Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network

Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied in other domains, such as medical image analysis. In this paper, we propose and evaluate a convolutional neural network (CNN), designed for the classification of ILD patterns. The proposed network consists of 5 convolutional layers with 2×2 kernels and LeakyReLU activations, followed by average pooling with size equal to the size of the final feature maps and three dense layers. The last dense layer has 7 outputs, equivalent to the classes considered: healthy, ground glass opacity (GGO), micronodules, consolidation, reticulation, honeycombing and a combination of GGO/reticulation. To train and evaluate the CNN, we used a dataset of 14696 image patches, derived by 120 CT scans from different scanners and hospitals. To the best of our knowledge, this is the first deep CNN designed for the specific problem. A comparative analysis proved the effectiveness of the proposed CNN against previous methods in a challenging dataset. The classification performance (~85.5%) demonstrated the potential of CNNs in analyzing lung patterns. Future work includes, extending the CNN to three-dimensional data provided by CT volume scans and integrating the proposed method into a CAD system that aims to provide differential diagnosis for ILDs as a supportive tool for radiologists.

The Role for Virtual Patients in the Future of Medical Education

The medical education community is working-across disciplines and across the continuum-to address the current challenges facing the medical education system and to implement strategies to improve educational outcomes. Educational technology offers the promise of addressing these important challenges in ways not previously possible. The authors propose a role for virtual patients (VPs), which they define as multimedia, screen-based interactive patient scenarios. They believe VPs offer capabilities and benefits particularly well suited to addressing the challenges facing medical education. Well-designed, interactive VP-based learning activities can promote the deep learning that is needed to handle the rapid growth in medical knowledge. Clinically oriented learning from VPs can capture intrinsic motivation and promote mastery learning. VPs can also enhance trainees' application of foundational knowledge to promote the development of clinical reasoning, the foundation of medical practice. Although not the entire solution, VPs can support competency-based education. The data created by the use of VPs can serve as the basis for multi-institutional research that will enable the medical education community both to better understand the effectiveness of educational interventions and to measure progress toward an improved system of medical education.

Classes of multichannel EEG microstates in light and deep hypnotic conditions

The study assessed the brain electric mechanisms of light and deep hypnotic conditions in the framework of EEG temporal microstates. Multichannel EEG of healthy volunteers during initial resting, light hypnosis, deep hypnosis, and eventual recovery was analyzed into temporal EEG microstates of four classes. Microstates are defined by the spatial configuration of their potential distribution maps ([Symbol: see text]potential landscapes') on the head surface. Because different potential landscapes must have been generated by different active neural assemblies, it is reasonable to assume that they also incorporate different brain functions. The observed four microstate classes were very similar to the four standard microstate classes A, B, C, D [Koenig, T. et al. Neuroimage, 2002;16: 41-8] and were labeled correspondingly. We expected a progression of microstate characteristics from initial resting to light to deep hypnosis. But, all three microstate parameters (duration, occurrence/second and %time coverage) yielded values for initial resting and final recovery that were between those of the two hypnotic conditions of light and deep hypnosis. Microstates of the classes B and D showed decreased duration, occurrence/second and %time coverage in deep hypnosis compared to light hypnosis; this was contrary to microstates of classes A and C which showed increased values of all three parameters. Reviewing the available information about microstates in other conditions, the changes from resting to light hypnosis in certain respects are reminiscent of changes to meditation states, and changes to deep hypnosis of those in schizophrenic states.

Food Recognition for Dietary Assessment Using Deep Convolutional Neural Networks

Diet management is a key factor for the prevention and treatment of diet-related chronic diseases. Computer vision systems aim to provide automated food intake assessment using meal images. We propose a method for the recognition of already segmented food items in meal images. The method uses a 6-layer deep convolutional neural network to classify food image patches. For each food item, overlapping patches are extracted and classified and the class with the majority of votes is assigned to it. Experiments on a manually annotated dataset with 573 food items justified the choice of the involved components and proved the effectiveness of the proposed system yielding an overall accuracy of 84.9%.

Inconsistencies in the planning of the duration of anticoagulation among outpatients with acute deep-vein thrombosis. Results from the OTIS-DVT Registry

Three-month anticoagulation is recommended to treat provoked or first distal deep-vein thrombosis (DVT), and indefinite-duration anticoagulation should be considered for patients with unprovoked proximal, unprovoked recurrent, or cancer-associated DVT. In the prospective Outpatient Treatment of Deep Vein Thrombosis in Switzerland (OTIS-DVT) Registry of 502 patients with acute objectively confirmed lower extremity DVT (59% provoked or first distal DVT; 41% unprovoked proximal, unprovoked recurrent, or cancer-associated DVT) from 53 private practices and 11 hospitals, we investigated the planned duration of anticoagulation at the time of treatment initiation. The decision to administer limited-duration anticoagulation therapy was made in 343 (68%) patients with a median duration of 107 (interquartile range 91-182) days for provoked or first distal DVT, and 182 (interquartile range 111-184) days for unprovoked proximal, unprovoked recurrent, or cancer-associated DVT. Among patients with provoked or first distal DVT, anticoagulation was recommended for < 3 months in 11%, 3 months in 63%, and for an indefinite period in 26%. Among patients with unprovoked proximal, unprovoked recurrent, or cancer-associated DVT, anticoagulation was recommended for < 6 months in 22%, 6-12 months in 38%, and for an indefinite period in 40%. Overall, there was more frequent planning of indefinite-duration therapy from hospital physicians as compared with private practice physicians (39% vs. 28%; p=0.019). Considerable inconsistency in planning the duration of anticoagulation therapy mandates an improvement in risk stratification of outpatients with acute DVT.

