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.

Formin 3 directs dendritic architecture via microtubule regulation and is required for somatosensory nociceptive behavior.

Dendrite shape impacts functional connectivity and is mediated by organization and dynamics of cytoskeletal fibers. Identifying the molecular factors that regulate dendritic cytoskeletal architecture is therefore important in understanding the mechanistic links between cytoskeletal organization and neuronal function. We identified Formin 3 (Form3) as an essential regulator of cytoskeletal architecture in nociceptive sensory neurons in Drosophila larvae. Time course analyses reveal that Form3 is cell-autonomously required to promote dendritic arbor complexity. We show that form3 is required for the maintenance of a population of stable dendritic microtubules (MTs), and mutants exhibit defects in the localization of dendritic mitochondria, satellite Golgi, and the TRPA channel Painless. Form3 directly interacts with MTs via FH1-FH2 domains. Mutations in human inverted formin 2 (INF2; ortholog of form3) have been causally linked to Charcot-Marie-Tooth (CMT) disease. CMT sensory neuropathies lead to impaired peripheral sensitivity. Defects in form3 function in nociceptive neurons result in severe impairment of noxious heat-evoked behaviors. Expression of the INF2 FH1-FH2 domains partially recovers form3 defects in MTs and nocifensive behavior, suggesting conserved functions, thereby providing putative mechanistic insights into potential etiologies of CMT sensory neuropathies.

Bibliometric analysis of neuroscience publications quantifies the impact of data sharing.

SUMMARY: Neural morphology, the branching geometry of brain cells, is an essential cellular substrate of nervous system function and pathology. Despite the accelerating production of digital reconstructions of neural morphology, the public accessibility of data remains a core issue in neuroscience. Deficiencies in the availability of existing data create redundancy of research efforts and limit synergy. We carried out a comprehensive bibliometric analysis of neural morphology publications to quantify the impact of data sharing in the neuroscience community. Our findings demonstrate that sharing digital reconstructions of neural morphology via NeuroMorpho.Org leads to a significant increase of citations to the original article, thus directly benefiting authors. The rate of data reusage remains constant for at least 16 years after sharing (the whole period analyzed), altogether nearly doubling the peer-reviewed discoveries in the field. Furthermore, the recent availability of larger and more numerous datasets fostered integrative applications, which accrue on average twice the citations of re-analyses of individual datasets. We also released an open-source citation tracking web-service allowing researchers to monitor reusage of their datasets in independent peer-reviewed reports. These results and tools can facilitate the recognition of shared data reuse for merit evaluations and funding decisions. AVAILABILITY AND IMPLEMENTATION: The application is available at: http://cng-nmo-dev3.orc.gmu.edu:8181/. The source code at https://github.com/HerveEmissah/nmo-authors-app and https://github.com/HerveEmissah/nmo-bibliometric-analysis.

Coronary microvascular dysfunction assessment: A comparative analysis of procedural aspects.

BACKGROUND: Full adoption of coronary microvascular dysfunction (CMD) assessment faces challenges due to its invasive nature and concerns about prolonged procedure time and increased contrast and/or radiation exposure. We compared procedural aspects of CMD invasive assessment to diagnostic left heart catheterization (DLHC) in patients with chest pain who were not found to have obstructive coronary artery disease. METHODS: A total of 227 patients in the Coronary Microvascular Disease Registry were compared to 1592 patients who underwent DLHC from August 2021 to November 2023. The two cohorts were compared using propensity-score matching; primary outcomes were fluoroscopy time and total contrast use. RESULTS: The participants' mean age was 64.1 ± 12.6 years. CMD-assessed patients were more likely to be female (66.5% vs. 45.2%, p < 0.001) and have hypertension (80.2% vs. 44.5%, p < 0.001), history of stroke (11.9% vs. 6.3%, p = 0.002), and history of myocardial infarction (20.3% vs. 7.7%, p < 0.001). CMD assessment was safe, without any reported adverse outcomes. A propensity-matched analysis showed that patients who underwent CMD assessment had slightly higher median contrast exposure (50 vs. 40 mL, p < 0.001), and slightly longer fluoroscopy time (6.9 vs. 4.7 min, p < 0.001). However, there was no difference in radiation dose (209.3 vs. 219 mGy, p = 0.58) and overall procedure time (31 vs. 29 min, p = 0.37). CONCLUSION: Compared to DLHC, CMD assessment is safe and requires only slightly additional contrast use (10 mL) and slightly longer fluoroscopy time (2 min) without clinical implications. These findings emphasize the favorable safety and feasibility of invasive CMD assessment.

