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"Moran, Christopher J."
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Long-Term Clinical and Angiographic Outcomes Following Pipeline Embolization Device Treatment of Complex Internal Carotid Artery Aneurysms: Five-Year Results of the Pipeline for Uncoilable or Failed Aneurysms Trial
Abstract
BACKGROUND: Early and mid-term safety and efficacy of aneurysm treatment with the Pipeline Embolization Device (PED) has been well demonstrated in prior studies.
OBJECTIVE: To present 5-yr follow-up for patients treated in the Pipeline for Uncoilable or Failed Aneurysms clinical trial.
METHODS: In our prospective, multicenter trial, 109 complex internal carotid artery (ICA) aneurysms in 107 subjects were treated with the PED. Patients were followed per a standardized protocol at 180 d and 1, 3, and 5 yr. Aneurysm occlusion, in-stent stenosis, modified Rankin Scale scores, and complications were recorded.
RESULTS: The primary endpoint of complete aneurysm occlusion at 180 d (73.6%) was previously reported. Aneurysm occlusion for those patients with angiographic follow-up progressively increased over time to 86.8% (79/91), 93.4% (71/76), and 95.2% (60/63) at 1, 3, and 5 yr, respectively. Six aneurysms (5.7%) were retreated. New serious device-related events at 1, 3, and 5 yr were noted in 1% (1/96), 3.5% (3/85), and 0% (0/81) of subjects. There were 4 (3.7%) reported deaths in our trial. Seventy-eight (96.3%) of 81 patients with 5-yr clinical follow-up had modified Rankin Scale scores ≤2. No delayed neurological deaths or hemorrhagic or ischemic cerebrovascular events were reported beyond 6 mo. No recanalization of a previously occluded aneurysm was observed.
CONCLUSION: Our 5-yr findings demonstrate that PED is a safe and effective treatment for large and giant wide-necked aneurysms of the intracranial ICA, with high rates of complete occlusion and low rates of delayed adverse events.
Journal Article
Autonomous multi-robot synthesis and optimization of metal halide perovskite nanocrystals
Metal halide perovskite (MHP) nanocrystals (NCs) offer extraordinary tunability in their optical properties, yet fully exploiting this potential is challenged by a vast and complex synthesis parameter space. Herein, we introduce Rainbow, a multi-robot self-driving laboratory that integrates automated NC synthesis, real-time characterization, and machine learning (ML)-driven decision-making to efficiently navigate MHP NCs’ mixed-variable high-dimensional landscape. Using parallelized, miniaturized batch reactors, robotic sample handling, and continuous spectroscopic feedback, Rainbow autonomously optimizes MHP NC optical performance—including photoluminescence quantum yield and emission linewidth at a targeted emission energy—through closed-loop experimentation. By systematically exploring varying ligand structures and precursor conditions, Rainbow elucidates critical structure–property relationships and identifies scalable Pareto-optimal formulations for targeted spectral outputs. Rainbow provides a versatile blueprint for accelerated, data-driven discovery and retrosynthesis of high-performance metal halide perovskite nanocrystals, facilitating the on-demand realization of next-generation photonic materials and technologies.
The full potential of tunable perovskite nanocrystals is limited by complex synthesis space. Here, authors developed a self-driving lab that autonomously discovers and produces optimal scalable nanocrystals for next-generation photonic technologies.
Journal Article
Benchmarking performance of annual burn probability modeling against subsequent wildfire activity in California
Wildfire simulation is deployed extensively to support risk management, and in the US has driven billions in federal investment. Foundational to strategic risk analysis is spatial information on the likelihood of burning in a fire year, typically provided by burn probability (BP) models. The recency of BP maps is a key driver of their accuracy, especially in disturbed landscapes that have experienced changes in fire spread potential. Few published examples exist comparing BP values against subsequent fire activity, and none to our knowledge evaluate annually updated BP maps. Here, we present a novel performance evaluation of the operational wildfire simulation system FSim, confronting updated BP maps with subsequent fire activity across the state of California over a 4-year period (2020–2023). Results show strong predictive ability: across 5 equal-area BP classes, 56.7–79.8% of the burned area occurred in the top 20% of mapped area; mean (median) BP values in burned areas were 238.5–348.8% (551.4–880.7%) greater than in unburned areas; differences in empirical cumulative distribution functions of BP for burned/unburned areas were statistically significant; Logarithmic Skill Scores ranged from − 0.072 to 0.389 against two reference models. Findings indicate reliable forecast performance and useful application of up-to-date BP maps, critical to support ongoing wildfire risk mitigation.
