T2-FLAIR mismatch sign predicts DNA methylation subclass and CDKN2A/B status in IDH-mutant astrocytomas.

PURPOSE: DNA methylation profiling stratifies isocitrate dehydrogenase (IDH)-mutant astrocytomas into methylation low-grade and high-grade groups. We investigated the utility of the T2-FLAIR mismatch sign for predicting DNA methylation grade and cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion, a molecular biomarker for grade 4 IDH-mutant astrocytomas, according to the 2021 World Health Organization (WHO) classification. EXPERIMENTAL DESIGN: Preoperative MRI scans of IDH-mutant astrocytomas subclassified by DNA methylation profiling (n=71) were independently evaluated by two radiologists for the T2-FLAIR mismatch sign. The diagnostic utility of T2-FLAIR mismatch in predicting methylation grade, CDKN2A/B status, copy number variation, and survival was analyzed. RESULTS: The T2-FLAIR mismatch sign was present in 21 of 45 (46.7%) methylation low-grade and 1 of 26 (3.9%) methylation high-grade cases (p<0.001), resulting in 96.2% specificity, 95.5% positive predictive value, and 51.0% negative predictive value for predicting low methylation grade. The T2-FLAIR mismatch sign was also significantly associated with intact CDKN2A/B status (p=0.028) with 87.5% specificity, 86.4% positive predictive value, and 42.9% negative predictive value. Overall multivariable Cox analysis showed that retained CDKN2A/B status remained significant for PFS (p=0.01). Multivariable Cox analysis of the histologic grade 3 subset, which was nearly evenly divided by CDKN2A/B status, CNV, and methylation grade, showed trends toward significance for DNA methylation grade with OS (p=0.045) and CDKN2A/B status with PFS (p=0.052). CONCLUSIONS: The T2-FLAIR mismatch sign is highly specific for low methylation grade and intact CDKN2A/B in IDH-mutant astrocytomas.

Synthesizing 3D Multi-Contrast Brain Tumor MRIs Using Tumor Mask Conditioning.

Data scarcity and data imbalance are two major challenges in training deep learning models on medical images, such as brain tumor MRI data. The recent advancements in generative artificial intelligence have opened new possibilities for synthetically generating MRI data, including brain tumor MRI scans. This approach can be a potential solution to mitigate the data scarcity problem and enhance training data availability. This work focused on adapting the 2D latent diffusion models to generate 3D multi-contrast brain tumor MRI data with a tumor mask as the condition. The framework comprises two components: a 3D autoencoder model for perceptual compression and a conditional 3D Diffusion Probabilistic Model (DPM) for generating high-quality and diverse multi-contrast brain tumor MRI samples, guided by a conditional tumor mask. Unlike existing works that focused on generating either 2D multi-contrast or 3D single-contrast MRI samples, our models generate multi-contrast 3D MRI samples. We also integrated a conditional module within the UNet backbone of the DPM to capture the semantic class-dependent data distribution driven by the provided tumor mask to generate MRI brain tumor samples based on a specific brain tumor mask. We trained our models using two brain tumor datasets: The Cancer Genome Atlas (TCGA) public dataset and an internal dataset from the University of Texas Southwestern Medical Center (UTSW). The models were able to generate high-quality 3D multi-contrast brain tumor MRI samples with the tumor location aligned by the input condition mask. The quality of the generated images was evaluated using the Fréchet Inception Distance (FID) score. This work has the potential to mitigate the scarcity of brain tumor data and improve the performance of deep learning models involving brain tumor MRI data.

Two-Stage Training Framework Using Multicontrast MRI Radiomics for IDH Mutation Status Prediction in Glioma.

