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


Journal

Academic radiology
ISSN: 1878-4046
Titre abrégé: Acad Radiol
Pays: United States
ID NLM: 9440159

Informations de publication

Date de publication:
08 2020
Historique:
received: 08 07 2019
revised: 16 10 2019
accepted: 30 10 2019
pubmed: 21 12 2019
medline: 11 11 2020
entrez: 21 12 2019
Statut: ppublish

Résumé

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. 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. 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. 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.

Identifiants

pubmed: 31859210
pii: S1076-6332(19)30547-1
doi: 10.1016/j.acra.2019.10.029
pmc: PMC7295667
mid: NIHMS1542265
pii:
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article Multicenter Study Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

1065-1074

Subventions

Organisme : NCI NIH HHS
ID : R01 CA140338
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2019 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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Auteurs

Anush Sridharan (A)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107; Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania.

John R Eisenbrey (JR)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107.

Maria Stanczak (M)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107.

Priscilla Machado (P)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107.

Daniel A Merton (DA)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107.

Annina Wilkes (A)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107.

Alexander Sevrukov (A)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107.

Haydee Ojeda-Fournier (H)

Department of Radiology, University of California, San Diego, California.

Robert F Mattrey (RF)

Department of Radiology, University of California, San Diego, California.

Kirk Wallace (K)

GE Global Research, Niskayuna, New York.

Flemming Forsberg (F)

Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107. Electronic address: flemming.forsberg@jefferson.edu.

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Classifications MeSH