Title
Carotid Plaque Fibrous Cap Thickness Measurement by ARFI Variance of Acceleration: In Vivo Human Results
Date Issued
01 December 2020
Access level
open access
Resource Type
journal article
Author(s)
Czernuszewicz T.J.
Homeister J.W.
Farber M.A.
Caughey M.C.
Gallippi C.M.
University of North Carolina
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
This study evaluates the performance of an acoustic radiation force impulse (ARFI)-based outcome parameter, the decadic logarithm of the variance of acceleration, or log(VoA), for measuring carotid fibrous cap thickness. Carotid plaque fibrous cap thickness measurement by log(VoA) was compared to that by ARFI peak displacement (PD) in patients undergoing clinically indicated carotid endarterectomy using a spatially-matched histological validation standard. Fibrous caps in parametric log(VoA) and PD images were automatically segmented using a custom clustering algorithm, and a pathologist with expertise in atherosclerosis hand-delineated fibrous caps in histology. Over 10 fibrous caps, log(VoA)-derived thickness was more strongly correlated to histological thickness than PD-derived thickness, with Pearson correlation values of 0.98 for log(VoA) compared to 0.89 for PD. The log(VoA)-derived cap thickness also had better agreement with histology-measured thickness, as assessed by the concordance correlation coefficient (0.95 versus 0.62), and, by Bland-Altman analysis, was more consistent than PD-derived fibrous cap thickness. These results suggest that ARFI log(VoA) enables improved discrimination of fibrous cap thickness relative to ARFI PD and further contributes to the growing body of evidence demonstrating ARFI's overall relevance to delineating the structure and composition of carotid atherosclerotic plaque for stroke risk prediction.
Start page
4383
End page
4390
Volume
39
Issue
12
Language
English
OCDE Knowledge area
Radiología, Medicina nuclear, Imágenes médicas Ingeniería médica
Scopus EID
2-s2.0-85097003642
PubMed ID
ISSN of the container
02780062
Conference
IEEE Transactions on Medical Imaging
Sponsor(s)
Manuscript received July 1, 2020; revised August 17, 2020; accepted August 19, 2020. Date of publication August 24, 2020; date of current version November 30, 2020. This work was supported in part by the NIH under Grant R01HL092944, Grant R01DK107740, Grant R01NS074057, and Grant T32HL069768. (Corresponding author: Gabriela Torres.) Gabriela Torres, Melissa C. Caughey, and Caterina M. Gallippi are with the Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514 USA, and also with the North Carolina State University, Raleigh, NC 27695 USA (e-mail: gtorres@live.unc.edu; melissa_caughey@med.unc.edu; cmgallip@email.unc.edu).
Sources of information: Directorio de Producción Científica Scopus