An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo.

Understanding brain operation demands linking basic behavioral traits to cell-type specific dynamics of different brain-wide subcircuits. This requires a system to classify the basic operational modes of neurons and circuits. Single-cell phenotyping of firing behavior during ongoing oscillations in vivo has provided a large body of evidence on entorhinal-hippocampal function, but data are dispersed and diverse. Here, we mined literature to search for information regarding the phase-timing dynamics of over 100 hippocampal/entorhinal neuron types defined in Hippocampome.org. We identified missing and unresolved pieces of knowledge (e.g., the preferred theta phase for a specific neuron type) and complemented the dataset with our own new data. By confronting the effect of brain state and recording methods, we highlight the equivalences and differences across conditions and offer a number of novel observations. We show how a heuristic approach based on oscillatory features of morphologically identified neurons can aid in classifying extracellular recordings of single cells and discuss future opportunities and challenges towards integrating single-cell phenotypes with circuit function.

Association between maternal dupilumab exposure and pregnancy outcomes in patients with moderate-to-severe atopic dermatitis: A nationwide retrospective cohort study.

BACKGROUND: There is limited epidemiological evidence on outcomes associated with dupilumab exposure during pregnancy; monitoring pregnancy outcomes in large populations is required. OBJECTIVE: To investigate the potential association between exposure to dupilumab in pregnant women with atopic dermatitis and any adverse pregnancy, neonatal, congenital and post-partum outcomes. METHODS: We performed a multicentre retrospective cohort study across 19 Italian tertiary referral hospital. Childbearing women were eligible if aged 18-49 years and carried out the pregnancy between 1 October 2018 and 1 September 2022. RESULTS: We retrospectively screened records of 5062 patients receiving dupilumab regardless of age and gender, identifying 951 female atopic dermatitis patients of childbearing age, 29 of whom had been exposed to the drug during pregnancy (3%). The median duration of dupilumab treatment prior to conception was 22.5 weeks (range: 3-118). The median time of exposure to the drug during pregnancy was 6 weeks (range: 2-24). All the documented pregnancies were unplanned, and the drug was discontinued in all cases once pregnancy status was reported. The comparison of the study cohort and the control group found no significant drug-associated risk for adverse pregnancy, congenital, neonatal or post-partum outcomes. The absence of a statistically significant effect of exposure on the event was confirmed by bivariate analysis and multivariate analysis adjusted for other confounding factors. CONCLUSIONS: This cohort of pregnant patients exposed to dupilumab adds to the existing evidence concerning the safety of biologic agents in pregnancy. No safety issues were identified regarding the primary outcome assessed. In clinical practice, these data provide reassurance in case of dupilumab exposure during the first trimester. However, the continuous use of dupilumab throughout pregnancy warrants further research.

A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal is to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software (version 1.0) is released as open source to enable broad community reuse and encourage novel applications.

Group member attachment style interacts with actor and partner helping alliance to predict decreasing binge eating episodes.

