Accurate quantification of vessel cross-sectional area using CT angiography: a simulation study

  • Sabee Molloi
  • Travis Johnson
  • Huanjun Ding
  • Jerry Lipinski
Original Paper


Coronary computed tomography (CT) angiography is a noninvasive method for visualizing coronary atherosclerosis. However, CT angiography is limited in assessment of stenosis severity by the partial volume effect and calcification. Therefore, a quantitative method for assessment of stenosis severity is needed. Polyenergetic fan beam CT simulations were performed to match the geometry of a 320-slice CT scanner. Contrast-enhanced vessel lumens were modeled as 8 mg/ml Iodine solution against a lipid background. Normal vessels were simulated by circles with diameters in the range of 0.1–3 mm. To simulate lesions, 2, 3, and 4 mm diameter vessels were simulated with area stenoses in a range of 10–90 %. The occlusion was created by a circular region of lipid placed within the lumen resulting in a crescent shaped lumen. Each vessel was simulated three times to obtain multiple noise realizations for a total of 126 vessels. Two trained readers performed manual cross-sectional area measurements in simulated normal and stenotic vessels. A new, semi-automated technique based on integrated Hounsfield units was also used to calculate vessel cross-sectional area. There was an excellent correlation between the measured and the known cross-sectional area for both normal and stenotic vessels using the manual and the semi-automated techniques. However, the overall measurement error for the manual method was more than twice as compared with the integrated HU technique. Determination of vessel cross-sectional area using the semi-automated integrated Hounsfield unit technique yields more than a factor of two improvement in accuracy as compared to the existing manual technique for vessels with and without stenosis. This technique can also be used to correct for the effect of coronary calcification.


Angiography Coronary disease Imaging Tomography 



The authors would like to thank Ms. Rachel Smith for her help with data analysis. This work was supported in part by a grant from Toshiba America Medical System Inc.

Conflict of interest

S. Molloi has recieved grant funding from Toshiba America Medical System Inc.


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Sabee Molloi
    • 1
  • Travis Johnson
    • 1
  • Huanjun Ding
    • 1
  • Jerry Lipinski
    • 1
  1. 1.Department of Radiological Sciences, Medical Sciences B, 140University of CaliforniaIrvineUSA

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