Acute hepatitis associated with Q fever in a man in Greece: a case report

Coxiella burnetii is the causative agent of Q fever. Q fever is a worldwide zoonosis that is responsible for various clinical manifestations. However, in Greece hepatitis due to Coxiella is rarely encountered. A case of Q fever associated with hepatitis is reported here. Diagnosis was made by specific serological investigation (enzyme-linked immunosorbent and indirect immunofluorescene assays) for Coxiella burnetii

Προσομοίωση μαγνητικής τομογραφίας

A new step-by-step comprehensive MR physics simulator (MRISIMUL) of the Bloch equations ispresented in this work. The aim was to develop a magnetic resonance imaging (MRI) simulator thatmakes no assumptions with respect to the underlying pulse sequence and also allows for complexlarge-scale analysis on a single-node computer without requiring simplifications of the MRI model.We hypothesized that such a simulation platform could be developed with parallel acceleration of theexecutable core within the graphic processing unit (GPU) environment. MRISIMUL integrates realisticaspects of the MRI experiment from signal generation to image formation and solves the entirecomplex problem for densely spaced isochromats and for a densely spaced time axis. The simulationplatform was developed in MATLAB whereas the computationally demanding core services weredeveloped in CUDA-C. The MRISIMUL simulator imaged three different computer models: a userdefinedphantom, a human brain model and a human heart model whereas three different motionmodels were introduced as well: cardiac motion, respiratory motion and flow.The high computational power of GPU-based simulations was compared against other computerconfigurations. A speedup of about 228 times was achieved when compared to serially executed Ccodeon the CPU whereas a speedup between 31 to 115 times was achieved when compared to theOpenMP parallel executed C-code on the CPU, depending on the number of threads used inmultithreading (2–8 threads). Moreover, simulations of motion with MRISIMUL on single-node andmulti-node multi-GPU systems were also examined demonstrating an almost linear scalableperformance with the increasing number of available GPU cards, in both single-node and multi-nodemulti-GPU computer systems.MRISIMUL is the first MR physics simulator that allows for computationally intense realistic simulationson multi-GPU computer systems. The high performance of MRISIMUL can bring the computationalpower of a supercomputer or a large computer cluster to a single GPU personal computer. Theincorporation of realistic aspects of MR experiments, such as motion, may benefit the design andoptimization of existing or new MR pulse sequences, protocols and algorithms.Σε αυτή την εργασία παρουσιάζεται ένας νέος, ολοκληρωμένος προσομοιωτής της φυσικής τηςΜαγνητικής Τομογραφίας (MRISIMUL) που βασίζεται στην επίληση του συστήματος των Blochεξισώσεων. Κύριος στόχος αυτής της εργασίας ήταν η ανάπτυξη ενός προσομοιωτή της ΜαγνητικήςΤομογραφίας (MRI) που δεν κάνει υποθέσεις σε σχέση με την υποκείμενη ακολουθία παλμών και πουεπιτρέπει την πολύπλοκη ανάλυση προβλημάτων μεγάλης κλίμακας με τη χρήση ενός υπολογιστή,χωρίς να απαιτείται απλούστευση του πειραματικού μοντέλου.Η εργασία αυτή βασίστηκε στην υπόθεση ότι μια τέτοια πλατφόρμα προσομοίωσης θα μπορούσε νααναπτυχθεί κάνοντας χρήση της παράλληλης τεχνολογίας που προσφέρει το προγραμματιστικόπεριβάλλον των σύγχρονων καρτών γραφικών (GPU). Ο προσομοιωτής MRISIMUL ενσωματώνειρεαλιστικές πτυχές του πειράματος της Μαγνητικής Τομογραφίας, από την παραγωγή του σήματος έωςτο σχηματισμό της εικόνας ενώ παράλληλα επιτρέπει την επίλυση του προβλήματος για πυκνά χωρικάκαι χρονικά μοντέλα. Η πλατφόρμα προσομοίωσης αναπτύχθηκε σε MATLAB ενώ οι υπολογιστικάαπαιτητικές βασικές διεργασίες αναπτύχθηκαν στο περιβάλλον της CUDA-C. Ο προσομοιωτήςMRISIMUL ενσωματώνει τρία διαφορετικά υπολογιστικά μοντέλα: ένα καθορισμένο από το χρήστημοντέλο, ένα ανθρώπινο μοντέλο του εγκεφάλου και ένα ανθρώπινο μοντέλο της καρδιάς, ενώ τρίαεπιπλέον μοντέλα κίνησης εισήχθησαν: καρδιακή κίνηση, αναπνευστική κίνηση και ροή.Η υψηλή υπολογιστική ισχύ των σύγχρονων καρτών γραφικών (GPU) στη προσομοίωση ΜαγνητικήςΤομογραφίας συγκρίθηκε έναντι άλλων διαμορφώσεων υπολογιστικών συστημάτων. Η χρήση μιαςκάρτας γραφικών παρουσίασε επιτάχυνση περίπου 228 φορές συγκριτικά με την εκτέλεση σειριακού C-κώδικα σε μια CPU ενώ επιτάχυνση μεταξύ 31 και 115 φορές παρουσιάστηκε συγκριτικά με τηνOpenMP έκδοση του C-κώδικα σε μια CPU, ανάλογα με τον αριθμό των νημάτων πουχρησιμοποιήθηκαν σε αρχιτεκτονική πολυνημάτωσης (2-8 νήματα). Επιπλέον, εξετάστηκανπροσομοιώσεις κίνησης με τον προσομοιωτή MRISIMUL σε συστήματα μονού κόμβου και πολλαπλώνκόμβων με τη χρήση πολλαπλών καρτών GPU επιδεικνύοντας μια σχεδόν γραμμική σχέση ανάμεσαστην επιτάχυνση και στον αριθμό των διαθέσιμων καρτών GPU στα συστήματα πολλαπλών καρτώνγραφικών, είτε μονού νόμβου είτε πολλαπλών κόμβων.Ο προσομοιωτής MRISIMUL είναι η πρώτη πλατφόρμα προσομοίωσης της φυσικής της ΜαγνητικήςΤομογραφίας που επιτρέπει την εκτέλεση υπολογιστικά επιβαρυμένων, ρεαλιστικών προσομοιώσεωνσε υπολογιστικά συστήματα πολλαπλών καρτών γραφικών. Η υψηλή απόδοση του MRISIMUL μπορείνα φέρει την υπολογιστική ισχύ ενός υπερυπολογιστή ή ενός μεγάλου συμπλέγματος υπολογιστών(cluster) σε έναν προσωπικό υπολογιστή που διαθέτει μια σύγχρονη κάρτα γραφικών. Η ενσωμάτωσηρεαλιστικών πτυχών των πειραμάτων Μαγνητικής Τομογραφίας , όπως πχ κίνηση, μπορεί να ωφελήσειστο μέλλον τον σχεδιασμό και τη βελτιστοποίηση των υφιστάμενων ή νέων παλμοσειρών,πρωτοκόλλων και αλγορίθμων της Μαγνητικής Τομογραφίας

