Literature DB >> 33956285

Statistical shape analysis of the left atrial appendage predicts stroke in atrial fibrillation.

Erik T Bieging1, Alan Morris2, Lowell Chang3,4, Lilas Dagher5, Nassir F Marrouche5, Joshua Cates4.   

Abstract

The shape of the left atrium (LA) and left atrial appendage (LAA) have been shown to predict stroke in patients with atrial fibrillation (AF). Prior studies rely on qualitative assessment of shape, which limits reproducibility and clinical utility. Statistical shape analysis (SSA) allows for quantitative assessment of shape. We use this method to assess the shape of the LA and LAA and predict stroke in patients with AF. From a database of AF patients who had previously undergone MRI of the LA, we identified 43 patients with AF who subsequently had an ischemic stroke. We also identified a cohort of 201 controls with AF who did not have a stroke after the MRI. We performed SSA of the LA and LAA shape to quantify the shape of these structures. We found three of the candidate LAA shape parameters to be predictive of stroke, while none of the LA shape parameters predicted stroke. When the three predictive LAA shape parameters were added to a logistic regression model that included the CHA2DS2-VASc score, the area under the ROC curve increased from 0.640 to 0.778 (p = .003). The shape of the LA and LAA can be assessed quantitatively using SSA. LAA shape predicts stroke in AF patients, while LA shape does not. Additionally, LAA shape predicts stroke independent of CHA2DS2-VASc score. SSA for assessment of LAA shape may improve stroke risk stratification and clinical decision making for AF patients.
© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Entities:  

Keywords:  Atrial fibrillation; Cerebrovascular disease/stroke; Left atrial appendage; Left atrium; Magnetic resonance imaging; Shape

Mesh:

Year:  2021        PMID: 33956285      PMCID: PMC8316337          DOI: 10.1007/s10554-021-02262-8

Source DB:  PubMed          Journal:  Int J Cardiovasc Imaging        ISSN: 1569-5794            Impact factor:   2.316


  32 in total

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3.  Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network.

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Journal:  IEEE Trans Med Imaging       Date:  2019-02       Impact factor: 10.048

4.  2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society.

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Journal:  Circulation       Date:  2014-03-28       Impact factor: 29.690

5.  The left atrial appendage morphology is associated with embolic stroke subtypes using a simple classification system: A proof of concept study.

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Journal:  J Cardiovasc Comput Tomogr       Date:  2019-04-16

6.  Regularization Paths for Generalized Linear Models via Coordinate Descent.

Authors:  Jerome Friedman; Trevor Hastie; Rob Tibshirani
Journal:  J Stat Softw       Date:  2010       Impact factor: 6.440

7.  Left Atrial and Left Atrial Appendage 4D Blood Flow Dynamics in Atrial Fibrillation.

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8.  Morphologic remodeling of left atrial appendage in patients with atrial fibrillation.

Authors:  Hideyuki Kishima; Takanao Mine; Satoshi Takahashi; Kenki Ashida; Masaharu Ishihara; Tohru Masuyama
Journal:  Heart Rhythm       Date:  2016-06-09       Impact factor: 6.343

9.  Does the left atrial appendage morphology correlate with the risk of stroke in patients with atrial fibrillation? Results from a multicenter study.

Authors:  Luigi Di Biase; Pasquale Santangeli; Matteo Anselmino; Prasant Mohanty; Ilaria Salvetti; Sebastiano Gili; Rodney Horton; Javier E Sanchez; Rong Bai; Sanghamitra Mohanty; Agnes Pump; Mauricio Cereceda Brantes; G Joseph Gallinghouse; J David Burkhardt; Federico Cesarani; Marco Scaglione; Andrea Natale; Fiorenzo Gaita
Journal:  J Am Coll Cardiol       Date:  2012-08-07       Impact factor: 24.094

10.  Statistical shape modeling of the left ventricle: myocardial infarct classification challenge.

Authors:  Avan Suinesiaputra; Pierre Ablin; Xenia Alba; Martino Alessandrini; Jack Allen; Wenjia Bai; Serkan Cimen; Peter Claes; Brett R Cowan; Jan D'hooge; Nicolas Duchateau; Jan Ehrhardt; Alejandro F Frangi; Ali Gooya; Vicente Grau; Karim Lekadir; Allen Lu; Anirban Mukhopadhyay; Ilkay Oksuz; Nripesh Parajali; Xavier Pennec; Marco Pereanez; Catarina Pinto; Paolo Piras; Marc-Michel Rohe; Daniel Rueckert; Dennis Saring; Maxime Sermesant; Kaleem Siddiqi; Mahdi Tabassian; Luciano Teresi; Sotirios A Tsaftaris; Matthias Wilms; Alistair A Young; Xingyu Zhang; Pau Medrano-Gracia
Journal:  IEEE J Biomed Health Inform       Date:  2017-01-17       Impact factor: 5.772

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1.  Increased Blood Residence Time as Markers of High-Risk Patent Foramen Ovale.

Authors:  Gianluca Rigatelli; Marco Zuin; Loris Roncon
Journal:  Transl Stroke Res       Date:  2022-06-11       Impact factor: 6.829

2.  Left atrial evaluation by cardiovascular magnetic resonance: sensitive and unique biomarkers.

Authors:  Dana C Peters; Jérôme Lamy; Albert J Sinusas; Lauren A Baldassarre
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2021-12-18       Impact factor: 6.875

3.  Evaluation of Stroke Risk in Patients With Atrial Fibrillation Using Morphological and Hemodynamic Characteristics.

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Review 4.  Stroke risk evaluation for patients with atrial fibrillation: Insights from left atrial appendage.

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Review 5.  A Review of Biomarkers for Ischemic Stroke Evaluation in Patients With Non-valvular Atrial Fibrillation.

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