STNet: Selective Tuning of Convolutional Networks for Object Localization

Visual attention modeling has recently gained momentum in developing visual hierarchies provided by Convolutional Neural Networks. Despite recent successes of feedforward processing on the abstraction of concepts form raw images, the inherent nature of feedback processing has remained computationally controversial. Inspired by the computational models of covert visual attention, we propose the Selective Tuning of Convolutional Networks (STNet). It is composed of both streams of Bottom-Up and Top-Down information processing to selectively tune the visual representation of Convolutional networks. We experimentally evaluate the performance of STNet for the weakly-supervised localization task on the ImageNet benchmark dataset. We demonstrate that STNet not only successfully surpasses the state-of-the-art results but also generates attention-driven class hypothesis maps

Internal auditory canal volume in normal and malformed inner ears

Purpose: A narrow bony internal auditory canal (IAC) may be associated with a hypoplastic cochlear nerve and poorer hearing performances after cochlear implantation. However, definitions for a narrow IAC vary widely and commonly, qualitative grading or two-dimensional measures are used to characterize a narrow IAC. We aimed to refine the definition of a narrow IAC by determining IAC volume in both control patients and patients with inner ear malformations (IEMs). Methods: In this multicentric study, we included high-resolution CT (HRCT) scans of 128 temporal bones (85 with IEMs: cochlear aplasia, n = 11; common cavity, n = 2; cochlear hypoplasia type, n = 19; incomplete partition type I/III, n = 8/8; Mondini malformation, n = 16; enlarged vestibular aqueduct syndrome, n = 19; 45 controls). The IAC diameter was measured in the axial plane and the IAC volume was measured by semi-automatic segmentation and three-dimensional reconstruction. Results: In controls, the mean IAC diameter was 5.5 mm (SD 1.1 mm) and the mean IAC volume was 175.3 mm3 (SD 52.6 mm3). Statistically significant differences in IAC volumes were found in cochlear aplasia (68.3 mm3, p < 0.0001), IPI (107.4 mm3, p = 0.04), and IPIII (277.5 mm3, p = 0.0004 mm3). Inter-rater reliability was higher in IAC volume than in IAC diameter (intraclass correlation coefficient 0.92 vs. 0.77). Conclusions: Volumetric measurement of IAC in cases of IEMs reduces measurement variability and may add to classifying IEMs. Since a hypoplastic IAC can be associated with a hypoplastic cochlear nerve and sensorineural hearing loss, radiologic assessment of the IAC is crucial in patients with severe sensorineural hearing loss undergoing cochlear implantation. Keywords: 3D segmentation; Cochlear malformation; Diagnosis; Inner ear malformation; Internal auditory canal; Volum

Volumetry improves the assessment of the vestibular aqueduct size in inner ear malformation

Objectives: Enlarged vestibular aqueduct (EVA) is a common finding associated with inner ear malformations (IEM). However, uniform radiologic definitions for EVA are missing and various 2D-measurement methods to define EVA have been reported. This study evaluates VA volume in different types of IEM and compares 3D-reconstructed VA volume to 2D-measurements. Methods: A total of 98 high-resolution CT (HRCT) data sets from temporal bones were analyzed (56 with IEM; [cochlear hypoplasia (CH; n = 18), incomplete partition type I (IPI; n = 12) and type II (IPII; n = 11) and EVA (n = 15)]; 42 controls). VA diameter was measured in axial images. VA volume was analyzed by software-based, semi-automatic segmentation and 3D-reconstruction. Differences in VA volume between the groups and associations between VA volume and VA diameter were assessed. Inter-rater-reliability (IRR) was assessed using the intra-class-correlation-coefficient (ICC). Results: Larger VA volumes were found in IEM compared to controls. Significant differences in VA volume between patients with EVA and controls (p < 0.001) as well as between IPII and controls (p < 0.001) were found. VA diameter at the midpoint (VA midpoint) and at the operculum (VA operculum) correlated to VA volume in IPI (VA midpoint: r = 0.78, VA operculum: r = 0.91), in CH (VA midpoint: r = 0.59, VA operculum: r = 0.61), in EVA (VA midpoint: r = 0.55, VA operculum: r = 0.66) and in controls (VA midpoint: r = 0.36, VA operculum: r = 0.42). The highest IRR was found for VA volume (ICC = 0.90). Conclusions: The VA diameter may be an insufficient estimate of VA volume, since (1) measurement of VA diameter does not reliably correlate with VA volume and (2) VA diameter shows a lower IRR than VA volume. 3D-reconstruction and VA volumetry may add information in diagnosing EVA in cases with or without additional IEM. Keywords: 3D segmentation; Cochlear malformation; Diagnosis; Inner ear malformation; Volum

Clinical Improvement Following Stroke Promptly Reverses Post-stroke Cellular Immune Alterations

