Predicting Disease-Free Survival by DWI and DCE MRI Scores for Breast Cancer Patients with Neoadjuvant Systemic Treatment
Motivation: MRI is expected to be a new surrogate marker of prognosis that can replace pathological complete response (pCR) for breast cancer patients who underwent neoadjuvant systemic treatment (NST). Goal(s): MRI is expected to be a new surrogate marker of prognosis that can replace pathological complete response (pCR) for breast cancer patients who underwent neoadjuvant systemic treatment (NST)Approach: Survival analysis was performed for disease-free survival using Kaplan-Meier method. Results: DWI score after NST of breast cancer was associated with DFS, in particular triple-negative, HER2-positive, and luminal-HER2 subtype. Impact: The DWI / kinetic score obtained from MRI after neoadjuvant systemic treatment (NST) were associated with disease-free survival (DFS), especially among triple-negative, HER2-positive, and luminal/HER2 subtype. The DWI score may be a biomarker for prognosis of breast cancer patients.
Authors
- Yosuke Yamada (ORCID: https://orcid.org/0000-0001-7952-2706)
- Takeshi Kubo (ORCID: https://orcid.org/0000-0002-3397-4472)
- Mizue Suzuki (ORCID: https://orcid.org/0000-0001-9332-8731)
- Yuji Nakamoto (ORCID: https://orcid.org/0000-0001-5783-8048)
- Masahiro Takada (ORCID: https://orcid.org/0000-0002-5954-1296)
- Yasuhide Takeuchi (ORCID: https://orcid.org/0000-0002-1262-2355)
- Masako Kataoka (ORCID: https://orcid.org/0000-0002-6212-3351)
- Maya Honda (ORCID: https://orcid.org/0000-0002-5337-3455)
- Rie Ota (ORCID: https://orcid.org/0000-0003-1248-9272)
- Shotaro Kanao (ORCID: https://orcid.org/0000-0002-0923-5207)
- Mami Iima (ORCID: https://orcid.org/0000-0002-1991-2494)
- Aika Okazawa
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/0202
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00