Using GES DISC Data to Study Kilauea Volcano of 2018

Kilauea volcano in Hawaii which erupted in early May 2018 injected massive amount of SO2 and ash into the atmosphere. The lava flow during the eruption destroyed many home and neighborhoods. The SO2 plume during the eruption of Kilauea volcano is analyzed from May to August 2018 using multiple satellite products such as Level 2 TROPspheric Monitoring Instrument (TROPOMI) and Level 3 Ozone Monitoring Instrument (OMI) from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). GES DISC hosts multi-disciplinary Earth science data sets that can be used to analyze natural disasters, such as the Kilauea volcano. Additionally, GES DISC's Giovanni tool can be used to visualize these data. We acquired OMI through the subsetting function, which is processed by the GES DISC in-house developed backend software Level3/4 Regrider and Subsetter (L34RS) and TROPOMI using OPeNDAP.Data from the OMI OMSO2e product showed elevated levels of SO2 amounts during the eruption between May to August 2018. Similarly, ground-based stations at Hawaii Volcanoes National Park recorded higher SO2 concentrations during the same time period. This study uses wind direction from Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) to analyze the transport and dispersion of SO2 plume and map lava flows from the volcano using thermal images from Visible Infrared Imaging Radiometer Suite (VIIRS). Furthermore, satellite observations combined with socioeconomic and public health data are used to analyze its impact in public health

A Simplified Motion Model for Estimating Respiratory Motion from Orbiting Views

We have shown previously that the internal motion caused by a patient’s breathing can be estimated from a sequence of slowly rotating 2D cone-beam X-ray projection views and a static prior of of the patient’s anatomy.1, 2 The estimator iteratively updates a parametric 3D motion model so that the modeled projection views of the deformed reference volume best match the measured projection views. Complicated motion models with many degrees of freedom may better describe the real motion, but the optimizations assiciated with them may overfit noise and may be easily trapped by local minima due to a large number of parameters. For the latter problem, we believe it can be solved by offering the optimization algorithm a good starting point within the valley containing the global minimum point. Therefore, we propose to start the motion estimation with a simplified motion model, in which we assume the displacement of each voxel at any time is proportional to the full movement of that voxel from extreme exhale to extreme inhale. We first obtain the full motion by registering two breathhold CT volumes at end-expiration and end-inspiration. We then estimate a sequence of scalar displacement proportionality parameters. Thus the goal simplifies to finding a motion amplitude signal. This estimation problem can be solved quickly using the exhale reference volume and projection views with coarse (downsampled) resolution, while still providing acceptable estimation accuracy. The estimated simple motion then can be used to initialize a more complicated motion estimator.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85923/1/Fessler224.pd

Respiratory Motion Estimation from Slowly Rotating X-Ray Projections

As radiotherapy has become increasingly conformal, geometric uncertainties caused by breathing and organ motion have become an important issue. Accurate motion estimates may lead to improved treatment planning and dose calculation in radiation therapy. However, respiratory motion is difficult to study by conventional X-ray CT imaging since object motion causes inconsistent projection views leading to artifacts in reconstructed images. We propose to estimate the parameters of a nonrigid motion model from a set of projection views of the thorax that are acquired using a slowly rotating cone-beam CT scanner, such as a radiotherapy simulator. We use a conventionally reconstructed 3D thorax image, acquired by breath-hold CT, as a reference volume. We represent respiratory motion using a flexible parametric nonrigid motion model based on B-splines. The motion parameters are estimated by optimizing a regularized cost function that includes the squared error between the measured projection views and the reprojections of the deformed reference image. Preliminary 2D simulation results show that there is good agreement between the estimated motion and the true motion.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85878/1/Fessler197.pd

Estimating 3-D Respiratory Motion From Orbiting Views by Tomographic Image Registration

Respiratory motion remains a significant source of errors in treatment planning for the thorax and upper abdomen. Recently, we proposed a method to estimate two-dimensional (2-D) object motion from a sequence of slowly rotating X-ray projection views, which we called deformation from orbiting views (DOVs). In this method, we model the motion as a time varying deformation of a static prior of the anatomy. We then optimize the parameters of the motion model by maximizing the similarity between the modeled and actual projection views. This paper extends the method to full three-dimensional (3-D) motion and cone-beam projection views. We address several practical issues for using a cone-beam computed tomography (CBCT) scanner that is integrated in a radiotherapy system, such as the effects of Compton scatter and the limited gantry rotation for one breathing cycle. We also present simulation and phantom results to illustrate the performance of this method.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85995/1/Fessler38.pd

