Quantitative assessment of the entire thoracic aorta from magnetic resonance images
| Autor: | Thomas D. Scholz, Andreas Wahle, Milan Sonka, Sonali S. Patel, Ryan K. Johnson, Senthil Premraj, Alan H. Stolpen |
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| Rok vydání: | 2010 |
| Předmět: |
Adult
Male Marfan syndrome medicine.medical_specialty Aortic Diseases Aorta Thoracic Thoracic aortic aneurysm Article medicine.artery Ascending aorta Image Processing Computer-Assisted Humans Medicine Thoracic aorta Aorta medicine.diagnostic_test business.industry Reproducibility of Results Magnetic resonance imaging General Medicine Gold standard (test) medicine.disease Magnetic Resonance Imaging Data set Pediatrics Perinatology and Child Health cardiovascular system Female Radiology Cardiology and Cardiovascular Medicine business Follow-Up Studies |
| Zdroj: | Cardiology in the Young. 21:170-177 |
| ISSN: | 1467-1107 1047-9511 |
| DOI: | 10.1017/s1047951110001678 |
| Popis: | Magnetic resonance imaging has emerged over the last decade as the gold standard for imaging of the aorta.1 Concerns about radiation exposure from computed tomography exist, especially when serial scanning is required. Echocardiographic imaging is limited to the aortic root and proximal ascending aorta and standardised methods of measurement are limited to two dimensions. Patients with connective tissue disorders such as Marfan, Ehlers–Danlos, and thoracic aortic aneurysm syndrome are at risk for the development of aortic aneurysms and require serial imaging of the entire thoracic aorta. This group of patients, in particular, may benefit from the comprehensive coverage of the aorta provided by magnetic resonance imaging. Due to time constraints, current manual methods of magnetic resonance image analysis result in processing of only a limited number of images contained in a complete three-dimensional or four-dimensional (three-dimensional plus time) image data set. The end result is static measurements at end diastole and/or end systole at various locations of the thoracic aorta. Often, reproducing consistent locations of measurements for year-to-year comparisons is difficult. In a recent study by Zhao et al,2 we described a method for automated segmentation of four-dimensional data sets that produced results capable of distinguishing shape characteristics between normal individuals and those with connective tissue disorders with 90% accuracy. From this initial study, it was clear that the cross-sectional area could be measured for any level of the thoracic aorta and plotted for the entire length of the vessel for accurate comparison with future scans. The goal of this study was to apply the graph theory-based segmentation method to four-dimensional magnetic resonance images of the thoracic aorta in normal controls to develop the first set of normative data for the dimensions of the entire thoracic aorta. The utility of the analysis and display technique was then applied to an initial group of patients with confirmed or suspected connective tissue disorders to show the utility of the method. |
| Databáze: | OpenAIRE |
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