How can the left atrial strain be correctly determined by cardiovascular magnetic resonance feature tracking?

Optimized LA planning procedure for assessment of the longest LA dimensions results in significant alterations in CMR quantifications with increased chamber volumetrics and decreased strain and strain rates compared to standard procedure.

Authors

Institutions

Publication Details

Journal
Frontiers in Cardiovascular Medicine
Published
2025-03-31
DOI
https://doi.org/10.3389/fcvm.2025.1558102
Citations
1
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
1.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How can the left atrial strain be correctly determined by cardiovascular magnetic resonance feature tracking?

Wolfgang Burchert, Christian Stehning, Hermann Körperich, Niroshan Shanmugarajah et al.
1 citations
Frontiers in Cardiovascular Medicine
Cardiovascular Function and Risk Factors
1.39
article

How can the left atrial strain be correctly determined by cardiovascular magnetic resonance feature tracking?

Wolfgang Burchert, Christian Stehning, Hermann Körperich, Niroshan Shanmugarajah, Rehsan Akkuzu, Jan Eckstein, O. Weber, Tobias Rossnagel
article en
1 citations

Abstract

Optimized LA planning procedure for assessment of the longest LA dimensions results in significant alterations in CMR quantifications with increased chamber volumetrics and decreased strain and strain rates compared to standard procedure.

Frontiers in Cardiovascular MedicineVol. 12
Philips (Germany) (DE)
Openalex Percentile: Top 21%
Cardiovascular Function and Risk Factors
1.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.