Quantitative Analysis of Radiation-Associated Parenchymal Lung Change

Radiation-induced lung damage (RILD) is a common consequence of thoracic radiotherapy (RT). We present here a novel classification of the parenchymal features of RILD. We developed a deep learning algorithm (DLA) to automate the delineation of 5 classes of parenchymal texture of increasing density. 200 scans were used to train and validate the network and the remaining 30 scans were used as a hold-out test set. The DLA automatically labelled the data with Dice Scores of 0.98, 0.43, 0.26, 0.47 and 0.92 for the 5 respective classes. Qualitative evaluation showed that the automated labels were acceptable in over 80% of cases for all tissue classes, and achieved similar ratings to the manual labels. Lung registration was performed and the effect of radiation dose on each tissue class and correlation with respiratory outcomes was assessed. The change in volume of each tissue class over time generated by manual and automated segmentation was calculated. The 5 parenchymal classes showed distinct temporal patterns We quantified the volumetric change in textures after radiotherapy and correlate these with radiotherapy dose and respiratory outcomes. The effect of local dose on tissue class revealed a strong dose-dependent relationship We have developed a novel classification of parenchymal changes associated with RILD that show a convincing dose relationship. The tissue classes are related to both global and local dose metrics, and have a distinct evolution over time. Although less strong, there is a relationship between the radiological texture changes we can measure and respiratory outcomes, particularly the MRC score which directly represents a patient’s functional status. We have demonstrated the potential of using our approach to analyse and understand the morphological and functional evolution of RILD in greater detail than previously possible

Corporate Acquisition Criteria: New Evidence

P.R. Chandy is an Assistant Professor of Finance at North Texas State University. Richard T. Cherry is Professor of Finance, College of Business, Lamar University

Space Efficient Breadth-First and Level Traversals of Consistent Global States of Parallel Programs

Enumerating consistent global states of a computation is a fundamental problem in parallel computing with applications to debug- ging, testing and runtime verification of parallel programs. Breadth-first search (BFS) enumeration is especially useful for these applications as it finds an erroneous consistent global state with the least number of events possible. The total number of executed events in a global state is called its rank. BFS also allows enumeration of all global states of a given rank or within a range of ranks. If a computation on n processes has m events per process on average, then the traditional BFS (Cooper-Marzullo and its variants) requires $\mathcal{O}(\frac{m^{n-1}}{n})$ space in the worst case, whereas ou r algorithm performs the BFS requires $\mathcal{O}(m^2n^2)$ space. Thus, we reduce the space complexity for BFS enumeration of consistent global states exponentially. and give the first polynomial space algorithm for this task. In our experimental evaluation of seven benchmarks, traditional BFS fails in many cases by exhausting the 2 GB heap space allowed to the JVM. In contrast, our implementation uses less than 60 MB memory and is also faster in many cases

Salmonella choleraesuis subsp. indica serovar bornheim causing urinary tract infection

An unusual Salmonella species, S. choleraesuis subsp. indica serovar bornheim, was isolated from the urine of a patient with aplastic anemia, diabetes mellitus, and a healed urethral injury. An immune response to this isolate was demonstrated by whole-bacterial-cell agglutination

Dense Building Instrumentation Application for City-Wide Structural Health Monitoring

The Community Seismic Network (CSN) has partnered with the NASA Jet Propulsion Laboratory (JPL) to initiate a campus-wide structural monitoring program of all buildings on the premises. The JPL campus serves as a proxy for a densely instrumented urban city with localized vibration measurements collected throughout the free-field and built environment. Instrumenting the entire campus provides dense measurements in a horizontal geospatial sense for soil response; in addition five buildings have been instrumented on every floor of the structure. Each building has a unique structural system as well as varied amounts of structural information via structural drawings, making several levels of assessment and evaluation possible. Computational studies with focus on damage detection applied to the campus structural network are demonstrated for a collection of buildings. For campus-wide real-time and post-event evaluation, ground and building response products using CSN data are illustrating the usefulness of higher spatial resolution compared to what was previously typical with sparser instrumentation

A Novel and Automated Approach to Classify Radiation Induced Lung Tissue Damage on CT Scans

