Characterization of the diffusion signal of breast tissues using multi-exponential models.

Restriction spectrum imaging (RSI) decomposes the diffusion-weighted (DW) MRI signal into separate diffusion 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. The DW-MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxel in cancer and control regions of interest (ROIs). Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative fitting residual and Bayesian information criterion (BIC) were assessed. Contrast-to-noise ratio (CNR) between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to dynamic contrast enhanced (DCE) imaging. A total of 74 women with breast cancer were scanned at 3.0T MRI. The fitting residuals of conventional ADC and BIC suggest that a three-component model improves the characterization of the diffusion signal over a bi-exponential model. Estimated ADCs of tri-exponential model were D1,3=0, D2,3=1.5×10−3 and D3,3=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 CNR and specificity at 80% sensitivity of DCE and a subset of RSI-derived maps were equivalent. Breast DW-MRI signal was best described using a tri-exponential 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.

限制频谱成像（RSI）将扩散加权（DW）磁共振成像信号分解为已知表观扩散系数（ADC）的独立扩散成分。RSI的扩散成分数量和最佳ADC因器官而异，并通过经验确定。本研究的目的是确定乳腺组织的RSI模型。 DW - MRI信号采用多个指数成分的线性组合来描述。估计了一组ADC值，以拟合癌症和对照感兴趣区域（ROI）中的体素。随后，使用这些固定的ADC值估计每个扩散成分的信号贡献。评估了相对拟合残差和贝叶斯信息准则（BIC）。将RSI衍生信号贡献图中癌症与纤维腺体组织之间的对比噪声比（CNR）与动态对比增强（DCE）成像进行了比较。 共有74名乳腺癌女性在3.0T磁共振成像仪上进行了扫描。常规ADC的拟合残差和BIC表明，三成分模型比双指数模型更能改善扩散信号的特征描述。三指数模型估计的ADC值为D1,3 = 0，D2,3 = 1.5×10⁻³和D3,3 = 10.8×10⁻³ mm²/s。在肿瘤中，较慢扩散成分的RSI衍生信号贡献比在纤维腺体组织中更大。此外，DCE和一部分RSI衍生图在80%灵敏度下的CNR和特异性相当。 乳腺DW - MRI信号用三指数模型描述最佳。乳腺RSI模型中肿瘤的显著程度与不使用外源性造影剂的DCE相当。这些数据可作为健康和恶性乳腺组织之间的鉴别特征。