Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8130920 | Ultrasound in Medicine & Biology | 2018 | 8 Pages |
Abstract
The vascular architecture in tumors contains relevant information for tumor classification and evaluation of therapy responses. To develop a reliable and user-independent analysis tool, a foreground detection algorithm was combined with a maximum-intensity projection to obtain a high signal-to-noise image from contrast-enhanced B-mode data sets, enabling vessel segmentation by thresholding. Parameters describing the density of the vascular network, the number of vessels and the number of branches were extracted. The highly angiogenic A431 tumors had a relative blood volume of 49%, a mean pixel distance to the next vessel of 1.8â±â0.3 px, 51â±â29 individual vessels and 478â±â184 branching points, whereas the more mature and heterogeneous vascularized human epithelial ovarian carcinoma (MLS) and A549 tumors had values of 30%, 3.7â±â2.7 px, 65â±â12 and 220â±â159, and 13%, 7.4â±â2 px, 31â±â9 and 59â±â40, respectively. Thus, our semi-automated analysis method enables the extraction of quantitative vascular features that may help to simplify and standardize tumor characterization.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Acoustics and Ultrasonics
Authors
Benjamin Theek, Tatjana Opacic, Twan Lammers, Fabian Kiessling,