title: Automated carotid IMT measurement and its validation in low contrast ultrasound database of 885 patient Indian population epidemiological study: results of AtheroEdge™ Software.
abstract: OBJECTIVE
  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%.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy. filippo.molinari@polito.it
authors.forename: F
authors.initials: F
authors.lastname: Molinari
authors.forename: K M
authors.initials: KM
authors.lastname: Meiburger
authors.forename: G
authors.initials: G
authors.lastname: Zeng
authors.forename: L
authors.initials: L
authors.lastname: Saba
authors.forename: U
authors.initials: U
authors.lastname: Rajendra Acharya
authors.forename: L
authors.initials: L
authors.lastname: Famiglietti
authors.forename: N
authors.initials: N
authors.lastname: Georgiou
authors.forename: A
authors.initials: A
authors.lastname: Nicolaides
authors.forename: R
authors.initials: R
authors.lastname: Sriswan Mamidi
authors.forename: H
authors.initials: H
authors.lastname: Kuper
authors.forename: J S
authors.initials: JS
authors.lastname: Suri
mesh_terms: D057205:Automation, Laboratory; D017536:Carotid Artery, Common / Q000000981:diagnostic imaging*; D059168:Carotid Intima-Media Thickness; D017143:Fuzzy Logic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007194:India / Q000453:epidemiology; D015588:Observer Variation; D011237:Predictive Value of Tests; D012016:Reference Values; D015203:Reproducibility of Results