Abstract
Cardiac digital twins convert clinical images into physiological measurements through observation operators, yet calibration studies often assume a fixed reference convention. Across four shared-backbone echocardiographic EF front-ends, phase conditioning appears to remove CAMUSbaselinebias.Matched-referenceanalysisrejectsthisgain:singleplane ground-truth EF error is statistically indistinguishable across models, while single-plane ground-truth EF exceeds CAMUS biplane clinical EF by+6.30points, explaining nearly all baseline bias. A prespecified EchoNet-Dynamic replication, with released data and our extractor aligned to the apical four-chamber plane, removes baseline overestimation and reverses the CAMUS ranking. We also quantify haemodynamic effects,conformalresidual-widthbudgets,andEF-stratumchanges,yielding a Convention-Aware EF Audit protocol that separates genuine observationoperatorcalibrationfrommeasurementartefacts.GitHub:Ejection- Fraction-Bias-in-Cardiac-Digital-Twin.git
Links to Paper and Supplementary Materials
Main Paper (Open Access Version): https://papers.miccai.org/miccai-2026-sat/paper/DT4H_028.pdf
SharedIt Link: Not yet available
SpringerLink (DOI): Not yet available
Supplementary Material: Not Submitted
Link to Open Review
Open Review Page: https://openreview.net/forum?id=LitFwO8HTm
BibTex
@InProceedings{CaoDan_When_DT4H_MICCAISAT2026,
author = { Cao, Dang P. M. AND Pham, Hieu},
title = { { When Measurement Conventions Masquerade as Calibration Gains in Cardiac Digital Twins } },
booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026 Workshops and Challenges},
year = {2026},
publisher = {Springer Nature Switzerland},
volume = {LNCS 17275},
month = {pending},
page = {pending}
}