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Personalised breast cancer screening with selective addition of digital breast tomosynthesis through artificial intelligence

Dahlblom, Victor LU ; Tingberg, Anders LU ; Zackrisson, Sophia LU and Dustler, Magnus LU (2020) 15th International Workshop on Breast Imaging, IWBI 2020 In Proceedings of SPIE - The International Society for Optical Engineering 11513.
Abstract

Breast cancer screening is predominantly performed using digital mammography (DM), but higher sensitivity has been demonstrated with digital breast tomosynthesis (DBT). A partial DBT screening in selected groups with a clear benefit from DBT might be more feasible than a full implementation, and using artificial intelligence (AI) to select women for DBT might be a possibility. This study used data from Malmö Breast Tomosynthesis Screening Trial, where all women prospectively were examined with separately read DM and DBT. We retrospectively analysed DM examinations (n=14768) with a breast cancer detection software and used the provided risk score (1-10) for risk stratification. We tested how different score thresholds for adding DBT to... (More)

Breast cancer screening is predominantly performed using digital mammography (DM), but higher sensitivity has been demonstrated with digital breast tomosynthesis (DBT). A partial DBT screening in selected groups with a clear benefit from DBT might be more feasible than a full implementation, and using artificial intelligence (AI) to select women for DBT might be a possibility. This study used data from Malmö Breast Tomosynthesis Screening Trial, where all women prospectively were examined with separately read DM and DBT. We retrospectively analysed DM examinations (n=14768) with a breast cancer detection software and used the provided risk score (1-10) for risk stratification. We tested how different score thresholds for adding DBT to an initial DM affects the number of detected cancers, additional DBT examinations needed, detection rate, and false positives. If using a threshold of 9.0, 25 (26 %) more cancers would be detected compared to using DM alone. Of the 41 cancers only detected on DBT, 61 % would be detected, with only 1797 (12 %) of the women examined with both DM and DBT. The detection rate for the added DBT would be 14/1000 women, while the false positive recalls would be increased with 58 (21 %). Using DBT only for selected high gain cases could be an alternative to a complete DBT screening. AI could be used for analysing DM to identify high gain cases, where DBT can be added during the same visit. There might be logistical challenges and further studies in a prospective setting are necessary.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Artificial intelligence, Breast cancer screening, Digital breast tomosynthesis, Personalised screening
host publication
15th International Workshop on Breast Imaging, IWBI 2020
series title
Proceedings of SPIE - The International Society for Optical Engineering
editor
Bosmans, Hilde ; Marshall, Nicholas and Van Ongeval, Chantal
volume
11513
article number
115130C
publisher
SPIE
conference name
15th International Workshop on Breast Imaging, IWBI 2020
conference location
Leuven, Belgium
conference dates
2020-05-25 - 2020-05-27
external identifiers
  • scopus:85086140189
ISSN
0277-786X
1996-756X
ISBN
9781510638310
DOI
10.1117/12.2564344
project
Can breast cancer screening be improved with artificial intelligence?
language
English
LU publication?
yes
id
30bfbe65-29f1-454a-a87c-44bab0cf3ceb
date added to LUP
2021-01-11 12:13:39
date last changed
2021-02-17 05:35:31
@inproceedings{30bfbe65-29f1-454a-a87c-44bab0cf3ceb,
  abstract     = {<p>Breast cancer screening is predominantly performed using digital mammography (DM), but higher sensitivity has been demonstrated with digital breast tomosynthesis (DBT). A partial DBT screening in selected groups with a clear benefit from DBT might be more feasible than a full implementation, and using artificial intelligence (AI) to select women for DBT might be a possibility. This study used data from Malmö Breast Tomosynthesis Screening Trial, where all women prospectively were examined with separately read DM and DBT. We retrospectively analysed DM examinations (n=14768) with a breast cancer detection software and used the provided risk score (1-10) for risk stratification. We tested how different score thresholds for adding DBT to an initial DM affects the number of detected cancers, additional DBT examinations needed, detection rate, and false positives. If using a threshold of 9.0, 25 (26 %) more cancers would be detected compared to using DM alone. Of the 41 cancers only detected on DBT, 61 % would be detected, with only 1797 (12 %) of the women examined with both DM and DBT. The detection rate for the added DBT would be 14/1000 women, while the false positive recalls would be increased with 58 (21 %). Using DBT only for selected high gain cases could be an alternative to a complete DBT screening. AI could be used for analysing DM to identify high gain cases, where DBT can be added during the same visit. There might be logistical challenges and further studies in a prospective setting are necessary.</p>},
  author       = {Dahlblom, Victor and Tingberg, Anders and Zackrisson, Sophia and Dustler, Magnus},
  booktitle    = {15th International Workshop on Breast Imaging, IWBI 2020},
  editor       = {Bosmans, Hilde and Marshall, Nicholas and Van Ongeval, Chantal},
  isbn         = {9781510638310},
  issn         = {0277-786X},
  language     = {eng},
  publisher    = {SPIE},
  series       = {Proceedings of SPIE - The International Society for Optical Engineering},
  title        = {Personalised breast cancer screening with selective addition of digital breast tomosynthesis through artificial intelligence},
  url          = {http://dx.doi.org/10.1117/12.2564344},
  doi          = {10.1117/12.2564344},
  volume       = {11513},
  year         = {2020},
}