Evidence map›Paper›PMID 40629198›Full record

ArticleJournal of imaging informatics in medicine2026

Inter-AI Agreement in Measuring Cine MRI-Derived Cardiac Function and Motion Patterns: A Pilot Study.

Kai Lin, Roberto Sarnari, Daniel Z Gordon, Michael Markl, James C Carr

Abstract read
In one paragraph

Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kai LinDepartment of Radiology, Northwestern University, 737 N Michigan Avenue, Suite 1600, Chicago, IL, 60611, USA. kai-lin@northwestern.edu.ORCID http://orcid.org/0000-0002-0540-4077
Roberto SarnariDepartment of Radiology, Northwestern University, 737 N Michigan Avenue, Suite 1600, Chicago, IL, 60611, USA.
Daniel Z GordonDepartment of Radiology, Northwestern University, 737 N Michigan Avenue, Suite 1600, Chicago, IL, 60611, USA.
Michael MarklDepartment of Radiology, Northwestern University, 737 N Michigan Avenue, Suite 1600, Chicago, IL, 60611, USA.
James C CarrDepartment of Radiology, Northwestern University, 737 N Michigan Avenue, Suite 1600, Chicago, IL, 60611, USA.

Funding

Comprehensive Cardiac Structure-Function Analysis in Heart TransplantationR01HL117888 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI CARR, JAMES, MARKL, MICHAEL · 2014 to 2025
$6.4M
Quantitative MRI for the assessment of subclinical CAD in T2DMK01HL121162 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI LIN, KAI · 2015 to 2019
$800k
Automatic quantification of myocardial motion in older adultsR03HL144891 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI LIN, KAI · 2018 to 2019
$158k
NHLBI NIH HHS K01HL121162NHLBI NIH HHS R01HL117888NHLBI NIH HHS R03HL144891
6 · The paper itself

Abstract

Manually analyzing a series of MRI images to obtain information about the heart's motion is a time-consuming and labor-intensive task. Recently, many AI-driven tools have been used to automatically analyze cardiac MRI. However, it is still unknown whether the results generated by these tools are consistent. The aim of the present study was to investigate the agreement of AI-powered automated tools for measuring cine MRI-derived cardiac function and motion indices. Cine MRI datasets of 23 healthy volunteers (10 males, 32.7 ± 11.3 years) were processed using heart deformation analysis (HDA, Trufistrain) and Circle CVI 42. The left and right ventricular (LV/RV) end-diastolic volume (LVEDV and RVEDV), end-systolic volume (LVESV and RVESV), stroke volume (LVSV and RVSV), cardiac output (LVCO and RVCO), ejection fraction (LVEF and RVEF), LV mass (LVM), LV global strain, strain rate, displacement, and velocity were calculated without interventions. Agreements and discrepancies of indices acquired with the two tools were evaluated from various aspects using t-tests, Pearson correlation coefficient (r), interclass correlation coefficient (ICC), and coefficient of variation (CoV). Systematic biases for measuring cardiac function and motion indices were observed. In global cardiac function indices, LVEF (56.9% ± 6.4 vs. 57.8% ± 5.7, p = 0.433, r = 0.609, ICC = 0.757, CoV = 6.7%) and LVM (82.7 g ± 21.6 vs. 82.6 g ± 18.7, p = 0.988, r = 0.923, ICC = 0.956, CoV = 11.7%) acquired with HDA and Circle seemed to be exchangeable. Among cardiac motion indices, circumferential strain rate demonstrated good agreements between two tools (97 ± 14.6 vs. 97.8 ± 13.6, p = 0.598, r = 0.89, ICC = 0.943, CoV = 5.1%). Cine MRI-derived cardiac function and motion indices obtained using different AI-powered image processing tools are related but may also differ. Such variations should be considered when evaluating results sourced from different studies.

Indexed as

Artificial IntelligenceHeartImage Interpretation, Computer-AssistedMagnetic Resonance Imaging, CineAdultFemaleHumansIntelligent SystemsMalePilot ProjectsReproducibility of ResultsStroke VolumeAgreementArtificial intelligenceCardiac functionCine MRIMotion

Identifiers

PMID40629198
PMCPMC13230414

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.