Quantitative MRI can accelerate drug development by providing non-invasive methods to determine treatment response. The primary aim of this study is to assess the change in normalized apparent diffusion coefficient values (ΔADCN), derived from diffusion-weighted MRI (DWI), as an alternative method to standard dynamic contrast-enhanced (DCE) MRI for assessing response of primary breast tumors to neoadjuvant chemotherapy. Secondary aims are to: assess the influence of image quality scoring on the predictive performance of ΔADCN; test correlations between ΔADCN and change in functional tumor volume (ΔFTV) at early (ΔFTV2) and late (ΔFTV4) time points; and assess ΔADCN of responders versus non-responders.
134 patients with primary breast cancers 2.5 cm in diameter and high MammaPrint scores were included. 62 and 72 patients received standard and experimental drug regimens respectively. ΔADCN was determined from DW images acquired at baseline and three weeks into chemotherapy. FTV (70% DCE-MRI enhancement at 2.5 minutes post-contrast) was used as an indication of tumor response throughout treatment. Pathologic complete response (pCR) was determined by histopathology following surgery. Whole tumor regions of interest (ROIs) and quality scoring was performed on 126 cases, of which 102 had passing quality scores.
The area under the receiver operating characteristic (ROC) curve (AUC) for ΔADCN was 0.653 (95% confidence interval (CI) [0.538, 0.768], p=0.00605). The estimated AUC for ΔFTV2 was not significantly higher than ΔADCN (mean difference: -0.011±0.086, p=0.896). Using a ΔFTV4 cutoff of -97.8% as a surrogate endpoint, the AUC estimates were not significantly greater than 0.5.
Image quality did not impact the predictive ability or distribution of ΔADCN, which increased by 0.836% (95% CI [-0.48, 0.026], p=0.34) with quality scoring. ΔADCN was not very correlated with ΔFTV2 or ΔFTV4. ΔADCN increased by 9.74% (95% CI [2.24, 17.51], p=0.012) with response in the full cohort.
These findings suggest that ΔADCN may be similar to ΔFTV2 in predictive performance. While changes in ADC and FTV both reflect changes in tissue properties, they are indicative of independent biological processes. DWI is a promising non-contrast technique that can provide additional information to better predict treatment response.