A Simple Ultrasound Based Classification Algorithm Allows Differentiation of Benign from Malignant Breast Lesions by Using Only Quantitative Parameters.
Purpose: We hypothesized that different quantitative ultrasound (US) parameters may be used as complementary diagnostic criteria and aimed to develop a simple classification algorithm to distinguish benign from malignant breast lesions and aid in the decision to perform biopsy or not.Procedures: One...
| Publicado en: | Molecular Imaging & Biology Vol. 20; no. 6; pp. 1053 - 1061 |
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| Autores principales: | , , , , , , |
| Formato: | algorithm diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2018
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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=132999389&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132999389 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15361632 KJU jtl: Molecular Imaging & Biology issn: 15361632 maglogo: N pubinfo: dt: Dec2018 vid: 20 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 132999389 132999389 NLM29633108 132999389 10.1007/s11307-018-1187-x NLM29633108 132999389 ppf: 1053 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Simple Ultrasound Based Classification Algorithm Allows Differentiation of Benign from Malignant Breast Lesions by Using Only Quantitative Parameters. aug: au: Kapetas, Panagiotis Woitek, Ramona Clauser, Paola Bernathova, Maria Pinker, Katja Helbich, Thomas H. Baltzer, Pascal A. affil: Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria sug: subj: Breast Neoplasms Pathology Breast Neoplasms Cell Differentiation Ultrasonography Algorithms Young Adult Middle Age Adult Aged, 80 and Over Adolescence Female Aged Human Middle Aged: 45-64 years Adult: 19-44 years Aged, 80 & over Adolescent: 13-18 years Aged: 65+ years Female ab: Purpose: We hypothesized that different quantitative ultrasound (US) parameters may be used as complementary diagnostic criteria and aimed to develop a simple classification algorithm to distinguish benign from malignant breast lesions and aid in the decision to perform biopsy or not.Procedures: One hundred twenty-four patients, each with one biopsy-proven, sonographically evident breast lesion, were included in this prospective, IRB-approved study. Each lesion was examined with B-mode US, Color/Power Doppler US and elastography (Acoustic Radiation Force Impulse-ARFI). Different quantitative parameters were recorded for each technique, including pulsatility (PI) and resistive Index (RI) for Doppler US and lesion maximum, intermediate, and minimum shear wave velocity (SWVmax, SWVinterm, and SWVmin) as well as lesion-to-fat SWV ratio for ARFI. Receiver operating characteristic curve (ROC) analysis was used to evaluate the diagnostic performance of each quantitative parameter. Classification analysis was performed using the exhaustive chi-squared automatic interaction detection method. Results include the probability for malignancy for every descriptor combination in the classification algorithm.Results: Sixty-five lesions were malignant and 59 benign. Out of all quantitative indices, maximum SWV (SWVmax), and RI were included in the classification algorithm, which showed a depth of three ramifications (SWVmax ≤ or > 3.16; if SWVmax ≤ 3.16 then RI ≤ 0.66, 0.66-0.77 or > 0.77; if RI ≤ 0.66 then SWVmax ≤ or > 2.71). The classification algorithm leads to an AUC of 0.887 (95 % CI 0.818-0.937, p < 0.0001), a sensitivity of 98.46 % (95 % CI 91.7-100 %), and a specificity of 61.02 % (95 % CI 47.4-73.5 %). By applying the proposed algorithm, a false-positive biopsy could have been avoided in 61 % of the cases.Conclusions: A simple classification algorithm incorporating two quantitative US parameters (SWVmax and RI) shows a high diagnostic performance, being able to accurately differentiate benign from malignant breast lesions and lower the number of unnecessary breast biopsies in up to 60 % of all cases, avoiding any subjective interpretation bias. pubtype: Academic Journal doctype: algorithm diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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