Extracting 3D Angiography Data from Simulated Computed Tomography Angiography Scans Using Low Iodine Contrast Agent ()
ABSTRACT
The purpose of this research is to investigate
the feasibility of using low contrast agent concentration with X-ray computed
tomography in visualizing and diagnosing the human vascular system while
minimizing the risk of toxicity to the patient. This research investigated the
effect of several iodine contrast agent concentrations on the ability to
extract and visualize human vessels using simulated computed tomography scans.
Monte Carlo simulation was used to perform these computed tomography
acquisitions. The simulated patient was based on actual computed tomography
angiography data, where a
technique was developed to simulate brain vessels with contrast agents ranging from 0 mg to 20 mg
of iodine. The simulation used segmented patient data along with basic image
processing techniques to model the various levels of iodine concentrations.
Cone beam computed tomography projections of a patient injected with and without iodine were
acquired in the simulations. Subtraction of the corresponding projections was
performed to generate images caused by
the contrast agent. Then, histogram analysis of these differences was used to
assess the validity of extracting and visualizing the human vessels. The
smallest amount of iodine, 0.5 mg, helped better visualize the brain vessels
and 2 mg of iodine was high enough to show almost 90% of the vessels. Additionally, the vessels were clearly visible in
all the subtracted images. This research showed very promising outcomes
in using low concentrations of iodine. Thus, this study proposes for the
pharmaceutical companies and others interested to clinically investigate and
evaluate the efficacy of using low concentrations of iodine and the associated side effects.
Share and Cite:
Alyassin, A. (2022) Extracting 3D Angiography Data from Simulated Computed Tomography Angiography Scans Using Low Iodine Contrast Agent.
International Journal of Medical Physics, Clinical Engineering and Radiation Oncology,
11, 135-149. doi:
10.4236/ijmpcero.2022.113012.
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