coreMRI: A high-performance, publicly available MR simulation platform on the cloud

IntroductionA Cloud-ORiented Engine for advanced MRI simulations (coreMRI) is presented in this study. The aim was to develop the first advanced MR simulation platform delivered as a web service through an on-demand, scalable cloud-based and GPU-based infrastructure. We hypothesized that such an online MR simulation platform could be utilized as a virtual MRI scanner but also as a cloud-based, high-performance engine for advanced MR simulations in simulation-based quantitative MR (qMR) methods.Methods and resultsThe simulation framework of coreMRI was based on the solution of the Bloch equations and utilized a ground-up-approach design based on the principles already published in the literature. The development of a front-end environment allowed the connection of the end-users to the GPU-equipped instances on the cloud. The coreMRI simulation platform was based on a modular design where individual modules (such as the Gadgetron reconstruction framework and a newly developed Pulse Sequence Designer) could be inserted in the main simulation framework. Different types and sources of pulse sequences and anatomical models were utilized in this study revealing the flexibility that the coreMRI simulation platform offers to the users. The performance and scalability of coreMRI were also examined on multi-GPU configurations on the cloud, showing that a multi-GPU computer on the cloud equipped with a newer generation of GPU cards could significantly mitigate the prolonged execution times that accompany more realistic MRI and qMR simulations.ConclusionscoreMRI is available to the entire MR community, whereas its high performance and scalability allow its users to configure advanced MRI experiments without the constraints imposed by experimentation in a true MRI scanner (such as time constraint and limited availability of MR scanners), without upfront investment for purchasing advanced computer systems and without any user expertise on computer programming or MR physics. coreMRI is available to the users through the webpage https://www.coreMRI.org

