The ANTsX Ecosystem for Mapping the Mouse Brain.

Precision mapping techniques coupled with high resolution image acquisition of the mouse brain permit the study of the spatial organization of gene expression and their mutual interaction for a comprehensive view of salient structural/functional relationships. Such research is facilitated by standardized anatomical coordinate systems, such as the well-known Allen Common Coordinate Framework (AllenCCFv3), and the ability to spatially map to such standardized spaces. The Advanced Normalization Tools Ecosystem is a comprehensive open-source software toolkit for generalized quantitative imaging with applicability to multiple organ systems, modalities, and animal species. Herein, we illustrate the utility of ANTsX for generating precision spatial mappings of the mouse brain and potential subsequent quantitation. We describe ANTsX-based workflows for mapping domain-specific image data to AllenCCFv3 accounting for common artefacts and other confounds. Novel contributions include ANTsX functionality for velocity flow-based mapping spanning the spatiotemporal domain of a longitudinal trajectory which we apply to the Developmental Common Coordinate Framework. Additionally, we present an automated structural morphological pipeline for determining volumetric and cortical thickness measurements analogous to the well-utilized ANTsX pipeline for human neuroanatomical structural morphology which illustrates a general open-source framework for tailored brain parcellations.

Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections.

This paper explicates a solution to building correspondences between molecular-scale transcriptomics and tissue-scale atlases. This problem arises in atlas construction and cross-specimen/technology alignment where specimens per emerging technology remain sparse and conventional image representations cannot efficiently model the high dimensions from subcellular detection of thousands of genes. We address these challenges by representing spatial transcriptomics data as generalized functions encoding position and high-dimensional feature (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling regions as homogeneous random fields with unknown transcriptomic feature distribution. We solve simultaneously for the minimizing geodesic diffeomorphism of coordinates through LDDMM and for these latent feature densities. We map tissue-scale mouse brain atlases to gene-based and cell-based transcriptomics data from MERFISH and BARseq technologies and to histopathology and cross-species atlases to illustrate integration of diverse molecular and cellular datasets into a single coordinate system as a means of comparison and further atlas construction.

NUT Expression Is of Diagnostic Utility in the Distinction of Digital Papillary Carcinoma From Poroid Hidradenoma.

ABSTRACT: The distinction between digital papillary adenocarcinoma (DPAC) and benign cutaneous adnexal tumors is clinically important and can be challenging. Poroid hidradenoma frequently occurs at acral sites and can show a number of histological features, which overlap with digital papillary adenocarcinoma. Recent work has shown that YAP1-NUTM1 fusions are frequent in poroid hidradenoma and are associated with nuclear protein in testis (NUT) expression by immunohistochemistry. We evaluated the expression of NUT-1 by immunohistochemistry in 4 cases of DPAC and 4 cases of poroid hidradenoma. Three of 4 cases of poroid hidradenoma showed strong NUT-1 expression, with no staining in any of the cases of DPAC. These results suggest that NUT-1 immunohistochemistry may be a useful additional tool in evaluating this differential diagnosis.

epDevAtlas: Mapping GABAergic cells and microglia in postnatal mouse brains.

During development, brain regions follow encoded growth trajectories. Compared to classical brain growth charts, high-definition growth charts could quantify regional volumetric growth and constituent cell types, improving our understanding of typical and pathological brain development. Here, we create high-resolution 3D atlases of the early postnatal mouse brain, using Allen CCFv3 anatomical labels, at postnatal days (P) 4, 6, 8, 10, 12, and 14, and determine the volumetric growth of different brain regions. We utilize 11 different cell type-specific transgenic animals to validate and refine anatomical labels. Moreover, we reveal region-specific density changes in γ-aminobutyric acid-producing (GABAergic), cortical layer-specific cell types, and microglia as key players in shaping early postnatal brain development. We find contrasting changes in GABAergic neuronal densities between cortical and striatal areas, stabilizing at P12. Moreover, somatostatin-expressing cortical interneurons undergo regionally distinct density reductions, while vasoactive intestinal peptide-expressing interneurons show no significant changes. Remarkably, microglia transition from high density in white matter tracks to gray matter at P10, and show selective density increases in sensory processing areas that correlate with the emergence of individual sensory modalities. Lastly, we create an open-access web-visualization (https://kimlab.io/brain-map/epDevAtlas) for cell-type growth charts and developmental atlases for all postnatal time points.

Online conversion of reconstructed neural morphologies into standardized SWC format.

