ArticleInsights into imaging2022
Mammographically occult breast cancers detected with AI-based diagnosis supporting software: clinical and histopathologic characteristics.
Article in Insights into imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Added value of diffusion-weighted imaging in detecting breast cancer missed by artificial intelligence-based mammography.La Radiologia medica · 2026Article
- Combined use of two artificial intelligence-based algorithms for mammography triaging: a retrospective simulation study.European radiology · 2026Article
- AI assistance improves reader agreement in digital mammography: A multireader crossover study of general and breast subspecialty radiologists.Scientific reports · 2025Article
- Exploring the Efficacy of Artificial Intelligence-Based Computer-Aided Detection for Breast Cancer Detection on Digital Mammograms.Journal of the Korean Society of Radiology · 2025Article
- A multimodal machine learning model for the stratification of breast cancer risk.Nature biomedical engineering · 2025Article
- Use of a commercial artificial intelligence-based mammography analysis software for improving breast ultrasound interpretations.European radiology · 2024Article
- Navigating the Metaverse: A New Virtual Tool with Promising Real Benefits for Breast Cancer Patients.Journal of clinical medicine · 2024Review
- Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software.European radiology · 2024Article
- Artificial Intelligence Improves Detection of Supplemental Screening Ultrasound-detected Breast Cancers in Mammography.Journal of breast cancer · 2023Article
- Comparison of Characteristics of Breast Cancer Detected through Different Imaging Modalities in a Large Cohort of Hong Kong Chinese Women: Implication of Imaging Choice on Upcoming Local Screening Program.The breast journal · 2022Article
- Artificial intelligence in breast cancer imaging: risk stratification, lesion detection and classification, treatment planning and prognosis-a narrative review.Exploration of targeted anti-tumor therapy · 2022Review
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo demonstrate the value of an artificial intelligence (AI) software in the detection of mammographically occult breast cancers and to determine the clinicopathologic patterns of the cancers additionally detected using the AI software.
methodsBy retrospectively reviewing our institutional database (January 2017-September 2019), we identified women with mammographically occult breast cancers and analyzed their mammography with an AI software that provided a malignancy score (range 0-100; > 10 considered as positive). The hot spots in the AI report were compared with the US and MRI findings to determine if the cancers were correctly marked by the AI software. The clinicopathologic characteristics of the AI-detected cancers were analyzed and compared with those of undetected cancers.
resultsAmong the 1890 breast cancers, 6.8% (128/1890) were mammographically occult, among which 38.3% (49/128) had positive results in the AI analysis. Of them, 81.6% (40/49) were correctly marked by the AI software and determined as "AI-detected cancers." As such, 31.3% (40/128) of mammographically occult breast cancers could be identified by the AI software. Of the AI-detected cancers, 97.5% were found in heterogeneously or extremely dense breasts, 52.5% were asymptomatic, 86.5% were invasive, and 29.7% had axillary lymph node metastasis. Compared with undetected cancers, the AI-detected cancers were more likely to be found in younger patients (p < 0.001), undergo neoadjuvant chemotherapy as well as mastectomy rather than breast-conserving operation (both p < 0.001), and accompany axillary lymph node metastasis (p = 0.003).
conclusionsAI conferred an added value in the detection of mammographically occult breast cancers.
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