Reference Framework for Implementation of Cardiovascular Imaging in Clinical Trials. A Scientific Statement of the European Association of Cardiovascular Imaging (EACVI) of the ESC

Clicks: 1
ID: 319190
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #87 of 96 articles by views in European Heart Journal - Cardiovascular Imaging

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Cardiovascular imaging is integral to modern clinical trials of new pharmaceuticals or devices, enabling refined eligibility, mechanistic insight, and sensitive assessment of treatment response and safety. Potential heterogeneity in data acquisition, analysis, and reporting may affect reproducibility and interpretability across multicentre settings. Rigorous standardization and fit-for-purpose validation of imaging endpoints can improve statistical efficiency, reduce trial duration and cost, and strengthen generated evidence. This Scientific Statement outlines a reference framework for the implementation of cardiovascular imaging in clinical trials. We provide considerations on use of imaging parameters as eligibility criteria in clinical trials, for efficacy signals evaluation, and for assessment of safety. We define principles for clinical, analytical, and operational validation of imaging endpoints, and discuss concepts of minimal clinically important change and minimal detectable change. Additionally, we discuss feasibility considerations for use of cardiovascular imaging endpoints in multicentre clinical trials where differences in equipment and local experience may exist. We delineate standards for harmonization, centralized analysis, and quality control in clinical trials, as well as challenges and opportunities of the integration of artificial intelligence within core-lab workflows. Lastly, we identify gaps in knowledge, challenge of preclinical-clinical translatability and highlight training needs and innovation priorities.
Reference Key
openalex_W7166873784 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Elena Surkova, Alessia Gimelli, Andreas A. Giannopoulos, Nina Ajmone Marsan, Andrea Baggiano, Maja Čikeš, Anna Baritussio, Arti A. Ramkisoensing, Marc R. Dweck, Maribel González‐Del‐Hoyo, Jaume Agüero, Philippe B. Bertrand, Marianna Fontana, Riccardo M. Inciardi, Michael T. Lu, Victoria Delgado
Journal European Heart Journal - Cardiovascular Imaging
Year 2026
DOI
10.1093/ehjci/jeag171
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.