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165 records · Page 10

Impact of regadenoson-induced myocardial creep on dynamic Rubidium-82 PET myocardial blood flow quantification

Background: Repositioning of the heart during myocardial perfusion imaging (MPI) using Rubidium-82 (Rb-82) PET may occur when using regadenoson. Our aim was to determine the prevalence and the effect of correcting for this myocardial creep on myocardial blood flow (MBF) quantification. Methods: We retrospectively included 119 consecutive patients who underwent dynamic rest- and regadenoson-induced stress MPI using Rb-82 PET. The presence of myocardial creep was visually assessed in the dynamic stress PET series by identifying differences between the automatically drawn myocardium contour and the activity. Uncorrected and corrected stress MBFs were compared for the three vascular territories (LAD, LCX, and RCA) and for the whole myocardium. Results: Myocardial creep was observed in 52% of the patients during stress. Mean MBF values decreased after correction in the RCA from 4.0 to 2.7 mL/min/g (P < 0.001), in the whole myocardium from 2.7 to 2.6 mL/min/g (P = 0.01), and increased in the LAD from 2.5 to 2.6 mL/min/g (P = 0.03) and remained comparable in the LCX (P = 0.3). Conclusions: Myocardial creep is a frequent phenomenon when performing regadenoson-induced stress Rb-82 PET and has a significant impact on MBF values, especially in the RCA territory. As this may hamper diagnostic accuracy, myocardial creep correction seems necessary for reliable quantification. [French] French Abstract: Contexte: Un repositionnement du cœur lors de l’imagerie de perfusion myocardique (MPI) à l’aide de la TEP au rubidium-82 (RB-82) peut survenir lors de l’utilisation du regadenoson. Notre objectif était de déterminer la prévalence et l’effet de la correction du fluage sur la quantification du débit sanguin myocardique (DSM). Méthodes: dans cette étude rétrospective, nous avons inclus 119 patients consécutifs ayant beneficié d’un examen au repos suivi d’un stress pharamacologique au régadénoson en utilisant le RB-82. La présence de fluage myocardique a été évaluée visuellement sur les images TEP de stress dynamique en utilisant les différences entre les contours automatiques et les images myocardiques. Les DSM de stress non corrigés et corrigés ont été comparés pour les trois territoires vasculaires (coronaire gauche-CG, la circonflexe-CX, et coronaire droite-CD) et pour l’ensemble du myocarde. Résultats: le fluage myocardique a été observé chez 52% des patients sur les examens de stress. Les valeurs moyennes de DSM ont diminué après correction dans le territoire de la CD de 4,0 à 2,7 mL/min/g (p < 0,001), dans le myocarde entier de 2,7 à 2,6 mL/min/g (p = 0,01) et augmenté dans le territoire de la CG de 2,5 à 2,6 mL/min/g (p = 0,03) et est