Fully automatic detection of strict left bundle branch block
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F18%3A00498008" target="_blank" >RIV/68081731:_____/18:00498008 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/00216305:26220/18:PU128406
Výsledek na webu
<a href="http://dx.doi.org/10.1016/j.jelectrocard.2018.06.013" target="_blank" >http://dx.doi.org/10.1016/j.jelectrocard.2018.06.013</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jelectrocard.2018.06.013" target="_blank" >10.1016/j.jelectrocard.2018.06.013</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Fully automatic detection of strict left bundle branch block
Popis výsledku v původním jazyce
Background: Strict left bundle branch block (tLBBB) is a diagnostic marker that was proposed for the detection of complete LBBB from ECG. The criteria for tLBBB include the presence of QS- or rS-configurations of QRS in V1 and V2, the presence of mid-QRS notching or slurring in at least two of leads V1, V2, V5, V6, I and avL, and finally a QRS duration (QRSd) of >130 ms (women) or 140 ms (men). Purpose: The main objective was to develop an automatic detector of tLBBB. This work was involved in the competition LBBB Initiative of the ICSE 2018. Methods: A total of 300 ECG recordings (10 s, 1000 Hz, 12 leads) from the MADIT-CRT database were used to develop the detector. QRS notching and slurring were detected by thresholding several features, e.g. width and prominence of local extremes in QRS (for QRS notching detection) and the width and prominence of the local extremes in the first derivative of QRS (for QRS slurring detection). The QRS configuration was evaluated according to the dominant deflection of the QRS. A publicly available algorithm (ECG SEEKER, Brno University of Technology) was used for measurement of QRS duration. Tests were performed using a hidden dataset (302 recordings). Results: The accuracy, sensitivity and specificity of tLBBB were 0.88, 0.86 and 0.90, respectively for the training dataset and 0.81, 0.69 and 0.87, respectively for the hidden testing dataset. The sensitivity and specificity of QRS configuration detection were 1.00 and 0.99, respectively for the training dataset. The average deviation of the reference values and measured QRSd is 9.8 ms. The positive predictive value (PPV) of QRS notching and slurring detection is 0.92 and 0.60, respectively for the training dataset. Conclusion: Although the created detector was the best in the competition LBBB Initiative of the ICSE 2018, the description of individual markers requires improvements prior to use in practice. More specifically, neither QRS notching and slurring nor the determination of the beginning and end of QRS notching/slurring are exactly defined. Our results also showed that the accuracy of tLBBB detection is also highly dependent on QRS onset and offset measurement which is generally problematic.
Název v anglickém jazyce
Fully automatic detection of strict left bundle branch block
Popis výsledku anglicky
Background: Strict left bundle branch block (tLBBB) is a diagnostic marker that was proposed for the detection of complete LBBB from ECG. The criteria for tLBBB include the presence of QS- or rS-configurations of QRS in V1 and V2, the presence of mid-QRS notching or slurring in at least two of leads V1, V2, V5, V6, I and avL, and finally a QRS duration (QRSd) of >130 ms (women) or 140 ms (men). Purpose: The main objective was to develop an automatic detector of tLBBB. This work was involved in the competition LBBB Initiative of the ICSE 2018. Methods: A total of 300 ECG recordings (10 s, 1000 Hz, 12 leads) from the MADIT-CRT database were used to develop the detector. QRS notching and slurring were detected by thresholding several features, e.g. width and prominence of local extremes in QRS (for QRS notching detection) and the width and prominence of the local extremes in the first derivative of QRS (for QRS slurring detection). The QRS configuration was evaluated according to the dominant deflection of the QRS. A publicly available algorithm (ECG SEEKER, Brno University of Technology) was used for measurement of QRS duration. Tests were performed using a hidden dataset (302 recordings). Results: The accuracy, sensitivity and specificity of tLBBB were 0.88, 0.86 and 0.90, respectively for the training dataset and 0.81, 0.69 and 0.87, respectively for the hidden testing dataset. The sensitivity and specificity of QRS configuration detection were 1.00 and 0.99, respectively for the training dataset. The average deviation of the reference values and measured QRSd is 9.8 ms. The positive predictive value (PPV) of QRS notching and slurring detection is 0.92 and 0.60, respectively for the training dataset. Conclusion: Although the created detector was the best in the competition LBBB Initiative of the ICSE 2018, the description of individual markers requires improvements prior to use in practice. More specifically, neither QRS notching and slurring nor the determination of the beginning and end of QRS notching/slurring are exactly defined. Our results also showed that the accuracy of tLBBB detection is also highly dependent on QRS onset and offset measurement which is generally problematic.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20601 - Medical engineering
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal of Electrocardiology
ISSN
0022-0736
e-ISSN
—
Svazek periodika
51
Číslo periodika v rámci svazku
6
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
4
Strana od-do
"S31"-"S34"
Kód UT WoS článku
000454674000007
EID výsledku v databázi Scopus
2-s2.0-85049903368