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While intravascular optical imaging has revolutionized diagnosis, it remains a passive observation tool, restricted by \u201cphysical bottlenecks\u201d in resolution and \u201ccognitive bottlenecks\u201d in interpretation. To address these challenges, we frame our analysis around \u201cSuitcordance\u201d, 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.<\/jats:p>","DOI":"10.1038\/s41377-026-02410-6","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T01:22:41Z","timestamp":1785806561000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["From intravascular imaging to adaptive vascular care: intelligent photonics and digital twins in panvascular disease"],"prefix":"10.1038","volume":"15","author":[{"given":"Lingsen","family":"You","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaxin","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaoqing","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunlu","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1798-9922","authenticated-orcid":false,"given":"Rongjun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9360-7332","authenticated-orcid":false,"given":"Junbo","family":"Ge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"2410_CR1","doi-asserted-by":"publisher","first-page":"4528","DOI":"10.1093\/eurheartj\/ehac448","volume":"43","author":"X Zhou","year":"2022","unstructured":"Zhou, X. et al. 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