Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Multicenter Study
. 2024 Jul;17(7):746-762.
doi: 10.1016/j.jcmg.2024.01.009. Epub 2024 Apr 10.

Cardiovascular Magnetic Resonance Reference Ranges From the Healthy Hearts Consortium

Zahra Raisi-Estabragh  1 , Liliana Szabo  2 , Celeste McCracken  3 , Robin Bülow  4 , Giovanni Donato Aquaro  5 , Florian Andre  6 , Thu-Thao Le  7 , Dominika Suchá  8 , Dorina-Gabriela Condurache  1 , Ahmed M Salih  9 , Sucharitha Chadalavada  1 , Nay Aung  1 , Aaron Mark Lee  10 , Nicholas C Harvey  11 , Tim Leiner  12 , Calvin W L Chin  7 , Matthias G Friedrich  13 , Andrea Barison  14 , Marcus Dörr  15 , Steffen E Petersen  16
Affiliations
Free article
Multicenter Study

Cardiovascular Magnetic Resonance Reference Ranges From the Healthy Hearts Consortium

Zahra Raisi-Estabragh et al. JACC Cardiovasc Imaging. 2024 Jul.
Free article

Abstract

Background: The absence of population-stratified cardiovascular magnetic resonance (CMR) reference ranges from large cohorts is a major shortcoming for clinical care.

Objectives: This paper provides age-, sex-, and ethnicity-specific CMR reference ranges for atrial and ventricular metrics from the Healthy Hearts Consortium, an international collaborative comprising 9,088 CMR studies from verified healthy individuals, covering the complete adult age spectrum across both sexes, and with the highest ethnic diversity reported to date.

Methods: CMR studies were analyzed using certified software with batch processing capability (cvi42, version 5.14 prototype, Circle Cardiovascular Imaging) by 2 expert readers. Three segmentation methods (smooth, papillary, anatomic) were used to contour the endocardial and epicardial borders of the ventricles and atria from long- and short-axis cine series. Clinically established ventricular and atrial metrics were extracted and stratified by age, sex, and ethnicity. Variations by segmentation method, scanner vendor, and magnet strength were examined. Reference ranges are reported as 95% prediction intervals.

Results: The sample included 4,452 (49.0%) men and 4,636 (51.0%) women with average age of 61.1 ± 12.9 years (range: 18-83 years). Among these, 7,424 (81.7%) were from White, 510 (5.6%) South Asian, 478 (5.3%) mixed/other, 341 (3.7%) Black, and 335 (3.7%) Chinese ethnicities. Images were acquired using 1.5-T (n = 8,779; 96.6%) and 3.0-T (n = 309; 3.4%) scanners from Siemens (n = 8,299; 91.3%), Philips (n = 498; 5.5%), and GE (n = 291, 3.2%).

Conclusions: This work represents a resource with healthy CMR-derived volumetric reference ranges ready for clinical implementation.

Keywords: artificial intelligence; automated analysis; cardiovascular magnetic resonance; ethnicity; healthy reference ranges; sex differences.

PubMed Disclaimer

Conflict of interest statement

Funding Support and Author Disclosures Dr Raisi-Estabragh recognizes the National Institute for Health and Care Research (NIHR) Integrated Academic Training program, which supports her Academic Clinical Lectureship post. Dr Szabo was supported by the Barts Charity (G-002389). Celeste McCracken is supported by the Oxford NIHR Biomedical Research Centre (IS-BRC-1215-20008). Dr Salih was supported by the British Heart Foundation (PG/21/10619). Dr Condurache was supported by the Barts Charity (G-002530). This work acknowledges the support of the NIHR Barts Biomedical Research Centre (NIHR203330); a delivery partnership of Barts Health National Health Service (NHS) Trust, Queen Mary University of London, St George’s University Hospitals NHS Foundation Trust, and St George’s University of London. Drs Szabo, Petersen, and Lee have received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement number 825903 (euCanSHare project). Barts Charity (G-002346) contributed to fees required to access UK Biobank data (access application 2964). Dr Leiner acknowledges support by the Netherlands Organization for Health Research and Development (grant number 90700432). Dr Harvey is supported by the UK Medical Research Council (MC_PC_21003; MC_PC_21001); NIHR Southampton Biomedical Research Centre, University of Southampton; and University Hospital Southampton NHS Foundation Trust, United Kingdom. Drs Friedrich and Petersen provide consultancy to Circle Cardiovascular Imaging Inc, Calgary, Alberta, Canada. This paper is supported by the London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare (AI4VBH), which is funded from the Data to Early Diagnosis and Precision Medicine strand of the government’s Industrial Strategy Challenge Fund, managed and delivered by Innovate UK on behalf of UK Research and Innovation (UKRI). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Publication types

MeSH terms

LinkOut - more resources