Comparison of short axis and long axis acquisitions of T1 and extracellular volume mapping using MOLLI and SASHA in patients with myocardial infarction and healthy volunteers

Background: Although previous studies have examined the impact of slice position in volumetric measurements in Cardiovascular Magnetic Resonance (CMR) imaging, very limited data are available today comparing T1 and Extra-Cellular Volume (ECV) measurements from short and long axis acquisitions. The purpose of this study was to investigate the impact of slice position and orientation on T1 and ECV measurements using the MOdified Look-Locker Inversion recovery (MOLLI) and Saturation recovery single-shot acquisition (SASHA) sequence in patients with myocardial infarction and in healthy volunteers. Methods: Eight (8) healthy volunteers with no medical history and eight (8) patients with myocardial infarction were included in this study. MOLLI and SASHA were utilized and short-axis and long-axis images were acquired. T1 and ECV measurements were performed by drawing same size regions of interest on the myocardium as well in the blood pool at the intersections of the short axis and long axis images. Results: In healthy volunteers, there were no statistically significant differences in native T1 and ECV values between short axis and long axis acquisitions using MOLLI (two-chamber, three-chamber and four-chamber) and SASHA (three-chamber). In patients, there were no statistically significant differences in native T1 and ECV values between short axis and 3-chamber long axis acquisitions in both remote and affected myocardium using MOLLI and SASHA. Conclusions: Long axis measurements of myocardial T1 and ECV using MOLLI and SASHA exhibit good agreement with the corresponding short axis measurements allowing for fast and reliable myocardial tissue characterization in cases where shortening of the overall imaging acquisition is required

Cloud GPU-based simulations for SQUAREMR

Quantitative Magnetic Resonance Imaging (MRI) is a research tool, used more and more in clinical practice, as it provides objective information with respect to the tissues being imaged. Pixel-wise T1 quantification (T1 mapping) of the myocardium is one such application with diagnostic significance. A number of mapping sequences have been developed for myocardial T1 mapping with a wide range in terms of measurement accuracy and precision. Furthermore, measurement results obtained with these pulse sequences are affected by errors introduced by the particular acquisition parameters used. SQUAREMR is a new method which has the potential of improving the accuracy of these mapping sequences through the use of massively parallel simulations on Graphical Processing Units (GPUs) by taking into account different acquisition parameter sets. This method has been shown to be effective in myocardial T1 mapping; however, execution times may exceed 30 min which is prohibitively long for clinical applications. The purpose of this study was to accelerate the construction of SQUAREMR's multi-parametric database to more clinically acceptable levels. The aim of this study was to develop a cloud-based cluster in order to distribute the computational load to several GPU-enabled nodes and accelerate SQUAREMR. This would accommodate high demands for computational resources without the need for major upfront equipment investment. Moreover, the parameter space explored by the simulations was optimized in order to reduce the computational load without compromising the T1 estimates compared to a non-optimized parameter space approach. A cloud-based cluster with 16 nodes resulted in a speedup of up to 13.5 times compared to a single-node execution. Finally, the optimized parameter set approach allowed for an execution time of 28 s using the 16-node cluster, without compromising the T1 estimates by more than 10 ms. The developed cloud-based cluster and optimization of the parameter set reduced the execution time of the simulations involved in constructing the SQUAREMR multi-parametric database thus bringing SQUAREMR's applicability within time frames that would be likely acceptable in the clinic

Parallel simulations for QUAntifying RElaxation magnetic resonance constants (SQUAREMR): an example towards accurate MOLLI T1 measurements.

T1 mapping is widely used today in CMR, however, it underestimates true T1 values and its measurement error is influenced by several acquisition parameters. The purpose of this study was the extraction of accurate T1 data through the utilization of comprehensive, parallel Simulations for QUAntifying RElaxation Magnetic Resonance constants (SQUAREMR) of the MOLLI pulse sequence on a large population of spins with physiologically relevant tissue relaxation constants