Background and Purpose: Stroke induces immediate profound alterations of the peripheral immune system rendering patients more susceptible to post-stroke infections. The precise mechanisms maintaining stroke-induced immune alterations (SIIA) remain unknown. High-Mobility-Group-Protein B1 (HMGB-1) is elevated for at least 7 days post-stroke and has been suggested to mediate SIIA. Patients with rapid clinical recovery of neurological deficits rarely develop severe infections. We therefore investigated whether rapid neurological recovery (either spontaneous or secondary to neurovascular recanalization therapy) alters the course of SIIA. National Institutes of Health Stroke Scale (NIHSS) served as surrogate marker for neurological improvement.Methods: Fluorescence-activated cell sorting was used to define leukocyte subpopulations. C-reactive protein (CRP), procalcitonin (PCT), HMGB-1, GM-CSF; IFN-β, IFN-γ, IL-1β, IL-1RA, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12, IL-17, IL-17F, IL-18, TNF-α, MIF, IL-8, MCP-1, MCP-4, MIP-3α, MIP-3β, Eotaxin, soluble IL-6 receptor, E-selectin, and P-selectin were analyzed by ELISA or Multiplex Assays. Serum miRNA expression changes were analyzed by qPCR.Results: Cellular parameters were similar in the improved and non-improved cohort on admission. In patients with rapid clinical recovery absolute and relative leukocyte, neutrophil, and lymphocyte numbers normalized promptly overnight. In contrast, HMGB-1 serum levels did not differ between the two groups. Nine miRNA were found to be differentially expressed between improved and non-improved patients.Conclusions: SIIA are detectable on admission of acute stroke patients. While it was assumed that post-stroke immunosuppression is rapidly reversed with improvement this is the first data set that shows that improvement actually is associated with a rapid reversal of SIIA demonstrating that SIIA require a constant signal to persist. The observation that HMGB-1 serum concentrations were similar in improved and non-improved cohorts argues against a role for this pro-inflammatory mediator in the maintenance of SIIA. Serum miRNA observed to be regulated in stroke in other publications was counter regulated with improvement in our cohort

Immunoadsorption for Treatment of Patients with Suspected Alzheimer Dementia and Agonistic Autoantibodies against Alpha1a-Adrenoceptor—Rationale and Design of the IMAD Pilot Study

Background: agonistic autoantibodies (agAABs) against G protein-coupled receptors (GPCR) have been linked to cardiovascular disease. In dementia patients, GPCR-agAABs against the &alpha;1- and &szlig;2-adrenoceptors (&alpha;1AR- and &szlig;2AR) were found at a prevalence of 50%. Elimination of agAABs by immunoadsorption (IA) was successfully applied in cardiovascular disease. The IMAD trial (Efficacy of immunoadsorption for treatment of persons with Alzheimer dementia and agonistic autoantibodies against alpha1A-adrenoceptor) investigates whether the removal of &alpha;1AR-AABs by a 5-day IA procedure has a positive effect (improvement or non-deterioration) on changes of hemodynamic, cognitive, vascular and metabolic parameters in patients with suspected Alzheimer&rsquo;s clinical syndrome within a one-year follow-up period. Methods: the IMAD trial is designed as an exploratory monocentric interventional trial corresponding to a proof-of-concept phase-IIa study. If cognition capacity of eligible patients scores 19&ndash;26 in the Mini Mental State Examination (MMSE), patients are tested for the presence of agAABs by an enzyme-linked immunosorbent assay (ELISA)-based method, followed by a bioassay-based confirmation test, further screening and treatment with IA and intravenous immunoglobulin G (IgG) replacement. We aim to include 15 patients with IA/IgG and to complete follow-up data from at least 12 patients. The primary outcome parameter of the study is uncorrected mean cerebral perfusion measured in mL/min/100 gr of brain tissue determined by magnetic resonance imaging with arterial spin labeling after 12 months. Conclusion: IMAD is an important pilot study that will analyze whether the removal of &alpha;1AR-agAABs by immunoadsorption in &alpha;1AR-agAAB-positive patients with suspected Alzheimer&rsquo;s clinical syndrome may slow the progression of dementia and/or may improve vascular functional parameters

Multimodal brain age prediction fusing morphometric and imaging data and association with cardiovascular risk factors

