Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment
<p>This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered fo...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2024
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| _version_ | 1811139690804281344 |
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| author | Corral Acero, J Lamata, P Eitel, I Zacur, E Evertz, R Lange, T Backhaus, SJ Stiermaier, T Thiele, H Bueno-Orovio, A Schuster, A Grau, V |
| author_facet | Corral Acero, J Lamata, P Eitel, I Zacur, E Evertz, R Lange, T Backhaus, SJ Stiermaier, T Thiele, H Bueno-Orovio, A Schuster, A Grau, V |
| author_sort | Corral Acero, J |
| collection | OXFORD |
| description | <p>This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered for the study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE, n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. Cardiac function was characterized from CMR in 3 potential directions: by (1) volume temporal transients (i.e. contraction dynamics); (2) feature tracking strain analysis (i.e. bulk tissue peak contraction); and (3) 3D shape analysis (i.e. 3D contraction morphology). A fully automated pipeline was developed to extract conventional and novel artificial-intelligence-derived metrics of cardiac contraction, and their relationship with MACE was investigated. Any of the 3 proposed directions demonstrated its additional prognostic value on top of established CMR indexes, myocardial injury markers, basic characteristics, and cardiovascular risk factors (<em>P</em> < 0.001). The combination of these 3 directions of enhancement towards a final CMR risk model improved MACE prediction by 13% compared to clinical baseline (0.774 (0.771—0.777) vs. 0.683 (0.681—0.685) cross-validated AUC, <em>P</em> < 0.001). The study evidences the contribution of the novel contraction characterization, enabled by a fully automated pipeline, to post-infarction assessment.</p> |
| first_indexed | 2024-09-25T04:10:06Z |
| format | Journal article |
| id | oxford-uuid:28910fb4-b99e-4b11-9139-47d00485e888 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:10:06Z |
| publishDate | 2024 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:28910fb4-b99e-4b11-9139-47d00485e8882024-06-20T11:42:02ZComprehensive characterization of cardiac contraction for improved post-infarction risk assessmentJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:28910fb4-b99e-4b11-9139-47d00485e888EnglishSymplectic ElementsSpringer Nature2024Corral Acero, JLamata, PEitel, IZacur, EEvertz, RLange, TBackhaus, SJStiermaier, TThiele, HBueno-Orovio, ASchuster, AGrau, V<p>This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered for the study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE, n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. Cardiac function was characterized from CMR in 3 potential directions: by (1) volume temporal transients (i.e. contraction dynamics); (2) feature tracking strain analysis (i.e. bulk tissue peak contraction); and (3) 3D shape analysis (i.e. 3D contraction morphology). A fully automated pipeline was developed to extract conventional and novel artificial-intelligence-derived metrics of cardiac contraction, and their relationship with MACE was investigated. Any of the 3 proposed directions demonstrated its additional prognostic value on top of established CMR indexes, myocardial injury markers, basic characteristics, and cardiovascular risk factors (<em>P</em> < 0.001). The combination of these 3 directions of enhancement towards a final CMR risk model improved MACE prediction by 13% compared to clinical baseline (0.774 (0.771—0.777) vs. 0.683 (0.681—0.685) cross-validated AUC, <em>P</em> < 0.001). The study evidences the contribution of the novel contraction characterization, enabled by a fully automated pipeline, to post-infarction assessment.</p> |
| spellingShingle | Corral Acero, J Lamata, P Eitel, I Zacur, E Evertz, R Lange, T Backhaus, SJ Stiermaier, T Thiele, H Bueno-Orovio, A Schuster, A Grau, V Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment |
| title | Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment |
| title_full | Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment |
| title_fullStr | Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment |
| title_full_unstemmed | Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment |
| title_short | Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment |
| title_sort | comprehensive characterization of cardiac contraction for improved post infarction risk assessment |
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