OBJECTIVE: An individual's attachment style may impact how they interact with their therapy group. This study examined the moderating role of a group member's attachment on the dynamic relationships between that group member's (actor) and other group members' (partner) therapeutic alliances and symptom outcomes. Method: This is a secondary analysis of data from a trial testing the outcome of emotionally-focused group therapy for binge-eating disorder. The sample consisted of 2,360 sessions nested within 118 group members who attended a 20-session treatment. Patients recorded binge eating episodes (BEE), their body weight and an alliance measure session-by-session. RESULTS: Dynamic structural equation modelling showed decreases in BEE and weight over the therapy. When attachment style was not included in the model, higher-than-average partner's alliance scores in the previous session were related to decreases in BEE in the current session. Attachment style moderated these actor and partner effects. For patients with preoccupied attachments, higher-than-average actor alliance in the previous session was related to subsequent decreases in BEE. For patients with dismissing or disorganized attachments, higher partner alliance in the previous session was related to subsequent decreases in BEE. CONCLUSION: Group members' attachment characteristics can play a role in the development of alliance-outcome patterns in group therapy.

The Promise and Challenges of Practice-Oriented Research: A Commentary on the Special Issue.

At the centre of POR is the concept of collaboration between patients, therapists, agencies, and third-party payers. For this commentary, I review the articles of the special issue with attention to both the opportunities and challenges offered by practice-oriented research (POR). I also reviewed some previous research on practice-research networks and how that research might inform POR. The use of routine outcome monitoring (ROM), artificial intelligence (AI), and program evaluation (PE) models show promise for advancing POR. However, each comes with its challenges. The use of ROM to improve patient outcomes has research support. However, researchers have identified problems with implementing ROM because of low uptake by clinicians and because clinicians may see ROM as a potential intrusion. AI shows promise to improve patient outcomes by potentially providing therapists with immediate and nuanced data to inform interventions and interpersonal stances specific to each patient. However, the scaling up of AI runs the risk of dehumanizing psychological interventions. PE may provide a context for allowing therapists to engage in POR to address real-world processes and outcomes of mental health interventions. However, like ROM PE faces the challenge of trust among clinicians and patients who may be reluctant to participate. Despite these challenges, and because of efforts to nurture and maintain respectful collaborations, articles in this special issue highlight how POR can play a pivotal role in bridging the gap between theory and practice.

Machine learning classification reveals robust morphometric biomarker of glial and neuronal arbors.

Neurons and glia are the two main cell classes in the nervous systems of most animals. Although functionally distinct, neurons and glia are both characterized by multiple branching arbors stemming from the cell bodies. Glial processes are generally known to form smaller trees than neuronal dendrites. However, the full extent of morphological differences between neurons and glia in multiple species and brain regions has not yet been characterized, nor is it known whether these cells can be reliably distinguished based on geometric features alone. Here, we show that multiple supervised learning algorithms deployed on a large database of morphological reconstructions can systematically classify neuronal and glial arbors with nearly perfect accuracy and precision. Moreover, we report multiple morphometric properties, both size related and size independent, that differ substantially between these cell types. In particular, we newly identify an individual morphometric measurement, Average Branch Euclidean Length that can robustly separate neurons from glia across multiple animal models, a broad diversity of experimental conditions, and anatomical areas, with the notable exception of the cerebellum. We discuss the practical utility and physiological interpretation of this discovery.

Neuron tracing from light microscopy images: automation, deep learning and bench testing.

MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey papers about neuron tracing from light microscopy data in the last decade, thanks to the rapid development of the field, there is a need to update recent progress in a review focusing on new methods and remarkable applications. RESULTS: This review outlines neuron tracing in various scenarios with the goal to help the community understand and navigate tools and resources. We describe the status, examples and accessibility of automatic neuron tracing. We survey recent advances of the increasingly popular deep-learning enhanced methods. We highlight the semi-automatic methods for single neuron tracing of mammalian whole brains as well as the resulting datasets, each containing thousands of full neuron morphologies. Finally, we exemplify the commonly used datasets and metrics for neuron tracing bench testing.

Local Microtubule and F-Actin Distributions Fully Constrain the Spatial Geometry of Drosophila Sensory Dendritic Arbors.

Dendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and straightness. We have previously demonstrated that microtubules and actin filaments are associated with arbor elongation and branching, fully constraining dendrogram topology. Here, we relate the local distribution of these two primary cytoskeletal components with dendritic spatial embedding. We first reconstruct and analyze 167 sensory neurons from the Drosophila larva encompassing multiple cell classes and genotypes. We observe that branches with a higher microtubule concentration tend to deviate less from the direction of their parent branch across all neuron types. Higher microtubule branches are also overall straighter. F-actin displays a similar effect on angular deviation and branch straightness, but not as consistently across all neuron types as microtubule. These observations raise the question as to whether the associations between cytoskeletal distributions and arbor geometry are sufficient constraints to reproduce type-specific dendritic architecture. Therefore, we create a computational model of dendritic morphology purely constrained by the cytoskeletal composition measured from real neurons. The model quantitatively captures both spatial embedding and dendrogram topology across all tested neuron groups. These results suggest a common developmental mechanism regulating diverse morphologies, where the local cytoskeletal distribution can fully specify the overall emergent geometry of dendritic arbors.

The Zinc-BED Transcription Factor Bedwarfed Promotes Proportional Dendritic Growth and Branching through Transcriptional and Translational Regulation in Drosophila.

Dendrites are the primary points of sensory or synaptic input to a neuron and play an essential role in synaptic integration and neural function. Despite the functional importance of dendrites, relatively less is known about the underlying mechanisms regulating cell type-specific dendritic patterning. Herein, we have dissected the functional roles of a previously uncharacterized gene, CG3995, in cell type-specific dendritic development in Drosophila melanogaster. CG3995, which we have named bedwarfed (bdwf), encodes a zinc-finger BED-type protein that is required for proportional growth and branching of dendritic arbors. It also exhibits nucleocytoplasmic expression and functions in both transcriptional and translational cellular pathways. At the transcriptional level, we demonstrate a reciprocal regulatory relationship between Bdwf and the homeodomain transcription factor (TF) Cut. We show that Cut positively regulates Bdwf expression and that Bdwf acts as a downstream effector of Cut-mediated dendritic development, whereas overexpression of Bdwf negatively regulates Cut expression in multidendritic sensory neurons. Proteomic analyses revealed that Bdwf interacts with ribosomal proteins and disruption of these proteins resulted in phenotypically similar dendritic hypotrophy defects as observed in bdwf mutant neurons. We further demonstrate that Bdwf and its ribosomal protein interactors are required for normal microtubule and F-actin cytoskeletal architecture. Finally, our findings reveal that Bdwf is required to promote protein translation and ribosome trafficking along the dendritic arbor. These findings shed light on the complex, combinatorial, and multi-functional roles of transcription factors (TFs) in directing the diversification of cell type-specific dendritic development.

High Filamin a Expression in Adrenocortical Carcinomas Is Associated with a Favourable Tumour Behaviour: A European Multicentric Study.

The insulin-like growth factor 2 (IGF2) promotes cell growth by overactivating the IGF system in an autocrine loop in adrenocortical carcinomas (ACCs). The cytoskeleton protein filamin A (FLNA) acts as a repressor of IGF2 mitogenic signalling in ACC cells. The aims of this study were to test FLNA expression by immunohistochemistry in 119 ACCs and 26 adrenocortical adenomas (ACAs) and to evaluate its relationship with clinicopathological features and outcome in ACCs. We found that 71.4% of ACCs did not express FLNA, whereas FLNA absence was a rare event in ACAs (15.4%, p < 0.001 vs. ACCs). In addition, the expression of FLNA was associated with a less aggressive tumour behaviour in ACCs. Indeed, the subgroup of ACCs with high FLNA showed a lower ENSAT stage, Weiss score, and S-GRAS score compared to ACCs with low FLNA expression (p < 0.05). Moreover, patients with high FLNA had a longer overall survival than those with low FLNA (p < 0.05). In conclusion, our data suggest that FLNA may represent a "protective" factor in ACCs, and the integration of FLNA immunohistochemical expression in ACC tissues along with other clinical and molecular markers could be helpful to improve diagnostic accuracy and prognosis prediction in ACCs.

Detecting defense mechanisms from Adult Attachment Interview (AAI) transcripts using machine learning.

