662-03-015 ISMRM Abstract

Preoperative Ki-67 Prediction in Invasive Breast Cancer via Adaptive Machine Learning and Multiparametric MRI Radiomics

Primary: Body - Breast

Secondary: Analysis Methods - Radiomics

662-03-015 · Classification: Other Cancer · Thursday, 14 May, 1:40 PM–2:35 PM · Digital Posters Row C

Keywords: Radiomics Breast cancer Machine learning Multiparametric MRI Ki-67

Accepted

Da Shi^1,2, Yanan Shi^1,2, Qingyun Wang^1,2, Yongzhou Xu ³, Zhaoyong Li^1,2

¹Dongguan Key Laboratory of Radiology and Molecular Imaging, Dongguan, China

²Department of Radiology, DongGuan Tungwah Hospital, Dongguan, China

³Clinical and Technical Support, Philips Healthcare (Guangzhou), Guangzhou, China

Presenting Author: Yongzhou Xu

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References

1. Polyak K. Heterogeneity in breast cancer[J]. Nat Rev Cancer. 2020;20(2):89-103.

2. Zhao J, Ding X, Peng C, et al. Assessment of Ki-67 proliferation index in prognosis prediction in patients with nonmetastatic clear cell renal cell carcinoma and tumor thrombus[J]. Urol Oncol. 2024;42(1):9.

3. Zhang L, Shen M, Zhang D, et al. Radiomics Nomogram Based on Dual-Sequence MRI for Assessing Ki-67 Expression in Breast Cancer[J]. J Magn Reson Imaging. 2024;60(3):1203-1212.

4. Wang X, Wu H, Wang Y, et al. Preoperative prediction of Ki-67 expression and risk stratification in gliomas using multiparametric MRI and intratumor heterogeneity-based habitat imaging: a multicenter study[J]. Int J Surg. 2025;111(4):3123-3128.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/662-03-015