Adaptive frequency tracking of the baseline ECG identifies the site of atrial fibrillation termination by catheter ablation

Multiple organization indices have been used to predict the outcome of stepwise catheter ablation in long-standing persistent atrial fibrillation (AF), however with limited success. Our study aims at developinginnovative organization indices from baseline ECG (i.e. during the procedure, before ablation) in orderto identify the site of AF termination by catheter ablation. Seventeen consecutive male patients (age60 ± 5 years, AF duration 7 ± 5 years) underwent a stepwise catheter ablation. Chest lead V6 was placedin the back (V6b). QRST cancelation was performed from chest leads V1 to V6b. Using an innovativeadaptive harmonic frequency tracking, two measures of AF organization were computed to quantify theharmonics components of ECG activity: (1) the adaptive phase difference variance (APD) between theAF harmonic components as a measure of AF regularity, and (2) and adaptive organization index (AOI)evaluating the cyclicity of the AF oscillations. Both adaptive indices were compared to indices computedusing a time-invariant approach: (1) ECG AF cycle length (AFCL), (2) the spectrum based organizationindex (OI), and (3) the time-invariant phase difference TIPD. Long-standing persistent AF was terminatedinto sinus rhythm or atrial tachycardia in 13/17 patients during stepwise ablation, 11 during left atriumablation (left terminated patients - LT), 2 during the right atrium ablation (right terminated patients -RT), and 4 were non terminated (NT) and required electrical cardioversion. Our findings showed that LTpatients were best separated from RT/NT before ablation by the duration of sustained AF and by AOI onchest lead V1 and APD from the dorsal lead V6b as compared to ECG AFCL, OI and TIPD, respectively. Ourresults suggest that adaptive measures of AF organization computed before ablation perform better thantime-invariant based indices for identifying patients whose AF will terminate during ablation within theleft atrium. These findings are indicative of a higher baseline organization in these patients that could beused to select candidates for the termination of AF by stepwise catheter ablation.© 2013 Elsevier Ltd. All rights reserved.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

l0-deconvolution for compressive diffusion MRI

Diffusion MRI is a well established imaging modality providing a powerful way to non-invasively probe the structure of the white matter. Despite the potential of the technique, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a wide variety of methods have been proposed to shorten acquisition times. [...] We here review a recent work where we propose to further exploit the versatility of compressed sensing and convex optimization with the aim to characterize the fiber orientation distribution sparsity more optimally. We re-formulate the spherical deconvolution problem as a constrained l0 minimization.

Coronary magnetic resonance angiography for assessment of the stent lumen: a phantom study.

PURPOSE: To evaluate the feasibility of visualizing the stent lumen using coronary magnetic resonance angiography in vitro. MATERIAL AND METHODS: Nineteen different coronary stents were implanted in plastic tubes with an inner diameter of 3 mm. The tubes were positioned in a plastic container filled with gel and included in a closed flow circuit (constant flow 18 cm/sec). The magnetic resonance images were obtained with a dual inversion fast spin-echo sequence. For intraluminal stent imaging, subtraction images were calculated from scans with and without flow. Subsequently, intraluminal signal properties were objectively assessed and compared. RESULTS: As a function of the stent type, various degrees of in-stent signal attenuation were observed. Tantalum stents demonstrated minimal intraluminal signal attenuation. For nitinol stents, the stent lumen could be identified, but the intraluminal signal was markedly reduced. Steel stents resulted in the most pronounced intraluminal signal voids. CONCLUSIONS: With the present technique, radiofrequency penetration into the stents is strongly influenced by the stent material. Thesefindings may have important implicationsforfuture stent design and stent imaging strategies.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Comparative study of human erythrocytes by digital holographic microscopy, confocal microscopy, and impedance volume analyzer.