Digital reconstructions provide an accurate and reliable way to store, share, model, quantify, and analyze neural morphology. Continuous advances in cellular labeling, tissue processing, microscopic imaging, and automated tracing catalyzed a proliferation of software applications to reconstruct neural morphology. These computer programs typically encode the data in custom file formats. The resulting format heterogeneity severely hampers the interoperability and reusability of these valuable data. Among these many alternatives, the SWC file format has emerged as a popular community choice, coalescing a rich ecosystem of related neuroinformatics resources for tracing, visualization, analysis, and simulation. This report presents a standardized specification of the SWC file format. In addition, we introduce xyz2swc, a free online service that converts all 26 reconstruction formats (and 72 variations) described in the scientific literature into the SWC standard. The xyz2swc service is available open source through a user-friendly browser interface ( https://neuromorpho.org/xyz2swc/ui/ ) and an Application Programming Interface (API).

Developmental Mouse Brain Common Coordinate Framework.

3D standard reference brains serve as key resources to understand the spatial organization of the brain and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of standard 3D reference atlases for developing mouse brains has hindered advancement of our understanding of brain development. Here, we present a multimodal 3D developmental common coordinate framework (DevCCF) spanning mouse embryonic day (E) 11.5, E13.5, E15.5, E18.5, and postnatal day (P) 4, P14, and P56 with anatomical segmentations defined by a developmental ontology. At each age, the DevCCF features undistorted morphologically averaged atlas templates created from Magnetic Resonance Imaging and co-registered high-resolution templates from light sheet fluorescence microscopy. Expert-curated 3D anatomical segmentations at each age adhere to an updated prosomeric model and can be explored via an interactive 3D web-visualizer. As a use case, we employed the DevCCF to unveil the emergence of GABAergic neurons in embryonic brains. Moreover, we integrated the Allen CCFv3 into the P56 template with stereotaxic coordinates and mapped spatial transcriptome cell-type data with the developmental ontology. In summary, the DevCCF is an openly accessible resource that can be used for large-scale data integration to gain a comprehensive understanding of brain development.

A guide to the BRAIN Initiative Cell Census Network data ecosystem.

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

A Universal Method for Crossing Molecular and Atlas Modalities using Simplex-Based Image Varifolds and Quadratic Programming.

This paper explicates a solution to the problem of building correspondences between molecular-scale transcriptomics and tissue-scale atlases. The central model represents spatial transcriptomics as generalized functions encoding molecular position and high-dimensional transcriptomic-based (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling each atlas compartment as a homogeneous random field with unknown transcriptomic feature distribution. The algorithm presented solves simultaneously for the minimizing geodesic diffeomorphism of coordinates and latent atlas transcriptomic feature fractions by alternating LDDMM optimization for coordinate transformations and quadratic programming for the latent transcriptomic variables. We demonstrate the universality of the algorithm in mapping tissue atlases to gene-based and cell-based MERFISH datasets as well as to other tissue scale atlases. The joint estimation of diffeomorphisms and latent feature distributions allows integration of diverse molecular and cellular datasets into a single coordinate system and creates an avenue of comparison amongst atlas ontologies for continued future development.

A whole-brain monosynaptic input connectome to neuron classes in mouse visual cortex.

Identification of structural connections between neurons is a prerequisite to understanding brain function. Here we developed a pipeline to systematically map brain-wide monosynaptic input connections to genetically defined neuronal populations using an optimized rabies tracing system. We used mouse visual cortex as the exemplar system and revealed quantitative target-specific, layer-specific and cell-class-specific differences in its presynaptic connectomes. The retrograde connectivity indicates the presence of ventral and dorsal visual streams and further reveals topographically organized and continuously varying subnetworks mediated by different higher visual areas. The visual cortex hierarchy can be derived from intracortical feedforward and feedback pathways mediated by upper-layer and lower-layer input neurons. We also identify a new role for layer 6 neurons in mediating reciprocal interhemispheric connections. This study expands our knowledge of the visual system connectomes and demonstrates that the pipeline can be scaled up to dissect connectivity of different cell populations across the mouse brain.

The Neurodata Without Borders ecosystem for neurophysiological data science.

