Correlation Between Tumor Metabolism and Semiquantitative Perfusion MRI Metrics in Non-small Cell Lung Cancer

Publication date: Available online 2 March 2018
Source:International Journal of Radiation Oncology*Biology*Physics
Author(s): Sang Ho Lee, Andreas Rimner, Emily Gelb, Joseph O. Deasy, Margie A. Hunt, John L. Humm, Neelam Tyagi
PurposeTo correlate semiquantitative parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) and ¹⁸F-FDG-PET for non-small cell lung cancer (NSCLC).MethodsTwenty-four NSCLC patients who underwent pretreatment ¹⁸F-FDG-PET and DCE-MRI were analyzed. The maximum standardized uptake value (SUVmax) was measured from ¹⁸F-FDG-PET. DCE-MRI was obtained on 3T MRI scanner using four-dimensional T1-weighted high-resolution imaging with volume excitation sequence. 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 s, 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).ResultsIn UVA, mean(WOS) (ρ = -0.456, p = 0.025), mean(IAUCtthp) (ρ = -0.439, p = 0.032), median(IAUCtthp) (ρ = -0.543, p = 0.006), and MAD(IAUCtthp) (ρ = -0.557, p = 0.005) 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 R² = 0.298, p = 0.0006). A decrease in SD(WIS), MAD(TTHP), and MAD(IAUCtthp) and an increase in SD(TTP) were associated with a significant increase in SUVmax.ConclusionAssociation 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.

Teaser

Balance between vascularity and glucose metabolism in tumor could prove to be an important indicator of its biological status and resistance to treatment. This study evaluates the use of semiquantitative dynamic contrast-enhanced MRI parameters for predicting the ¹⁸F-FDG-PET maximum standardized uptake value in non-small cell lung cancer (NSCLC). It was found that intratumoral heterogeneity in wash-in contrast kinetics is associated with tumor metabolism. Investigating vascular-metabolic relationship will help in guiding personalized targeted therapy in NSCLC.


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