resté comparable dans le territoire de la CX (p = 0,3). Conclusions: le fluage myocardique est un phénomène fréquent lors de l’exécution du stress phramacologique au régadénoson à l’aide du RB-82. Il a un impact significatif sur les valeurs de DSM, en particulier dans le territoire de la CD. La correction du fluage myocardique semble donc nécessaire pour une quantification fiable des flux coronariens. [Spanish] Spanish Abstract: Antecedentes: El movimiento del corazón durante la imagen de perfusión miocárdica usando Rubidio-82 (Rb-82) PET puede ocurrir cuando se usa regadenosón. Nuestro enfoque fue determinar la prevalencia y efecto de la corrección de este Artefacto de movimiento en la cuantificación del flujo sanguíneo miocárdico. Métodos: Se incluyeron de forma retrospectiva 119 pacientes que se realizaron estudio dinámico en reposo y estudio de perfusión miocárdica en estrés inducido por regadenosón usando Rb-82 PET. La presencia de el artefacto de movimiento fue evaluado visualmente en el estudio en serie de PET dinámico en estrés identificando las diferencias entre el contorno miocárdico dibujado automáticamente y la actividad. La perfusión miocárdica en estrés corregida y sin corregir se compararon para los tres territorios vasculares (Descendente Anterior, Circunfleja, Coronaria Derecha) y para todo el miocardio. Resultados: El artefacto de movimiento miocárdico se observo en un 52% de los pacientes durante el estrés. El promedio de los valores de flujo sanguíneo miocárdico disminuyen después de la corrección en la arteria coronaria derecha de 4.0 a 2.7 ml/min/g (p < 0.001), en todo el miocardio de 2.7 a 2.6 mL/min/g (p = 0.01) y un aumento en la arteria descendente anterior de 2.5 a 2.6 mL/min/g (p = 0.03) y se mantuvo comparable en la arteria circunfleja (p = 0.3). Conclusiones: El artefacto de movimiento miocárdico es un fenómeno frecuente cuando se realiza la prueba de estrés inducido con regadenosón Rb-82 PET y tiene un impacto significativo en los valores de flujo sanguíneo miocárdico, principalmente en el territorio de la coronaria derecha. Esto puede disminuir la precisión diagnostica, la corección del artefacto de movimiento es necesario para una cuantificación confiable. [Chinese] Chinese Abstract: 背景: 铷-82 (Rb-82) PET心肌灌注成像 (MPI) 过程在使用类伽腺苷时可能会发生心脏重定位。我们的目的是确定心肌蠕动 (myocardial creep) 校正对心肌血流灌注定量的影响及其普遍性。 方法: 我们连续回顾了119 名使用 Rb-82 PET 进行动态的静息与类伽腺苷负荷MPI的患者。通过识别自动绘制的心肌轮廓和心肌活动之间的差异, 在动态负荷 PET 检查中肉眼评估心肌蠕动的存在。分别在已校正和未校正的负荷 MBF上, 对三个血管区域 (LAD, LCX, RCA) 和整个心肌灌注情况进行比较。 结果: 负荷检查中, 52% 的患者观察到心肌蠕动。 RCA 校正后平均MBF值从4.0降至 2.7 mL / min / g (p <0.001), 整个心肌从 2.7降至 2.6 mL / min / g (p = 0.01) , LAD 从 2.5 升至 2.6mL / min / g (p = 0.03) 并且在LCX中保持不变 (p = 0.3) 。 结论: 类伽腺苷负荷 Rb-82 PET 检查中, 心肌蠕动是一种常见的现象, 并且对 MBF 值有显著影响, 特别在 RCA 区域。这可能妨碍诊断准确性, 因此心肌蠕动校正是准确定量的必要条件。.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

