Both dynamic contrast-enhanced (DCE) MRI and PET provide quantitative information on tumor biology in living organisms. However, imaging biomarkers often neglect tissue heterogeneity by focusing on distributional summary statistics. We analyzed the spatial relationship of α(v)β(3) expression, glucose metabolism, and perfusion by PET and DCE MRI, focusing on tumor heterogeneity.
Methods: Thirteen patients with primary or metastasized cancer (non-small cell lung cancer, n = 9; others, n = 4) were examined with DCE MRI and with PET using (18)F-galacto-RGD and (18)F-FDG. Twenty-three different regions of interest were defined by cluster analysis based on the heterogeneity of tracer uptake. In these regions, the initial area under the gadopentetate dimeglumine concentration-time curve (IAUGC), as well as the regional blood volume (rBV) and regional blood flow (rBF), were estimated from DCE MRI and correlated with standardized uptake values from PET.
Results: Regions with simultaneously high uptake of (18)F-galacto-RGD and (18)F-FDG showed higher functional MRI data (IAUGC, 0.35 ± 0.04 mM·s; rBF, 70.2 ± 12.7 mL/min/100 g; rBV, 23.3 ± 2.7 mL/100 g) than did areas with low uptake of both tracers (IAUGC, 0.15 ± 0.04 mM·s [P < 0.01]; rBF, 28.3 ± 10.8 mL/min/100 g; rBV, 9.9 ± 1.9 mL/100 g [P < 0.01]). There was a weak to moderate correlation between the functional MRI parameters and (18)F-galacto-RGD (r = 0.30-0.62) and also (18)F-FDG (r = 0.44-0.52); these correlations were significant (P < 0.05), except for (18)F-galacto-RGD versus rBF (P = 0.17).
Conclusion: These data show that multiparametric assessment of tumor heterogeneity is feasible by combining PET and MRI. Perfusion is highest in tumor areas with simultaneously high α(v)β(3) expression and high glucose metabolism and restricted in areas with both low α(v)β(3) expression and low glucose metabolism. The current limitations resulting from imaging with separate scanners might be overcome by future hybrid PET/MRI scanners.