TY - GEN
T1 - New quantification methods for carotid intraplaque neovascularization in contrast enhanced ultrasound
AU - Akkus, Zeynettin
AU - Renaud, Guillaume
AU - De Jong, Nico
AU - Van Der Steen, Antonius F.W.
AU - Bosch, Johan G.
AU - Van Den Oord, Stijn C.H.
AU - Schinkel, Arend F.L.
AU - Sanchez-Ferrero, Gonzalo Vegas
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Carotid intraplaque neovascularization (IPN) has been associated with progressive atherosclerotic disease and plaque vulnerability. Therefore, its accurate quantification might allow early detection of plaque vulnerability. Contrast enhanced ultrasound (CEUS) can detect these small microvessels. To quantify IPN, we developed quantitative methods based on time intensity curve (TIC) and maximum intensity projection (MIP), micro-vascular structure analysis (VSA), and statistical segmentation (SS). Plaque region of interest (ROI) is manually drawn and motion compensation is applied before each analysis. In TIC and MIP, we examine perfusion dynamics and regions within plaques. In VSA, we detect and track contrast spots to examine the microvessel network. In SS, we classify plaque intensities into different components for quantification of IPN. Through an iterative expectation-maximization algorithm, plaque pixels are initially labeled into artifacts, contrast, intermediate, and background class. Next, spatiotemporal and neighborhood information is used to relabel intermediate class pixels, remove artifacts and correct false-contrast. From the applied analyses, we derived several parameters - e.g. MIP based IPN surface area (MIPNSA), MIP based surface ratio (MIPNSR), SS based IPN surface area (SSIPNSA), plaque mean intensity, mean plaque contrast percentage, and number of microvessels (MVN) - and compared them to consensus of visual grading of IPN by two independent physicians. We analyzed 45 carotid arteries with stenosis. To verify if SSIPNSA improves the suppression of artifacts, we analyzed 8 plaques twice, with saturation artifacts included and excluded from the ROI. Five parameters were found to be significantly correlated to visual scoring and may thus have the potential to replace qualitative visual scoring and to measure the degree of carotid IPN. The MIPNSA & SSIPNSA parameters gave the best distinction between visual scores. SSIPNSA proved less sensitive for artifacts than MIPNSA.
AB - Carotid intraplaque neovascularization (IPN) has been associated with progressive atherosclerotic disease and plaque vulnerability. Therefore, its accurate quantification might allow early detection of plaque vulnerability. Contrast enhanced ultrasound (CEUS) can detect these small microvessels. To quantify IPN, we developed quantitative methods based on time intensity curve (TIC) and maximum intensity projection (MIP), micro-vascular structure analysis (VSA), and statistical segmentation (SS). Plaque region of interest (ROI) is manually drawn and motion compensation is applied before each analysis. In TIC and MIP, we examine perfusion dynamics and regions within plaques. In VSA, we detect and track contrast spots to examine the microvessel network. In SS, we classify plaque intensities into different components for quantification of IPN. Through an iterative expectation-maximization algorithm, plaque pixels are initially labeled into artifacts, contrast, intermediate, and background class. Next, spatiotemporal and neighborhood information is used to relabel intermediate class pixels, remove artifacts and correct false-contrast. From the applied analyses, we derived several parameters - e.g. MIP based IPN surface area (MIPNSA), MIP based surface ratio (MIPNSR), SS based IPN surface area (SSIPNSA), plaque mean intensity, mean plaque contrast percentage, and number of microvessels (MVN) - and compared them to consensus of visual grading of IPN by two independent physicians. We analyzed 45 carotid arteries with stenosis. To verify if SSIPNSA improves the suppression of artifacts, we analyzed 8 plaques twice, with saturation artifacts included and excluded from the ROI. Five parameters were found to be significantly correlated to visual scoring and may thus have the potential to replace qualitative visual scoring and to measure the degree of carotid IPN. The MIPNSA & SSIPNSA parameters gave the best distinction between visual scores. SSIPNSA proved less sensitive for artifacts than MIPNSA.
KW - Carotid plaques
KW - Contrast enhanced ultrasound
KW - Intraplaque neovascularization
KW - Microbubbles
KW - Microvessel quantification
UR - http://www.scopus.com/inward/record.url?scp=84894360309&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84894360309&partnerID=8YFLogxK
U2 - 10.1109/ULTSYM.2013.0316
DO - 10.1109/ULTSYM.2013.0316
M3 - Conference contribution
AN - SCOPUS:84894360309
SN - 9781467356862
T3 - IEEE International Ultrasonics Symposium, IUS
SP - 1236
EP - 1239
BT - 2013 IEEE International Ultrasonics Symposium, IUS 2013
T2 - 2013 IEEE International Ultrasonics Symposium, IUS 2013
Y2 - 21 July 2013 through 25 July 2013
ER -