Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (CNNs), which have shown to be successful in many medical image analysis tasks, are typically sensitive to the variations in imaging protocols. Therefore, in many cases, networks trained on data acquired with one MRI protocol, do not perform satisfactorily on data acquired with different protocols. This limits the use of models trained with large annotated legacy datasets on a new dataset with a different domain which is often a recurring situation in clinical settings. In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, 1) How much data from the new domain is required for a decent adaptation of the original network?; and, 2) What portion of the pre-trained model parameters should be retrained given a certain number of the new domain training samples? To address these questions, we conducted extensive experiments in white matter hyperintensity segmentation task. We trained a CNN on legacy MR images of brain and evaluated the performance of the domain-adapted network on the same task with images from a different domain. We then compared the performance of the model to the surrogate scenarios where either the same trained network is used or a new network is trained from scratch on the new dataset.The domain-adapted network tuned only by two training examples achieved a Dice score of 0.63 substantially outperforming a similar network trained on the same set of examples from scratch.Comment: 8 pages, 3 figure

Efficient Behavior of Small-World Networks

We introduce the concept of efficiency of a network, measuring how efficiently it exchanges information. By using this simple measure small-world networks are seen as systems that are both globally and locally efficient. This allows to give a clear physical meaning to the concept of small-world, and also to perform a precise quantitative a nalysis of both weighted and unweighted networks. We study neural networks and man-made communication and transportation systems and we show that the underlying general principle of their construction is in fact a small-world principle of high efficiency.Comment: 1 figure, 2 tables. Revised version. Accepted for publication in Phys. Rev. Let

A model for cascading failures in complex networks

Large but rare cascades triggered by small initial shocks are present in most of the infrastructure networks. Here we present a simple model for cascading failures based on the dynamical redistribution of the flow on the network. We show that the breakdown of a single node is sufficient to collapse the efficiency of the entire system if the node is among the ones with largest load. This is particularly important for real-world networks with an highly hetereogeneous distribution of loads as the Internet and electrical power grids.Comment: 4 pages, 4 figure

Start of SPIDER operation towards ITER neutral beams

Heating Neutral Beam (HNB) Injectors will constitute the main plasma heating and current drive tool both in ITER and JT60-SA, which are the next major experimental steps for demonstrating nuclear fusion as viable energy source. In ITER, in order to achieve the required thermonuclear fusion power gain Q=10 for short pulse operation and Q=5 for long pulse operation (up to 3600s), two HNB injectors will be needed [1], each delivering a total power of about 16.5 MW into the magnetically-confined plasma, by means of neutral hydrogen or deuterium particles having a specific energy of about 1 MeV. Since only negatively charged particles can be efficiently neutralized at such energy, the ITER HNB injectors [2] will be based on negative ions, generated by caesium-catalysed surface conversion of atoms in a radio-frequency driven plasma source. A negative deuterium ion current of more than 40 A will be extracted, accelerated and focused in a multi-aperture, multi-stage electrostatic accelerator, having 1280 apertures (~ 14 mm diam.) and 5 acceleration stages (~200 kV each) [3]. After passing through a narrow gas-cell neutralizer, the residual ions will be deflected and discarded, whereas the neutralized particles will continue their trajectory through a duct into the tokamak vessels to deliver the required heating power to the ITER plasma for a pulse duration of about 3600 s. Although the operating principles and the implementation of the most critical parts of the injector have been tested in different experiments, the ITER NBI requirements have never been simultaneously attained. In order to reduce the risks and to optimize the design and operating procedures of the HNB for ITER, a dedicated Neutral Beam Test Facility (NBTF) [4] has been promoted by the ITER Organization with the contribution of the European Union\u2019s Joint Undertaking for ITER and of the Italian Government, with the participation of the Japanese and Indian Domestic Agencies (JADA and INDA) and of several European laboratories, such as IPP-Garching, KIT-Karlsruhe, CCFE-Culham, CEA-Cadarache. The NBTF, nicknamed PRIMA, has been set up at Consorzio RFX in Padova, Italy [5]. The planned experiments will verify continuous HNB operation for one hour, under stringent requirements for beam divergence (< 7 mrad) and aiming (within 2 mrad). To study and optimise HNB performances, the NBTF includes two experiments: MITICA, full-scale NBI prototype with 1 MeV particle energy and SPIDER, with 100 keV particle energy and 40 A current, aiming at testing and optimizing the full-scale ion source. SPIDER will focus on source uniformity, negative ion current density and beam optics. In June 2018 the experimental operation of SPIDER has started

Knee position at the moment of bone bruise could reflect the late phase of non-contact anterior cruciate ligament injury rather than the mechanisms leading to ligament failure