Estimating 3D Respiratory Motion from Orbiting Views

This paper describes a method for estimating 3D respiratory motion so as to characterize tumor motion. This method uses two sets of measurements. One is a reference thorax volume obtained from a conventional fast CT scanner under breath-hold condition. The other is a sequence of projection views of the same patient (acquired at treatment time) using a slowly rotating cone-beam system (1 minute per rotation) during free breathing. We named this method deformation from orbiting views (DOV). Breathing motion over the entire acquisition period is estimated by deforming the reference volume through time so that its projections best match the measured projection views. The nonrigid breathing motion is described by a B-spline based deformation model. The parameters of this model are estimated by minimizing a regularized squared error cost function, using a conjugate gradient descent algorithm. Performance of this approach was evaluated by simulation. Results showed good agreement between the estimated and synthesized motion, with a mean absolute error of 1.63 mm. Relatively larger errors tended to occur in uniform regions, which would not have significant effects on generating deformed volumes based on the estimated motion. The results indicate that it is feasible to estimate realistic nonrigid motion from a sequence of slowly rotating cone beam projection views.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85996/1/Fessler214.pd

Iterative Sorting for 4DCT Images Based ON Internal Anatomy Motion

Geometric uncertainties caused by respiratory motion complicate radiotherapy treatment planning. Therefore 4D CT imaging is important in characterizing anatomy motion during breathing. Current 4D CT imaging techniques using multislice CT scanners involve multiple scans at several axial positions and retrospective sorting processes. Most sorting methods are based on externally monitored signals recorded by external monitoring instruments, which may not always accurately catch the actual breathing status and may lead to severe discontinuity artifacts in the sorted CT volumes. We propose a method to reconstruct time-resolved CT volumes based on internal motion to avoid the inaccuracies caused by external breathing signals. In our method, we iteratively sort the 4D CT slices using internal motion based breathing indices. In each iteration, respiratory motion is estimated by updating a motion model to best match a deformed reference volume to each moving multi-slice sub-volumes. The breathing indices as well as the reference volumes are refined for each iteration based on the currently estimated respiratory motion. An example is presented to illustrate the feasibility of our 4D CT sorting method without using any external motion monitoring systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85803/1/Fessler229.pd

Size-resolved particulate matter composition in Beijing during pollution and dust events

Each spring, Beijing, China, experiences dust storms which cause high particulate matter concentrations. Beijing also has many anthropogenic sources of particulate matter including the large Capitol Steel Company. On the basis of measured size segregated, speciated particulate matter concentrations, and calculated back trajectories, three types of pollution events occurred in Beijing from 22 March to 1 April 2001: dust storms, urban pollution events, and an industrial pollution event. For each event type, the source of each measured element is determined to be soil or anthropogenic and profiles are created that characterize the particulate matter composition. Dust storms are associated with winds traveling from desert regions and high total suspended particle (TSP) and PM2.5 concentrations. Sixty-two percent of TSP is due to elements with oxides and 98% of that is from soil. Urban pollution events have smaller particulate concentrations but 49% of the TSP is from soil, indicating that dust is a major component of the particulate matter even when there is not an active dust storm. The industrial pollution event is characterized by winds from the southwest, the location of the Capitol Steel Company, and high particulate concentrations. PM2.5 mass and acidic ion concentrations are highest during the industrial pollution event as are Mn, Zn, As, Rb, Cd, Cs and Pb concentrations. These elements can be used as tracers for industrial pollution from the steel mill complex. The industrial pollution is potentially more detrimental to human health than dust storms due to higher PM2.5 concentrations and higher acidic ion and toxic particulate matter concentrations

Randomised Comparison of the AMBU AuraOnce Laryngeal Mask and the LMA Unique Laryngeal Mask Airway in Spontaneously Breathing Adults

We conducted a randomised single-blind controlled trial comparing the LMA-Unique (LMAU) and the AMBU AuraOnce (AMBU) disposable laryngeal mask in spontaneously breathing adult patients undergoing general anaesthesia. Eighty-two adult patients (ASA status I–IV) were randomly allocated to receive the LMAU or AMBU and were blinded to device selection. Patients received a standardized anesthetic and all airway devices were inserted by trained anaesthetists. Size selection was guided by manufacturer recommendations. All data were collected by a single, unblinded observer. When compared with the LMAU, the AMBU produced significantly higher airway sealing pressures (AMBU 20 ± 6; LMAU 15 ± 7 cm H2O; P = 0.001). There was no statistical difference between the two devices for overall success rate, insertion time, number of adjustments, laryngeal alignment, blood-staining, and sore throat (P ≥ 0.05). The AMBU AuraOnce disposable laryngeal mask provided a higher oropharyngeal leak pressure compared to the LMA Unique in spontaneously breathing adult patients