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB's impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

The brain is an immensely complex organ which regulates many of the behaviors that animals need to survive. To understand how the brain works, scientists monitor and record brain activity under different conditions using a variety of experimental techniques. These neurophysiological studies are often conducted on multiple types of cells in the brain as well as a variety of species, ranging from mice to flies, or even frogs and worms. Such a range of approaches provides us with highly informative, complementary 'views' of the brain. However, to form a complete, coherent picture of how the brain works, scientists need to be able to integrate all the data from these different experiments. For this to happen effectively, neurophysiology data need to meet certain criteria: namely, they must be findable, accessible, interoperable, and re-usable (or FAIR for short). However, the sheer diversity of neurophysiology experiments impedes the 'FAIR'-ness of the information obtained from them. To overcome this problem, researchers need a standardized way to communicate their experiments and share their results ­ in other words, a 'standard language' to describe neurophysiology data. Rübel, Tritt, Ly, Dichter, Ghosh et al. therefore set out to create such a language that was not only FAIR, but could also co-evolve with neurophysiology research. First, they produced a computer software program (called Neurodata Without Borders, or NWB for short) which generated and defined the different components of the new standard language. Then, other tools for data management were created to expand the NWB platform using the standardized language. This included data analysis and visualization methods, as well as an 'archive' to store and access data. Testing the new language and associated tools showed that they indeed allowed researchers to access, analyze, and share information from many different types of experiments, in organisms ranging from flies to humans. The NWB software is open-source, meaning that anyone can obtain a copy and make changes to it. Thus, NWB and its associated resources provide the basis for a collaborative, community-based system for sharing neurophysiology data. Rübel et al. hope that NWB will inspire similar developments across other fields of biology that share similar levels of complexity with neurophysiology.

A simulated comparison of lung tumor target verification using stereoscopic tomosynthesis or radiography.

PURPOSE: Mobile lung tumors are increasingly being treated with ablative radiotherapy, for which precise motion management is essential. In-room stereoscopic radiography systems are able to guide ablative radiotherapy for stationary cranial lesions but not optimally for lung tumors unless fiducial markers are inserted. We propose augmenting stereoscopic radiographic systems with multiple small x-ray sources to provide the capability of imaging with stereoscopic, single frame tomosynthesis. METHODS: In single frame tomosynthesis, nine x-ray sources are placed in a 3 × 3 configuration and energized simultaneously. The beams from these sources are collimated so that they converge on the tumor and then diverge to illuminate nine non-overlapping sectors on the detector. These nine sector images are averaged together and filtered to create the tomosynthesis effect. Single frame tomosynthesis is intended to be an alternative imaging mode for existing stereoscopic systems with a field of view that is three times smaller and a temporal resolution equal to the frame rate of the detector. We simulated stereoscopic tomosynthesis and radiography using Monte Carlo techniques on 60 patients with early-stage lung cancer from the NSCLC-Radiomics dataset. Two board-certified radiation oncologists reviewed these simulated images and rated them on a 4-point scale (1: tumor not visible; 2: tumor visible but inadequate for motion management; 3: tumor visible and adequate for motion management; 4: tumor visibility excellent). Each tumor was independently presented four times (two viewing angles from radiography and two viewing angles from tomosynthesis) in a blinded fashion over two reading sessions. RESULTS: The fraction of tumors that were rated as adequate or excellent for motion management (scores 3 or 4) from at least one viewing angle was 53% using radiography and 90% using tomosynthesis. From both viewing angles, the corresponding fractions were 7% for radiography and 48% for tomosynthesis. Readers agreed exactly on 62% of images and within 1 point on 98% of images. The acquisition technique was estimated to be 75 mAs at 120 kVp per treatment fraction assuming one verification image per breath, approximately one order of magnitude less than a standard dose cone beam CT. CONCLUSIONS: Stereoscopic tomosynthesis may provide a noninvasive, low dose, intrafraction motion verification technique for lung tumors treated by ablative radiotherapy. The system architecture is compatible with real-time video capture at 30 frames per second. Simulations suggest that most, but not all, lung tumors can be adequately visualized from at least one viewing angle.

Cellular resolution anatomical and molecular atlases for prenatal human brains.

Increasing interest in studies of prenatal human brain development, particularly using new single-cell genomics and anatomical technologies to create cell atlases, creates a strong need for accurate and detailed anatomical reference atlases. In this study, we present two cellular-resolution digital anatomical atlases for prenatal human brain at postconceptional weeks (PCW) 15 and 21. Both atlases were annotated on sequential Nissl-stained sections covering brain-wide structures on the basis of combined analysis of cytoarchitecture, acetylcholinesterase staining, and an extensive marker gene expression dataset. This high information content dataset allowed reliable and accurate demarcation of developing cortical and subcortical structures and their subdivisions. Furthermore, using the anatomical atlases as a guide, spatial expression of 37 and 5 genes from the brains, respectively, at PCW 15 and 21 was annotated, illustrating reliable marker genes for many developing brain structures. Finally, the present study uncovered several novel developmental features, such as the lack of an outer subventricular zone in the hippocampal formation and entorhinal cortex, and the apparent extension of both cortical (excitatory) and subcortical (inhibitory) progenitors into the prenatal olfactory bulb. These comprehensive atlases provide useful tools for visualization, segmentation, targeting, imaging, and interpretation of brain structures of prenatal human brain, and for guiding and interpreting the next generation of cell census and connectome studies.