Journal Article
Mapping Forest Canopy Fuels in the Western United States with LiDAR–Landsat Covariance
Comprehensive spatial coverage of forest canopy fuels is relied upon by fire management in the US to predict fire behavior, assess risk, and plan forest treatments. Here, a collection of light detection and ranging (LiDAR) datasets from the western US are fused with Landsat-derived spectral indices to map the canopy fuel attributes needed for wildfire predictions: canopy cover (CC), canopy height (CH), canopy base height (CBH), and canopy bulk density (CBD). A single, gradient boosting machine (GBM) model using data from all landscapes is able to characterize these relationships with only small reductions in model performance (mean 0.04 reduction in R²) compared to local GBM models trained on individual landscapes. Model evaluations on independent LiDAR datasets show the single global model outperforming local models (mean 0.24 increase in R²), indicating improved model generality. The global GBM model significantly improves performance over existing LANDFIRE canopy fuels data products (R² ranging from 0.15 to 0.61 vs. −3.94 to −0.374). The ability to automatically update canopy fuels following wildfire disturbance is also evaluated, and results show intuitive reductions in canopy fuels for high and moderate fire severity classes and little to no change for unburned to low fire severity classes. Improved canopy fuel mapping and the ability to apply the same predictive model on an annual basis enhances forest, fuel, and fire management.
Journal Article
Genetic variants in cellular transport do not affect mesalamine response in ulcerative colitis
Mesalamine is commonly used to treat ulcerative colitis (UC). Although mesalamine acts topically, in vitro data suggest that intracellular transport is required for its beneficial effect. Genetic variants in mucosal transport proteins may affect this uptake, but the clinical relevance of these variants has not been studied. The aim of this study was to determine whether variants in genes involved in cellular transport affect the response to mesalamine in UC.
Subjects with UC from a 6-week clinical trial using multiple doses of mesalamine were genotyped using a genome-wide array that included common exome variants. Analysis focused on cellular transport gene variants with a minor allele frequency >5%. Mesalamine response was defined as improvement in Week 6 Physician's Global Assessment (PGA) and non-response as a lack of improvement in Week 6 PGA. Quality control thresholds included an individual genotyping rate of >90%, SNP genotyping rate of >98%, and exclusion for subjects with cryptic relatedness. All included variants met Hardy-Weinberg equilibrium (p>0.001).
457 adults with UC were included with 280 responders and 177 non-responders. There were no common variants in transporter genes that were associated with response to mesalamine. The genetic risk score of responders was similar to that of non-responders (p = 0.18). Genome-wide variants demonstrating a trend towards mesalamine response included ST8SIA5 (p = 1x10-5).
Common transporter gene variants did not affect response to mesalamine in adult UC. The response to mesalamine may be due to rare genetic events or environmental factors such as the intestinal microbiome.
Journal Article
Simulating Daily Large Fire Spread Events in the Northern Front Range, Colorado, USA
Extreme spread events (ESEs), often characterized by high intensity and rapid rates of spread, can overwhelm fire suppression and emergency response capacity, threaten responder and public safety, damage landscapes and communities, and result in high socioeconomic costs and losses. Advances in remote sensing and geospatial analysis provide an improved understanding of observed ESEs and their contributing factors; however, there is a need to improve anticipatory and predictive capabilities to better prepare, mitigate, and respond. Here, leveraging individual-fire day-of-arrival raster outputs from the FSim fire modeling system, we prototype and evaluate methods for the simulation and categorization of ESEs. We describe the analysis of simulation outputs on a case study landscape in Colorado, USA, summarize daily spread event characteristics, threshold and probabilistically benchmark ESEs, spatially depict ESE potential, and describe limitations, extensions, and potential applications of this work. Simulation results generally showed strong alignment with historical patterns of daily growth and the proportion of cumulative area burned in the western US and identified hotspots of high ESE potential. Continued analysis and simulation of ESEs will likely expand the horizon of uses and grow in salience as ESEs become more common.
Journal Article
Use of Pipeline™ embolization device for the treatment of traumatic intracranial pseudoaneurysms: Case series and review of cases from literature
•Traumatic pseudoaneurysms without dissection are complex vascular pathologies.•Pipeline flow-diverting stents can be used to treat traumatic pseudoaneurysms.•Long-term clinical and radiographical follow-up of this treatment is discussed.
