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Updated: Jun 26, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Image Quality Assessment of Diffusion-Weighted Imaging (DWI) and Its Impact on Apparent Diffusion Coefficient (ADC)
Wen Li1, Lisa J Wilmes1, Julia Carmona-Bozo1
1Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94158, USA.
Background/Objectives:
Apparent diffusion coefficient (ADC) calculated from diffusion-weighted MRI (DWI) can predict tumor response to neoadjuvant chemotherapy for breast cancer. However, obtaining consistently adequate image quality in breast DWI can be challenging, and the effect of image quality on ADC's predictive performance is unclear. The objective of this study was to evaluate inter-reader variability in image quality assessment and the effect of DWI image quality on the predictive performance of ADC.
Methods:
This multi-institutional study included 428 patients. Two readers assessed three DWI image quality factors-fat suppression, artifacts, and signal-to-noise ratio (SNR). Inter-reader agreement was estimated using Fleiss' Kappa. The percent change in tumor ADC from pretreatment (T0) to early treatment (T1) was used to predict pathologic complete response (pCR), assessed at surgery.
Results:
Out of 428 patients, 134 were excluded (missing pCR [n = 17]; missing/incorrect DWI [n = 23]; inability to define region-of-interest [ROI, n = 94]) and 294 were included in the analysis. Kappa coefficients were estimated as: 0.47 (95% confidence interval [CI]: 0.42, 0.52) for fat suppression, 0.54 (0.50, 0.59) for artifact, and 0.38 (0.32, 0.44) for SNR. The AUC of ADC calculated from DWI with adequate (high or medium at both time points) image quality was 0.61 (95% CI: 0.52, 0.702), while it was 0.68 (95% CI: 0.53, 0.83) from DWI with inadequate image quality at either T0 or T1. The p-value for the difference in AUCs was 0.45.
Conclusions:
The inter-reader agreement was moderate to fair across all three quality categories. When a manually delineated tumor ROI was possible, no statistically significant difference in ADC predictive performance was observed between the quality-adequate and quality-inadequate cohorts; still, both were predictive of pCR. Furthermore, no statistically significant differences were observed in inter-reader agreement or ADC predictive performance between 1.5T and 3T scanners. These findings are clinically relevant to the use of ADC as an imaging biomarker in real-world conditions.
