the uterus, by sub-surface analysis. Then, it segments the ROI into BVs, the body, the amniotic fluid, and the uterine wall, using nested graph cut. Simultaneously multilevel thresholding is applied to the whole-body image to propose candidate BV components. These candidates are further truncated by the embryo mask (body+BVs) to refine the BV candidates. Finally, subsets of all candidate BVs are compared with pre-trained spring models describing valid BV structures, to identify true BV components. The system can segment the body accurately in most cases based on visual inspection, and achieves average Dice similarity coefficient of 0.8924 ± 0.043 for the BVs on 36 HFU image volumes.

The main cell of origin of the Sonic hedgehog (SHH) subgroup of medulloblastoma (MB) is granule cell precursors (GCPs), a SHH-dependent transient amplifying population in the developing cerebellum. SHH-MBs can be further subdivided based on molecular and clinical parameters, as well as location because SHH-MBs occur preferentially in the lateral cerebellum (hemispheres). Our analysis of adult patient data suggests that tumors with Smoothened (SMO) mutations form more specifically in the hemispheres than those with Patched 1 (PTCH1) mutations. Using sporadic mouse models of SHH-MB with the two mutations commonly seen in adult MB, constitutive activation ofSmo(SmoM2) or loss-of-Ptch1, we found that regardless of timing of induction or type of mutation, tumors developed primarily in the hemispheres, withSmoM2-mutants indeed showing a stronger specificity. We further uncovered that GCPs in the hemispheres are more susceptible to high-level SHH signaling compared with GCPs in the medial cerebellum (vermis), as moreSmoM2orPtch1-mutant hemisphere cells remain undifferentiated and show increased tumorigenicity when transplanted. Finally, we identified location-specific GCP gene-expression profiles, and found that deletion of the genes most highly expressed in the hemispheres (Nr2f2) or vermis (Engrailed1) showed opposing effects on GCP differentiation. Our studies thus provide insights into intrinsic differences within GCPs that impact on SHH-MB progression.

The early postnatal mouse cerebellum poses a unique challenge for in vivo developmental imaging studies, with rapidly changing cellular and morphological features that are difficult to detect and characterize with conventional approaches. High field (>= 7 Tesla) magnetic resonance imaging (MRI) can be utilized effectively for adult mouse neuroimaging, but conventional MRI contrast depends on differences in tissue properties that are largely absent in the developing brain. We have developed 4D (3D + time) Manganese (Mn)-Enhanced MRI (MEMRI) for in vivo longitudinal analysis of the developing mouse brain, from fetal stages through the critical neonatal stages of cerebellar growth and foliation. Non-toxic levels of paramagnetic Mn2+ ions are introduced by maternal intraperitoneal (IP) injection, and delivered to the pups noninvasively via lactation. Recent ultra-high resolution images demonstrate that Mnuptake and contrast enhancement in the cerebellum is localized to the Purkinje cell layer and the cerebellar nuclei (CN), allowing exquisite visualization and volumetric analyses of the developing lobules, and an effective in vivo phenotyping approach for mousemutants with defects in CN morphology and cerebellar foliation. The ability to visualize motor nuclei has also led to applications of MEMRI for in vivo mapping of functional cerebellar circuits. In addition to imaging cerebellum foliation and nuclei, MEMRI also provides a sensitive method to detect early preneoplastic lesions and to quantify tumor formation and progression in mouse models of medulloblastoma. These in vivo imaging methods are providing a quantitative framework for understanding the morphogenesis of the normal mouse cerebellum, and for analyzing mutant phenotypes and disease in a wide range of mouse models of cerebellar disorders

Genetically engineered mouse models are used extensively as models of human development and developmental diseases. Conventional histological approaches are static and two-dimensional, and do not provide a full understanding of the dynamic, spatiotemporal changes in developing mouse embryos. Magnetic resonance imaging (MRI) offers a noninvasive and longitudinal approach for three-dimensional in utero imaging of normal and mutant mouse embryos. In this chapter, we describe MRI approaches that have been developed for imaging the living embryonic mouse brain and vasculature. Details are provided on the animal preparation and setup, MRI equipment, acquisition and reconstruction methods that have been found to be most useful for in utero MRI, including examples of applications to fetal mouse neuroimaging.

Real-time imaging of the embryonic murine cardiovascular system is challenging due to the small size of the mouse embryo and rapid heart rate. High-frequency, linear-array ultrasound systems designed for small-animal imaging provide high-frame-rate and Doppler modes but are limited in regards to the field of view that can be imaged at fine-temporal and -spatial resolution. Here, a plane-wave imaging method was used to obtain high-speed image data from in utero mouse embryos and multi-angle, vector-flow algorithms were applied to the data to provide information on blood flow patterns in major organs. An 18-MHz linear array was used to acquire plane-wave data at absolute frame rates >/=10 kHz using a set of fixed transmission angles. After beamforming, vector-flow processing and image compounding, effective frame rates were on the order of 2 kHz. Data were acquired from the embryonic liver, heart and umbilical cord. Vector-flow results clearly revealed the complex nature of blood-flow patterns in the embryo with fine-temporal and -spatial resolution.