Use of a commercial artificial intelligence-based mammography analysis software for improving breast ultrasound interpretations
- 03.04.2024
- Breast
Erschienen in:
- Verfasst von
- Hee Jeong Kim
- Hak Hee Kim
- Ki Hwan Kim
- Ji Sung Lee
- Woo Jung Choi
- Eun Young Chae
- Hee Jung Shin
- Joo Hee Cha
- Woo Hyun Shim
- Erschienen in
- European Radiology | Ausgabe 10/2024
Abstract
Objectives
To evaluate the use of a commercial artificial intelligence (AI)–based mammography analysis software for improving the interpretations of breast ultrasound (US)-detected lesions.
Methods
A retrospective analysis was performed on 1109 breasts that underwent both mammography and US-guided breast biopsy. The AI software processed mammograms and provided an AI score ranging from 0 to 100 for each breast, indicating the likelihood of malignancy. The performance of the AI score in differentiating mammograms with benign outcomes from those revealing cancers following US-guided breast biopsy was evaluated. In addition, prediction models for benign outcomes were constructed based on clinical and imaging characteristics with and without AI scores, using logistic regression analysis.
Results
The AI software had an area under the receiver operating characteristics curve (AUROC) of 0.79 (95% CI, 0.79–0.82) in differentiating between benign and cancer cases. The prediction models that did not include AI scores (non-AI model), only used AI scores (AI-only model), and included AI scores (integrated model) had AUROCs of 0.79 (95% CI, 0.75–0.83), 0.78 (95% CI, 0.74–0.82), and 0.85 (95% CI, 0.81–0.88) in the development cohort, and 0.75 (95% CI, 0.68–0.81), 0.82 (95% CI, 0.76–0.88), and 0.84 (95% CI, 0.79–0.90) in the validation cohort, respectively. The integrated model outperformed the non-AI model in the development and validation cohorts (p < 0.001 for both).
Conclusion
The commercial AI-based mammography analysis software could be a valuable adjunct to clinical decision-making for managing US-detected breast lesions.
Clinical relevance statement
The commercial AI-based mammography analysis software could potentially reduce unnecessary biopsies and improve patient outcomes.
Key Points
• Breast US has high rates of false-positive interpretations.
• A commercial AI-based mammography analysis software could distinguish mammograms having benign outcomes from those revealing cancers after US-guided breast biopsy.
• A commercial AI-based mammography analysis software may improve interpretations for breast US-detected lesions.
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- Titel
- Use of a commercial artificial intelligence-based mammography analysis software for improving breast ultrasound interpretations
- Verfasst von
-
Hee Jeong Kim
Hak Hee Kim
Ki Hwan Kim
Ji Sung Lee
Woo Jung Choi
Eun Young Chae
Hee Jung Shin
Joo Hee Cha
Woo Hyun Shim
- Publikationsdatum
- 03.04.2024
- Verlag
- Springer Berlin Heidelberg
- Erschienen in
-
European Radiology / Ausgabe 10/2024
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084 - DOI
- https://doi.org/10.1007/s00330-024-10718-3
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