Department of Medical Physics, New York, New York.
Department of Radiation Oncology Memorial Sloan-Kettering Cancer Center, New York, New York.
Int J Radiat Oncol Biol Phys. 2018 Nov 15;102(4):718-726. doi: 10.1016/j.ijrobp.2018.02.031. Epub 2018 Mar 2.
To correlate semiquantitative parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and F-fluorodeoxyglucose positron emission tomography (F-FDG-PET) for non-small cell lung cancer (NSCLC).
Twenty-four NSCLC patients who underwent pretreatment F-FDG-PET and DCE-MRI were analyzed. The maximum standardized uptake value (SUVmax) was measured from 18F-FDG-PET. Dynamic contrast-enhanced MRI was obtained on a 3T MRI scanner using 4-dimensional T1-weighted high-resolution imaging with a volume excitation sequence. The DCE-MRI parameters, consisting of mean, median, standard deviation (SD), and median absolute deviation (MAD) of peak enhancement, time to peak (TTP), time to half peak (TTHP), wash-in slope (WIS), wash-out slope (WOS), initial gradient, wash-out gradient, signal enhancement ratio, and initial area under the relative signal enhancement curve taken up to 30, 60, 90, 120, 150, and 180 seconds, TTP, and TTHP (IAUCtthp), were calculated for each lesion. Univariate analysis (UVA) was performed using Spearman correlation. A linear regression model to predict SUVmax from DCE-MRI parameters was developed by multivariate analysis (MVA) using least absolute shrinkage selection operator in combination with leave-one-out cross-validation (LOOCV).
In UVA, mean(WOS) (ρ = -0.456, P = .025), mean(IAUCtthp) (ρ = -0.439, P = .032), median(IAUCtthp) (ρ = -0.543, P = .006), and MAD(IAUCtthp) (ρ = -0.557, P = .005) were statistically significant; all these parameters were negatively correlated with SUVmax. In MVA, a linear combination of SD(WIS), SD(TTP), MAD(TTHP), and MAD(IAUCtthp) was statistically significant for predicting SUVmax (LOOCV-based adjusted R = 0.298, P = .0006). A decrease in SD(WIS), MAD(TTHP), and MAD(IAUCtthp) and an increase in SD(TTP) were associated with a significant increase in SUVmax.
An association was found between SUVmax, the SD, and MAD of DCE-MRI metrics derived during contrast uptake in NSCLC, reflecting that intratumoral heterogeneity in wash-in contrast kinetics is associated with tumor metabolism. Although MAD(IAUCtthp) was a significant feature in both UVA and MVA, the LASSO-based multivariate regression model yielded better predictability of SUVmax than a univariate regression model using MAD(IAUCtthp). This study will facilitate understanding of the complex relationship between tumor vascularization and metabolism and eventually help in guiding targeted therapy.
探讨动态对比增强磁共振成像（DCE-MRI）和 F-氟代脱氧葡萄糖正电子发射断层扫描（F-FDG-PET）的半定量参数在非小细胞肺癌（NSCLC）中的相关性。
对 24 例接受 F-FDG-PET 及 DCE-MRI 术前检查的 NSCLC 患者进行分析。从 18F-FDG-PET 中测量最大标准化摄取值（SUVmax）。在 3T MRI 扫描仪上使用四维 T1 加权高分辨率成像和容积激发序列获得动态对比增强 MRI。DCE-MRI 参数包括：峰值增强的均值、中位数、标准差（SD）和中位数绝对偏差（MAD）、达峰时间（TTP）、半峰时间（TTHP）、上升斜率（WIS）、下降斜率（WOS）、初始梯度、洗脱梯度、信号增强比以及 30、60、90、120、150 和 180 秒时的相对信号增强曲线下面积的初始值，TTP 和 TTHP（IAUCtthp）。使用 Spearman 相关性进行单变量分析（UVA）。使用最小绝对值收缩和选择算子结合留一法交叉验证（LOOCV）的多元分析（MVA）建立从 DCE-MRI 参数预测 SUVmax 的线性回归模型。
UVA 中，均值（WOS）（ρ=-0.456，P=0.025）、均值（IAUCtthp）（ρ=-0.439，P=0.032）、中位数（IAUCtthp）（ρ=-0.543，P=0.006）和 MAD（IAUCtthp）（ρ=-0.557，P=0.005）有统计学意义；所有这些参数均与 SUVmax 呈负相关。MVA 中，SD（WIS）、SD（TTP）、MAD（TTHP）和 MAD（IAUCtthp）的线性组合对 SUVmax 的预测具有统计学意义（基于 LOOCV 的调整 R2=0.298，P=0.0006）。SD（WIS）、MAD（TTHP）和 MAD（IAUCtthp）的降低和 SD（TTP）的增加与 SUVmax 的显著增加相关。
在 NSCLC 中，SUVmax 与 DCE-MRI 摄取期间的 SD 和 MAD 之间存在相关性，这反映了肿瘤内对比动力学的异质性与肿瘤代谢有关。尽管 MAD（IAUCtthp）在 UVA 和 MVA 中均为显著特征，但基于 LASSO 的多元回归模型对 SUVmax 的预测能力优于使用 MAD（IAUCtthp）的单变量回归模型。本研究将有助于理解肿瘤血管生成和代谢之间的复杂关系，并最终有助于指导靶向治疗。
