Type B Aortic Dissection CTA Collection with True and False Lumen Expert Annotations for the Development of AI-based Algorithms

• Published in: Scientific data Vol. 11; no. 1; pp. 596 - 9
• Main Authors: Mayer, Christian, Pepe, Antonio, Hossain, Sophie, Karner, Barbara, Arnreiter, Melanie, Kleesiek, Jens, Schmid, Johannes, Janisch, Michael, Hannes, Deutschmann, Fuchsjäger, Michael, Zimpfer, Daniel, Egger, Jan, Mächler, Heinrich
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 06.06.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 692/308/1426; 692/699/75/593/1287; 692/699/75/593/1301; Algorithms; Angiography; Aorta; Aortic dissection; Aortic Dissection - diagnostic imaging; Artificial Intelligence; Blood flow; Computed tomography; Computed Tomography Angiography; Data collection; Data Descriptor; Decision making; Dissection; Humanities and Social Sciences; Humans; Morbidity; multidisciplinary; Science; Science (multidisciplinary)
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-024-03284-2

Aortic dissections (ADs) are serious conditions of the main artery of the human body, where a tear in the inner layer of the aortic wall leads to the formation of a new blood flow channel, named false lumen. ADs affecting the aorta distally to the left subclavian artery are classified as a Stanford type B aortic dissection (type B AD). This is linked to substantial morbidity and mortality, however, the course of the disease for the individual case is often unpredictable. Computed tomography angiography (CTA) is the gold standard for the diagnosis of type B AD. To advance the tools available for the analysis of CTA scans, we provide a CTA collection of 40 type B AD cases from clinical routine with corresponding expert segmentations of the true and false lumina. Segmented CTA scans might aid clinicians in decision making, especially if it is possible to fully automate the process. Therefore, the data collection is meant to be used to develop, train and test algorithms.