Literature DB >> 23930821

Inter- and intra-observer variability analysis of completely automated cIMT measurement software (AtheroEdge™) and its benchmarking against commercial ultrasound scanner and expert Readers.

Luca Saba1, Filippo Molinari, Kristen M Meiburger, U Rajendra Acharya, Andrew Nicolaides, Jasjit S Suri.   

Abstract

The purpose of this study was to evaluate the measurement error and inter- and intra-observer variability of completely off-line automated and semi-automated carotid intima-media thickness (cIMT) measurement software (AtheroEdge™). Two hundred carotid ultrasound images from 50 asymptomatic women were analyzed. AtheroEdge™ was benchmarked against a commercial system (Syngo, Siemens) using automated and semi-automated modes. The measurement error and inter- and intra-observer variability of AtheroEdge™ were tested using three readings. The measurement error of AtheroEdge™ compared to the commercial software was 0.002±0.019mm (r=0.99) in the automated mode and -0.001±0.004mm in the semi-automated mode (r=0.99). The measurement error of AtheroEdge™ compared to the mean value of the three expert Readers (cIMT bias) for the automated and semi-automated methods was -0.0004±0.158mm and -0.008±0.157mm, respectively. The Figure-of-Merit was 99.8% and 99.9% when compared to the commercial ultrasound scanner (using the automated and semi-automated method, respectively) and was 99.9% and 98.9% when compared to the mean value of the three expert Readers. Regarding inter- and intra-observer variability, the intra-class correlation coefficient of the three independent users using the semi-automated AtheroEdge™ was 0.98. AtheroEdge™ showed a measurement performance comparable to the commercial ultrasound scanner software and the expert Readers' tracings. AtheroEdge™ belongs to a class of automated systems that could find application in processing large datasets for common carotid arteries, avoiding subjectivity in cIMT measurements.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Atherosclerosis; Automated segmentation; CC; Carotid Intima-Media Thickness; Commercial system; Correlation Coefficient; DA; Diagnostic Accuracy; Figure-of-Merit; FoM; Intimamedia thickness; LI; Lumen–Intima interface; MA; Media–Adventitia interface; ROI; Region Of Interest; Reproducibility; Ultrasound imaging; cIMT

Mesh:

Year:  2013        PMID: 23930821     DOI: 10.1016/j.compbiomed.2013.06.012

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  4 in total

1.  Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm.

Authors:  Luca Saba; Pankaj K Jain; Harman S Suri; Nobutaka Ikeda; Tadashi Araki; Bikesh K Singh; Andrew Nicolaides; Shoaib Shafique; Ajay Gupta; John R Laird; Jasjit S Suri
Journal:  J Med Syst       Date:  2017-05-13       Impact factor: 4.460

2.  Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

Authors:  Ankush D Jamthikar; Deep Gupta; Laura E Mantella; Luca Saba; John R Laird; Amer M Johri; Jasjit S Suri
Journal:  Int J Cardiovasc Imaging       Date:  2020-11-12       Impact factor: 2.357

3.  Inter-observer Variability Analysis of Automatic Lung Delineation in Normal and Disease Patients.

Authors:  Luca Saba; Joel C M Than; Norliza M Noor; Omar M Rijal; Rosminah M Kassim; Ashari Yunus; Chue R Ng; Jasjit S Suri
Journal:  J Med Syst       Date:  2016-04-25       Impact factor: 4.460

Review 4.  A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework.

Authors:  Mainak Biswas; Luca Saba; Tomaž Omerzu; Amer M Johri; Narendra N Khanna; Klaudija Viskovic; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Antonella Balestrieri; Petros P Sfikakis; Athanasios Protogerou; Durga Prasanna Misra; Vikas Agarwal; George D Kitas; Raghu Kolluri; Aditya Sharma; Vijay Viswanathan; Zoltan Ruzsa; Andrew Nicolaides; Jasjit S Suri
Journal:  J Digit Imaging       Date:  2021-06-02       Impact factor: 4.903

  4 in total

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