Purpose To develop a radiomics framework for preoperative MRI-based prediction of isocitrate dehydrogenase (IDH) mutation status, a crucial glioma prognostic indicator. Materials and Methods Radiomics features (shape, first-order statistics, and texture) were extracted from the whole tumor or the combination of nonenhancing, necrosis, and edema regions. Segmentation masks were obtained via the federated tumor segmentation tool or the original data source. Boruta, a wrapper-based feature selection algorithm, identified relevant features. Addressing the imbalance between mutated and wild-type cases, multiple prediction models were trained on balanced data subsets using random forest or XGBoost and assembled to build the final classifier. The framework was evaluated using retrospective MRI scans from three public datasets (The Cancer Imaging Archive [TCIA, 227 patients], the University of California San Francisco Preoperative Diffuse Glioma MRI dataset [UCSF, 495 patients], and the Erasmus Glioma Database [EGD, 456 patients]) and internal datasets collected from the University of Texas Southwestern Medical Center (UTSW, 356 patients), New York University (NYU, 136 patients), and University of Wisconsin-Madison (UWM, 174 patients). TCIA and UTSW served as separate training sets, while the remaining data constituted the test set (1617 or 1488 testing cases, respectively). Results The best performing models trained on the TCIA dataset achieved area under the receiver operating characteristic curve (AUC) values of 0.89 for UTSW, 0.86 for NYU, 0.93 for UWM, 0.94 for UCSF, and 0.88 for EGD test sets. The best performing models trained on the UTSW dataset achieved slightly higher AUCs: 0.92 for TCIA, 0.88 for NYU, 0.96 for UWM, 0.93 for UCSF, and 0.90 for EGD. Conclusion This MRI radiomics-based framework shows promise for accurate preoperative prediction of IDH mutation status in patients with glioma. Keywords: Glioma, Isocitrate Dehydrogenase Mutation, IDH Mutation, Radiomics, MRI Supplemental material is available for this article. Published under a CC BY 4.0 license. See also commentary by Moassefi and Erickson in this issue.

Signalling switches maintain intercellular communication in the vascular endothelium.

BACKGROUND AND PURPOSE: The single layer of cells lining all blood vessels, the endothelium, is a sophisticated signal co-ordination centre that controls a wide range of vascular functions including the regulation of blood pressure and blood flow. To co-ordinate activities, communication among cells is required for tissue level responses to emerge. While a significant form of communication occurs by the propagation of signals between cells, the mechanism of propagation in the intact endothelium is unresolved. EXPERIMENTAL APPROACH: Precision signal generation and targeted cellular manipulation was used in conjunction with high spatiotemporal mesoscale Ca2+ imaging in the endothelium of intact blood vessels. KEY RESULTS: Multiple mechanisms maintain communication so that Ca2+ wave propagation occurs irrespective of the status of connectivity among cells. Between adjoining cells, regenerative IP3-induced IP3 production transmits Ca2+ signals and explains the propagated vasodilation that underlies the increased blood flow accompanying tissue activity. The inositide is itself sufficient to evoke regenerative phospholipase C-dependent Ca2+ waves across coupled cells. None of gap junctions, Ca2+ diffusion or the release of extracellular messengers is required to support this type of intercellular Ca2+ signalling. In contrast, when discontinuities exist between cells, ATP released as a diffusible extracellular messenger transmits Ca2+ signals across the discontinuity and drives propagated vasodilation. CONCLUSION AND IMPLICATIONS: These results show that signalling switches underlie endothelial cell-to-cell signal transmission and reveal how communication is maintained in the face of endothelial damage. The findings provide a new framework for understanding wave propagation and cell signalling in the endothelium.

MRI-Based Deep Learning Method for Classification of IDH Mutation Status.

Isocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas. This study sought to develop deep learning networks for non-invasive IDH classification using T2w MR images while comparing their performance to a multi-contrast network. Methods: Multi-contrast brain tumor MRI and genomic data were obtained from The Cancer Imaging Archive (TCIA) and The Erasmus Glioma Database (EGD). Two separate 2D networks were developed using nnU-Net, a T2w-image-only network (T2-net) and a multi-contrast network (MC-net). Each network was separately trained using TCIA (227 subjects) or TCIA + EGD data (683 subjects combined). The networks were trained to classify IDH mutation status and implement single-label tumor segmentation simultaneously. The trained networks were tested on over 1100 held-out datasets including 360 cases from UT Southwestern Medical Center, 136 cases from New York University, 175 cases from the University of Wisconsin-Madison, 456 cases from EGD (for the TCIA-trained network), and 495 cases from the University of California, San Francisco public database. A receiver operating characteristic curve (ROC) was drawn to calculate the AUC value to determine classifier performance. Results: T2-net trained on TCIA and TCIA + EGD datasets achieved an overall accuracy of 85.4% and 87.6% with AUCs of 0.86 and 0.89, respectively. MC-net trained on TCIA and TCIA + EGD datasets achieved an overall accuracy of 91.0% and 92.8% with AUCs of 0.94 and 0.96, respectively. We developed reliable, high-performing deep learning algorithms for IDH classification using both a T2-image-only and a multi-contrast approach. The networks were tested on more than 1100 subjects from diverse databases, making this the largest study on image-based IDH classification to date.

