From intravascular imaging to adaptive vascular care: intelligent photonics and digital twins in panvascular disease.

Authors

Lingsen You, Jiaxin Yao, Yaoqing Qiu, Yu Wang, Yunlu Sun, Rongjun Zhang, Li Shen, Junbo Ge

Published in

Light, science & applications. Volume 15. Issue 1. Aug 04, 2026. Epub Aug 04, 2026.

Abstract

Panvascular diseases (PVDs) stand as the leading cause of global mortality, necessitating a paradigm shift from local anatomical repair to the systemic restoration of vascular homeostasis. While intravascular optical imaging has revolutionized diagnosis, it remains a passive observation tool, restricted by "physical bottlenecks" in resolution and "cognitive bottlenecks" in interpretation. To address these challenges, we frame our analysis around "Suitcordance", a concept aiming to capture the dynamic state of matching between interventional devices and the vascular microenvironment. In this review, we use Suitcordance as a working analytical framework to represent such a clinically-targeted, integrated perspective, and to organize the evidence on intravascular optical imaging and its integration with artificial intelligence. First, we summarize recent advances in intravascular imaging modalities, including micro-OCT, hybrid systems, and emerging detection technologies. Second, we review how AI-based image analysis and image-derived digital twin models are being applied to interpret these data and to support procedural decision-making. On this basis, we discuss how such tools may contribute to a more individualized assessment of device-vessel matching in panvascular disease.

PMID:
42547494
Bibliographic data and abstract were imported from PubMed on 04 Aug 2026.

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