[Low-Frequency Flow Oscillation

The results of the research conducted under this grant are presented in detail in three Master theses, by Heinrich, Balow, and Broeren. Additional analysis of the experimental data can be found in two AIAA Journal articles and two conference papers. Citations for all of the studies' publications can be found in the bibliography which is attached. The objective of Heinrich's study was to document the low-frequency flow oscillation on the LRN-1007 airfoil, which had been previously observed at low Reynolds number, to determine its origin, and explore the phenomenon at higher Reynolds number. Heinrich performed detailed flow visualization on the airfoil using surface fluorescent oil and laser-sheet off-body visualization. A large leading-edge separation bubble and trailing-edge separation was identified on the airfoil just prior to the onset of the unsteady stall flow oscillation. From the laser-sheet data, the unsteady flow appeared as a massive boundary-layer separation followed by flow reattachment. Hot-wire data were taken in the wake to identify the presence of the flow oscillation and the dominant frequency. The oscillation was found in the flow from a Reynolds number of 0.3 to 1.3 x 10 exp 6. The Strouhal number based on airfoil projected height was nominally 0.02 and increased slightly with increasing Reynolds number and significantly with increasing airfoil angle of attack. Balow focused his research on the leading-edge separation bubble which was hypothesized to be the origin of the low-frequency oscillation. Initially, experimental measurements in the bubble at the onset of the low-frequency oscillation were attempted to study the characteristics of the bubble and explain possible relationships to the shear-layer-flapping phenomena. Unfortunately, the bubble proved to be extremely sensitive to the probe interference and it drastically reduced the size of the bubble. These detailed measurements were then abandoned by Balow. However, this led to a series of tests where the leading-edge bubble and trailing-edge separation were altered and the affect on the flow-oscillation studied. Balow found that by tripping the airfoil boundary-layer with "zigzag" tape ahead of bubble separation, the bubble was effectively eliminated mid the oscillation suppressed. Wake survey drag measurements showed a drastic reduction in airfoil drag when the bubble and oscillation were eliminated. Using the "zigzag" tape, the trailing-edge separation was moved downstream approximately 5 percent chord. This was found to reduce the amplitude of the oscillation, particularly in the onset stage at low angle of attack (around 14 degrees). Through detailed analysis of the wake behind the airfoil during the unsteady flow oscillation, Balow provided a better understanding of the wake flowfield. Broeren studied the oscillating flowfield in detail at Reynolds number equal 3 x 10 exp 5 and an angle of attack of 15 degrees using laser Doppler velocimetry (LDV). Two-dimensional LDV data were acquired at 687 grid points above the model upper surface while hot-wire data were taken simultaneously in the wake. Using the hot-wire signal, the LDV data were phase averaged into 24 bins to represent a single ensemble average of one oscillation cycle. The velocity data showed a flowfield oscillation that could be divided into three flow regimes. In the first regime, the flow over the airfoil was completely separated initially, the flowfield reattached from the leading edge and the reattachment point moved downstream with increasing time or phase. Broeren referred to this as the reattachment regime. The bubble development regime followed, where a leading-edge separation bubble formed at the leading edge and grew with increasing time. During the initial part of this regime the trailing-edge separation continued to move downstream. However, during the last 30 degrees of phase the trailing-edge separation moved rapidly forward and appeared to merge with the leading-edge bubble. During the third regime, the separation regime, the flow was segmented from the airfoil leading edge and did not reattach to the airfoil surface. The reverse flow was seen to grow in vertical extent up from the model surface as the phase increased. Next reattachment began again at the leading edge signaling the start of the reattachment regime, and so the cycle continued. From Broeren's work, the details of the unsteady flowfield over the airfoil were seen for the first time. From this research a great deal has been learned about the low-frequency flow oscillation which naturally occurs on the LRN-1007 airfoil near stall. The oscillation was seen to persist at higher Reynolds number, the dependence of the Strouhal number on angle of attack and Reynolds number were discovered, the critical role played by the laminar bubble was shown and the entire upper surface flowfield during a flow oscillation cycle was measured and analyzed. What still eludes understanding is the scaling of the flow oscillation and why certain airfoils, such as the LRN, have a very strong low-frequency mode and other airfoils exhibit no organized low-frequency oscillation at all.

Bragg, Michael B.↗

Water Security Toolkit User Manual Version 1.2.

