Understanding and Improving Risk Assessment After Myocardial Infarction Using Automated Left Ventricular Shape Analysis

Acero, Jorge Corral; Schuster, Andreas; Zacur, Ernesto; Lange, Torben; Stiermaier, Thomas; Backhaus, Sören J.; Thiele, Holger; Bueno‐Orovio, Alfonso; Lamata, Pablo; Eitel, Ingo; Grau, Vicente

doi:10.1016/j.jcmg.2021.11.027

Cited by 25 publications

(19 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The shape features derived in this study can be automatically computed, using machine learning image analysis combined with an automated modelling pipeline, as demonstrated recently for the LV [ 26 , 27 ]. Routine computation of shape scores will add to the spectrum of imaging biomarkers, including tissue characterization, fluid dynamics, and stress imaging in order to improve patient characterization and risk prediction.…”

Section: Discussionmentioning

confidence: 99%

Le CÅ“ur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot

Mira

Lamata

Pushparajah

et al. 2022

Journal of Cardiovascular Magnetic Resonance

Self Cite

View full text Add to dashboard Cite

Background Maladaptive remodelling mechanisms occur in patients with repaired tetralogy of Fallot (rToF) resulting in a cycle of metabolic and structural changes. Biventricular shape analysis may indicate mechanisms associated with adverse events independent of pulmonary regurgitant volume index (PRVI). We aimed to determine novel remodelling patterns associated with adverse events in patients with rToF using shape and function analysis. Methods Biventricular shape and function were studied in 192 patients with rToF (median time from TOF repair to baseline evaluation 13.5 years). Linear discriminant analysis (LDA) and principal component analysis (PCA) were used to identify shape differences between patients with and without adverse events. Adverse events included death, arrhythmias, and cardiac arrest with median follow-up of 10 years. Results LDA and PCA showed that shape characteristics pertaining to adverse events included a more circular left ventricle (LV) (decreased eccentricity), dilated (increased sphericity) LV base, increased right ventricular (RV) apical sphericity, and decreased RV basal sphericity. Multivariate LDA showed that the optimal discriminative model included only RV apical ejection fraction and one PCA mode associated with a more circular and dilated LV base (AUC = 0.77). PRVI did not add value, and shape changes associated with increased PRVI were not predictive of adverse outcomes. Conclusion Pathological remodelling patterns in patients with rToF are significantly associated with adverse events, independent of PRVI. Mechanisms related to incident events include LV basal dilation with a reduced RV apical ejection fraction.

show abstract

Section: Discussionmentioning

confidence: 99%

Le CÅ“ur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot

Mira

Lamata

Pushparajah

et al. 2022

Journal of Cardiovascular Magnetic Resonance

Self Cite

View full text Add to dashboard Cite

show abstract

“…Consequently, for automated comprehensive cardiac functional analyses and tissue characterisation parallel to image acquisition, further developments are warranted. Such future developments combining myocardial shape and function have recently been described and may even further expand our options for fully AI based quantification of cardiac phenotypes with potentially even better prediction of clinical outcome and management of cardiac therapies 34 .…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence fully automated myocardial strain quantification for risk stratification following acute myocardial infarction

Backhaus

Aldehayat

Kowallick

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Feasibility of automated volume-derived cardiac functional evaluation has successfully been demonstrated using cardiovascular magnetic resonance (CMR) imaging. Notwithstanding, strain assessment has proven incremental value for cardiovascular risk stratification. Since introduction of deformation imaging to clinical practice has been complicated by time-consuming post-processing, we sought to investigate automation respectively. CMR data (n = 1095 patients) from two prospectively recruited acute myocardial infarction (AMI) populations with ST-elevation (STEMI) (AIDA STEMI n = 759) and non-STEMI (TATORT-NSTEMI n = 336) were analysed fully automated and manually on conventional cine sequences. LV function assessment included global longitudinal, circumferential, and radial strains (GLS/GCS/GRS). Agreements were assessed between automated and manual strain assessments. The former were assessed for major adverse cardiac event (MACE) prediction within 12 months following AMI. Manually and automated derived GLS showed the best and excellent agreement with an intraclass correlation coefficient (ICC) of 0.81. Agreement was good for GCS and poor for GRS. Amongst automated analyses, GLS (HR 1.12, 95% CI 1.08–1.16, p < 0.001) and GCS (HR 1.07, 95% CI 1.05–1.10, p < 0.001) best predicted MACE with similar diagnostic accuracy compared to manual analyses; area under the curve (AUC) for GLS (auto 0.691 vs. manual 0.693, p = 0.801) and GCS (auto 0.668 vs. manual 0.686, p = 0.425). Amongst automated functional analyses, GLS was the only independent predictor of MACE in multivariate analyses (HR 1.10, 95% CI 1.04–1.15, p < 0.001). Considering high agreement of automated GLS and equally high accuracy for risk prediction compared to the reference standard of manual analyses, automation may improve efficiency and aid in clinical routine implementation.Trial registration: ClinicalTrials.gov, NCT00712101 and NCT01612312.

show abstract

“…Although they were able to determine a low-risk subgroup, there was a poor positive predictive value, plausibly because VT does not only require the appropriate substrate, but also sufficient triggers that may fluctuate over time. Other mechanical properties besides scarring could also be used in analogy to the research of Balaban et al [74], who used left ventricle threedimensional (3D) shapes to predict VTs in dilated cardiomyopathy patients, and of Corral Acero et al [75], who showed in a multi-centre cohort that 3D left ventricle shape and contraction metrics could predict major adverse cardiac events 1 year after MI.…”

Section: Ventricular Tachycardia Predictionmentioning

confidence: 99%

From evidence-based medicine to digital twin technology for predicting ventricular tachycardia in ischaemic cardiomyopathy

Lepper

Buck

Veer

et al. 2022

J. R. Soc. Interface.

View full text Add to dashboard Cite

Survivors of myocardial infarction are at risk of life-threatening ventricular tachycardias (VTs) later in their lives. Current guidelines for implantable cardioverter defibrillators (ICDs) implantation to prevent VT-related sudden cardiac death is solely based on symptoms and left ventricular ejection fraction. Catheter ablation of scar-related VTs is performed following ICD therapy, reducing VTs, painful shocks, anxiety, depression and worsening heart failure. We postulate that better prediction of the occurrence and circuit of VT, will improve identification of patients at risk for VT and boost preventive ablation, reducing mortality and morbidity. For this purpose, multiple time-evolving aspects of the underlying pathophysiology, including the anatomical substrate, triggers and modulators, should be part of VT prediction models. We envision digital twins as a solution combining clinical expertise with three prediction approaches: evidence-based medicine (clinical practice), data-driven models (data science) and mechanistic models (biomedical engineering). This paper aims to create a mutual understanding between experts in the different fields by providing a comprehensive description of the clinical problem and the three approaches in an understandable manner, leveraging future collaborations and technological innovations for clinical decision support. Moreover, it defines open challenges and gains for digital twin solutions and discusses the potential of hybrid modelling.

show abstract

Understanding and Improving Risk Assessment After Myocardial Infarction Using Automated Left Ventricular Shape Analysis

Cited by 25 publications

References 25 publications

Le CÅ“ur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot

Le CÅ“ur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot

Artificial intelligence fully automated myocardial strain quantification for risk stratification following acute myocardial infarction

From evidence-based medicine to digital twin technology for predicting ventricular tachycardia in ischaemic cardiomyopathy

Contact Info

Product

Resources

About