Red blood cell (RBC) parameters such as morphology, volume, refractive index, and hemoglobin content are of great importance for diagnostic purposes. Existing approaches require complicated calibration procedures and robust cell perturbation. As a result, reference values for normal RBC differ depending on the method used. We present a way for measuring parameters of intact individual RBCs by using digital holographic microscopy (DHM), a new interferometric and label-free technique with nanometric axial sensitivity. The results are compared with values achieved by conventional techniques for RBC of the same donor and previously published figures. A DHM equipped with a laser diode (lambda = 663 nm) was used to record holograms in an off-axis geometry. Measurements of both RBC refractive indices and volumes were achieved via monitoring the quantitative phase map of RBC by means of a sequential perfusion of two isotonic solutions with different refractive indices obtained by the use of Nycodenz (decoupling procedure). Volume of RBCs labeled by membrane dye Dil was analyzed by confocal microscopy. The mean cell volume (MCV), red blood cell distribution width (RDW), and mean cell hemoglobin concentration (MCHC) were also measured with an impedance volume analyzer. DHM yielded RBC refractive index n = 1.418 +/- 0.012, volume 83 +/- 14 fl, MCH = 29.9 pg, and MCHC 362 +/- 40 g/l. Erythrocyte MCV, MCH, and MCHC achieved by an impedance volume analyzer were 82 fl, 28.6 pg, and 349 g/l, respectively. Confocal microscopy yielded 91 +/- 17 fl for RBC volume. In conclusion, DHM in combination with a decoupling procedure allows measuring noninvasively volume, refractive index, and hemoglobin content of single-living RBCs with a high accuracy.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Simultaneous cell morphometry and refractive index measurement with dual-wavelength digital holographic microscopy and dye-enhanced dispersion of perfusion medium.

Digital holographic microscopy (DHM) allows optical-path-difference (OPD) measurements with nanometric accuracy. OPD induced by transparent cells depends on both the refractive index (RI) of cells and their morphology. This Letter presents a dual-wavelength DHM that allows us to separately measure both the RI and the cellular thickness by exploiting an enhanced dispersion of the perfusion medium achieved by the utilization of an extracellular dye. The two wavelengths are chosen in the vicinity of the absorption peak of the dye, where the absorption is accompanied by a significant variation of the RI as a function of the wavelength.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Sub-cortical and brainstem sites associated with chemo-stimulated increases in ventilation in humans.

We investigated the neural basis for spontaneous chemo-stimulated increases in ventilation in awake, healthy humans. Blood oxygen level dependent (BOLD) functional MRI was performed in nine healthy subjects using T2 weighted echo planar imaging. Brain volumes (52 transverse slices, cortex to high spinal cord) were acquired every 3.9 s. The 30 min paradigm consisted of six, 5-min cycles, each cycle comprising 45 s of hypoxic-isocapnia, 45 s of isooxic-hypercapnia and 45 s of hypoxic-hypercapnia, with 55 s of non-stimulatory hyperoxic-isocapnia (control) separating each stimulus period. Ventilation was significantly (p<0.001) increased during hypoxic-isocapnia, isooxic-hypercapnia and hypoxic-hypercapnia (17.0, 13.8, 24.9 L/min respectively) vs. control (8.4 L/min) and was associated with significant (p<0.05, corrected for multiple comparisons) signal increases within a bilateral network that included the basal ganglia, thalamus, red nucleus, cerebellum, parietal cortex, cingulate and superior mid pons. The neuroanatomical structures identified provide evidence for the spontaneous control of breathing to be mediated by higher brain centres, as well as respiratory nuclei in the brainstem.

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

Electrical neuroimaging reveals intensity-dependent activation of human cortical gustatory and somatosensory areas by electric taste.

To analyze the neural basis of electric taste we performed electrical neuroimaging analyses of event-related potentials (ERPs) recorded while participants received electrical pulses to the tongue. Pulses were presented at individual taste threshold to excite gustatory fibers selectively without concomitant excitation of trigeminal fibers and at high intensity evoking a prickling and, thus, activating trigeminal fibers. Sour, salty and metallic tastes were reported at both intensities while clear prickling was reported at high intensity only. ERPs exhibited augmented amplitudes and shorter latencies for high intensity. First activations of gustatory areas (bilateral anterior insula, medial orbitofrontal cortex) were observed at 70-80ms. Common somatosensory regions were more strongly, but not exclusively, activated at high intensity. Our data provide a comprehensive view on the dynamics of cortical processing of the gustatory and trigeminal portions of electric taste and suggest that gustatory and trigeminal afferents project to overlapping cortical areas.

Kinematics and dynamic complexity of postural transitions in frail elderly subjects.

The aim of this study was to propose a methodology allowing a detailed characterization of body sit-to-stand/stand-to-sit postural transition. Parameters characterizing the kinematics of the trunk movement during sit-to-stand (Si-St) postural transition were calculated using one initial sensor system fixed on the trunk and a data logger. Dynamic complexity of these postural transitions was estimated by fractal dimension of acceleration-angular velocity plot. We concluded that this method provides a simple and accurate tool for monitoring frail elderly and to objectively evaluate the efficacy of a rehabilitation program.