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Assessment of cardiac rotation and twist from bi-plane angiograms

Various types of heart disease change left ventricular (LV) rotation. Measures of LV rotation are correlated with early onset symptoms of heart disease, such as subclinical aortic stenosis and diastolic dysfunction. Noninvasive assessment of LV torsion, however, is challenging with modalities other than tagged MRI, which oftentimes is contraindicated due to metal implants.
Coronary angiography is the imaging modality of choice for heart diseases. Virtually all clinical cases undergo this procedure at least once. In coronary angiography the heart arteries are selectively contrasted using a catheter that is inserted into the cardiac vessel system, making them clearly visible in projection X-ray imaging. As the coronary arteries are attached to the heart’s surface, they follow LV torsion.
The proposed research project aims at the development of a segmentation and reconstruction algorithm for 3D + t coronary angiograms in order to fully describe myocardial surface motion including torsion that is invisible in Computed Tomography and Magnetic Resonance Imaging. As the proposed project re-uses image data from standard imaging protocols, no additional radiation dose and discomfort is caused to the patient.
Project manager:
Prof. Dr.-Ing. Joachim Hornegger

Project participants:
Prof. Dr.-Ing. habil. Andreas Maier, Prof. Dr.-Ing. Joachim Hornegger, Dr.-Ing. Mathias Unberath

Keywords:
cardiac rotation; torsion; twist; angiography; vessel segmentation; CT

Start: 15.11.2014

Sponsored by:
Graduate School of Advanced Optical Technologies

Contact:
Unberath, Mathias
Phone +49 9131 85 28982, Fax +49 9131 85 27270, E-Mail: mathias.unberath@fau.de
Publications
Unberath, Mathias ; Mentl, Katrin ; Taubmann, Oliver ; Achenbach, Stephan ; Fahrig, Rebecca ; Hornegger, Joachim ; Maier, Andreas: Torsional Heart Motion in Cone-beam Computed Tomography Reconstruction. In: Michael King ; Stephen Glick ; Klaus Mueller (Ed.) : Proceedings of the Fully3D (13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine Newport, RI 31.5.2015-4.6.2015). 2015, pp 651-654.

Institution: Chair of Computer Science 5 (Pattern Recognition)
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