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Poster

Simultaneous multimodal imaging of patients with bronchial carcinoma in a whole body MR/PET system

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons83809

Sauter A, Schmidt H, Schraml C, Bezrukov,  I
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Brendle, C., Sauter A, Schmidt H, Schraml C, Bezrukov, I., Martirosian P, Hetzel J, Müller M, Claussen CD, Schwenzer, N., & Pfannenberg, C. (2011). Simultaneous multimodal imaging of patients with bronchial carcinoma in a whole body MR/PET system. Poster presented at 28th Annual Scientific Meeting ESMRMB 2011, Leipzig, Germany.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-B9E2-F
Zusammenfassung
Purpose/Introduction: Lung cancer is among the most frequent cancers (1). Exact determination of tumour extent and viability is crucial for adequate therapy guidance. [18F]-FDG-PET allows accurate staging and the evaluation of therapy response based on glucose metabolism. Diffusion weighted MRI (DWI) is another promising tool for the evaluation of tumour viability (2,3). The aim of the study was the simultaneous PET-MR acquisition in lung cancer patients and correlation of PET and MR data. Subjects and Methods: Seven patients (age 38-73 years, mean 61 years) with highly suspected or known bronchial carcinoma were examined. First, a [18F]-FDG-PET/CT was performed (injected dose: 332-380 MBq). Subsequently, patients were examined at the whole-body MR/PET (Siemens Biograph mMR). The MRI is a modified 3T Verio whole body system with a magnet bore of 60 cm (max. amplitude gradients 45 mT/m, max. slew rate 200 T/m/s). Concerning the PET, the whole-body MR/PET system comprises 56 detector cassettes with a 59.4 cm transaxial and 25.8 cm axial FoV. The following parameters for PET acquisition were applied: 2 bed positions, 6 min/bed with an average uptake time of 124 min after injection (range: 110-143 min). The attenuation correction of PET data was conducted with a segmentation-based method provided by the manufacturer. Acquired PET data were reconstructed with an iterative 3D OSEM algorithm using 3 iterations and 21 subsets, Gaussian filter of 3 mm. DWI MR images were recorded simultaneously for each bed using two b-values (0/800 s/mm2). SUVmax and ADCmin were assessed in a ROI analysis. The following ratios were calculated: SUVmax(tumor)/SUVmean(liver) and ADCmin(tumor)/ADCmean(muscle). Correlation between SUV and ADC was analyzed (Pearson’s correlation). Results: Diagnostic scans could be obtained in all patients with good tumour delineation. The spatial matching of PET and DWI data was very exact. Most tumours showed a pronounced FDG-uptake in combination with decreased ADC values. Significant correlation was found between SUV and ADC ratios (r = -0.87, p = 0.0118). Discussion/Conclusion: Simultaneous MR/PET imaging of lung cancer is feasible. The whole-body MR/PET system can provide complementary information regarding tumour viability and cellularity which could facilitate a more profound tumour characterization. Further studies have to be done to evaluate the importance of these parameters for therapy decisions and monitoring