title: Axial-shear strain imaging for differentiating benign and malignant breast masses.
abstract: Axial strain imaging has been utilized for the characterization of breast masses for over a decade; however, another important feature namely the shear strain distribution around breast masses has only recently been used. In this article, we examine the feasibility of utilizing in vivo axial-shear strain imaging for differentiating benign from malignant breast masses. Radio-frequency data was acquired using a VFX 13-5 linear array transducer on 41 patients using a Siemens SONOLINE Antares real-time clinical scanner at the University of Wisconsin Breast Cancer Center. Free-hand palpation using deformations of up to 10% was utilized to generate axial strain and axial-shear strain images using a two-dimensional cross-correlation algorithm from the radio-frequency data loops. Axial-shear strain areas normalized to the lesion size, applied strain and lesion strain contrast was utilized as a feature for differentiating benign from malignant masses. The normalized axial-shear strain area feature estimated on eight patients with malignant tumors and 33 patients with fibroadenomas was utilized to demonstrate its potential for lesion differentiation. Biopsy results were considered the diagnostic standard for comparison. Our results indicate that the normalized axial-shear strain area is significantly larger for malignant tumors compared with benign masses such as fibroadenomas. Axial-shear strain pixel values greater than a specified threshold, including only those with correlation coefficient values greater than 0.75, were overlaid on the corresponding B-mode image to aid in diagnosis. A scatter plot of the normalized area feature demonstrates the feasibility of developing a linear classifier to differentiate benign from malignant masses. The area under the receiver operator characteristic curve utilizing the normalized axial-shear strain area feature was 0.996, demonstrating the potential of this feature to noninvasively differentiate between benign and malignant breast masses.
authors.affiliation: Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors.forename: Haiyan
authors.initials: H
authors.lastname: Xu
authors.forename: Min
authors.initials: M
authors.lastname: Rao
authors.forename: Tomy
authors.initials: T
authors.lastname: Varghese
authors.forename: Amy
authors.initials: A
authors.lastname: Sommer
authors.forename: Sara
authors.initials: S
authors.lastname: Baker
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Hall
authors.forename: Gale A
authors.initials: GA
authors.lastname: Sisney
authors.forename: Elizabeth S
authors.initials: ES
authors.lastname: Burnside
mesh_terms: D000328:Adult; D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003937:Diagnosis, Differential; D054459:Elasticity Imaging Techniques; D005240:Feasibility Studies; D005260:Female; D018226:Fibroadenoma / Q000000981:diagnostic imaging / Q000473:pathology; D006801:Humans; D010173:Palpation; D019047:Phantoms, Imaging; D012372:ROC Curve; D014159:Transducers; D016217:Ultrasonography, Mammary / Q000379:methods*
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