Ústav biomedicínského inženýrství


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Now showing 1 - 5 of 147
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    Multi-channel delineation of intracardiac electrograms for arrhythmia substrate analysis using implicitly regularized convolutional neural network with wide receptive field.
    (Elsevier, 2024-04-09) Hejč, Jakub; Ředina, Richard; Kolářová, Jana; Stárek, Zdeněk
    Objective Automated segmentation of intracardiac electrograms and extraction of fundamental cycle length intervals is crucial for reproducible arrhythmia substrate analysis conducted during electrophysiology procedures. The objective of this study is to develop a robust, computationally efficient end-to-end model for the precise electrogram multi-channel delineation using a highly imbalanced dataset. Methods A temporal deep convolutional neural network (CNN) based on the UNet architecture incorporating convolutional layers of varying dilation rates was implicitly regularized through data augmentations (DAs), a domain specific Tversky loss function, and distinct labelling strategies for segments comprising atrial fibrillation (AF). An exploratory study utilizing Bayesian search was conducted to optimize architectural and loss function hyperparameters. The impact of dilated convolutions, data augmentations, and labelling strategies on the performance and generalization capability was assessed through an ablation study. The performance of different models was evaluated using a cross-validation procedure and two independent test datasets derived from two separate patient cohorts containing 326, 84, and 97 electrograms encompassing sinus rhythms, abnormal complexes during ongoing tachycardias, and stimulation protocols. Results A UNet model with optimized loss hyperparameters, a dilated receptive field, and atrial fibrillation (AF) annotated as a positive class (D-UNet-L) achieved an average Srensen-Dice coefficient (SDC) of 84.9% on recordings with regular atrial beats across test datasets, surpassing the performance of models without loss optimization (81.5%), without dilated kernels (81.3%), and with inversed AF labelling (77.5%). Notably, the highest average accuracy (Acc) of 95.8% for AF recordings was obtained by a model trained on negatively assigned AF segments, outperforming D-UNet-L (88.9%), the model without loss optimization (81.5%), and the model without dilated kernels (81.3%). The reference D-UNet-L model exhibited overall root-mean-square errors of 8.3 and 9.0ms across test datasets. Additionally, 61.5% and 20.8% of delineations exhibited absolute errors below 5ms and 10ms, respectively. Disabling data augmentation (DAs) resulted in a 2.7% decrease in validation SDC and a 5.3% increase in training SDC.“ Conclusion Generalization capability across independent datasets was improved by employing exponentially weighted Tversky loss. The model's segmentation performance on longer sequences with atrial fibrillation was improved by incorporating dilated convolution kernels. Noise-aware and morphology data augmentations effectively mitigated overfitting potential in a limited training dataset. Label noise introduced by annotating atrial fibrillation sequences into a positive class strengthened regularization of the model, particularly in its ability to identify regular beats. However, it also negatively impacted performance on F-waves.
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    Ultra-high-frequency ECG volumetric and negative derivative epicardial ventricular electrical activation pattern
    (NATURE PORTFOLIO, 2024-03-07) Leinveber, Pavel; Halámek, Josef; Čurila, Karol; Prinzen, Frits; Lipoldová, Jolana; Matejková, Magdaléna; Smíšek, Radovan; Plešinger, Filip; Nagy, Andrej; Novák, Miroslav; Viščor, Ivo; Vondra, Vlastimil; Jurák, Pavel
    From precordial ECG leads, the conventional determination of the negative derivative of the QRS complex (ND-ECG) assesses epicardial activation. Recently we showed that ultra-high-frequency electrocardiography (UHF-ECG) determines the activation of a larger volume of the ventricular wall. We aimed to combine these two methods to investigate the potential of volumetric and epicardial ventricular activation assessment and thereby determine the transmural activation sequence. We retrospectively analyzed 390 ECG records divided into three groups-healthy subjects with normal ECG, left bundle branch block (LBBB), and right bundle branch block (RBBB) patients. Then we created UHF-ECG and ND-ECG-derived depolarization maps and computed interventricular electrical dyssynchrony. Characteristic spatio-temporal differences were found between the volumetric UHF-ECG activation patterns and epicardial ND-ECG in the Normal, LBBB, and RBBB groups, despite the overall high correlations between both methods. Interventricular electrical dyssynchrony values assessed by the ND-ECG were consistently larger than values computed by the UHF-ECG method. Noninvasively obtained UHF-ECG and ND-ECG analyses describe different ventricular dyssynchrony and the general course of ventricular depolarization. Combining both methods based on standard 12-lead ECG electrode positions allows for a more detailed analysis of volumetric and epicardial ventricular electrical activation, including the assessment of the depolarization wave direction propagation in ventricles.
