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False lumen haemodynamics is a key determinant of aneurysmal growth, rupture, and thrombosis. Quantifying the haemodynamics in the false lumen can provide markers to predict these events and stratify patient risk. While such metrics can be extracted from numerical simulations or imaging modalities such as 4D flow MR, high-resolution experimental data are needed to validate them. The present study provides an in vitro characterization of the flow inside the false lumen of a type B aortic dissection using a patient-specific flexible phantom and Particle Image Velocimetry. A mock circulatory loop imposing patient-specific flow waveforms at the inlet and outlets of the aortic phantom and a refractive index matching blood analog were employed. Time-resolved measurements of the velocity field in four selected planes of the false lumen were acquired. Compared against our previous work on the same dissection assuming rigid walls, the results demonstrate the impact of wall compliance on the flow in the false lumen. They revealed the generation of a jet during the systolic phase that enters the false lumen through the primary tear and impinging on the opposite wall with high velocity, generating a strong rotational flow therein. During the diastolic phase, a reversal of the flow was observed generating multiple vortical structures both inside the true and false lumen. Haemodynamic markers such as false lumen ejection fraction were calculated and compared with clinical measurements. The results provide an insight on AD haemodynamics and highlight the potential of this in vitro method as a validation tool for simulations, as well as to physically test interventions in vitro.<\/jats:p>","DOI":"10.1007\/s10439-025-03875-z","type":"journal-article","created":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T19:10:24Z","timestamp":1763838624000},"page":"466-478","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["False Lumen Haemodynamics in Type B Aortic Dissection: An in Vitro Study Using PIV and Patient-Specific Flexible Phantoms"],"prefix":"10.1007","volume":"54","author":[{"given":"A.","family":"Koulogiannis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Q.","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Homer-Vanniasinkam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"V.","family":"Diaz-Zuccarini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6287-1106","authenticated-orcid":false,"given":"S.","family":"Balabani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,22]]},"reference":[{"key":"3875_CR1","doi-asserted-by":"publisher","unstructured":"Rolf-Pissarczyk, M., Schussnig, R., Fries, T. P., Fleischmann, D., Elefteriades, J. A., Humphrey, J. D., & Holzapfel, G. A. (2025). Mechanisms of aortic dissection: from pathological changes to experimental and in silico models. In Progress in Materials Science (Vol. 150). Elsevier Ltd. https:\/\/doi.org\/10.1016\/j.pmatsci.2024.101363","DOI":"10.1016\/j.pmatsci.2024.101363"},{"issue":"2","key":"3875_CR2","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1016\/j.jvs.2021.01.027","volume":"74","author":"F Squizzato","year":"2021","unstructured":"Squizzato, F., G. S. Oderich, P. Balachandran, E. R. Tenorio, B. C. Mendes, and R. R. De Martino. Effect of aortic angulation on the outcomes of fenestrated-branched endovascular aortic repair. 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Insights from the international registry of acute aortic dissection: A 20-year experience of collaborative clinical research. In Circulation 137(17), 1846\u20131860). Lippincott Williams and Wilkins. https:\/\/doi.org\/10.1161\/CIRCULATIONAHA.117.031264","DOI":"10.1161\/CIRCULATIONAHA.117.031264"},{"key":"3875_CR5","doi-asserted-by":"publisher","unstructured":"Bonfanti, M., Balabani, S., Greenwood, J. P., Puppala, S., Homer-Vanniasinkam, S., & Di\u00e1z-Zuccarini, V. (2017). Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data. J. Royal. Soc. Interface, 14(136). https:\/\/doi.org\/10.1098\/rsif.2017.0632","DOI":"10.1098\/rsif.2017.0632"},{"key":"3875_CR6","doi-asserted-by":"publisher","unstructured":"Stokes, C., Bonfanti, M., Li, Z., Xiong, J., Chen, D., Balabani, S., & D\u00edaz-Zuccarini, V. (2021). 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