Hybrid high-definition microvessel imaging/shear wave elastography improves breast lesion characterization.
Background: Low specificity in current breast imaging modalities leads to increased unnecessary follow-ups and biopsies. The purpose of this study is to evaluate the efficacy of combining the quantitative parameters of high-definition microvasculature imaging (HDMI) and 2D shear wave elastography (S...
| Publicado en: | Breast Cancer Research Vol. 24; no. 1; pp. 1 - 14 |
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| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
BioMed Central
3/5/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=155685959&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 155685959 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14655411 8UYJ jtl: Breast Cancer Research issn: 14655411 maglogo: N pubinfo: dt: 3/5/2022 vid: 24 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 155685959 155685959 NLM35248115 155685959 10.1186/s13058-022-01511-5 NLM35248115 155685959 ppf: 1 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Hybrid high-definition microvessel imaging/shear wave elastography improves breast lesion characterization. aug: au: Gu, Juanjuan Ternifi, Redouane Larson, Nicholas B. Carter, Jodi M. Boughey, Judy C. Stan, Daniela L. Fazzio, Robert T. Fatemi, Mostafa Alizad, Azra affil: Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, 200 First Street SW, 55905, Rochester, MN, USA sug: subj: Breast Neoplasms Ultrasonography Blood Vessels Ultrasonography Sensitivity and Specificity Evaluation Human Female Adult Middle Age Aged Prospective Studies Ultrasonography Methods Prediction Models Image Processing, Computer Assisted ROC Curve Descriptive Statistics Confidence Intervals Validity Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Female ab: Background: Low specificity in current breast imaging modalities leads to increased unnecessary follow-ups and biopsies. The purpose of this study is to evaluate the efficacy of combining the quantitative parameters of high-definition microvasculature imaging (HDMI) and 2D shear wave elastography (SWE) with clinical factors (lesion depth and age) for improving breast lesion differentiation.Methods: In this prospective study, from June 2016 through April 2021, patients with breast lesions identified on diagnostic ultrasound and recommended for core needle biopsy were recruited. HDMI and SWE were conducted prior to biopsies. Two new HDMI parameters, Murray's deviation and bifurcation angle, and a new SWE parameter, mass characteristic frequency, were included for quantitative analysis. Lesion malignancy prediction models based on HDMI only, SWE only, the combination of HDMI and SWE, and the combination of HDMI, SWE and clinical factors were trained via elastic net logistic regression with 70% (360/514) randomly selected data and validated with the remaining 30% (154/514) data. Prediction performances in the validation test set were compared across models with respect to area under the ROC curve as well as sensitivity and specificity based on optimized threshold selection.Results: A total of 508 participants (mean age, 54 years ± 15), including 507 female participants and 1 male participant, with 514 suspicious breast lesions (range, 4-72 mm, median size, 13 mm) were included. Of the lesions, 204 were malignant. The SWE-HDMI prediction model, combining quantitative parameters from SWE and HDMI, with AUC of 0.973 (95% CI 0.95-0.99), was significantly higher than the result predicted with the SWE model or HDMI model alone. With an optimal cutoff of 0.25 for the malignancy probability, the sensitivity and specificity were 95.5% and 89.7%, respectively. The specificity was further improved with the addition of clinical factors. The corresponding model defined as the SWE-HDMI-C prediction model had an AUC of 0.981 (95% CI 0.96-1.00).Conclusions: The SWE-HDMI-C detection model, a combination of SWE estimates, HDMI quantitative biomarkers and clinical factors, greatly improved the accuracy in breast lesion characterization. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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