X-Cardia: Phenotype-Guided Cross-Modal Alignment for Opportunistic Cardiac Screening on Routine Chest CT

Nusrat Binta Nizam, Fengbei Liu, Sunwoo Kwak, Ilan Richter, Jayant K Raikhelkar, Ashley Beecy, Nir Uriel, Deborah Estrin, Mert R. Sabuncu

Keywords: Multimodal Alignment, Phenotype-Guided, Nadaraya–Watson head, Chest CT, Echocardiography, Electrocardiography.

TL;DR: Cross-Modal Alignment for Opportunistic Cardiac Screening

Abstract: Multimodal medical data offer an opportunity to learn general-purpose representations for cardiovascular diagnosis. We introduce X-Cardia, a cardiac phenotype-guided multimodal framework that uses structured data as intermediate supervision during pre-training. X-Cardia learns to extract cardiac information from non-contrast, non-gated chest CT scans by aligning CT features with tabular measurements derived from echocardiography (ECHO) and electrocardiography (ECG). Our method combines CLIP-style contrastive pre-training with a non-parametric Nadaraya–Watson (NW) prediction head that enforces phenotype-level similarity via exemplar-based alignment. Pre-training on 20,574 patients, followed by fine-tuning on ten cardiac abnormality prediction tasks, yields substantial performance gains. X-Cardia improves AUROC by up to 8% on the held-out test set and delivers an average 9.8% AUROC improvement in a 5-shot regime. These results demonstrate that explicit phenotype alignment produces interpretable, data-efficient representations and enables routine chest CT to support opportunistic cardiac screening. Code is available at: https://github.com/sumona00/X-Cardia.

Primary Subject Area: Application: Cardiology

Secondary Subject Area: Integration of Imaging and Clinical Data

Registration Requirement: Yes

Reproducibility: https://github.com/sumona00/X-Cardia

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Originality Policy: Yes

Single-blind & Not Under Review Elsewhere: Yes

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Submission Number: 133