OBJECTIVE: Defensive functioning (i.e., unconscious process used to manage real or perceived threats) may play a role in the development of various psychopathologies. It is typically assessed via observer rating measures, however, human coding of defensive functioning is resource-intensive and time-consuming. The purpose of this study was to develop a machine learning approach to automate coding of defense mechanisms from interview transcripts. METHOD: Participants included a clinical sample of women with binge-eating disorder (n = 92) and a community sample without binge-eating disorder (n = 66). We trained and evaluated five RoBERTa-based models to detect the presence of defenses in 16,785 interviewer-participant talk-turn pairs nested within 192 interviews. A model detected the presence of any defense, while four additional models detected the most common defenses in this sample (repression, intellectualization, reaction formation, undoing). RESULTS: The models were capable of distinguishing defenses (ROC-AUC .82-.90) but were not proficient enough to warrant replacing human coders (PR-AUC .28-.60). Follow-up analysis was performed to assess other practical uses of these models. DISCUSSION: Our machine learning models could be used to assist coders. Future research should conduct a deployment study to determine if human coding of defense mechanisms can be expedited using machine learning models.

Comprehensive Estimates of Potential Synaptic Connections in Local Circuits of the Rodent Hippocampal Formation by Axonal-Dendritic Overlap.

A quantitative description of the hippocampal formation synaptic architecture is essential for understanding the neural mechanisms of episodic memory. Yet the existing knowledge of connectivity statistics between different neuron types in the rodent hippocampus only captures a mere 5% of this circuitry. We present a systematic pipeline to produce first-approximation estimates for most of the missing information. Leveraging the www.Hippocampome.org knowledge base, we derive local connection parameters between distinct pairs of morphologically identified neuron types based on their axonal-dendritic overlap within every layer and subregion of the hippocampal formation. Specifically, we adapt modern image analysis technology to determine the parcel-specific neurite lengths of every neuron type from representative morphologic reconstructions obtained from either sex. We then compute the average number of synapses per neuron pair using relevant anatomic volumes from the mouse brain atlas and ultrastructurally established interaction distances. Hence, we estimate connection probabilities and number of contacts for >1900 neuron type pairs, increasing the available quantitative assessments more than 11-fold. Connectivity statistics thus remain unknown for only a minority of potential synapses in the hippocampal formation, including those involving long-range (23%) or perisomatic (6%) connections and neuron types without morphologic tracings (7%). The described approach also yields approximate measurements of synaptic distances from the soma along the dendritic and axonal paths, which may affect signal attenuation and delay. Overall, this dataset fills a substantial gap in quantitatively describing hippocampal circuits and provides useful model specifications for biologically realistic neural network simulations, until further direct experimental data become available.SIGNIFICANCE STATEMENT The hippocampal formation is a crucial functional substrate for episodic memory and spatial representation. Characterizing the complex neuron type circuit of this brain region is thus important to understand the cellular mechanisms of learning and navigation. Here we present the first numerical estimates of connection probabilities, numbers of contacts per connected pair, and synaptic distances from the soma along the axonal and dendritic paths, for more than 1900 distinct neuron type pairs throughout the dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex. This comprehensive dataset, publicly released online at www.Hippocampome.org, constitutes an unprecedented quantification of the majority of the local synaptic circuit for a prominent mammalian neural system and provides an essential foundation for data-driven, anatomically realistic neural network models.

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.

Quantification of neuron types in the rodent hippocampal formation by data mining and numerical optimization.

Quantifying the population sizes of distinct neuron types in different anatomical regions is an essential step towards establishing a brain cell census. Although estimates exist for the total neuronal populations in different species, the number and definition of each specific neuron type are still intensively investigated. Hippocampome.org is an open-source knowledge base with morphological, physiological and molecular information for 122 neuron types in the rodent hippocampal formation. While such framework identifies all known neuron types in this system, their relative abundances remain largely unknown. This work quantitatively estimates the counts of all Hippocampome.org neuron types by literature mining and numerical optimization. We report the number of neurons in each type identified by main neurotransmitter (glutamate or GABA) and axonal-dendritic patterns throughout 26 subregions and layers of the dentate gyrus, Ammon's horn, subiculum and entorhinal cortex. We produce by sensitivity analysis reliable numerical ranges for each type and summarize the amounts across broad neuronal families defined by biomarkers expression and firing dynamics. Study of density distributions indicates that the number of dendritic-targeting interneurons, but not of other neuronal classes, is independent of anatomical volumes. All extracted values, experimental evidence and related software code are released on Hippocampome.org.

