Ultrasound IMT measurement on a multi-ethnic and multi-institutional database: Our review and experience using four fully automated and one semi-automated methods

• Published in: Computer methods and programs in biomedicine Vol. 108; no. 3; pp. 946 - 960
• Main Authors: Molinari, Filippo, Meiburger, Kristen M., Saba, Luca, Acharya, U. Rajendra, Ledda, Giuseppe, Zeng, Guang, Ho, Sin Yee Stella, Ahuja, Anil T., Ho, Suzanne C., Nicolaides, Andrew, Suri, Jasjit S.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ireland Ltd 01.12.2012; Elsevier
• Subjects: Accuracy and reproducibility; Aged; Aged, 80 and over; Atherosclerosis; Automation; Benchmarking; Biological and medical sciences; Carotid Arteries - diagnostic imaging; Carotid artery; Database Management Systems; Ethnic Groups; Humans; Internal Medicine; Intima-media thickness measurement; Medical sciences; Middle Aged; Other; Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects); Segmentation; Technology. Biomaterials. Equipments. Material. Instrumentation; Tunica Intima - diagnostic imaging; Ultrasonography - methods; Ultrasound; Validation; Intima-media thickness measurement; Validation; Automation; Segmentation; Atherosclerosis; Benchmarking; Carotid artery; Accuracy and reproducibility; Ultrasound; Image processing; Biomedical engineering
• ISSN: 0169-2607; 1872-7565; 1872-7565
• DOI: 10.1016/j.cmpb.2012.05.008

Automated and high performance carotid intima-media thickness (IMT) measurement is gaining increasing importance in clinical practice to assess the cardiovascular risk of patients. In this paper, we compare four fully automated IMT measurement techniques (CALEX, CAMES, CARES and CAUDLES) and one semi-automated technique (FOAM). We present our experience using these algorithms, whose lumen-intima and media-adventitia border estimation use different methods that can be: (a) edge-based; (b) training-based; (c) feature-based; or (d) directional Edge-Flow based. Our database (DB) consisted of 665 images that represented a multi-ethnic group and was acquired using four OEM scanners. The performance evaluation protocol adopted error measures, reproducibility measures, and Figure of Merit (FoM). FOAM showed the best performance, with an IMT bias equal to 0.025±0.225mm, and a FoM equal to 96.6%. Among the four automated methods, CARES showed the best results with a bias of 0.032±0.279mm, and a FoM to 95.6%, which was statistically comparable to that of FOAM performance in terms of accuracy and reproducibility. This is the first time that completely automated and user-driven techniques have been compared on a multi-ethnic dataset, acquired using multiple original equipment manufacturer (OEM) machines with different gain settings, representing normal and pathologic cases.