Lauren K. Fang

Background: To date, the accuracy and variability of diffusion‐weighted MRI (DW‐MRI) metrics have been reported in a limited number of scanner/protocol/coil combinations.Purpose: To evaluate the reproducibility of DW‐MRI estimates across multiple scanners and DW‐MRI protocols and to assess the effects of using an 8‐channel vs. 16‐channel breast coil in a breast phantom.Study Type: Prospective.Phantom: Breast phantom containing tubes of water and differing polyvinylpyrrolidone (PVP) concentrations with apparent diffusion coefficients (ADCs) matching breast tissue.Field Strength/Sequence: 3 T (three standard and one wide bore), three DW‐MRI single‐shot echo planar imaging protocols of varying acquired spatial resolution.Assessment: Accuracy of estimated ADCs was assessed using percent differences (PD) relative to nuclear magnetic resonance spectroscopy‐derived reference values. Coefficients of variation (CV) were calculated to determine variation across scanners. CVs based on the median standard deviation (CV_M) were used to evaluate tube‐specific dispersion using 8‐ or 16‐channel coils at a single scanner. ADCs of PVP‐containing tubes were additionally normalized by the median water tube ADC to account for temperature effects.Statistical Tests: Two‐way repeated measures analysis of variance and post hoc tests were used to evaluate differences in ADC, CV, and CV_M across scanners and protocols (α = 0.05).Results: ADCs were within 11% (interquartile range [IQR] 7%) of reference values and significantly improved to 2% (IQR 7%) after normalization to an internal water reference. Normalization significantly reduced interscanner variability of ADC estimates from 7% to 4%. DW‐MRI protocol did not affect ADC accuracy; however, the clinical and higher‐resolution clinical protocols resulted in the greatest (9%) and least (6%) interscanner variability, respectively. The 8‐ and 16‐channel receive coils yielded similar accuracy (PD: 12% vs. 16%) and precision (CV_M: 2.7% vs. 2.9%).Data Conclusion: Normalization by an internal reference improved interscanner ADC reproducibility. High‐resolution protocols yielded comparably accurate and significantly less variable ADCs compared to a clinical standard protocol.Evidence Level: 2Technical Efficacy: Stage 1

Diffusion-weighted MRI (DW-MRI) offers a potential adjunct to dynamic contrast-enhanced MRI to discriminate benign from malignant breast lesions by yielding quantitative information about tissue microstructure. Multi-component modeling of the DW-MRI signal over an extended b-value range (up to 3000 s/mm²) theoretically isolates the slowly diffusing (restricted) water component in tissues. Previously, a three-component restriction spectrum imaging (RSI) model demonstrated the ability to distinguish malignant lesions from healthy breast tissue. We further evaluated the utility of this three-component model to differentiate malignant from benign lesions and healthy tissue in 12 patients with known malignancy and synchronous pathology-proven benign lesions. The signal contributions from three distinct diffusion compartments were measured to generate parametric maps corresponding to diffusivity on a voxel-wise basis. The three-component model discriminated malignant from benign and healthy tissue, particularly using the restricted diffusion C₁ compartment and product of the restricted and intermediate diffusion compartments (C₁ and C₂). However, benign lesions and healthy tissue did not significantly differ in diffusion characteristics. Quantitative discrimination of these three tissue types (malignant, benign, and healthy) in non-pre-defined lesions may enhance the clinical utility of DW-MRI in reducing excessive biopsies and aiding in surveillance and surgical evaluation without repeated exposure to gadolinium contrast.

Purpose: Restriction spectrum imaging (RSI) decomposes the diffusion‐weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ‐specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues.Methods: The diffusion‐weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative‐fitting residuals and Bayesian information criterion were assessed. Contrast‐to‐noise ratio between cancer and fibroglandular tissue in RSI‐derived signal contribution maps was compared to DCE imaging.Results: A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3‐component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D_1,3 = 0, D_2,3 = 1.5 × 10⁻³, and D_3,3 = 10.8 × 10⁻³ mm²/s. The RSI‐derived signal contributions of the slower diffusion components were larger in tumors than in fibroglandular tissues. Further, the contrast‐to‐noise and specificity at 80% sensitivity of DCE and a subset of RSI‐derived maps were equivalent.Conclusion: Breast diffusion‐weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues.