Semi-Automated Segmentation of
Three-dimensional Ultrasound
Carotid Artery Plaque Volume
T. Lindenmaier D. Buchanan, S. McKay, I. Gyacskov,
A. Fenster and G. Parraga
Imaging Research Laboratories, Robarts Research Institute,
Department of Medical Biophysics, Biomedical Engineering Graduate Program,
The University of Western Ontario,
London, CANADA
April 4, 2012
Overview
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Atherosclerosis and the carotid artery
Image acquisition using ultrasound
Imaging phenotypes of carotid atherosclerosis
Limitations of current methods
Development of semi-automated measurement
Application and Reproducibility
Motivation: Carotid Atherosclerosis
Libby, Peter. Inflammation in Atherosclerosis. Nature. December 2002.
ICA
ECA
BF
CCA
Motivation: Atherosclerosis in Carotid Artery
Cerebrovascular disease accounts for
10% of all deaths worldwide1
1WHO,
2004
Ultrasound of Carotid Atherosclerosis
Intima-Media Thickness
Courtesy of Christiane Mallet
Manual Planimetry Measurements
lumen-intima
media-adventitia
Longitudinal View
Axial View
Carotid Atherosclerosis: US Measurements
Vessel
Wall Volume
Egger et al. J Ultrasound Med. (2008)
Intima-Media Thickness
Buchanan et al. Accepted to Ultrasound Med Biol. (2012)
Total Plaque Area
Riccio et al. Cardiovascular Ultrasound. (2006)
Total Al-Shali
Plaque
Volume
et al. Atherosclerosis. (2005)
Egger et al. Ultrasound Med Biol. (2007)
Manual Segmentation of 3DUS TPV
CV (%)
20
15
10
5
0
0 100 200 300 400 500 600
V (mm3)
Total Plaque Volume
Adapted from Landry et al. Stroke. (2004)
• User sets axis of segmentation
• Measurements made in an axial view at 1mm inter-slice distance
• Inter-slice distance multiplied by segmentation area to calculate volume
Limitations of Current Measurements
Intima-Media Thickness (IMT)
• Narrow dynamic range (0.5mm to 1.0mm)
• 1-dimensional measurement
• No plaque
Total Plaque Area (TPA)
• High inter-observer variability
• 2-dimensional measurement
• Not adequate to estimate 3D change
with 2D measurement
Total Plaque Volume (TPV)
• Long measurement time (slice-by-slice)
• Laborious
Semi-automated TPV Measurement
Axial View
Longitudinal View
Semi-Automated TPV
Measurement
Schematic of
Longitudinal View
Measurement View
Contour 1
(longitudinal view)
Min Z
C1
Max Z
Contour 2
(axial view)
C2
Contour 3
(axial view)
C3
Contour 4
(axial view)
C4
Semi-Automated TPV Measurement
C1
Min Z
C2 C3 C4
1 m-1
1 m-1
V =  PFj  A j =  PFj  (2A j )
3 j0
6 j0
Max Z
y
z
x
V = volume
a
b
P
PFj = representative vertex
Aj = area of triangle
1Van
Gelder. Graphic Gems 5. (1995)
Methodology
Selection of
23
echogenic plaques
from 17 subjects
2x5 rounds of
semi - automated
segmentation
Images measured
5x with 5 Minutes
between
measurements
Images measured
5x with 20 hours
between
measurements
1 round
manual
segmentation
Manual vs. SA Measurements
Results
Landry et al. Stroke. (2004)
Conclusion
• Intra-observer variability similar to manual measurement
variability reported by Landry et al. (2004)
• High correlation between manual and SA for both time
durations between measurements
• The manual TPV measurement can be replaced by the novel
segmentation method.
• If adopted for clinical use, measurements could be generated
right away (faster diagnosis).
Acknowledgements
Supervisory Committee
Grace Parraga PhD
Daniel Buchanan BSc
Collaborators
Aaron Fenster PhD FCCPM
Igor Gyacskov
Research Team
Sandra Halko CRCC RPT
Shayna McKay BSc
Andrew Wheatley BSc
Miranda Kirby BSc
Stephen Costella MESc
Amir Owrangi MSc
Trevor Szekeres MRT
Sarah Svenningsen
Lauren Villemaire
Thank you