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    Decreased quality of life in Duchenne muscular disease patients related to functional neurological and cardiac impairment
    (FRONTIERS MEDIA SA, 2024-02-08) Juříková, Lenka; Masárová, Lucia; Panovský, Roman; Pešl, Martin; Žondra Revendová, Kamila; Volný, Ondřej; Feitová, Věra; Holeček, Tomáš; Kincl, Vladimír; Danhofer, Pavlína; Voháňka, Stanislav; Haberlová, Jana; Podolská, Karolína
    In this prospective study involving 37 Duchenne muscular dystrophy (DMD) patients aged 8-18 years and older, we examined the impact of neurological and cardiac factors on quality of life (QoL). Our findings revealed a negative correlation between upper limb movement and overall mobility, self-service, and usual activities. Ambulatory and non-ambulatory DMD patients showed significant differences in mobility-related parameters. Cardiac evaluations demonstrated associations between mitral annular plane systolic excursion (MAPSE) and mobility-related aspects. The PEDSQL 3.0 neuromuscular model questionnaire further highlighted age-related and movement-related correlations with QoL. The loss of ambulatory status and reduced upper limb movement were negatively associated with QoL, while upper limb movement positively correlated with septal MAPSE. However, no significant associations were found between MAPSE and anxiety/depression. These findings underscore the multifaceted impact of DMD on QoL and emphasize the importance of considering both neurological and cardiac factors in comprehensive patient care.
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    Extracellular Vesicles and Hydrogels: An Innovative Approach to Tissue Regeneration
    (American Chemical Society, 2024-01-31) Hashemi, Amir; Ezati, Masoumeh; Partovi Nasr, Minoo; Zumberg, Inna; Provazník, Valentine
    Extracellular vesicles have emerged as promising tools in regenerative medicine due to their inherent ability to facilitate intercellular communication and modulate cellular functions. These nanosized vesicles transport bioactive molecules, such as proteins, lipids, and nucleic acids, which can affect the behavior of recipient cells and promote tissue regeneration. However, the therapeutic application of these vesicles is frequently constrained by their rapid clearance from the body and inability to maintain a sustained presence at the injury site. In order to overcome these obstacles, hydrogels have been used as extracellular vesicle delivery vehicles, providing a localized and controlled release system that improves their therapeutic efficacy. This Review will examine the role of extracellular vesicle-loaded hydrogels in tissue regeneration, discussing potential applications, current challenges, and future directions. We will investigate the origins, composition, and characterization techniques of extracellular vesicles, focusing on recent advances in exosome profiling and the role of machine learning in this field. In addition, we will investigate the properties of hydrogels that make them ideal extracellular vesicle carriers. Recent studies utilizing this combination for tissue regeneration will be highlighted, providing a comprehensive overview of the current research landscape and potential future directions.
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    Corynebacterium mendelii sp. nov., a novel bacterium isolated from Adélie penguin oral cavity
    (Microbiology Society, 2024-01-30) Koublová, Vendula; Sedlář, Karel; Sedláček, Ivo; Musilová, Jana; Staňková, Eva; Králová, Stanislava; Koudelková, Sylva; Krsek, Daniel; Švec, Pavel
    The taxonomic status of strain P5891T, isolated from an Adélie penguin beak swab, was investigated. Based on the 16S rRNA gene sequence, the strain was identified as a potentially novel Corynebacterium species, with the highest sequence similarities to Corynebacterium rouxii FRC0190T (96.7%) and Corynebacterium epidermidicanis DSM 45586T (96.6%). The average nucleotide identity values between strain P5891T and C. rouxii FRC0190T and C. epidermidicanis DSM 45586T were 68.2 and 69.2%, respectively. The digital DNA–DNA hybridization values between strain P5891T and C. rouxii FRC0190T and C. epidermidicanis DSM 45586T were 23.7 and 21.4%, respectively. Phylogenetic trees based on the 16S rRNA sequence placed strain P5891T in a separate branch with Corynebacterium canis 1170T and Corynebacterium freiburgense 1045T, while a phylogenomic tree based on the Corynebacterium species core genome placed the strain next to Corynebacterium choanae 200CHT. Extensive phenotyping and genomic analyses clearly confirmed that strain P5891T represents a novel species of the genus Corynebacterium, for which the name Corynebacterium mendelii sp. nov. is proposed, with the type strain P5891T (=CCM 8862T=LMG 31627T).