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.

PURPOSE: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas. METHODS: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS). RESULTS: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS. CONCLUSION: Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas.

Mitochondrial ATP Production is Required for Endothelial Cell Control of Vascular Tone.

Arteries and veins are lined by nonproliferating endothelial cells that play a critical role in regulating blood flow. Endothelial cells also regulate tissue perfusion, metabolite exchange, and thrombosis. It is thought that endothelial cells rely on ATP generated via glycolysis, rather than mitochondrial oxidative phosphorylation, to fuel each of these energy-demanding processes. However, endothelial metabolism has mainly been studied in the context of proliferative cells, and little is known about energy production in endothelial cells within the fully formed vascular wall. Using intact arteries isolated from rats and mice, we show that inhibiting mitochondrial respiration disrupts endothelial control of vascular tone. Basal, mechanically activated, and agonist-evoked calcium activity in intact artery endothelial cells are each prevented by inhibiting mitochondrial ATP synthesis. Agonist-evoked calcium activity was also inhibited by blocking the transport of pyruvate, the master fuel for mitochondrial energy production, through the mitochondrial pyruvate carrier. The role for mitochondria in endothelial cell energy production is independent of species, sex, or vascular bed. These data show that a mitochondrial ATP supply is necessary for calcium-dependent, nitric oxide-mediated endothelial control of vascular tone, and identifies the critical role of endothelial mitochondrial energy production in fueling perfused blood vessel function.

Endothelial PAR2 activation evokes resistance artery relaxation.

Protease-activated receptor-1 & -2 (PAR1 and PAR2) are expressed widely in cardiovascular tissues including endothelial and smooth muscle cells. PAR1 and PAR2 may regulate blood pressure via changes in vascular contraction or relaxation mediated by endothelial Ca2+ signaling, but the mechanisms are incompletely understood. By using single-cell Ca2+ imaging across hundreds of endothelial cells in intact blood vessels, we explored PAR-mediated regulation of blood vessel function using PAR1 and PAR2 activators. We show that PAR2 activation evoked multicellular Ca2+ waves that propagated across the endothelium. The PAR2-evoked Ca2+ waves were temporally distinct from those generated by muscarinic receptor activation. PAR2 activated distinct clusters of endothelial cells, and these cells were different from those activated by muscarinic receptor stimulation. These results indicate that distinct cell clusters facilitate spatial segregation of endothelial signal processing. We also demonstrate that PAR2 is a phospholipase C-coupled receptor that evokes Ca2+ release from the IP3 -sensitive store in endothelial cells. A physiological consequence of this PAR2 signaling system is endothelium-dependent relaxation. Conversely, PAR1 activation did not trigger endothelial cell Ca2+ signaling nor relax or contract mesenteric arteries. Neither did PAR1 activators alter the response to PAR2 or muscarinic receptor activation. Collectively, these results suggest that endothelial PAR2 but not PAR1 evokes mesenteric artery relaxation by evoking IP3 -mediated Ca2+ release from the internal store. Sensing mediated by PAR2 receptors is distributed to spatially separated clusters of endothelial cells.

Distinguishing Brain Metastasis Progression From Radiation Effects After Stereotactic Radiosurgery Using Longitudinal GRASP Dynamic Contrast-Enhanced MRI.

