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Open Access 01-12-2018 | Research Article

A Simple Ultrasound Based Classification Algorithm Allows Differentiation of Benign from Malignant Breast Lesions by Using Only Quantitative Parameters

Authors: Panagiotis Kapetas, Ramona Woitek, Paola Clauser, Maria Bernathova, Katja Pinker, Thomas H. Helbich, Pascal A. Baltzer

Published in: Molecular Imaging and Biology | Issue 6/2018

Abstract

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 (SWV_max, SWV_interm, and SWV_min) 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 (SWV_max), and RI were included in the classification algorithm, which showed a depth of three ramifications (SWV_max ≤ or > 3.16; if SWV_max ≤ 3.16 then RI ≤ 0.66, 0.66–0.77 or > 0.77; if RI ≤ 0.66 then SWV_max ≤ 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 (SWV_max 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.

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Title: A Simple Ultrasound Based Classification Algorithm Allows Differentiation of Benign from Malignant Breast Lesions by Using Only Quantitative Parameters
Authors: Panagiotis Kapetas
Ramona Woitek
Paola Clauser
Maria Bernathova
Katja Pinker
Thomas H. Helbich
Pascal A. Baltzer
Publication date: 01-12-2018
Publisher: Springer International Publishing
Published in: Molecular Imaging and Biology / Issue 6/2018
Print ISSN: 1536-1632
Electronic ISSN: 1860-2002
DOI: https://doi.org/10.1007/s11307-018-1187-x

At a glance: The STEP trials

Springer Medicine

A Simple Ultrasound Based Classification Algorithm Allows Differentiation of Benign from Malignant Breast Lesions by Using Only Quantitative Parameters

Abstract

Purpose

Procedures

Results

Conclusions

At a glance: The STEP trials

Springer Medicine

Abstract

Purpose

Procedures

Results

Conclusions

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