Xu Junzhong, Li Ke, Smith R Adam, Waterton John C, Zhao Ping, Ding Zhaohua, Does Mark D, Manning H Charles, Gore John C
Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN 37232, USA.
Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA.
Magn Reson Imaging. 2017 Apr;37:195-202. doi: 10.1016/j.mri.2016.12.002. Epub 2016 Dec 3.
Diffusion-weighted MRI (DWI) signal attenuation is often not mono-exponential (i.e. non-Gaussian diffusion) with stronger diffusion weighting. Several non-Gaussian diffusion models have been developed and may provide new information or higher sensitivity compared with the conventional apparent diffusion coefficient (ADC) method. However the relative merits of these models to detect tumor therapeutic response is not fully clear.
Conventional ADC, and three widely-used non-Gaussian models, (bi-exponential, stretched exponential, and statistical model), were implemented and compared for assessing SW620 human colon cancer xenografts responding to barasertib, an agent known to induce apoptosis via polyploidy. Bayesian Information Criterion (BIC) was used for model selection among all three non-Gaussian models.
All of tumor volume, histology, conventional ADC, and three non-Gaussian DWI models could show significant differences between control and treatment groups after four days of treatment. However, only the non-Gaussian models detected significant changes after two days of treatment. For any treatment or control group, over 65.7% of tumor voxels indicate the bi-exponential model is strongly or very strongly preferred.
Non-Gaussian DWI model-derived biomarkers are capable of detecting tumor earlier chemotherapeutic response of tumors compared with conventional ADC and tumor volume. The bi-exponential model provides better fitting compared with statistical and stretched exponential models for the tumor and treatment models used in the current work.
在扩散加权磁共振成像（DWI）中，随着扩散加权增强，信号衰减通常并非单指数形式（即非高斯扩散）。已经开发了几种非高斯扩散模型，与传统的表观扩散系数（ADC）方法相比，这些模型可能会提供新的信息或更高的灵敏度。然而，这些模型在检测肿瘤治疗反应方面的相对优势尚不完全清楚。
实施并比较了传统的ADC以及三种广泛使用的非高斯模型（双指数模型、拉伸指数模型和统计模型），以评估SW620人结肠癌异种移植瘤对巴瑞替尼的反应，巴瑞替尼是一种已知可通过多倍体诱导细胞凋亡的药物。贝叶斯信息准则（BIC）用于在所有三种非高斯模型中进行模型选择。
治疗四天后，肿瘤体积、组织学、传统ADC以及三种非高斯DWI模型在对照组和治疗组之间均显示出显著差异。然而，只有非高斯模型在治疗两天后检测到显著变化。对于任何治疗组或对照组，超过65.7%的肿瘤体素表明双指数模型是强烈或非常强烈优选的。
与传统的ADC和肿瘤体积相比，非高斯DWI模型衍生的生物标志物能够更早地检测到肿瘤的化疗反应。对于当前工作中使用的肿瘤和治疗模型，双指数模型比统计模型和拉伸指数模型提供了更好的拟合。