BACKGROUND: Differentiating brain metastasis progression from radiation effects or radiation necrosis (RN) remains challenging. Golden-angle radial sparse parallel (GRASP) dynamic contrast-enhanced MRI provides high spatial and temporal resolution to analyze tissue enhancement, which may differ between tumor progression (TP) and RN. OBJECTIVE: To investigate the utility of longitudinal GRASP MRI in distinguishing TP from RN after gamma knife stereotactic radiosurgery (SRS). METHODS: We retrospectively evaluated 48 patients with brain metastasis managed with SRS at our institution from 2013 to 2020 who had GRASP MRI before and at least once after SRS. TP (n = 16) was pathologically confirmed. RN (n = 16) was diagnosed on either resected tissue without evidence of tumor or on lesion resolution on follow-up. As a reference, we included a separate group of patients with non-small-cell lung cancer that showed favorable response with tumor control and without RN on subsequent imaging (n = 16). Mean contrast washin and washout slopes normalized to the superior sagittal sinus were compared between groups. Receiver operating characteristic analysis was performed to determine diagnostic performance. RESULTS: After SRS, progression showed a significantly steeper washin slope than RN on all 3 follow-up scans (scan 1: 0.29 ± 0.16 vs 0.18 ± 0.08, P = .021; scan 2: 0.35 ± 0.19 vs 0.18 ± 0.09, P = .004; scan 3: 0.32 ± 0.12 vs 0.17 ± 0.07, P = .002). No significant differences were found in the post-SRS washout slope. Post-SRS washin slope differentiated progression and RN with an area under the curve (AUC) of 0.74, a sensitivity of 75%, and a specificity of 69% on scan 1; an AUC of 0.85, a sensitivity of 92%, and a specificity of 69% on scan 2; and an AUC of 0.87, a sensitivity of 63%, and a specificity of 100% on scan 3. CONCLUSION: Longitudinal GRASP MRI may help to differentiate metastasis progression from RN.

Deep multi-task learning and random forest for series classification by pulse sequence type and orientation.

PURPOSE: Increasingly complex MRI studies and variable series naming conventions reveal limitations of rule-based image routing, especially in health systems with multiple scanners and sites. Accurate methods to identify series based on image content would aid post-processing and PACS viewing. Recent deep/machine learning efforts classify 5-8 basic brain MR sequences. We present an ensemble model combining a convolutional neural network and a random forest classifier to differentiate 25 brain sequences and image orientation. METHODS: Series were grouped by descriptions into 25 sequences and 4 orientations. Dataset A, obtained from our institution, was divided into training (16,828 studies; 48,512 series; 112,028 images), validation (4746 studies; 16,612 series; 26,222 images) and test sets (6348 studies; 58,705 series; 3,314,018 images). Dataset B, obtained from a separate hospital, was used for out-of-domain external validation (1252 studies; 2150 series; 234,944 images). We developed an ensemble model combining a 2D convolutional neural network with a custom multi-task learning architecture and random forest classifier trained on DICOM metadata to classify sequence and orientation by series. RESULTS: The neural network, random forest, and ensemble achieved 95%, 97%, and 98% overall sequence accuracy on dataset A, and 98%, 99%, and 99% accuracy on dataset B, respectively. All models achieved > 99% orientation accuracy on both datasets. CONCLUSION: The ensemble model for series identification accommodates the complexity of brain MRI studies in state-of-the-art clinical practice. Expanding on previous work demonstrating proof-of-concept, our approach is more comprehensive with greater sequence diversity and orientation classification.

Small-world connectivity dictates collective endothelial cell signaling.

Every blood vessel is lined by a single layer of highly specialized, yet adaptable and multifunctional endothelial cells. These cells, the endothelium, control vascular contractility, hemostasis, and inflammation and regulate the exchange of oxygen, nutrients, and waste products between circulating blood and tissue. To control each function, the endothelium processes endlessly arriving requests from multiple sources using separate clusters of cells specialized to detect specific stimuli. A well-developed but poorly understood communication system operates between cells to integrate multiple lines of information and coordinate endothelial responses. Here, the nature of the communication network has been addressed using single-cell Ca2+ imaging across thousands of endothelial cells in intact blood vessels. Cell activities were cross-correlated and compared to a stochastic model to determine network connections. Highly correlated Ca2+ activities occurred in scattered cell clusters, and network communication links between them exhibited unexpectedly short path lengths. The number of connections between cells (degree distribution) followed a power-law relationship revealing a scale-free network topology. The path length and degree distribution revealed an endothelial network with a "small-world" configuration. The small-world configuration confers particularly dynamic endothelial properties including high signal-propagation speed, stability, and a high degree of synchronizability. Local activation of small clusters of cells revealed that the short path lengths and rapid signal transmission were achieved by shortcuts via connecting extensions to nonlocal cells. These findings reveal that the endothelial network design is effective for local and global efficiency in the interaction of the cells and rapid and robust communication between endothelial cells in order to efficiently control cardiovascular activity.

