MRI-based quantification of intratumoral heterogeneity for predicting recurrence risk in ER+/HER2- breast cancer.
Authors
Affiliations (9)
Affiliations (9)
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- MR Research China, GE Healthcare, Beijing, China.
- Department of Ultrasound, Secondary Sanatorium of Air Force Healthcare Center for Special Services, Hangzhou, China.
- Department of Data Science & AI, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia.
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China. [email protected].
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. [email protected].
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China. [email protected].
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. [email protected].
Abstract
The need for a cost-effective, rapid, and increasingly accessible alternative to the 21-gene assay prompted this study, which developed a novel MRI-based intratumoral heterogeneity score (ITHscore) to quantify tumor heterogeneity and integrated it with radiomic and clinical features to predict the 21-gene recurrence score (RS). This retrospective study included ER+/HER2- breast cancer patients who underwent 21-gene assay and preoperative MRI at our institution (April 2017-March 2019). Patients were randomly split into training (70%) and internal test (30%) cohorts, with an external test cohort from the public Duke-Breast-Cancer-MRI dataset. Tumor volumes of interest were automatically segmented using a pre-trained Scalable and Transferable U-Net framework, followed by k-means clustering to compute the ITHscore. Predictive models for the RS were built using clinical, radiomics, and ITHscore features with the support vector machine method, and evaluated by receiver operating characteristic curves. The institutional dataset comprised 452 patients (training: 316 (187 high-risk, 129 low-risk); internal test: 136 (80 high-risk, 56 low-risk)), while the external Duke cohort included 230 patients (44 high-risk, 186 low-risk). The ITHscore was significantly elevated in high-risk patients (p < 0.001), and its incorporation into the clinical-radiomic model improved RS prediction, yielding AUCs of 0.86 for the internal test cohort and 0.82 for the external test cohort. In this exploratory study, the ITHscore, which held promise as a noninvasive and intuitive means of characterizing intratumoral heterogeneity, demonstrated a potential incremental value for predicting RS in patients with ER+/HER2- breast cancer. The MRI-derived quantification of intratumoral heterogeneity facilitates simple and quantitative assessment of tumor heterogeneity and demonstrates potential incremental value in providing a rapid, cost-effective, and accessible prediction of the recurrence score in ER+/HER2- breast cancer. There is a need for a cost-effective, rapid, and increasingly accessible alternative to the 21-gene assay for predicting recurrence risk in ER+/HER2- breast cancer. The intratumoral heterogeneity score demonstrated potential as a noninvasive, intuitive, and quantitative biomarker for characterizing intratumoral heterogeneity and predicting recurrence score.