Related Experiment Videos
Application of MR Cytometry in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer:
Jie Ding1, Diwei Shi2,3, Shiyun Sun4,5
1Medical Imaging Center, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, China.
Journal of Magnetic Resonance Imaging : JMRI
|August 11, 2026
Summary
MR cytometry models accurately predict pathological complete response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). Combining MR cytometry parameters with time-dependent apparent diffusion coefficients (ADCs) further enhances prediction accuracy for NAC outcomes.
Area of Science:
- Biomedical Imaging
- Radiology
- Oncology
Background:
- MR cytometry imaging characterizes in vivo microstructures.
- Its clinical utility in predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer is not well-established.
Purpose of the Study:
- To implement MR cytometry for predicting pCR in breast cancer.
- To compare the performance of different quantitative MR cytometry models (IMPULSED, JOINT, and EXCHANGE).
Main Methods:
- Prospective study involving 209 female patients across two centers.
- Utilized 3T MRI with pulsed and oscillating gradient spin-echo diffusion-weighted imaging (DWI).
- Calculated time-dependent apparent diffusion coefficients (ADCs) and MR cytometry parameters before and after NAC.
Main Results:
- Changes in intracellular volume fraction, cellularity, and water exchange rate constant significantly differed between pCR and non-pCR groups.
- JOINT and EXCHANGE models showed higher predictive performance (AUCs up to 0.864) compared to IMPULSED (AUC up to 0.716).
- Combined models (e.g., JOINT-ADC) improved prediction accuracy (AUCs up to 0.868).
Conclusions:
- MR cytometry models, particularly JOINT and EXCHANGE incorporating transcytolemmal water exchange, effectively predict pCR after NAC for breast cancer.
- Combining MR cytometry parameters with time-dependent ADCs enhances predictive performance.