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Mammographic Density Assessment by Artificial Intelligence-Based Computer-Assisted Diagnosis: A Comparison with Automated Volumetric Assessment

Authors
 Si Eun Lee  ;  Nak-Hoon Son  ;  Myung Hyun Kim  ;  Eun-Kyung Kim 
Citation
 JOURNAL OF DIGITAL IMAGING, Vol.35(2) : 173-179, 2022-04 
Journal Title
JOURNAL OF DIGITAL IMAGING
ISSN
 0897-1889 
Issue Date
2022-04
MeSH
Artificial Intelligence ; Breast Density* ; Breast Neoplasms* / diagnostic imaging ; Computers ; Female ; Humans ; Mammography / methods ; Retrospective Studies
Keywords
Artificial intelligence ; Breast density ; Diagnosis, Computer-assisted ; Digital mammography
Abstract
We evaluated and compared the mammographic density assessment of an artificial intelligence-based computer-assisted diagnosis (AI-CAD) program using inter-rater agreements between radiologists and an automated density assessment program. Between March and May 2020, 488 consecutive mammograms of 488 patients (56.2 ± 10.9 years) were collected from a single institution. We assigned four classes of mammographic density based on BI-RADS (Breast Imaging Reporting and Data System) using commercial AI-CAD (Lunit INSIGHT MMG), and compared inter-rater agreements between radiologists, AI-CAD, and another commercial automated density assessment program (Volpara®). The inter-rater agreement between AI-CAD and the reader consensus was 0.52 with a matched rate of 68.2% (333/488). The inter-rater agreement between Volpara® and the reader consensus was similar to AI-CAD at 0.50 with a matched rate of 62.7% (306/488). The inter-rater agreement between AI-CAD and Volpara® was 0.54 with a matched rate of 61.5% (300/488). In conclusion, density assessments by AI-CAD showed fair agreement with those of radiologists, similar to the agreement between the commercial automated density assessment program and radiologists.
Full Text
https://link.springer.com/article/10.1007/s10278-021-00555-x
DOI
10.1007/s10278-021-00555-x
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Eun-Kyung(김은경) ORCID logo https://orcid.org/0000-0002-3368-5013
Lee, Si Eun(이시은) ORCID logo https://orcid.org/0000-0002-3225-5484
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/188338
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