Cheung, WK;
Williams, KJ;
Christensen-Jeffries, K;
Dharmarajah, B;
Eckersley, RJ;
Davies, AH;
Tang, M-X;
(2017)
A Temporal and Spatial Analysis Approach to Automated Segmentation of Microbubble Signals in Contrast-Enhanced Ultrasound Images: Application to Quantification of Active Vascular Density in Human Lower Limbs.
Ultrasound in Medicine & Biology
, 43
(10)
pp. 2221-2234.
10.1016/j.ultrasmedbio.2017.05.021.
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Abstract
Contrast-enhanced ultrasound (CEUS) using microbubble contrast agents has shown great promise in visualising and quantifying active vascular density. Most existing approaches for vascular density quantification using CEUS are calculated based on image intensity and are susceptible to confounding factors and imaging artefact. Poor reproducibility is a key challenge to clinical translation. In this study, a new automated temporal and spatial signal analysis approach is developed for reproducible microbubble segmentation and quantification of contrast enhancement in human lower limbs. The approach is evaluated in vitro on phantoms and in vivo in lower limbs of healthy volunteers before and after physical exercise. In this approach, vascular density is quantified based on the relative areas microbubbles occupy instead of their image intensity. Temporal features of the CEUS image sequences are used to identify pixels that contain microbubble signals. A microbubble track density (MTD) measure, the ratio of the segmented microbubble area to the whole tissue area, is calculated as a surrogate for active capillary density. In vitro results reveal a good correlation (r2 = 0.89) between the calculated MTD measure and the known bubble concentration. For in vivo results, a significant increase (129% in average) in the MTD measure is found in lower limbs of healthy volunteers after exercise, with excellent repeatability over a series of days (intra-class correlation coefficient = 0.96). This compares to the existing state-of-the-art approach of destruction and replenishment analysis on the same patients (intra-class correlation coefficient ≤0.78). The proposed new approach shows great potential as an accurate and highly reproducible clinical tool for quantification of active vascular density.
| Type: | Article |
|---|---|
| Title: | A Temporal and Spatial Analysis Approach to Automated Segmentation of Microbubble Signals in Contrast-Enhanced Ultrasound Images: Application to Quantification of Active Vascular Density in Human Lower Limbs |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ultrasmedbio.2017.05.021 |
| Publisher version: | https://doi.org/10.1016/j.ultrasmedbio.2017.05.021 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | contrast enhanced ultrasound, lower limb, vascular density quantification, image segmentation, temporal analysis, reproducibility, peripheral arterial disease |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10072827 |
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