Morphological diversity of single neurons in molecularly defined cell types.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.

Highlights from the Era of Open Source Web-Based Tools.

High digital connectivity and a focus on reproducibility are contributing to an open science revolution in neuroscience. Repositories and platforms have emerged across the whole spectrum of subdisciplines, paving the way for a paradigm shift in the way we share, analyze, and reuse vast amounts of data collected across many laboratories. Here, we describe how open access web-based tools are changing the landscape and culture of neuroscience, highlighting six free resources that span subdisciplines from behavior to whole-brain mapping, circuits, neurons, and gene variants.

Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network.

The evolutionarily conserved default mode network (DMN) is a distributed set of brain regions coactivated during resting states that is vulnerable to brain disorders. How disease affects the DMN is unknown, but detailed anatomical descriptions could provide clues. Mice offer an opportunity to investigate structural connectivity of the DMN across spatial scales with cell-type resolution. We co-registered maps from functional magnetic resonance imaging and axonal tracing experiments into the 3D Allen mouse brain reference atlas. We find that the mouse DMN consists of preferentially interconnected cortical regions. As a population, DMN layer 2/3 (L2/3) neurons project almost exclusively to other DMN regions, whereas L5 neurons project in and out of the DMN. In the retrosplenial cortex, a core DMN region, we identify two L5 projection types differentiated by in- or out-DMN targets, laminar position, and gene expression. These results provide a multi-scale description of the anatomical correlates of the mouse DMN.

The Allen Mouse Brain Common Coordinate Framework: A 3D Reference Atlas.

Recent large-scale collaborations are generating major surveys of cell types and connections in the mouse brain, collecting large amounts of data across modalities, spatial scales, and brain areas. Successful integration of these data requires a standard 3D reference atlas. Here, we present the Allen Mouse Brain Common Coordinate Framework (CCFv3) as such a resource. We constructed an average template brain at 10 µm voxel resolution by interpolating high resolution in-plane serial two-photon tomography images with 100 µm z-sampling from 1,675 young adult C57BL/6J mice. Then, using multimodal reference data, we parcellated the entire brain directly in 3D, labeling every voxel with a brain structure spanning 43 isocortical areas and their layers, 329 subcortical gray matter structures, 81 fiber tracts, and 8 ventricular structures. CCFv3 can be used to analyze, visualize, and integrate multimodal and multiscale datasets in 3D and is openly accessible (https://atlas.brain-map.org/).

Traumatic dental injuries presenting to a paediatric emergency department in a tertiary children's hospital, Adelaide, Australia.

BACKGROUND/AIM: There is a scarcity of data regarding paediatric traumatic dental injuries (TDI) in tertiary teaching hospitals. Therefore, the aim of this study was to review the TDI presenting to the Women's and Children's Hospital in Adelaide (Australia) on an emergency basis and to identify the characteristics of the presenting patient cohort, their accident, injuries and management. METHODS: Medical health records of 337 paediatric patients attending the Paediatric Emergency Department (PED) for the management of TDI over 18 months were prospectively reviewed. RESULTS: TDI were more frequent in children under 5 years of age (56.1%) with a predominance of injuries sustained by males (63.8%). The accident characteristics included weekend occurrence (35.6%), the most common aetiology was falls (64.4%) and many incidents occurred at home (48.5%). Overall, 654 teeth were injured with the majority affecting deciduous teeth (58.4%) and the maxillary central incisors (69.9%). The most frequent injury was lateral luxation (27.5%). The majority of patients were referred to the Paediatric Dentistry Department (60.8%). However, almost half of presenting patients did not require further management locally and were subsequently discharged to their dental practitioners (39.2%). Most patients receiving treatment were managed under general anaesthetic (36.9%), and there was often a delay of 3-12 hours before treatment commenced (49.1%). Similarly, more severe injuries in the permanent dentition (avulsion, extrusion, root fracture, intrusion, alveolar fracture) were more frequently managed between 3 and 12 hours following the accident. CONCLUSION: The patient, accident, injury and management characteristics are comparable to what has previously been reported in other studies in paediatric populations. Injuries affecting the permanent dentition are more likely to be managed within 3 and 12 hours in an outpatient setting, whereas injuries affecting the deciduous dentition had a delay in management between 12 and 24 hours under general anaesthetic.

