发现心脏数字孪生中测量惯例导致的误差，而非模型校准问题。
When Measurement Conventions Masquerade as Calibration Gains in Cardiac Digital Twins
- 通过统一参考标准分析，发现相位调理并非真正提升性能。
- 单平面真实射血分数比双平面临床值高6.30点，解释了偏差来源。
- 提出规范感知的射血分数审计协议，适合医疗影像模型评估者。
心脏数字孪生通过观测算子将临床影像转化为生理参数，但校准研究常假设参考标准固定。在四个共享骨干的超声心动图射血分数前端中，相位调理看似消除了CAMUS基线偏差。然而，匹配参考分析显示：各模型的单平面真实射血分数误差无统计差异；且单平面真实射血分数比CAMUS双平面临床值高出6.30个百分点，几乎完全解释了基线偏差。一项预设的EchoNet-Dynamic复现研究（公开数据与提取器对齐心尖四腔面）消除了基线高估，并逆转了CAMUS排名。我们还量化了血流动力学影响、共形残差宽度预算及射血分数分层变化，提出‘惯例感知’射血分数审计协议，可区分真实观测算子校准与测量伪影。代码仓库：EjectionFraction-Bias-in-Cardiac-Digital-Twin.git
原文摘要 · Abstract (English)
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 CAMUS baseline bias. Matched-reference analysis rejects this gain: singleplane ground-truth EF error is statistically indistinguishable across models, while single-plane ground-truth EF exceeds CAMUS biplane clinical EF by +6.30 points, 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, conformal residual-width budgets, and EF-stratum changes, yielding a Convention-Aware EF Audit protocol that separates genuine observation operator calibration from measurement artefacts. GitHub: EjectionFraction-Bias-in-Cardiac-Digital-Twin.git
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