ORIGINAL ARTICLES   

International Angiology 2012 February;31(1):42-53

Copyright © 2012 EDIZIONI MINERVA MEDICA

language: English

Automated carotid IMT measurement and its validation in low contrast ultrasound database of 885 patient indian population epidemiological study: results of AtheroEdge™ Software

Molinari F. ¹, Meiburger K. M. ¹, Zeng G. ², Saba L. ³, Rajendra Acharya U. ⁴, Famiglietti L. ³, Georgiou N. ⁵, Nicolaides A. ⁵, Sriswan Mamidi R. ⁶, Kuper H. ⁷, Suri J. S. ^{8, 9} ✉

¹ Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy; ² Mayo Clinic, Rochester, MN, USA; ³ Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, Cagliari, Italy; ⁴ Department ECE, Ngee Ann Polytechnic, Singapore; ⁵ Vascular Screening and Diagnostic Centre, London, and Department of Biological Sciences, University of Cyprus, Nicosia, Cyprus; ⁶ National Institute of Nutrition, Hyderabad, India; ⁷ Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK; ⁸ Research Professor (Affiliated), Biomedical Engineering, Idaho State University, Pocatello, ID, USA; ⁹ Global Biomedical Technologies inc., Roseville, CA, USA

AIM:The aim of this paper was to demonstrate the usage of an automated computer-based IMT measurement system called - CALEX 3.0 (a class of patented AtheroEdge™ software) on a low contrast and low resolution image database acquired during an epidemiological study from India. The image contrast was very low with pixel density of 12.7 pixels/mm. Further, to demonstrate the accuracy and reproducibility of the AtheroEdge™ software system we compared it with the manual tracings of a vascular surgeon – considered as a gold standard.
METHODS: We automatically measured the IMT value of 885 common carotid arteries in longitudinal B-Mode images. CALEX 3.0 consisted of a stage for the automatic recognition of the carotid artery and an IMT measurement modulus made of a fuzzy K-means classifier. Performance was assessed by measuring the system accuracy and reproducibility against manual tracings by experts.
RESULTS: CALEX 3.0 processed all the 885 images of the dataset (100% success). The average automated obtained IMT measurement by CALEX 3.0 was 0.407±0.083 mm compared with 0.429 ± 0.052 mm for the manual tracings, which led to an IMT bias of 0.022±0.081mm. The IMT measurement accuracy (0.022 mm) was comparable to that obtained on high-resolution images and the reproducibility (0.081 mm) was very low and suitable to clinical application. The Figure-of-Merit defined as the percent agreement between the computer-estimated IMT and manually measured IMT for CALEX 3.0 was 94.7%.
CONCLUSION:CALEX 3.0 had a 100% success in processing low contrast/low-resolution images. CALEX 3.0 is the first technique, which has led to high accuracy and reproducibility on low-resolution images acquired during an epidemiological study. We propose CALEX 3.0 as a generalized framework for IMT measurement on large datasets.