Deep Learning for Early Breast Cancer Detection on Contrast-Enhanced Breast MRI: A Multicenter Study. | ScholarDeck

Paper

Deep Learning for Early Breast Cancer Detection on Contrast-Enhanced Breast MRI: A Multicenter Study.

New research · Radiology

Cancers · 3w

AI / informaticsCancers· Jul 2026

Deep Learning for Early Breast Cancer Detection on Contrast-Enhanced Breast MRI: A Multicenter Study.

Na Young Jung, Jihe Lim, Hyug-Gi Kim … Min Sun Bae

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Breast ImagingAI / informaticsDiagnosisQ1IF 4.9

AI aid raised radiologists' precision detecting subcentimeter breast cancers on MRI

Deep Learning for Early Breast Cancer Detection on Contrast-Enhanced Breast MRI: A Multicenter Study.

Na Young Jung … Min Sun Bae

Cancers · Jul 2026

Background

Accurate visual categorization of small enhancing lesions on contrast-enhanced breast MRI remains challenging.

Purpose

The purpose of this study was to develop a deep learning (deep learning) model for detecting small (≤2 cm) invasive breast cancers using multi-institutional breast MRI data.

Methods

This retrospective study included a total of 1721 women (mean age: 54 years; range, 21-87 years) with T1-stage invasive breast cancer across five hospitals.

n = 1721 women

Results

AI assistance made radiologists more accurate, fewer false alarms on tiny cancers

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Conclusion

The deep learning model demonstrated potential as an assistive tool by improving radiologists' precision for detecting small invasive breast cancers on contrast-enhanced breast MRI in this enriched reader-study setting, although it did not significantly improve their sensitivity.

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