Supine versus Prone 3D Abus Accuracy in Breast Tumor Size Evaluation

Breast-conserving surgery (BCS) with negative resection margins decreases the locoregional recurrence rate. Breast cancer size is one of the main determinants of Tumor-Node-Metastasis (TNM) staging. Our study aimed to investigate the accuracy of supine 3D automated breast ultrasound (3D ABUS) compared to prone 3D ABUS in the evaluation of tumor size in breast cancer patient candidates for BCS. In this prospective two-center study (Groups 1 and 2), we enrolled patients with percutaneous biopsy-proven early-stage breast cancer, in the period between June 2019 and May 2020. Patients underwent hand-held ultrasound (HHUS), contrast-enhanced magnetic resonance imaging (CE-MRI) and 3D ABUS-supine 3D ABUS in Group 1 and prone 3D ABUS in Group 2. Histopathological examination (HE) was considered the reference standard. Bland-Altman analysis and plots were used. Eighty-eight patients were enrolled. Compared to prone, supine 3D ABUS showed better agreement with HE, with a slight tendency toward underestimation (mean difference of -2 mm). Supine 3D ABUS appears to be a useful tool and more accurate than HHUS in the staging of breast cancer.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:8

Enthalten in:

Tomography (Ann Arbor, Mich.) - 8(2022), 4 vom: 12. Aug., Seite 1997-2009

Sprache:

Englisch

Beteiligte Personen:

D'Angelo, Anna [VerfasserIn]
Gatta, Gianluca [VerfasserIn]
Di Grezia, Graziella [VerfasserIn]
Mercogliano, Sara [VerfasserIn]
Ferrara, Francesca [VerfasserIn]
Trombadori, Charlotte Marguerite Lucille [VerfasserIn]
Franco, Antonio [VerfasserIn]
Cina, Alessandro [VerfasserIn]
Belli, Paolo [VerfasserIn]
Manfredi, Riccardo [VerfasserIn]

Links:

Volltext

Themen:

3D automated breast ultrasound (ABUS)
Breast cancer
Breast imaging
Hand-held ultrasound (HHUS)
Journal Article
Magnetic resonance imaging (MRI)

Anmerkungen:

Date Completed 29.08.2022

Date Revised 04.10.2022

published: Electronic

Citation Status MEDLINE

doi:

10.3390/tomography8040167

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM345244877