The Water Security Toolkit (WST) is a suite of open source software tools that can be used by water utilities to create response strategies to reduce the impact of contamination in a water distribution network . WST includes hydraulic and water quality modeling software , optimizati on methodologies , and visualization tools to identify: (1) sensor locations to detect contamination, (2) locations in the network in which the contamination was introduced, (3) hydrants to remove contaminated water from the distribution system, (4) locations in the network to inject decontamination agents to inactivate, remove, or destroy contaminants, (5) locations in the network to take grab sample s to help identify the source of contamination and (6) valves to close in order to isolate contaminate d areas of the network. This user manual describes the different components of WST , along w ith examples and case studies. License Notice The Water Security Toolkit (WST) v.1.2 Copyright c 2012 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000, there is a non-exclusive license for use of this work by or on behalf of the U.S. government. This software is distributed under the Revised BSD License (see below). In addition, WST leverages a variety of third-party software packages, which have separate licensing policies: Acro Revised BSD License argparse Python Software Foundation License Boost Boost Software License Coopr Revised BSD License Coverage BSD License Distribute Python Software Foundation License / Zope Public License EPANET Public Domain EPANET-ERD Revised BSD License EPANET-MSX GNU Lesser General Public License (LGPL) v.3 gcovr Revised BSD License GRASP AT&T Commercial License for noncommercial use; includes randomsample and sideconstraints executable files LZMA SDK Public Domain nose GNU Lesser General Public License (LGPL) v.2.1 ordereddict MIT License pip MIT License PLY BSD License PyEPANET Revised BSD License Pyro MIT License PyUtilib Revised BSD License PyYAML MIT License runpy2 Python Software Foundation License setuptools Python Software Foundation License / Zope Public License six MIT License TinyXML zlib License unittest2 BSD License Utilib Revised BSD License virtualenv MIT License Vol Common Public License vpykit Revised BSD License Additionally, some precompiled WST binary distributions might bundle other third-party executables files: Coliny Revised BSD License (part of Acro project) Dakota GNU Lesser General Public License (LGPL) v.2.1 PICO Revised BSD License (part of Acro project) i Revised BSD License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of Sandia National Laboratories nor Sandia Corporation nor the names of its con- tributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IM- PLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUD- ING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ii Acknowledgements This work was supported by the U.S. Environmental Protection Agency through its Office of Research and Development (Interagency Agreement # DW8992192801). The material in this document has been subject to technical and policy review by the U.S. EPA, and approved for publication. The views expressed by individual authors, however, are their own, and do not necessarily reflect those of the U.S. Environmental Protection Agency. Mention of trade names, products, or services does not convey official U.S. EPA approval, endorsement, or recommendation. The Water Security Toolkit is an extension of the Threat Ensemble Vulnerability Assessment-Sensor Place- ment Optimization Tool (TEVA-SPOT), which was also developed with funding from the U.S. Environ- mental Protection Agency through its Office of Research and Development (Interagency Agreement # DW8992192801). The authors acknowledge the following individuals for their contributions to the devel- opment of TEVA-SPOT: Jonathan Berry (Sandia National Laboratories), Erik Boman (Sandia National Laboratories), Lee Ann Riesen (Sandia National Laboratories), James Uber (University of Cincinnati), and Jean-Paul Watson (Sandia National Laboratories). iii Acronyms ATUS American Time-Use Survey BLAS Basic linear algebra sub-routines CFU Colony-forming unit CVAR Conditional value at risk CWS Contamination warning system EA Evolutionary algorithm EDS Event detection system EPA U.S. Environmental Protection Agency EC Extent of Contamination ERD EPANET results database file GLPK GNU Linear Programming Kit GRASP Greedy randomized adaptive sampling process HEX Hexadecimal HTML HyperText markup language INP EPANET input file LP Linear program MC Mass consumed MILP Mixed integer linear program MIP Mixed integer program MSX Multi-species extension for EPANET NFD Number of failed detections NS Number of sensors NZD Non-zero demand PD Population dosed PE Population exposed PK Population killed TAI Threat assessment input file TCE Tailed-conditioned expectation TD Time to detection TEC Timed extent of contamination TEVA Threat ensemble vulnerability assessment TSB Tryptic soy broth TSG Threat scenario generation file TSI Threat simulation input file VAR Value at risk VC Volume consumed WST Water Security Toolkit YML YAML configuration file format for WST iv Symbols Notation Definition Example { , } set brackets { 1,2,3 } means a set containing the values 1,2, and 3. [?] is an element of s [?] S means that s is an element of the set S . [?] for all s = 1 [?] s [?] S means that the statement s = 1 is true for all s in set S . P summation P n i =1 s i means s 1 + s 2 + * * * + s n . \ set minus S \ T means the set that contains all those elements of S that are not in set T . %7C given %7C is used to define conditional probability. P ( s %7C t ) means the prob- ability of s occurring given that t occurs. %7C ... %7C cardinality Cardinality of a set is the number of elements of the set. If set S = { 2,4,6 } , then %7C S %7C = 3. v

Klise, Katherine A.↗