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Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts
OBJECTIVES: To determine the effect of computer-aided-detection (CAD) software for automated breast ultrasound (ABUS) on reading time (RT) and performance in screening for breast cancer. MATERIAL AND METHODS: Unilateral ABUS examinations of 120 women with dense breasts were randomly selected from a...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5986849/ https://www.ncbi.nlm.nih.gov/pubmed/29417251 http://dx.doi.org/10.1007/s00330-017-5280-3 |
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author | van Zelst, Jan C. M. Tan, Tao Clauser, Paola Domingo, Angels Dorrius, Monique D. Drieling, Daniel Golatta, Michael Gras, Francisca de Jong, Mathijn Pijnappel, Ruud Rutten, Matthieu J. C. M. Karssemeijer, Nico Mann, Ritse M. |
author_facet | van Zelst, Jan C. M. Tan, Tao Clauser, Paola Domingo, Angels Dorrius, Monique D. Drieling, Daniel Golatta, Michael Gras, Francisca de Jong, Mathijn Pijnappel, Ruud Rutten, Matthieu J. C. M. Karssemeijer, Nico Mann, Ritse M. |
author_sort | van Zelst, Jan C. M. |
collection | PubMed |
description | OBJECTIVES: To determine the effect of computer-aided-detection (CAD) software for automated breast ultrasound (ABUS) on reading time (RT) and performance in screening for breast cancer. MATERIAL AND METHODS: Unilateral ABUS examinations of 120 women with dense breasts were randomly selected from a multi-institutional archive of cases including 30 malignant (20/30 mammography-occult), 30 benign, and 60 normal cases with histopathological verification or ≥ 2 years of negative follow-up. Eight radiologists read once with (CAD-ABUS) and once without CAD (ABUS) with > 8 weeks between reading sessions. Readers provided a BI-RADS score and a level of suspiciousness (0-100). RT, sensitivity, specificity, PPV and area under the curve (AUC) were compared. RESULTS: Average RT was significantly shorter using CAD-ABUS (133.4 s/case, 95% CI 129.2-137.6) compared with ABUS (158.3 s/case, 95% CI 153.0-163.3) (p < 0.001). Sensitivity was 0.84 for CAD-ABUS (95% CI 0.79-0.89) and ABUS (95% CI 0.78-0.88) (p = 0.90). Three out of eight readers showed significantly higher specificity using CAD. Pooled specificity (0.71, 95% CI 0.68-0.75 vs. 0.67, 95% CI 0.64-0.70, p = 0.08) and PPV (0.50, 95% CI 0.45-0.55 vs. 0.44, 95% CI 0.39-0.49, p = 0.07) were higher in CAD-ABUS vs. ABUS, respectively, albeit not significantly. Pooled AUC for CAD-ABUS was comparable with ABUS (0.82 vs. 0.83, p = 0.53, respectively). CONCLUSION: CAD software for ABUS may decrease the time needed to screen for breast cancer without compromising the screening performance of radiologists. KEY POINTS: • ABUS with CAD software may speed up reading time without compromising radiologists’ accuracy. • CAD software for ABUS might prevent non-detection of malignant breast lesions by radiologists. • Radiologists reading ABUS with CAD software might improve their specificity without losing sensitivity. |
format | Online Article Text |
id | pubmed-5986849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-59868492018-06-12 Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts van Zelst, Jan C. M. Tan, Tao Clauser, Paola Domingo, Angels Dorrius, Monique D. Drieling, Daniel Golatta, Michael Gras, Francisca de Jong, Mathijn Pijnappel, Ruud Rutten, Matthieu J. C. M. Karssemeijer, Nico Mann, Ritse M. Eur Radiol Breast OBJECTIVES: To determine the effect of computer-aided-detection (CAD) software for automated breast ultrasound (ABUS) on reading time (RT) and performance in screening for breast cancer. MATERIAL AND METHODS: Unilateral ABUS examinations of 120 women with dense breasts were randomly selected from a multi-institutional archive of cases including 30 malignant (20/30 mammography-occult), 30 benign, and 60 normal cases with histopathological verification or ≥ 2 years of negative follow-up. Eight radiologists read once with (CAD-ABUS) and once without CAD (ABUS) with > 8 weeks between reading sessions. Readers provided a BI-RADS score and a level of suspiciousness (0-100). RT, sensitivity, specificity, PPV and area under the curve (AUC) were compared. RESULTS: Average RT was significantly shorter using CAD-ABUS (133.4 s/case, 95% CI 129.2-137.6) compared with ABUS (158.3 s/case, 95% CI 153.0-163.3) (p < 0.001). Sensitivity was 0.84 for CAD-ABUS (95% CI 0.79-0.89) and ABUS (95% CI 0.78-0.88) (p = 0.90). Three out of eight readers showed significantly higher specificity using CAD. Pooled specificity (0.71, 95% CI 0.68-0.75 vs. 0.67, 95% CI 0.64-0.70, p = 0.08) and PPV (0.50, 95% CI 0.45-0.55 vs. 0.44, 95% CI 0.39-0.49, p = 0.07) were higher in CAD-ABUS vs. ABUS, respectively, albeit not significantly. Pooled AUC for CAD-ABUS was comparable with ABUS (0.82 vs. 0.83, p = 0.53, respectively). CONCLUSION: CAD software for ABUS may decrease the time needed to screen for breast cancer without compromising the screening performance of radiologists. KEY POINTS: • ABUS with CAD software may speed up reading time without compromising radiologists’ accuracy. • CAD software for ABUS might prevent non-detection of malignant breast lesions by radiologists. • Radiologists reading ABUS with CAD software might improve their specificity without losing sensitivity. Springer Berlin Heidelberg 2018-02-07 2018 /pmc/articles/PMC5986849/ /pubmed/29417251 http://dx.doi.org/10.1007/s00330-017-5280-3 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Breast van Zelst, Jan C. M. Tan, Tao Clauser, Paola Domingo, Angels Dorrius, Monique D. Drieling, Daniel Golatta, Michael Gras, Francisca de Jong, Mathijn Pijnappel, Ruud Rutten, Matthieu J. C. M. Karssemeijer, Nico Mann, Ritse M. Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts |
title | Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts |
title_full | Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts |
title_fullStr | Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts |
title_full_unstemmed | Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts |
title_short | Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts |
title_sort | dedicated computer-aided detection software for automated 3d breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts |
topic | Breast |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5986849/ https://www.ncbi.nlm.nih.gov/pubmed/29417251 http://dx.doi.org/10.1007/s00330-017-5280-3 |
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