A No-Math Primer on the Principles of Machine Learning for Radiologists.

Machine learning is becoming increasingly important in both research and clinical applications in radiology due to recent technological developments, particularly in deep learning. As these technologies are translated toward clinical practice, there is a need for radiologists and radiology trainees to understand the basic principles behind them. This primer provides an accessible introduction to the vocabulary and concepts that are central to machine learning and relevant to the radiologist.

Mitochondria regulate TRPV4-mediated release of ATP.

BACKGROUND AND PURPOSE: Ca2+ influx via TRPV4 channels triggers Ca2+ release from the IP3 -sensitive internal store to generate repetitive oscillations. Although mitochondria are acknowledged regulators of IP3 -mediated Ca2+ release, how TRPV4-mediated Ca2+ signals are regulated by mitochondria is unknown. We show that depolarised mitochondria switch TRPV4 signalling from relying on Ca2+ -induced Ca2+ release at IP3 receptors to being independent of Ca2+ influx and instead mediated by ATP release via pannexins. EXPERIMENTAL APPROACH: TRPV4-evoked Ca2+ signals were individually examined in hundreds of cells in the endothelium of rat mesenteric resistance arteries using the indicator Cal520. KEY RESULTS: TRPV4 activation with GSK1016790A (GSK) generated repetitive Ca2+ oscillations that required Ca2+ influx. However, when the mitochondrial membrane potential was depolarised, by the uncoupler CCCP or complex I inhibitor rotenone, TRPV4 activation generated large propagating, multicellular, Ca2+ waves in the absence of external Ca2+ . The ATP synthase inhibitor oligomycin did not potentiate TRPV4-mediated Ca2+ signals. GSK-evoked Ca2+ waves, when mitochondria were depolarised, were blocked by the TRPV4 channel blocker HC067047, the SERCA inhibitor cyclopiazonic acid, the PLC blocker U73122 and the inositol trisphosphate receptor blocker caffeine. The Ca2+ waves were also inhibited by the extracellular ATP blockers suramin and apyrase and the pannexin blocker probenecid. CONCLUSION AND IMPLICATIONS: These results highlight a previously unknown role of mitochondria in shaping TRPV4-mediated Ca2+ signalling by facilitating ATP release. When mitochondria are depolarised, TRPV4-mediated release of ATP via pannexin channels activates plasma membrane purinergic receptors to trigger IP3 -evoked Ca2+ release.

"The Pituitary within GRASP" - Golden-Angle Radial Sparse Parallel Dynamic MRI Technique and Applications to the Pituitary Gland.

MRI is the preferred radiologic modality for evaluating the pituitary gland. An important component of pituitary MRI examinations is dynamic contrast-enhanced MRI. Compared to conventional dynamic techniques, golden-angle radial sparse parallel (GRASP) imaging offers multiple advantages, including the ability to achieve higher spatial and temporal resolution. In this narrative review, we discuss dynamic imaging of the pituitary gland, the technical fundamentals of GRASP, and applications of GRASP to the pituitary gland.

COVID-19 as 'Game Changer' for the Physical Activity and Mental Well-Being of Augmented Reality Game Players During the Pandemic: Mixed Methods Survey Study.

