Agreement between a computer-assisted tool and radiologists to classify lesions in breast elastography images

Karem D. Marcomini; Eduardo F. C. Fleury; Vilmar M. Oliveira; Antonio A. O. Carneiro; Homero Schiabel; Robert M. Nishikawa

doi:10.1117/12.2255001

3 March 2017 Agreement between a computer-assisted tool and radiologists to classify lesions in breast elastography images

Karem D. Marcomini, Eduardo F. C. Fleury, Vilmar M. Oliveira, Antonio A. O. Carneiro, Homero Schiabel, Robert M. Nishikawa

Author Affiliations +

Proceedings Volume 10134, Medical Imaging 2017: Computer-Aided Diagnosis; 101342T (2017) https://doi.org/10.1117/12.2255001
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Breast elastography is a new sonographic technique that provides additional information to evaluate tissue stiffness. However, interpreting breast elastography images can vary depending on the radiologist. In order to provide quantitative and less subjective data regarding the stiffness of a lesion, we developed a tool to measure the amount of hard area in a lesion from the 2D image. The database consisted of 78 patients with 83 breast lesions (31 malignant and 52 benign). Two radiologists and one resident manually drew the contour of the lesions in B-mode ultrasound images and the contour was mapped in the elastography image. By using the system proposed, the radiologists obtained a very good diagnostic agreement among themselves (kappa = 0.86), achieving the same sensitivity and specificity (80.7 and 88.5, respectively), and an AUC of 0.883 for Radiologist 1 and 0.892 for Radiologist 2. The Resident had less interobserver agreement, as well as lower specificity and AUC, which may be related to less experience. Furthermore, the radiologists had an agreement with the tool used in the automatic method higher than 90%. Thus, the method developed was useful in aiding the diagnosis of breast lesions in strain elastography, minimizing its subjectivity.

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Karem D. Marcomini, Eduardo F. C. Fleury, Vilmar M. Oliveira, Antonio A. O. Carneiro, Homero Schiabel, and Robert M. Nishikawa "Agreement between a computer-assisted tool and radiologists to classify lesions in breast elastography images", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101342T (3 March 2017); https://doi.org/10.1117/12.2255001

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KEYWORDS

Elastography

Breast

Ultrasonography

Visualization

RGB color model

Visual analytics

Breast cancer

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