Radiation-induced lung damage (RILD) is a common side effect of radiotherapy (RT). The ability to automatically segment, classify, and quantify different types of lung parenchymal change is essential to uncover underlying patterns of RILD and their evolution over time. A RILD dedicated tissue classification system was developed to describe lung parenchymal tissue changes on a voxel-wise level. The classification system was automated for segmentation of five lung tissue classes on computed tomography (CT) scans that described incrementally increasing tissue density, ranging from normal lung (Class 1) to consolidation (Class 5). For ground truth data generation, we employed a two-stage data annotation approach, akin to active learning. Manual segmentation was used to train a stage one auto-segmentation method. These results were manually refined and used to train the stage two auto-segmentation algorithm. The stage two auto-segmentation algorithm was an ensemble of six 2D Unets using different loss functions and numbers of input channels. The development dataset used in this study consisted of 40 cases, each with a pre-radiotherapy, 3-, 6-, 12-, and 24-month follow-up CT scans (n = 200 CT scans). The method was assessed on a hold-out test dataset of 6 cases (n = 30 CT scans). The global Dice score coefficients (DSC) achieved for each tissue class were: Class (1) 99% and 98%, Class (2) 71% and 44%, Class (3) 56% and 26%, Class (4) 79% and 47%, and Class (5) 96% and 92%, for development and test subsets, respectively. The lowest values for the test subsets were caused by imaging artefacts or reflected subgroups that occurred infrequently and with smaller overall parenchymal volumes. We performed qualitative evaluation on the test dataset presenting manual and auto-segmentation to a blinded independent radiologist to rate them as 'acceptable', 'minor disagreement' or 'major disagreement'. The auto-segmentation ratings were similar to the manual segmentation, both having approximately 90% of cases rated as acceptable. The proposed framework for auto-segmentation of different lung tissue classes produces acceptable results in the majority of cases and has the potential to facilitate future large studies of RILD

Reverse Remodeling of the Atria After Treatment of Chronic Stretch in Humans Implications for the Atrial Fibrillation Substrate

ObjectivesThe aim of this report was to study the effect of chronic stretch reversal on the electrophysiological characteristics of the atria in humans.BackgroundAtrial stretch is an important determinant for atrial fibrillation. Whether relief of stretch reverses the substrate predisposed to atrial fibrillation is unknown.MethodsTwenty-one patients with mitral stenosis undergoing mitral commissurotomy (MC) were studied before and after intervention. Catheters were placed at multiple sites in the right atrium (RA) and sequentially within the left atrium (LA) to determine: effective refractory period (ERP) at 10 sites (600 and 450 ms) and P-wave duration (PWD). Bi-atrial electroanatomic maps determined conduction velocity (CV) and voltage. In 14 patients, RA studies were repeated ≥6 months after MC.ResultsImmediately after MC, there was significant increase in mitral valve area (2.1 ± 0.2 cm2, p < 0.0001) with decrease in LA (23 ± 7 mm Hg to 10 ± 4 mm Hg, p < 0.0001) and pulmonary arterial pressures (38 ± 16 mm Hg to 27 ± 12 mm Hg, p < 0.0001) and LA volume (75 ± 20 ml to 52 ± 18 ml, p < 0.0001). This was associated with reduction in PWD (139 ± 19 ms to 135 ± 20 ms, p = 0.047), increase in CV (LA: 1.3 ± 0.3 mm/ms to 1.7 ± 0.2 mm/ms, p = 0.006; and RA: 1.0 ± 0.1 mm/ms to 1.3 ± 0.3 mm/ms, p = 0.002) and voltage (LA: 1.7 ± 0.6 mV to 2.5 ± 1.0 mV, p = 0.005; and RA: 1.8 ± 0.6 mV to 2.2 ± 0.7 mV, p = 0.09), and no change in ERP. Late after MC, mitral valve area remained at 2.1 ± 0.3 cm2 (p = 0.7) but with further decrease in PWD (113 ± 19 ms, p = 0.04) and RA ERP (at 600 ms, p < 0.0001), with increase in CV (1.0 ± 0.1 mm/ms to 1.3 ± 0.2 mm/ms, p = 0.006) and voltage (1.8 ± 0.7 mV to 2.8 ± 0.6 mV, p = 0.002).ConclusionsThe atrial electrophysiologic and electroanatomic abnormalities that result from chronic stretch due to MS reverses after MC. These observations suggest that the substrate predisposing to atrial arrhythmias might be reversed