Purpose: The aim of the present study was to trace knee position at the time of bone bruise (BB) and investigate how much this position departed from the knee biomechanics of an in vivo flexion–extension. Methods: From an original cohort of 62 patients, seven (11%) presented bicompartmental edemas and were included in the study. 3D models of bones and BB were obtained from MRI. Matching bone edemas, a reconstruction of the knee at the moment of BB was obtained. For the same patients, knee kinematics of a squat was calculated using dynamic Roentgen sterephotogrammetric analysis (RSA). Data describing knee position at the moment of BB were compared to kinematics of the same knee extrapolated from RSA system. Results: Knee positions at the moment of BB was significantly different from the kinematics of the squat. In particular, all the patients’ positions were out of squat range for both anterior and proximal tibial translation, varus–valgus rotation (five in valgus and two in varus), tibial internal–external rotation (all but one, five externally and one internally). A direct comparison at same flexion angle between knee at the moment of BB (average 46.1° ± 3.8°) and knee during squat confirmed that tibia in the former was significantly more anterior (p &lt; 0.0001), more externally rotated (6.1 ± 3.7°, p = 0.04), and valgus (4.1 ± 2.4°, p = 0.03). Conclusion: Knee position at the moment of Bone bruise position was out of physiological in-vivo knee range of motion and could reflect a locked anterior subluxation occurring in the late phase of ACL injury rather than the mechanism leading to ligament failure. Level of evidence: Level I

Finding and evaluating community structure in networks

We propose and study a set of algorithms for discovering community structure in networks -- natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems.Comment: 16 pages, 13 figure

Light-emitting porphyrin derivative obtained from a subproduct of the cashew nut shell liquid: A promising material for OLED applications

In this work, the meso-tetra[4-(2-(3-n-pentadecylphenoxy)ethoxy]phenylporphyrin (H2P), obtained from the cashew nut shell liquid (CNSL), and its zinc (ZnP) and copper (CuP) metallic complexes, were applied as emitting layers in organic light emitting diodes (OLEDs). These compounds were characterized via optical and electrochemical analysis and the electroluminescent properties of the device have been studied. We performed a cyclic voltammetry analysis to determine the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) energy levels for the porphyrins, in order to select the proper materials to assemble the device. H2P and ZnP presented fluorescence emission band in the red region, from 601 nm to 718 nm. Moreover, we verified that the introduction of bulky substituents hinders the π-πstacking, favoring the emission in the film. In addition, the strongest emitter, ZnP, presented a threshold voltage of 4 V and the maximum irradiance of 10 μW cm-2 with a current density (J) of 15 mA cm-2 at 10 V. The CuP complex showed to be a favorable material for the design of OLEDs in the infrared. These results suggest that the porphyrins derived from a renewable source, such as CNSL, is a promising material to be used in organic optoelectronic devices such as OLEDs

Low number of neurosecretory vesicles in neuroblastoma impairs massive catecholamine release and prevents hypertension

Introduction: Neuroblastoma (NB) is a pediatric cancer of the developing sympathetic nervous system. It produces and releases metanephrines, which are used as biomarkers for diagnosis in plasma and urine. However, plasma catecholamine concentrations remain generally normal in children with NB. Thus, unlike pheochromocytoma and paraganglioma (PHEO/PGL), two other non-epithelial neuroendocrine tumors, hypertension is not part of the usual clinical picture of patients with NB. This suggests that the mode of production and secretion of catecholamines and metanephrines in NB is different from that in PHEO/PGL, but little is known about these discrepancies. Here we aim to provide a detailed comparison of the biosynthesis, metabolism and storage of catecholamines and metanephrines between patients with NB and PHEO. Method: Catecholamines and metanephrines were quantified in NB and PHEO/PGL patients from plasma and tumor tissues by ultra-high pressure liquid chromatography tandem mass spectrometry. Electron microscopy was used to quantify neurosecretory vesicles within cells derived from PHEO tumor biopsies, NB-PDX and NB cell lines. Chromaffin markers were detected by qPCR, IHC and/or immunoblotting. Results: Plasma levels of metanephrines were comparable between NB and PHEO patients, while catecholamines were 3.5-fold lower in NB vs PHEO affected individuals. However, we observed that intratumoral concentrations of metanephrines and catecholamines measured in NB were several orders of magnitude lower than in PHEO. Cellular and molecular analyses revealed that NB cell lines, primary cells dissociated from human tumor biopsies as well as cells from patient-derived xenograft tumors (NB-PDX) stored a very low amount of intracellular catecholamines, and contained only rare neurosecretory vesicles relative to PHEO cells. In addition, primary NB expressed reduced levels of numerous chromaffin markers, as compared to PHEO/PGL, except catechol O-methyltransferase and monoamine oxidase A. Furthermore, functional assays through induction of chromaffin differentiation of the IMR32 NB cell line with Bt2cAMP led to an increase of neurosecretory vesicles able to secrete catecholamines after KCl or nicotine stimulation. Conclusion: The low amount of neurosecretory vesicles in NB cytoplasm prevents catecholamine storage and lead to their rapid transformation by catechol O-methyltransferase into metanephrines that diffuse in blood. Hence, in contrast to PHEO/PGL, catecholamines are not secreted massively in the blood, which explains why systemic hypertension is not observed in most patients with NB