ArticleJournal of digital imaging2015
Relationship between the contrast effects of raw data projection images from three-dimensional digital subtraction angiography and the optimal volume rendering parameters.
Article in Journal of digital imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Relationship between Injection Rate and Contrast Enhancement on Three-dimensional Digital Subtraction Angiography of the Cerebral Arteries.Journal of the Belgian Society of Radiology · 2018Article
- [Application of three-dimensional digital subtraction angiography on hepatic artery chemoembolization].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2018Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Volume rendering (VR) is a technique commonly used for the reconstruction of three-dimensional (3D) digital subtraction angiography (DSA) images, and the rendering parameters greatly affect the characteristics of the 3D image. This study aimed to test whether the optimal VR parameters for 3D DSA could be estimated from the contrast effects in rotational two-dimensional (2D) DSA images acquired using 3D DSA. Simulated blood vessels filled with various concentrations of contrast medium were scanned, and the 3D DSA data sets were reconstructed. The syngo AX vessel analysis software that was able to analyze 3D DSA VR image was used for objective measures. Raw data projection images of the 3D DSA data sets in which the mean diameter was calculated as a true value by the software at nine different thresholds for vessel segmentation were selected. In each image set, five images of all 133 rotational 2D DSA images were selected, and the contrast-enhanced area was extracted using a region-growing algorithm. Mean values and standard deviations of each contrast-enhanced area were calculated, and as the thresholds for vessel segmentation of the software increased by 500 every time, significant differences were observed in the mean values (P < 0.01). This optimal threshold can be applied to the window settings of the VR technique. Therefore, the optimal VR parameters for 3D DSA may be determined by analyzing the contrast effects of the raw data projection images, and user-dependent over- and underestimations of 3D DSA VR images also may be prevented.
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