Objectives: The purpose of this study was to determine whether multiparametric magnetic resonance imaging (MRI) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DWI), obtained before and after the first cycle of neoadjuvant chemotherapy (NAC), is superior to single-parameter measurements for predicting pathologic complete response (pCR) in patients with breast cancer.
Materials and Methods: Patients with stage II/III breast cancer were enrolled in an institutional review board–approved study in which 3-T DCE-MRI and DWI data were acquired before (n = 42) and after 1 cycle (n = 36) of NAC. Estimates of the volume transfer rate (Ktrans), extravascular extracellular volume fraction (ve), blood plasma volume fraction (vp), and the efflux rate constant (kep = Ktrans/ve) were generated from the DCE-MRI data using the Extended Tofts-Kety model. The apparent diffusion coefficient (ADC) was estimated from the DWI data. The derived parameter kep/ADC was compared with single-parameter measurements for its ability to predict pCR after the first cycle of NAC.
Results: The kep/ADC after the first cycle of NAC discriminated patients who went on to achieve a pCR (P < 0.001) and achieved a sensitivity, specificity, positive predictive value, and area under the receiver operator curve (AUC) of 0.92, 0.78, 0.69, and 0.88, respectively. These values were superior to the single parameters kep (AUC, 0.76) and ADC (AUC, 0.82). The AUCs between kep/ADC and kep were significantly different on the basis of the bootstrapped 95% confidence intervals (0.018–0.23), whereas the AUCs between kep/ADC and ADC trended toward significance (−0.11 to 0.24).
Conclusions: The multiparametric analysis of DCE-MRI and DWI was superior to the single-parameter measurements for predicting pCR after the first cycle of NAC.
From the *Institute of Imaging Science, †Department of Radiology and Radiological Sciences, ‡the Vanderbilt-Ingram Cancer Center, Departments of §Biostatistics, ∥Radiation Oncology, ¶Medical Oncology, #Surgical Oncology, **Pathology, ††Physics and Astronomy, ‡‡Cancer Biology, and §§Biomedical Engineering, Vanderbilt University, Nashville, TN.
Received for publication April 15, 2014; and accepted for publication, after revision, August 14, 2014.
Conflicts of interest and sources of funding: Supported by the National Institutes of Health through NCI R01CA138599, NCI 1U01CA142565, NCI 1U01CA174706, NCI 1P50 098131, NCI P30 CA068485, and NCRR/NIH UL1 RR024975-01 (Vanderbilt CTSA grant) as well as the Kleberg Foundation (support for the imaging program at our institution) and the AUR-GE Radiology Research Academic Fellowship.
The authors report no conflicts of interest.
Reprints: Thomas E. Yankeelov, PhD, Institute of Imaging Science, Vanderbilt University, AA-1105 Medical Center North, 1161 21st Ave S, Nashville, TN 37232–2310. E-mail: email@example.com.