English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background. Magnetic resonance imaging (MRI) offers the opportunity to quantify the vessel diameters in vivo . This technique can have a breakthrough impact on the evaluation, risk stratification and therapeutical planning in hemodynamic-related pathologies, e.g., arterial stenosis. However, its applicability in clinics is limi­ted due to the complex post-processing required to extract the information and the difficulty to synthesize the obtained data into clinical useful parameters. Objective. In this work, we use the vessel diameter distribution along its central line obtained with the use of MRI technology in order to detect the existence of stenosis in internal carotid arteries (ICA) and vertebral arteries (VA) with the minimal amount of False Negative predictions and to estimate the efficiency of therapy. Methods. Special normalized and smoothed characteristics will be used to develop the stenosis detection criteria which can be used for every artery separately and for both vessels simultaneously. Linear and non-linear characteristics were used to increase the reliability of diagnostics. Study is based on the Receiver Operating Characteristics (ROC) and optimization methods. Real diameter data of 10 patients (80 data sets) were used. Results. To detect stenosis, three different criteria have been proposed, based on the optimal smoothing parameters of vessel diameter distributions and the corresponding threshold values for linear and nonlinear characteristics. The use of the developed criteria allows increasing the reliability of stenosis detection. Conclusions. Different linear, non-linear, smoothed and non-smoothed parameters and ROC were applied to detect stenosis in internal carotid and vertebral arteries. It was shown that smoothed data are necessary for VA and the criterion applicable both for VA and ICA. For ICA it is possible to use initial (unsmoothed) data. Only one False Positive case was detected for every artery. Results of application of proposed criteria are presented, tested and discussed. For VA it is possible to use criteria 1 and 2 and smoothed normalized diameter data. For ICA criterion 2 can be recommended to detect long enough narrowing areas. To detect short zones of stenosis in ICA, the criterion 3 is useful, since it uses the non-smoothed diameter data.

Stenosis Detection in Internal Carotid and Vertebral Arteries With the Use of Diameters Estimated from MRI Data