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  • Combined PET imaging and di...
    Wetter, Axel; Nensa, Felix; Schenck, Marcus; Heusch, Philipp; Pöppel, Thorsten; Bockisch, Andreas; Forsting, Michael; Schlosser, Thomas W; Lauenstein, Thomas C; Nagarajah, James

    PloS one, 07/2014, Volume: 9, Issue: 7
    Journal Article

    To characterize intermediate and high-risk prostate carcinomas with measurements of standardized uptake values (SUVs) and apparent diffusion coefficient (ADC) values by means of simultaneous 18F choline PET/MRI. 35 patients with primary prostate cancer underwent simultaneous 18F choline PET/MRI. From these, 21 patients with an intermediate and high risk constellation who were not under ongoing hormonal therapy were included. Altogether 32 tumor lesions with a focal uptake of 18F choline could be identified. Average ADC values (ADCaver) minimum ADC values (ADCmin) as well as maximum and mean SUVs (SUVmax, SUVmean) of tumor lesions were assessed with volume-of-interest (VOI) and Region-of-interest (ROI) measurements. As a reference, also ADCaver, ADCmin and SUVmax and SUVmean of non-tumorous prostate tissue were measured. Statistical analysis comprised calculation of descriptive parameters and calculation of Pearson's product moment correlations between ADC values and SUVs of tumor lesions. Mean ADCaver and ADCmin of tumor lesions were 0.94±0.22×10(-3) mm2/s and 0.65±0.21×10(-3) mm2/s, respectively. Mean SUVmax and SUVmean of tumor lesions were 6.3±2.3 and 2.6±0.8, respectively. These values were in each case significantly different from the reference values (p<0.001). There was no significant correlation between the measured SUVs and ADC values (SUVmax vs. ADCaver: R = -0.24, p = 0.179; SUVmax vs. ADCmin: R = -0.03, p = 0.877; SUVmean vs. ADCaver: R = -0.27, p = 0.136; SUVmean vs. ADCmin: R = -0.08, p = 0.679). Both SUVs and ADC values differ significantly between tumor lesions and healthy tissue. However, there is no significant correlation between these two parameters. This might be explained by the fact that SUVs and ADC values characterize different parts of tumor biology.