Hybrid [¹⁸F]-FDG PET/MRI including non-Gaussian diffusion-weighted imaging (DWI): preliminary results in non-small cell lung cancer (NSCLC)

Philipp Heusch, Jens Köhler, Hans-Joerg Wittsack, Till A Heusner, Christian Buchbender, Thorsten D Poeppel, Felix Nensa, Axel Wetter, Thomas Gauler, Verena Hartung, Rotem S Lanzman
European Journal of Radiology 2013, 82 (11): 2055-60

PURPOSE: To assess the feasibility of non-Gaussian DWI as part of a FDG-PET/MRI protocol in patients with histologically proven non-small cell lung cancer.

MATERIAL AND METHODS: 15 consecutive patients with histologically proven NSCLC (mean age 61 ± 11 years) were included in this study and underwent whole-body FDG-PET/MRI following whole-body FDG-PET/CT. As part of the whole-body FDG-PET/MRI protocol, an EPI-sequence with 5 b-values (0, 100, 500, 1000 and 2000 s/mm(2)) was acquired for DWI of the thorax during free-breathing. Volume of interest (VOI) measurements were performed to determine the maximum and mean standardized uptake value (SUV(max); SUV(mean)). A region of interest (ROI) was manually drawn around the tumor on b=0 images and then transferred to the corresponding parameter maps to assess ADC(mono), D(app) and K(app). To assess the goodness of the mathematical fit R(2) was calculated for monoexponential and non-Gaussian analysis. Spearman's correlation coefficients were calculated to compare SUV values and diffusion coefficients. A Student's t-test was performed to compare the monoexponential and non-Gaussian diffusion fitting (R(2)).

RESULTS: T staging was equal between FDG-PET/CT and FDG-PET/MRI in 12 of 15 patients. For NSCLC, mean ADC(mono) was 2.11 ± 1.24 × 10(-3) mm(2)/s, Dapp was 2.46 ± 1.29 × 10(-3) mm(2)/s and mean Kapp was 0.70 ± 0.21. The non-Gaussian diffusion analysis (R(2)=0.98) provided a significantly better mathematical fitting to the DWI signal decay than the monoexponetial analysis (R(2)=0.96) (p<0.001). SUV(max) and SUV(mean) of NSCLC was 13.5 ± 7.6 and 7.9 ± 4.3 for FDG-PET/MRI. ADC(mono) as well as Dapp exhibited a significant inverse correlation with the SUV(max) (ADC(mono): R=-0.67; p<0.01; Dapp: R=-0.69; p<0.01) as well as with SUV(mean) assessed by FDG-PET/MRI (ADC(mono): R=-0.66; p<0.01; Dapp: R=-0.69; p<0.01). Furthermore, Kapp exhibited a significant correlation with SUV(max) (R=0.72; p<0.05) and SUV(mean) as assessed by FDG-PET/MRI (R=0.71; p<0.005).

CONCLUSION: Simultaneous PET and non-Gaussian diffusion acquisitions are feasible. Non-Gaussian diffusion parameters show a good correlation with SUV and might provide additional information beyond monoexponential ADC, especially as non-Gaussian diffusion exhibits better mathematical fitting to the decay of the diffusion signal than monoexponential DWI.

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