PURPOSE: To develop and evaluate a user-friendly tool to enable efficient, accurate, and reproducible quantification of blood vessel stenosis in computed tomographic (CT) and magnetic resonance (MR) angiographic data sets. MATERIALS AND METHODS: All clinical experiments were approved by the institutional review board, and informed patient consent was acquired. Animal experiments were approved by the governmental review committee on animal care. A virtual elastic sphere passes through a blood vessel specified by user-provided start and end points, and the adapting diameter over the course of the vessel is recorded. The program was tested in phantoms to determine the accuracy of diameter estimation, and it was applied in micro-CT data sets of mice with induced vessel stenosis. Dual-energy CT angiography and MR angiography were performed in 16 patients with carotid artery stenosis, and reproducibility and required reader time of this automated technique were compared with manual measurements. Additionally, the effect of dual-energy CT-based discrimination between iodine- and calcium-based enhancement was investigated. Differences between carotid artery diameters of mice and between automated and manual measurement durations were assessed with a paired t test. Reproducibility of stenosis scores was evaluated with the Fisher z test. RESULTS: Phantom diameters were determined with an average error of 0.094 mm. Diameters of normal and injured carotid arteries of mice were significantly different (P < .01). For patient data, automated interreader variability was significantly (P < .01) lower than manual intra- and interreader variability, while time efficiency was improved (P < .01). CONCLUSION: The virtual elastic sphere tool is applicable to CT, dual-energy CT, and MR angiography, and it improves reproducibility and efficiency over that achieved with manual stenosis measurements.
PURPOSE: To develop and evaluate a user-friendly tool to enable efficient, accurate, and reproducible quantification of blood vessel stenosis in computed tomographic (CT) and magnetic resonance (MR) angiographic data sets. MATERIALS AND METHODS: All clinical experiments were approved by the institutional review board, and informed patient consent was acquired. Animal experiments were approved by the governmental review committee on animal care. A virtual elastic sphere passes through a blood vessel specified by user-provided start and end points, and the adapting diameter over the course of the vessel is recorded. The program was tested in phantoms to determine the accuracy of diameter estimation, and it was applied in micro-CT data sets of mice with induced vessel stenosis. Dual-energy CT angiography and MR angiography were performed in 16 patients with carotid artery stenosis, and reproducibility and required reader time of this automated technique were compared with manual measurements. Additionally, the effect of dual-energy CT-based discrimination between iodine- and calcium-based enhancement was investigated. Differences between carotid artery diameters of mice and between automated and manual measurement durations were assessed with a paired t test. Reproducibility of stenosis scores was evaluated with the Fisher z test. RESULTS: Phantom diameters were determined with an average error of 0.094 mm. Diameters of normal and injured carotid arteries of mice were significantly different (P < .01). For patient data, automated interreader variability was significantly (P < .01) lower than manual intra- and interreader variability, while time efficiency was improved (P < .01). CONCLUSION: The virtual elastic sphere tool is applicable to CT, dual-energy CT, and MR angiography, and it improves reproducibility and efficiency over that achieved with manual stenosis measurements.
Authors: Marko Weidensdorfer; Ju Ik Chae; Celestine Makobe; Julia Stahl; Beate Averhoff; Volker Müller; Christoph Schürmann; Ralf P Brandes; Gottfried Wilharm; Wibke Ballhorn; Sara Christ; Dirk Linke; Doris Fischer; Stephan Göttig; Volkhard A J Kempf Journal: Infect Immun Date: 2015-12-28 Impact factor: 3.441
Authors: Andreas Schober; Maliheh Nazari-Jahantigh; Yuanyuan Wei; Kiril Bidzhekov; Felix Gremse; Jochen Grommes; Remco T A Megens; Kathrin Heyll; Heidi Noels; Michael Hristov; Shusheng Wang; Fabian Kiessling; Eric N Olson; Christian Weber Journal: Nat Med Date: 2014-03-02 Impact factor: 53.440
Authors: Stephan Christian Möhlhenrich; Kristian Kniha; Zuzanna Magnuska; Benita Hermanns-Sachweh; Felix Gremse; Frank Hölzle; Gholamreza Danesh; Ali Modabber Journal: Sci Rep Date: 2021-06-30 Impact factor: 4.379