Lazy Luna: extendible software for multilevel reader comparison in cardiovascular magnetic resonance imaging

BACKGROUND AND OBJECTIVES: Cardiovascular Magnetic Resonance (CMR) imaging is a growing field with increasing diagnostic utility in clinical routine. Quantitative diagnostic parameters are typically calculated based on contours or points provided by readers, e.g. natural intelligences (NI) such as clinicians or researchers, and artificial intelligences (AI). As clinical applications multiply, evaluating the precision and reproducibility of quantitative parameters becomes increasingly important. Although segmentation challenges for AIs and guidelines for clinicians provide quality assessments and regulation, the methods ought to be combined and streamlined for clinical applications. The goal of the developed software, Lazy Luna (LL), is to offer a flexible evaluation tool that is readily extendible to new sequences and scientific endeavours. METHODS: An interface was designed for LL, which allows for comparing annotated CMR images. Geometric objects ensure precise calculations of metric values and clinical results regardless of whether annotations originate from AIs or NIs. A graphical user interface (GUI) is provided to make the software available to non-programmers. The GUI allows for an interactive inspection of image datasets as well as implementing tracing procedures, which follow statistical reader differences in clinical results to their origins in individual image contours. The backend software builds on a set of meta-classes, which can be extended to new imaging sequences and clinical parameters. Following an agile development procedure with clinical feedback allows for a quick implementation of new classes, figures and tables for evaluation. RESULTS: Two application cases present LL's extendibility to clinical evaluation and AI development contexts. The first concerns T1 parametric mapping images segmented by two expert readers. Quantitative result differences are traced to reveal typical segmentation dissimilarities from which these differences originate. The meta-classes are extended to this new application scenario. The second applies to the open source Late Gadolinium Enhancement (LGE) quantification challenge for AI developers “Emidec”, which illustrates LL's usability as open source software. CONCLUSION: The presented software Lazy Luna allows for an automated multilevel comparison of readers as well as identifying qualitative reasons for statistical reader differences. The open source software LL can be extended to new application cases in the future

Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imaging

Cardiovascular magnetic resonance imaging is the gold standard for cardiac function assessment. Quantification of clinical results (CR) requires precise segmentation. Clinicians statistically compare CRs to ensure reproducibility. Convolutional Neural Network developers compare their results via metrics. Aim: Introducing software capable of automatic multilevel comparison. A multilevel analysis covering segmentations and CRs builds on a generic software backend. Metrics and CRs are calculated with geometric accuracy. Segmentations and CRs are connected to track errors and their effects. An interactive GUI makes the software accessible to different users. The software's multilevel comparison was tested on a use case based on cardiac function assessment. The software shows good reader agreement in CRs and segmentation metrics (Dice > 90%). Decomposing differences by cardiac position revealed excellent agreement in midventricular slices: > 90% but poorer segmentations in apical (> 71%) and basal slices (> 74%). Further decomposition by contour type locates the largest millilitre differences in the basal right cavity (> 3 ml). Visual inspection shows these differences being caused by different basal slice choices. The software illuminated reader differences on several levels. Producing spreadsheets and figures concerning metric values and CR differences was automated. A multilevel reader comparison is feasible and extendable to other cardiac structures in the future

The human brain response to dental pain relief

Local anesthesia has made dental treatment more comfortable since 1884, but little is known about associated brain mechanisms. Functional magnetic resonance imaging is a modern neuroimaging tool widely used for investigating human brain activity related to sensory perceptions, including pain. Most brain regions that respond to experimental noxious stimuli have recently been found to react not only to nociception alone, but also to visual, auditory, and other stimuli. Thus, presumed functional attributions have come under scrutiny regarding selective pain processing in the brain. Evidently, innovative approaches are warranted to identify cerebral regions that are nociceptive specific. In this study, we aimed at circumventing known methodological confounders by applying a novel paradigm in 14 volunteers: rather than varying the intensity and thus the salience of painful stimuli, we applied repetitive noxious dental stimuli at constant intensity to the left mandibular canine. During the functional magnetic resonance imaging paradigm, we suppressed the nociceptive barrage by a mental nerve block. Brain activity before and after injection of 4% articaine was compared intraindividually on a group level. Dental pain extinction was observed to correspond to activity reduction in a discrete region of the left posterior insular cortex. These results confirm previous reports demonstrating that direct electrical stimulation of this brain region-but not of others-evokes bodily pain sensations. Hence, our investigation adds further evidence to the notion that the posterior insula plays a unique role in nociceptive processing

