Background: Stanford type B dissection of the descending aorta is a potentially fatal condition that is poorly understood. Limited scientific understanding of the role of current interventional techniques, as well as heterogeneity in the condition, contributes to lack of consensus as to the most effective treatment strategy. This study introduces an anatomically accurate model for investigating aortic dissection in a laboratory setting.
Materials And Methods: A silicone model was fabricated and filled with fluid to mimic human blood. Flow was established, and the model was scanned using a four-dimensional flow magnetic resonance imaging protocol. On analysis, luminal flow rates were quantified by multiplying local velocity by included area.
Results: The upstream total flow was compared with the sum of the flow in the true and false lumens. The two values were within the margin of error. Furthermore, flow rates matched with the relative areas of each compartment.
Conclusions: These results validate our model as a novel and unique system that mimics a type B aortic dissection and will allow for more sophisticated analysis of dissection physiology in future studies.
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http://dx.doi.org/10.1016/j.jss.2015.03.024 | DOI Listing |
Hypertension
January 2025
Cardiology Division, Department of Medicine, Emory University School of Medicine, Atlanta, GA. (X.Z., Q.X., A.V., Z.L.).
Background: Recent studies show that hyperactivation of mTOR (mammalian target of rapamycin) signaling plays a causal role in the development of thoracic aortic aneurysm and dissection. Modulation of PP2A (protein phosphatase 2A) activity has been shown to be of significant therapeutic value. In light of the effects that PP2A can exert on the mTOR pathway, we hypothesized that PP2A activation by small-molecule activators of PP2A could mitigate AA progression in Marfan syndrome (MFS).
View Article and Find Full Text PDFJ Vasc Surg Cases Innov Tech
April 2025
Department of Cardiovascular Surgery, Higashiosaka City Medical Center, Higashiosaka, Osaka, Japan.
A 69-year-old man with chest pain was diagnosed with acute type B aortic dissection with the entry tear located at distal arch and a distal aortic arch aneurysm. Therefore, we performed debranching thoracic endovascular aortic repair 2 weeks after type B aortic dissection onset. First, the graft was anastomosed to bilateral axillary arteries.
View Article and Find Full Text PDFClin Neurol Neurosurg
January 2025
The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address:
Objective: To explore the anatomical and clinical factors that affect the radiographic exposure time in radial artery cerebral angiography and to establish a model.
Method: A total of 210 patients who underwent radial artery cerebral angiography at this center from September 2021 to May 2022 were selected, and their anatomical and clinical factors were analyzed to evaluate the correlation between these factors and the duration of radiographic exposure. A related neural network prediction model was established.
Ann Med
December 2025
Department of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, PR China.
Background: This study aimed to investigate the demographics and to evaluate long-term outcomes of acute type A aortic dissection (ATAAD) in surgically treated patients ≤40 years in China.
Methods: This study included patients aged ≤40 with ATAAD who underwent surgical treatment at our institution between 2015 and 2019. The patients were categorized into groups according to heritable thoracic aortic disease (HTAD) presence or absence.
Front Cardiovasc Med
January 2025
Department of Anesthesiology and Operation, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Objective: We aimed to explore the application value of unsupervised machine learning in identifying acute gastrointestinal injury (AGI) after extracorporeal circulation for acute type A aortic dissection (ATAAD).
Methods: Patients who underwent extracorporeal circulation for ATAAD at the First Hospital of Lanzhou University from January 2016 to January 2021 were included. Unsupervised machine learning algorithm was used to stratify patients into different phenogroups according to the similarity of their clinical features and laboratory test results.
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