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Characterizing Breast Lesions Using Quantitative Parametric 3D Subharmonic Imaging: A Multicenter Study
Journal article   Open access   Peer reviewed

Characterizing Breast Lesions Using Quantitative Parametric 3D Subharmonic Imaging: A Multicenter Study

Anush Sridharan, John R. Eisenbrey, Maria Stanczak, Priscilla Machado, Daniel A. Merton, Annina Wilkes, Alexander Sevrukov, Haydee Ojeda-Fournier, Robert F. Mattrey, Kirk Wallace, …
Academic radiology, v 27(8), pp 1065-1074
01 Aug 2020
PMID: 31859210
url
https://doi.org/10.1016/j.acra.2019.10.029View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze) Restricted

Abstract

Life Sciences & Biomedicine Radiology, Nuclear Medicine & Medical Imaging Science & Technology
Rationale and Objectives: Breast cancer is the leading type of cancer among women. Visualization and characterization of breast lesions based on vascularity kinetics was evaluated using three-dimensional (3D) contrast-enhanced ultrasound imaging in a clinical study. Materials and Methods: Breast lesions (n = 219) were imaged using power Doppler imaging (PDI), 3D contrast-enhanced harmonic imaging (HI), and 3D contrast-enhanced subharmonic imaging (SHI) with a modified Logiq 9 ultrasound scanner using a 4D10L transducer. Quantitative metrics of vascularity derived from 3D parametric volumes (based on contrast perfusion; PER and area under the curve; AUC) were generated by off-line processing of contrast wash-in and wash-out. Diagnostic accuracy of these quantitative vascular parameters was assessed with biopsy results as the reference standard. Results: Vascularity was observed with PDI in 93 lesions (69 benign and 24 malignant), 3D HI in 8 lesions (5 benign and 3 malignant), and 3D SHI in 83 lesions (58 benign and 25 malignant). Diagnostic accuracy for vascular heterogeneity, PER, and AUC ranged from 0.52 to 0.75, while the best logistical regression model (vascular heterogeneity ratio, central PER, and central AUC) reached 0.90. Conclusion: 3D SHI successfully detects contrast agent flow in breast lesions and characterization of these lesions based on quantitative measures of vascular heterogeneity and 3D parametric volumes is promising.

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12 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#5 Gender Equality
#3 Good Health and Well-Being

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Collaboration types
Industry collaboration
Domestic collaboration
Web of Science research areas
Radiology, Nuclear Medicine & Medical Imaging
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