Cardiometry: Open-Source, Reliable and Efficient Computation of Quantitative Parameters in Cardiovascular Magnetic Resonance

Motivation: The calculation of clinical results in cardiovascular magnetic resonance (CMR) depends on the exact processing of image and contour information. Research applications require reliable and automatable software with open interfaces. Goal(s): Our goal was to establish Cardiometry as a tested and open library for the computation of reliable quantitative parameters in CMR. Approach: We compared cardiac function parameters in 149 patients as well as parametric mapping, late gadolinium enhancement and atrial volumes in ten patients each to proprietary medical software. Results: Cardiometry rendered results in 0.34 seconds per case. Mean absolute deviations were close to zero for all comparisons. Impact: Cardiometry produces equivalent clinical results to proprietary medical software. As an open-source library, it enables efficient and automated quantification of cardiac function, T1 and T2 parametric mapping and late gadolinium enhancement for research applications in cardiovascular magnetic resonance.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0945
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cardiometry: Open-Source, Reliable and Efficient Computation of Quantitative Parameters in Cardiovascular Magnetic Resonance

Richard Hickstein, Jan Gröschel, Clemens Ammann, Jeanette Schulz‐Menger et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Advanced MRI Techniques and Applications
article

Cardiometry: Open-Source, Reliable and Efficient Computation of Quantitative Parameters in Cardiovascular Magnetic Resonance

Richard Hickstein, Jan Gröschel, Clemens Ammann, Jeanette Schulz‐Menger, Thomas Hadler, Halil Noyan, Philine Reisdorf, Jonathan Gavrysh
article en

Abstract

Motivation: The calculation of clinical results in cardiovascular magnetic resonance (CMR) depends on the exact processing of image and contour information. Research applications require reliable and automatable software with open interfaces. Goal(s): Our goal was to establish Cardiometry as a tested and open library for the computation of reliable quantitative parameters in CMR. Approach: We compared cardiac function parameters in 149 patients as well as parametric mapping, late gadolinium enhancement and atrial volumes in ten patients each to proprietary medical software. Results: Cardiometry rendered results in 0.34 seconds per case. Mean absolute deviations were close to zero for all comparisons. Impact: Cardiometry produces equivalent clinical results to proprietary medical software. As an open-source library, it enables efficient and automated quantification of cardiac function, T1 and T2 parametric mapping and late gadolinium enhancement for research applications in cardiovascular magnetic resonance.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 65%
Advanced MRI Techniques and Applications
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.