Affiliations 

  • 1 Department of Radiology, Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA
  • 2 Razak School of Engineering and Advanced Technology, University of Technology Malaysia, Kuala Lumpur, Malaysia
  • 3 Institute of Mathematical Sciences, University of Malaya, Kuala Lumpur, Malaysia
  • 4 Department of Vascular Surgery, Imperial College, London, UK
  • 5 Vascular Screening and Diagnostic Center, London, UK
  • 6 UC Davis Vascular Center, University of California, Sacramento, CA, USA
  • 7 Cagliari University Hospital, Monserrato, Cagliari, Italy
  • 8 Diagnostic and Monitoring Division, AtheroPoint, Roseville, CA, USA - jasjit.suri@atheropoint.com
Int Angiol, 2017 Oct;36(5):445-461.
PMID: 28541017 DOI: 10.23736/S0392-9590.17.03811-1

Abstract

BACKGROUND: The extent of calcium volume in the carotid arteries of contrast-based computer tomography (CT) is a valuable indicator of stroke risk. This study presents an automated, simple and fast calcium volume computation system. Since the high contrast agent can sometimes obscure the presence of calcium in the CT slices, it is therefore necessary to identify these slices before the corrected volume can be estimated.

METHODS: The system typically consists of segmenting the calcium region from the CT scan into slices based on Hounsfield Unit-based threshold, and subsequently computing the summation of the calcium areas in each slice. However, when the carotid volume has intermittently higher concentration of contrast agent, a dependable approach is adapted to correct the calcium region using the neighboring slices, thereby estimating the correct volume. Furthermore, mitigation is provided following the regulatory constraints by changing the system to semi-automated criteria as a fall back solution. We evaluate the automated and semi-automated techniques using completely manual calcium volumes computed based on the manual tracings by the neuroradiologist.

RESULTS: A total of 64 patients with calcified plaque in the internal carotid artery were analyzed. Using the above algorithm, our automated and semi-automated system yields correlation coefficients (CC) of 0.89 and 0.96 against first manual readings and 0.90 and 0.96 against second manual readings, respectively. Using the t-test, there was no significant difference between the automated and semi-automated methods against manual. The intra-observer reliability was excellent with CC 0.98.

CONCLUSIONS: Compared to automated method, the semi-automated method for calcium volume is acceptable and closer to manual strategy for calcium volume. Further work evaluating and confirming the performance of our semi-automated protocol is now warranted.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.