BACKGROUND: Location-based augmented reality (AR) games, such as Pokémon GO and Harry Potter: Wizards Unite, have been shown to have a beneficial impact on the physical activity, social connectedness, and mental health of their players. In March 2020, global social distancing measures related to the COVID-19 pandemic prompted the AR games developer Niantic Inc to implement several changes to ensure continued player engagement with Pokémon GO and Harry Potter: Wizards Unite. We sought to examine how the physical and mental well-being of players of these games were affected during the unprecedented COVID-19 restriction period as well as how their video game engagement was affected. OBJECTIVE: The aims of this study were to examine the impact of COVID-19-related social restrictions on the physical and mental well-being of AR game players; to examine the impact of COVID-19-related social restrictions on the use of video games and motivations for their use; and to explore the potential role of AR games (and video games in general) in supporting well-being during COVID-19-related social restrictions. METHODS: A mixed methods web-based self-reported survey was conducted in May 2020, during which COVID-19-related social restrictions were enforced in many countries. Participants were recruited on the web via four subreddits dedicated to Pokémon GO or Harry Potter: Wizards Unite. Data collected included quantitative data on demographics, time spent playing video games, physical activity, and mental health; qualitative data included motivations to play and the impact of video games on mental health during COVID-19 lockdown. RESULTS: We report results for 2004 participants (1153/1960 male, 58.8%, average age 30.5 years). Self-reported physical activity during COVID-19-related social restrictions significantly decreased from 7.50 hours per week on average (SD 11.12) to 6.50 hours (SD 7.81) (P<.001). More than half of the participants reported poor mental health (925/1766, 52.4%; raw World Health Organization-5 Well-Being Index score <13). Female gender, younger age, and reduced exercise were significant predictors of poor mental health. Participants reported a significant increase in video game play time from 16.38 hours per week on average (SD 19.12) to 20.82 hours (SD 17.49) (P<.001). Approximately three quarters of the participants (n=1102/1427, 77.2%) reported that playing video games had been beneficial to their mental health. The changes made to Pokémon GO and Harry Potter: Wizards Unite were very well received by players, and the players continued to use these games while exercising and to maintain social connection. In addition to seeking an escape during the pandemic and as a form of entertainment, participants reported that they used video games for emotional coping and to lower stress, relax, and alleviate mental health conditions. CONCLUSIONS: AR games have the potential to promote physical and mental health during the COVID-19 pandemic. Used by populations under isolation and distress, these games can improve physical and mental health by providing virtual socialization, sustained exercise, temporal routine, and mental structure. Further research is needed to explore the potential of AR games as digital behavioral interventions to maintain human well-being in the wider population.

Disrupted endothelial cell heterogeneity and network organization impair vascular function in prediabetic obesity.

BACKGROUND: Obesity is a major risk factor for diabetes and cardiovascular diseases such as hypertension, heart failure, and stroke. Impaired endothelial function occurs in the earliest stages of obesity and underlies vascular alterations that give rise to cardiovascular disease. However, the mechanisms that link weight gain to endothelial dysfunction are ill-defined. Increasing evidence suggests that endothelial cells are not a population of uniform cells but are highly heterogeneous and are organized as a communicating multicellular network that controls vascular function. PURPOSE: To investigate the hypothesis that disrupted endothelial heterogeneity and network-level organization contribute to impaired vascular reactivity in obesity. METHODS AND RESULTS: To study obesity-related vascular function without complications associated with diabetes, a state of prediabetic obesity was induced in rats. Small artery diameter recordings confirmed nitric-oxide mediated vasodilator responses were dependent on increases in endothelial calcium levels and were impaired in obese animals. Single-photon imaging revealed a linear relationship between blood vessel relaxation and population-wide calcium responses. Obesity did not alter the slope of this relationship, but impaired calcium responses in the endothelial cell network. The network comprised structural and functional components. The structural architecture, a hexagonal lattice network of connected cells, was unchanged in obesity. The functional network contained sub-populations of clustered specialized agonist-sensing cells from which signals were communicated through the network. In obesity there were fewer but larger clusters of sensory cells and communication path lengths between clusters increased. Communication between neighboring cells was unaltered in obesity. Altered network organization resulted in impaired, population-level calcium signaling and deficient endothelial control of vascular tone. CONCLUSIONS: The distribution of cells in the endothelial network is critical in determining overall vascular response. Altered cell heterogeneity and arrangement in obesity decreases endothelial function and provides a novel framework for understanding compromised endothelial function in cardiovascular disease.