von Willebrand factor-mediated platelet adhesion is critical for deep vein thrombosis in mouse models

Deep vein thrombosis (DVT) and its complication, pulmonary embolism, are frequent causes of disability and mortality. Although blood flow disturbance is considered an important triggering factor, the mechanism of DVT initiation remains elusive. Here we show that 48-hour flow restriction in the inferior vena cava (IVC) results in the development of thrombi structurally similar to human deep vein thrombi. von Willebrand factor (VWF)-deficient mice were protected from thrombosis induced by complete (stasis) or partial (stenosis) flow restriction in the IVC. Mice with half normal VWF levels were also protected in the stenosis model. Besides promoting platelet adhesion, VWF carries Factor VIII. Repeated infusions of recombinant Factor VIII did not rescue thrombosis in VWF(-/-) mice, indicating that impaired coagulation was not the primary reason for the absence of DVT in VWF(-/-) mice. Infusion of GPG-290, a mutant glycoprotein Ib?-immunoglobulin chimera that specifically inhibits interaction of the VWF A1 domain with platelets, prevented thrombosis in wild-type mice. Intravital microscopy showed that platelet and leukocyte recruitment in the early stages of DVT was dramatically higher in wild-type than in VWF(-/-) IVC. Our results demonstrate a pathogenetic role for VWF-platelet interaction in flow disturbance-induced venous thrombosis.

Deep-sequencing identification of the genomic targets of the cytidine deaminase AID and its cofactor RPA in B lymphocytes

The cytidine deaminase AID hypermutates immunoglobulin genes but can also target oncogenes, leading to tumorigenesis. The extent of AID's promiscuity and its predilection for immunoglobulin genes are unknown. We report here that AID interacted broadly with promoter-proximal sequences associated with stalled polymerases and chromatin-activating marks. In contrast, genomic occupancy of replication protein A (RPA), an AID cofactor, was restricted to immunoglobulin genes. The recruitment of RPA to the immunoglobulin loci was facilitated by phosphorylation of AID at Ser38 and Thr140. We propose that stalled polymerases recruit AID, thereby resulting in low frequencies of hypermutation across the B cell genome. Efficient hypermutation and switch recombination required AID phosphorylation and correlated with recruitment of RPA. Our findings provide a rationale for the oncogenic role of AID in B cell malignancy.

Comparison of the diagnostic performance of the original and modified Wells score in inpatients and outpatients with suspected deep vein thrombosis

The original and modified Wells score are widely used prediction rules for pre-test probability assessment of deep vein thrombosis (DVT). The objective of this study was to compare the predictive performance of both Wells scores in unselected patients with clinical suspicion of DVT.

Outpatient management of acute deep vein thrombosis: Results from the OTIS-DVT registry

We aimed to investigate clinical practice patterns for the outpatient management of acute deep vein thrombosis (DVT).

Accuracy of diagnostic tests for clinically suspected upper extremity deep vein thrombosis: a systematic review

The best available test for the diagnosis of upper extremity deep venous thrombosis (UEDVT) is contrast venography. The aim of this systematic review was to assess whether the diagnostic accuracy of other tests for clinically suspected UEDVT is high enough to justify their use in clinical practise and to evaluate if any test can replace venography.

Deep ocean ventilation, carbon isotopes, marine sedimentation and the deglacial CO2 rise

The link between the atmospheric CO2 level and the ventilation state of the deep ocean is an important building block of the key hypotheses put forth to explain glacial-interglacial CO2 fluctuations. In this study, we systematically examine the sensitivity of atmospheric CO2 and its carbon isotope composition to changes in deep ocean ventilation, the ocean carbon pumps, and sediment formation in a global three-dimensional ocean-sediment carbon cycle model. Our results provide support for the hypothesis that a break up of Southern Ocean stratification and invigorated deep ocean ventilation were the dominant drivers for the early deglacial CO2 rise of ~35 ppm between the Last Glacial Maximum and 14.6 ka BP. Another rise of 10 ppm until the end of the Holocene is attributed to carbonate compensation responding to the early deglacial change in ocean circulation. Our reasoning is based on a multi-proxy analysis which indicates that an acceleration of deep ocean ventilation during the early deglaciation is not only consistent with recorded atmospheric CO2 but also with the reconstructed opal sedimentation peak in the Southern Ocean at around 16 ka BP, the record of atmospheric δ13CCO2, and the reconstructed changes in the Pacific CaCO3 saturation horizon.