Intracranial traumatic pseudoaneurysms (PSA) are a rare but dangerous subtype of cerebral aneurysm. Reports documenting use of flow-diverting stents to treat traumatic intracranial PSAs are few and lack long-term follow-up. To our knowledge, this is the largest case-series to date demonstrating use of Pipeline Endovascular Device (PED) for traumatic intracranial PSAs.
Retrospective review of 8 intracranial traumatic PSAs in 7 patients treated using only PED placement. Patients were followed clinically and angiographically for at least 6 months.
Seven patients with a mean age of 37 years were treated for 8 intracranial pseudo-aneurysms between 2011–2015. Six aneurysms were the result of blunt trauma; 2 were from iatrogenic injury during transsphenoidal surgery. Mean clinical and angiographic follow-up in surviving patients was 15.2 months. In patients with angiographic follow-up, complete occlusion was achieved in all but one patient, who demonstrated near-complete occlusion. No ischemic events or stent-related stenosis were observed. One patient developed a carotid-cavernous fistula after PED, which was successfully retreated with placement of a second PED. There were two mortalities. One was due to suspected microwire perforation remote from the target aneurysm resulting in SAH/IPH. The other was due to a traumatic SDH and brainstem hemorrhage from an unrelated fall during follow-up interval.
Use of PED for treatment of intracerebral PSAs following trauma or iatrogenic injury showed good persistent occlusion, and acceptable complication rate for this high-risk pathology. Risks of this procedure and necessary antiplatelet therapy require appropriate patient selection. Larger prospective studies are warranted.
Journal Article
Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems
Remotely piloted aircraft systems (RPAS) are providing fresh perspectives for the remote sensing of fire. One opportunity is mapping tree crown scorch following fires, which can support science and management. This proof-of-concept shows that crown scorch is distinguishable from uninjured canopy in point clouds derived from low-cost RGB and calibrated RGB-NIR cameras at fine resolutions (centimeter level). The Normalized Difference Vegetation Index (NDVI) provided the most discriminatory spectral data, but a low-cost RGB camera provided useful data as well. Scorch heights from the point cloud closely matched field measurements with a mean absolute error of 0.52 m (n = 29). Voxelization of the point cloud, using a simple threshold NDVI classification as an example, provides a suitable dataset worthy of application and further research. Field-measured scorch heights also showed a relationship to RPAS-thermal-camera-derived fire radiative energy density (FRED) estimates with a Spearman rank correlation of 0.43, but there are many issues still to resolve before robust inference is possible. Mapping fine-scale scorch in 3D with RPAS and SfM photogrammetry is a viable, low-cost option that can support related science and management.
Journal Article
Relationships of Fire Rate of Spread with Spectral and Geometric Features Derived from UAV-Based Photogrammetric Point Clouds
Unmanned aerial vehicles (UAVs) equipped with RGB, multispectral, or thermal cameras have demonstrated their potential to provide high-resolution data before, during, and after wildfires and prescribed burns. Pre-burn point clouds generated through the photogrammetric processing of UAV images contain geometrical and spectral information of vegetation, while active fire imagery allows for deriving fire behavior metrics. This paper focuses on characterizing the relationship between the fire rate of spread (RoS) in prescribed burns and a set of independent geometrical, spectral, and neighborhood variables extracted from UAV-derived point clouds. For this purpose, different flights were performed before and during the prescribed burning in seven grasslands and open forest plots. Variables extracted from the point cloud were interpolated to a grid, which was sized according to the RoS semivariogram. Random Forest regressions were applied, obtaining up to 0.56 of R2 in the different plots studied. Geometric variables from the point clouds, such as planarity and the spectral normalized blue–red difference index (NBRDI), are related to fire RoS. In analyzing the results, the minimum value of the eigenentropy (Eigenentropy_MIN), the mean value of the planarity (Planarity_MEAN), and percentile 75 of the NBRDI (NBRDI_P75) obtained the highest feature importance. Plot-specific analyses unveiled distinct combinations of geometric and spectral features, although certain features, such as Planarity_MEAN and the mean value of the grid obtained from the standard deviation of the distance between points (Dist_std_MEAN), consistently held high importance across all plots. The relationships between pre-burning UAV data and fire RoS can complement meteorological and topographic variables, enhancing wildfire and prescribed burn models.
Journal Article