IntroductionThe difference between the chronological and biological brain age, called the brain age gap (BAG), has been identified as a promising biomarker to detect deviation from normal brain aging and to indicate the presence of neurodegenerative diseases. Moreover, the BAG has been shown to encode biological information about general health, which can be measured through cardiovascular risk factors. Current approaches for biological brain age estimation, and therefore BAG estimation, either depend on hand-crafted, morphological measurements extracted from brain magnetic resonance imaging (MRI) or on direct analysis of brain MRI images. The former can be processed with traditional machine learning models while the latter is commonly processed with convolutional neural networks (CNNs). Using a multimodal setting, this study aims to compare both approaches in terms of biological brain age prediction accuracy and biological information captured in the BAG.MethodsT1-weighted MRI, containing brain tissue information, and magnetic resonance angiography (MRA), providing information about brain arteries, from 1,658 predominantly healthy adults were used. The volumes, surface areas, and cortical thickness of brain structures were extracted from the T1-weighted MRI data, while artery density and thickness within the major blood flow territories and thickness of the major arteries were extracted from MRA data. Independent multilayer perceptron and CNN models were trained to estimate the brain age from the hand-crafted features and image data, respectively. Next, both approaches were fused to assess the benefits of combining image data and hand-crafted features for brain age prediction.ResultsThe combined model achieved a mean absolute error of 4 years between the chronological and predicted biological brain age. Among the independent models, the lowest mean absolute error was observed for the CNN using T1-weighted MRI data (4.2 years). When evaluating the BAGs obtained using the different approaches and imaging modalities, diverging associations between cardiovascular risk factors were found. For example, BAGs obtained from the CNN models showed an association with systolic blood pressure, while BAGs obtained from hand-crafted measurements showed greater associations with obesity markers.DiscussionIn conclusion, the use of more diverse sources of data can improve brain age estimation modeling and capture more diverse biological deviations from normal aging

Computed tomography hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch to identify stroke patients eligible for thrombolysis

Background and purposeAutomated perfusion imaging can detect stroke patients with unknown time of symptom onset who are eligible for thrombolysis. However, the availability of this technique is limited. We, therefore, established the novel concept of computed tomography (CT) hypoperfusion-hypodensity mismatch, i.e., an ischemic core lesion visible on cerebral perfusion CT without visible hypodensity in the corresponding native cerebral CT. We compared both methods regarding their accuracy in identifying patients suitable for thrombolysis.MethodsIn a retrospective analysis of the MissPerfeCT observational cohort study, patients were classified as suitable or not for thrombolysis based on established time window and imaging criteria. We calculated predictive values for hypoperfusion-hypodensity mismatch and automated perfusion imaging to compare accuracy in the identification of patients suitable for thrombolysis.ResultsOf 247 patients, 219 (88.7%) were eligible for thrombolysis and 28 (11.3%) were not eligible for thrombolysis. Of 197 patients who were within 4.5 h of symptom onset, 190 (96.4%) were identified by hypoperfusion-hypodensity mismatch and 88 (44.7%) by automated perfusion mismatch (p &lt; 0.001). Of 22 patients who were beyond 4.5 h of symptom onset but were eligible for thrombolysis, 5 patients (22.7%) were identified by hypoperfusion-hypodensity mismatch. Predictive values for the hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch were as follows: sensitivity, 89.0% vs. 50.2%; specificity, 71.4% vs. 100.0%; positive predictive value, 96.1% vs. 100.0%; and negative predictive value, 45.5% vs. 20.4%.ConclusionThe novel method of hypoperfusion-hypodensity mismatch can identify patients suitable for thrombolysis with higher sensitivity and lower specificity than established techniques. Using this simple method might therefore increase the proportion of patients treated with thrombolysis without the use of special automated software.The MissPerfeCT study is a retrospective observational multicenter cohort study and is registered with clinicaltrials.gov (NCT04277728)

Exome chip analysis identifies low-frequency and rare variants in MRPL38 for white matter hyperintensities on brain MRI

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Comparison of parameter threshold combinations for diffusion tensor tractography in chronic stroke patients and healthy subjects.

BACKGROUND: Although quantitative evaluation of diffusion tensor imaging (DTI) data seemed to be extremely important for clinical research its application is under debate. Besides fractional anisotropy (FA) the quantitative comparison between hemispheres of the number of fibers reconstructed by means of diffusion tensor tractography (DTT) is commonly used. However, the tractography-related parameters FA, minimum tract length (LENGTH) and the angle between two contiguous tracking steps (ANGLE) are inconsistently applied. Using 18 combinations we tested for the influence of parameter thresholds on the amount of reconstructed fibers for the posterior pyramidal tract in both hemispheres in order to obtain meaningful thresholds for DTT. RESULTS: In 14 chronic stroke patients with unilateral lesions of the pyramidal tract around the height of the internal capsule and considerable motor deficits a 3-way repeated-measures ANOVA showed a significant interaction between the effects of FA and ANGLE level on reconstructed fiber lateralization, F (2.9, 37.67) = 3.01, p = 0.044, and a significant main effect FA, F (1.4, 18.1) = 11.58, p = 0.001. Post-hoc pairwise comparisons showed that this interaction was completely driven by FA. In 22 right-handed healthy subjects no significant interactions or main effects could be found. CONCLUSION: The parameter threshold combinations with highest FA showed highest effect. ANGLE and LENGTH insofar influenced the lateralization effect when selected as liberal as possible, short LENGTH and large ANGLE thresholds. The DTT approach should be used with great care since results are highly dependent on the thresholds applied