First evaluation of the performance of MR cytometry incorporating transcytolemmal water exchange in predicting immunohistochemical factor status and molecular subtypes of breast cancer. We prospectively enrolled 90 breast cancer patients in the study. For each participant, pulsed gradient spin-echo (PGSE) with diffusion time of 70 ms and oscillating gradient spin-echo (OGSE) diffusion-weighted imaging of 25 Hz and 50 Hz were performed on a 3T MRI scanner. Time-dependent apparent diffusion coefficients (ADC) and microstructural parameters including cell diameter d , intracellular volume fraction vin , water exchange rate constant kin , and apparent extracellular diffusivity Dex were calculated. Single- and multi-variable logistic regression analyses were performed to evaluate their performance in identifying immunohistochemistry (IHC) factor status and molecular subtypes. The area under the receiver operating characteristic curve (AUC) was computed. The multi-variable regression models generated from MR cytometry-derived metrics provided higher AUC compared to those from time-dependent ADC metrics, i.e. 0.744 vs. 0.645 for estrogen receptor (ER), 0.727 vs. 0.688 for progesterone receptor (PR), 0.734 vs.0.623 for HER2, and 0.679 vs. 0.633 for Ki67, 0.751 vs. 0.644 for Triple-Negative Breast Cancer (TNBC), 0.819 vs. 0.765 for HER2-enriched, 0.730 vs. 0.659 for Luminal A, 0.633 vs. 0.633 for Luminal B. MR cytometry with transcytolemmal water exchange (JOINT and EXCHANGE) outperformed the original one with the impermeable model (IMPULSED) in predicting PR (0.727 vs. 0.705), HER2 (0.734 vs. 0.689), Ki67 (0.679 vs. 0.646), TNBC (0.751 vs. 0.748) and HER2-enriched (0.819 vs. 0.739), Luminal A (0.730 vs. 0.666), Luminal B (0.633 vs. 0.630). MR cytometry outperformed conventional ADC measurements in clinical breast cancer subtyping. Incorporating transcytolemmal water exchange further enhanced classification accuracy.
Wu et al. (Wed,) studied this question.