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Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study

Background: The purpose of this study was to assess the effectiveness of the radiomic analysis of contrast-enhanced spectral mammography (CESM) in discriminating between breast cancers and background parenchymal enhancement (BPE). Methods: This retrospective study included 38 patients that underwent...

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Autores principales: Boca (Bene), Ioana, Ciurea, Anca Ileana, Ciortea, Cristiana Augusta, Ștefan, Paul Andrei, Lisencu, Lorena Alexandra, Dudea, Sorin Marian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305277/
https://www.ncbi.nlm.nih.gov/pubmed/34359332
http://dx.doi.org/10.3390/diagnostics11071248
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author Boca (Bene), Ioana
Ciurea, Anca Ileana
Ciortea, Cristiana Augusta
Ștefan, Paul Andrei
Lisencu, Lorena Alexandra
Dudea, Sorin Marian
author_facet Boca (Bene), Ioana
Ciurea, Anca Ileana
Ciortea, Cristiana Augusta
Ștefan, Paul Andrei
Lisencu, Lorena Alexandra
Dudea, Sorin Marian
author_sort Boca (Bene), Ioana
collection PubMed
description Background: The purpose of this study was to assess the effectiveness of the radiomic analysis of contrast-enhanced spectral mammography (CESM) in discriminating between breast cancers and background parenchymal enhancement (BPE). Methods: This retrospective study included 38 patients that underwent CESM examinations for clinical purposes between January 2019–December 2020. A total of 57 malignant breast lesions and 23 CESM examinations with 31 regions of BPE were assessed through radiomic analysis using MaZda software. The parameters that demonstrated to be independent predictors for breast malignancy were exported into the B11 program and a k-nearest neighbor classifier (k-NN) was trained on the initial groups of patients and was tested using a validation group. Histopathology results obtained after surgery were considered the gold standard. Results: Radiomic analysis found WavEnLL_s_2 parameter as an independent predictor for breast malignancies with a sensitivity of 68.42% and a specificity of 83.87%. The prediction model that included CH1D6SumAverg, CN4D6Correlat, Kurtosis, Perc01, Perc10, Skewness, and WavEnLL_s_2 parameters had a sensitivity of 73.68% and a specificity of 80.65%. Higher values were obtained of WavEnLL_s_2 and the prediction model for tumors than for BPEs. The comparison between the ROC curves provided by the WaveEnLL_s_2 and the entire prediction model did not show statistically significant results (p = 0.0943). The k-NN classifier based on the parameter WavEnLL_s_2 had a sensitivity and specificity on training and validating groups of 71.93% and 45.16% vs. 60% and 44.44%, respectively. Conclusion: Radiomic analysis has the potential to differentiate CESM between malignant lesions and BPE. Further quantitative insight into parenchymal enhancement patterns should be performed to facilitate the role of BPE in personalized clinical decision-making and risk assessment.
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spelling pubmed-83052772021-07-25 Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study Boca (Bene), Ioana Ciurea, Anca Ileana Ciortea, Cristiana Augusta Ștefan, Paul Andrei Lisencu, Lorena Alexandra Dudea, Sorin Marian Diagnostics (Basel) Article Background: The purpose of this study was to assess the effectiveness of the radiomic analysis of contrast-enhanced spectral mammography (CESM) in discriminating between breast cancers and background parenchymal enhancement (BPE). Methods: This retrospective study included 38 patients that underwent CESM examinations for clinical purposes between January 2019–December 2020. A total of 57 malignant breast lesions and 23 CESM examinations with 31 regions of BPE were assessed through radiomic analysis using MaZda software. The parameters that demonstrated to be independent predictors for breast malignancy were exported into the B11 program and a k-nearest neighbor classifier (k-NN) was trained on the initial groups of patients and was tested using a validation group. Histopathology results obtained after surgery were considered the gold standard. Results: Radiomic analysis found WavEnLL_s_2 parameter as an independent predictor for breast malignancies with a sensitivity of 68.42% and a specificity of 83.87%. The prediction model that included CH1D6SumAverg, CN4D6Correlat, Kurtosis, Perc01, Perc10, Skewness, and WavEnLL_s_2 parameters had a sensitivity of 73.68% and a specificity of 80.65%. Higher values were obtained of WavEnLL_s_2 and the prediction model for tumors than for BPEs. The comparison between the ROC curves provided by the WaveEnLL_s_2 and the entire prediction model did not show statistically significant results (p = 0.0943). The k-NN classifier based on the parameter WavEnLL_s_2 had a sensitivity and specificity on training and validating groups of 71.93% and 45.16% vs. 60% and 44.44%, respectively. Conclusion: Radiomic analysis has the potential to differentiate CESM between malignant lesions and BPE. Further quantitative insight into parenchymal enhancement patterns should be performed to facilitate the role of BPE in personalized clinical decision-making and risk assessment. MDPI 2021-07-13 /pmc/articles/PMC8305277/ /pubmed/34359332 http://dx.doi.org/10.3390/diagnostics11071248 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Boca (Bene), Ioana
Ciurea, Anca Ileana
Ciortea, Cristiana Augusta
Ștefan, Paul Andrei
Lisencu, Lorena Alexandra
Dudea, Sorin Marian
Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study
title Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study
title_full Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study
title_fullStr Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study
title_full_unstemmed Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study
title_short Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics—A Pilot Reader Study
title_sort differentiating breast tumors from background parenchymal enhancement at contrast-enhanced mammography: the role of radiomics—a pilot reader study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305277/
https://www.ncbi.nlm.nih.gov/pubmed/34359332
http://dx.doi.org/10.3390/diagnostics11071248
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