Status Assessment of Heavy Metals in Water of the Lepenci River Basin, Kosova

Water represents an essential element for life and living things on earth. Aquatic ecosystems play a decisive role in the socio-economic development in urban and rural areas. In recent decades, there has been concern at the global level with regard to the deterioration of aquatic ecosystems due to the pollution, which is a product of mainly anthropogenic activity. Heavy metals pollution is worrisome for the ecological balance of the aquatic environment, affecting a variety of organisms. Therefore, the objective of this paper was to characterize the quality of water in the Lepenci River basin, to express heavy metals concentration, and to determine the surface water quality index in this basin. In order to achieve such an objective, water samples were collected at eight stations for analyzing the concentrations for heavy metals. Heavy metals were determined by means of atomic absorption spectrophotometry. A good correlation was found between Pb and Zn (r = 0.84), whereas the average negative correlation coefficient was shown between Mn and Cr (r = -0.6513). The heavy metals concentrations varied from 0.0092 to 0.1135 mg/L.The mean concentrations of heavy metals found in the river water were in the order of: Mn > Fe > Pb > Ni > Cd > Zn > Cr > Cu. The Water Quality Index varied from 57 to 81, with the average value of WQI = 68.1250, which ranks the surface water of this basin as fair. From the results we have concluded that the Lepenci River waters during the monitoring period have had low pollution from heavy metals

Analysis of climatic changes based on indicators of temperature extremes in the Balkan and in the Mediterranean region

Realization of this study is based on research and processing of climatic temperature indicators reflected in materials science in 2008. After receiving the data, processing is done on the basis of deductive logic, based on environmental arguments which are changing due to climate change impacts. Space climate change affects countries and regions around the globe. This overview on the ends of the temperature indicator for Balkan and Mediterranean countries, gives us an opportunity to pass on to deeper studies, because the impact of climate change on physical and biological environment has no borders. The risk of global climate change is becoming increasingly apparent, there is a true need to focus on efforts to limit greenhouse gases and to minimize this issue the impacts on climate change. Lower extremity temperatures ranging up to - 32 0C station Rozaje, Montenegro and high ends of the temperature station Kebili +50 oC

Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction

Part 2: MAKE Smart FactorInternational audienceThe current trend of integrating machines and factories into cyber-physical systems (CPS) creates an enormous complexity for operators of such systems. Especially the search for the root cause of cascading failures becomes highly time-consuming. Within this paper, we address the question on how to help human users to better and faster understand root causes of such situations. We propose a concept of interactive alarm flood reduction and present the implementation of a first vertical prototype for such a system. We consider this prototype as a first artifact to be discussed by the research community and aim towards an incremental further development of the system in order to support humans in complex error situations

Product Delivery and Simulation for Industry 4.0

Capitulo de libro internacionalAbstract Industry 4.0 is having machines working connected as a collaborative community, both inside and outside thewalls of themanufacturing sites. Manufacturing, sourcing, and delivery supply chains are nowconnected, making synchronization possible. Physical product delivery has changed significantly. Smart deliveries are now possible by directing end customer location in dynamic conditions. The capabilities of the delivery system can be simulated using discrete event simulation to compromise on-time delivery. Big data analytics are nowa fundamental tool for product delivery analysis of optimal vehicle routing conditions and resource allocation. As companies have improved product delivery capabilities, more complex supply chains have been created. Analytic tools can tackle this complexity in estimating delivery time and product delivery windows under different workload scenarios