Hierarchical organization of cortical and thalamic connectivity.

The mammalian cortex is a laminar structure containing many areas and cell types that are densely interconnected in complex ways, and for which generalizable principles of organization remain mostly unknown. Here we describe a major expansion of the Allen Mouse Brain Connectivity Atlas resource1, involving around a thousand new tracer experiments in the cortex and its main satellite structure, the thalamus. We used Cre driver lines (mice expressing Cre recombinase) to comprehensively and selectively label brain-wide connections by layer and class of projection neuron. Through observations of axon termination patterns, we have derived a set of generalized anatomical rules to describe corticocortical, thalamocortical and corticothalamic projections. We have built a model to assign connection patterns between areas as either feedforward or feedback, and generated testable predictions of hierarchical positions for individual cortical and thalamic areas and for cortical network modules. Our results show that cell-class-specific connections are organized in a shallow hierarchy within the mouse corticothalamic network.

Automatic navigation system for the mouse brain.

Identification and delineation of brain regions in histologic mouse brain sections is especially pivotal for many neurogenomics, transcriptomics, proteomics, and connectomics studies, yet this process is prone to observer error and bias. Here we present a novel brain navigation system, named NeuroInfo, whose general principle is similar to that of a global positioning system (GPS) in a car. NeuroInfo automatically navigates an investigator through the complex microscopic anatomy of histologic sections of mouse brains (thereafter: "experimental mouse brain sections"). This is achieved by automatically registering a digital image of an experimental mouse brain section with a three-dimensional (3D) digital mouse brain atlas that is essentially based on the third version of the Allen Mouse Brain Common Coordinate Framework (CCF v3), retrieving graphical region delineations and annotations from the 3D digital mouse brain atlas, and superimposing this information onto the digital image of the experimental mouse brain section on a computer screen. By doing so, NeuroInfo helps in solving the long-standing problem faced by researchers investigating experimental mouse brain sections under a light microscope-that of correctly identifying the distinct brain regions contained within the experimental mouse brain sections. Specifically, NeuroInfo provides an intuitive, readily-available computer microscopy tool to enhance researchers' ability to correctly identify specific brain regions in experimental mouse brain sections. Extensive validation studies of NeuroInfo demonstrated that this novel technology performs remarkably well in accurately delineating regions that are large and/or located in the dorsal parts of mouse brains, independent on whether the sections were imaged with fluorescence or bright-field microscopy. This novel navigation system provides a highly efficient way for registering a digital image of an experimental mouse brain section with the 3D digital mouse brain atlas in a minute and accurate delineation of the image in real-time.

Dose Sculpting Intensity Modulated Radiation Therapy for Vertebral Body Sparing in Children With Neuroblastoma.

PURPOSE: To assess the effect of dose sculpting intensity modulated radiation therapy on vertebral body growth in children with neuroblastoma. METHODS AND MATERIALS: From 2000 to 2011, 88 children with neuroblastoma underwent radiation at the authors' institution. Children with paravertebral tumors with at least 3 years of evaluable posttreatment imaging were included, and children who underwent spine reirradiation before follow-up were excluded. If vertebral bodies could not be spared, these "target" vertebral bodies were treated to at least 18 Gy. Thoracic and lumbar vertebral bodies were assessed separately. Dose data for target, spared, and internal control vertebral bodies were extracted. Multivariate generalized estimating equation modeling was used to assess the effect of dose and other clinical factors on vertebral body growth. RESULTS: A total of 34 patients (20 boys, 14 girls) met study criteria. Median age at start of radiation was 4.3 years; all but 1 had prior high-dose chemotherapy with stem cell rescue. Mean growth rates of target, spared, and control vertebral bodies (cm/body/y) were, respectively, 0.027, 0.032, and 0.044 in thoracic spine and 0.033, 0.055, and 0.083 in lumbar spine. On multivariate generalized estimating equation analysis, higher dose, older treatment age, male gender, and thoracic spine location were significantly associated with decreased vertebral body growth (P<.0001, P<.0001, P=.007, and P<.0001, respectively). Dose and spine location were significant in a 3-way interaction model (P<.0001). CONCLUSIONS: Vertebral bodies spared by intensity modulated radiation therapy grew faster than target vertebrae. Regardless of intent to spare or target, multivariate analysis confirms that lower dose results in significantly increased growth rate. This technique should be investigated prospectively.