Contemporary post-marketing adverse events and modes of failure related to VASCADE Vascular Closure System: The utility of the MAUDE database.

OBJECTIVES: To analyze post-marketing surveillance data from the United States Food and Drug Administration (FDA) Manufacturer and User Facility Device Experience (MAUDE) database for the VASCADE Vascular Closure System (Cardiva Medical Inc., Santa Clara, CA). BACKGROUND: The VASCADE Vascular Closure System is a closure device for femoral arterial and venous access-site closure that was approved by the FDA in 2013. However, post-marketing data and experience on the most commonly reported complications and modes of failure associated with the VASCADE Vascular Closure System are limited. METHODS: Post-marketing surveillance data from the FDA MAUDE database from October 2013 through March 2020 were analyzed, yielding 201 reports. RESULTS: Of the 201 reports of major complications involving VASCADE devices, 156 reports involved either injury (145) or death (11) related to the device. Of the 145 injury reports, bleeding was the most common adverse outcome described (85), followed by pseudoaneurysm (29) and pulselessness of an extremity (21). The device malfunction incidents (41 reports) were reported in three main categories, with deployment failure being the most commonly reported complication. CONCLUSIONS: Our analysis of the MAUDE database demonstrates that in contemporary post-marketing practice, physicians should be well-trained and educated to use the VASCADE closure device because improper utilization is a common cause of device failure, and complications with the VASCADE device can have profound clinical implications.

Impact of left ventricular outflow tract calcium on valve geometry in self-expanding transcatheter aortic-valve replacement.

OBJECTIVES: Evaluate transcatheter heart valve (THV) geometry according to left ventricular outflow tract (LVOT) calcium degree and its impact on hemodynamics and outcomes in patients undergoing transcatheter aortic valve replacement (TAVR) with a contemporary self-expanding THV. BACKGROUND: LVOT calcium remains challenging for contemporary THVs. LVOT calcium location and degree may affect THV deployment and impact flow patterns and shear stress, accelerating THV degeneration. METHODS: EPROMPT (CoreValve Evolut Pro Prospective Registry; NCT03423459) is a prospective, investigator-initiated, multicenter registry of patients undergoing TAVR using CoreValve Evolut PRO/PRO + THVs. A total of 107 patients were enrolled in EPROMPT's computed tomography (CT) cohort between January 2018 and October 2021. These patients underwent follow-up CT scan 30 days post-TAVR. We analyzed THV geometry and its interaction with the aortic root following deployment using 30-day post-TAVR CT in patients with none/mild versus moderate/severe LVOT calcium. RESULTS: Thirty-day THV inflows were less eccentric in the short axis in patients with none/mild versus moderate/severe LVOT calcium (1.16 ± 0.09 vs. 1.21 ± 0.12; p = 0.007). THV became more circular and was similar between both cohorts at the THV waist (1.08 ± 0.06 vs. 1.09 ± 0.11; p = 0.551), leaflet tips (1.03 ± 0.04 vs. 1.05 ± 0.09; p = 0.299), and THV outflow (1.04 ± 2.2 vs. 1.03 ± 2.7; p = 0.143). Thirty-day > mild paravalvular leak was low in both cohorts (1.5% vs. 2.4%; p = 0.724); mean gradients were similar (7.7 ± 3.6 vs. 7.7 ± 3.4 mmHg; p = 0.955). CONCLUSIONS: Despite inflow deformities observed in patients with moderate/severe LVOT calcium, Evolut PRO/PRO + conforms to elliptical aortic annuli, maintaining circularity and proper function at the leaflets and outflow, even in patients with moderate/severe LVOT calcium.