Community seismic network and localized earthquake situational awareness

Community-hosted seismic networks are a solution to the need for large numbers of sensors to operate over a seismically active region in order to accurately measure the size and location of an earthquake, assess resulting damage, and provide alerts. The Community Seismic Network is one such strong-motion network, currently comprising hundreds of elements located in California. It consists of low-cost, three-component, MEMS accelerometers capable of recording accelerations up to twice the level of gravity. The primary product of the network is to produce measurements of shaking of the ground and multiple locations of every upper floor in buildings, in the seconds during and following a major earthquake. Each sensor uses a small, dedicated ARM processor computer running Linux, and analyzes time series data in real time at hundreds of samples per second. The network reports on shaking parameters that indicate intensity of the structural response levels such as maximum floor acceleration and velocity, displacement of a floor in a building, as well as data products that depend on the response time histories. To do this, Cloud computing has been expanded through the use of statically defined subsets of sensors called cloudlets. These are smaller subsets of similar sensors that carry out customized calculations for those locations. The measurements are reported as rapidly as possible following an earthquake so that they may be incorporated into structural diagnosis and prognosis applications that can be used by first responders to prioritize their initial disaster management efforts. The cloudlet displays are customized for specific buildings and they show in real time: instantaneous displacement, inter-story drift, and resonant frequency and mode shapes using system identification software tools. The real-time display products are useful for decision-making about whether the potential for damage exists, what level of damage may have occurred and where, and whether total business disruption is necessary. City-wide dense monitoring makes it possible for emergency response managers to prioritize the target locations requiring first response on a block-by-block scale based on reports of shaking intensity

Sequence analysis of human T cell lymphotropic virus type I strains from southern India: gene amplification and direct sequencing from whole blood blotted onto filter paper

Human T cell lymphotropic virus type I (HTLV-I) infection in India has been found to be associated with adult T cell leukaemia/lymphoma (ATLL) and HTLV-I-associated myelopathy/tropical spastic paraparesis (HAM/TSP) among life-long residents of southern India. To examine the heterogeneity of HTLV-I strains from southern India and to determine their relationship with the sequence variants of HTLV-I from Melanesia, 1149 nucleotides spanning selected regions of the HTLV-I gag, pol, env and pX genes were amplified and directly sequenced from DNA extracted from whole blood blotted onto filter paper and from peripheral blood mononuclear cells, obtained from one patient with HAM/TSP, two with ATLL and eight asymptomatic carriers from Andhra Pradesh, Kerala and Tamil Nadu. Sequence alignments and comparisons indicated that the 11 HTLV-I strains from southern India were 99.2% to 100% identical among themselves and 98.7% to 100% identical to the Japanese prototype HTLV-I ATK. The majority of base substitutions were transitions and silent. No frameshifts, insertions, deletions or possibly disease-specific base changes were found in the regions sequenced. The observed clustering of the Indian HTLV-I strains with those from Japan, as determined by the maximum parsimony method, suggested a common source of HTLV-I infection with subsequent parallel evolution. Amplification of DNA from blood specimens collected on filter paper may be useful for the study of other blood-borne pathogens

Automatic generation of hardware/software interfaces

Enabling new applications for mobile devices often requires the use of specialized hardware to reduce power consumption. Because of time-to-market pressure, current design methodologies for embedded applications require an early partitioning of the design, allowing the hardware and software to be developed simultaneously, each adhering to a rigid interface contract. This approach is problematic for two reasons: (1) a detailed hardware-software interface is difficult to specify until one is deep into the design process, and (2) it prevents the later migration of functionality across the interface motivated by efficiency concerns or the addition of features. We address this problem using the Bluespec Codesign Language~(BCL) which permits the designer to specify the hardware-software partition in the source code, allowing the compiler to synthesize efficient software and hardware along with transactors for communication between the partitions. The movement of functionality across the hardware-software boundary is accomplished by simply specifying a new partitioning, and since the compiler automatically generates the desired interface specifications, it eliminates yet another error-prone design task. In this paper we present BCL, an extension of a commercially available hardware design language (Bluespec SystemVerilog), a new software compiling scheme, and preliminary results generated using our compiler for various hardware-software decompositions of an Ogg Vorbis audio decoder, and a ray-tracing application.National Science Foundation (U.S.) (NSF (#CCF-0541164))National Research Foundation of Korea (grant from the Korean Government (MEST) (#R33-10095)