Department of Radiology, Peking University Cancer Hospital & Institute, Key Laboratory of Carcinogenesis and Translational Research, Beijing, China.
Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA.
Magn Reson Med. 2018 Mar;79(3):1399-1406. doi: 10.1002/mrm.26798. Epub 2017 Jun 22.
To demonstrate the clinical value of a non-Gaussian diffusion model using fractional order calculus (FROC) for early prediction of the response of gastrointestinal stromal tumor to second-line sunitinib targeted therapy.
Fifteen patients underwent sunitinib treatment after imatinib resistance. Diffusion-weighted imaging with multiple b-values was performed before treatment (baseline) and 2 weeks (for early prediction of response) after initiating sunitinib treatment. Conventional MRI images at 12 weeks were used to determine the good and poor responders according to the modified Choi criteria for MRI. Diffusion coefficient D, fractional order parameter β (which correlates to intravoxel tissue heterogeneity), and a microstructural quantity µ were calculated using the FROC model. The FROC parameters and the longest diameter of the lesion, as well as their changes after 2 weeks of treatment, were compared between the good and poor responders. Additionally, the pretreatment FROC parameters were individually combined with the change in D (ΔD) using a logistic regression model to evaluate response to sunitinib treatment with a receiver operating characteristic analysis.
Forty-two good-responding and 32 poor-responding lesions were identified. Significant differences were detected in pretreatment β (0.67 versus 0.74, P = 0.011) and ΔD (45.7% versus 12.4%, P = 0.001) between the two groups. The receiver operating characteristic analysis showed that ΔD had a significantly higher predictive power than the tumor size change (area under the curve: 0.725 versus 0.580; 0.95 confidence interval). When ΔD was combined with pretreatment β, the area under the curve improved to 0.843 with a predictive accuracy of 75.7% (56 of 74).
The non-Gaussian FROC diffusion model showed clinical value in early prediction of gastrointestinal stromal tumor response to second-line sunitinib targeted therapy. The pretreatment FROC parameter β can increase the predictive accuracy when combined with the change in diffusion coefficient during treatment. Magn Reson Med 79:1399-1406, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
利用分数阶微积分（FROC）展示一种非高斯扩散模型的临床价值，以便对胃肠道间质瘤（GIST）二线接受舒尼替尼靶向治疗的反应进行早期预测。
15 例患者在伊马替尼耐药后接受舒尼替尼治疗。在开始舒尼替尼治疗前（基线）和治疗后 2 周（用于早期预测反应）进行了多 b 值扩散加权成像。根据改良 Choi 标准 MRI 确定 12 周时的良、差反应者。使用 FROC 模型计算扩散系数 D、分数阶参数β（与体素内组织异质性相关）和微结构量µ。比较良、差反应者之间的 FROC 参数和病变最长径，以及治疗后 2 周的变化。此外，采用逻辑回归模型将预处理 FROC 参数与 D 的变化（ΔD）相结合，通过受试者工作特征（ROC）分析评估舒尼替尼治疗的反应。
确定了 42 个良反应和 32 个差反应病灶。两组之间的预处理β（0.67 与 0.74，P=0.011）和ΔD（45.7%与 12.4%，P=0.001）存在显著差异。ROC 分析显示，ΔD 的预测能力明显高于肿瘤大小的变化（曲线下面积：0.725 与 0.580；95%置信区间）。当将ΔD 与预处理β结合时，曲线下面积提高到 0.843，预测准确率为 75.7%（74 例中的 56 例）。
非高斯 FROC 扩散模型在胃肠道间质瘤二线接受舒尼替尼靶向治疗反应的早期预测中具有临床价值。预处理 FROC 参数β与治疗期间扩散系数的变化相结合时，可以提高预测准确性。磁共振医学 79：1399-1406，2018。© 2017 国际磁共振学会。
