Ahmed E Othman1, Florian Falkner2, David-Emanuel Kessler2, Petros Martirosian2, Jakob Weiss2, Stephan Kruck3, Sascha Kaufmann2, Robert Grimm4, Ulrich Kramer2, Konstantin Nikolaou2, Mike Notohamiprodjo2. 1. Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, University Hospital Tuebingen, 72076 Tuebingen, Germany. Electronic address: ahmed.e.othman@googlemail.com. 2. Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, University Hospital Tuebingen, 72076 Tuebingen, Germany. 3. Department of Urology, Eberhard Karls University Tuebingen, University Hospital Tuebingen, 72076, Tuebingen, Germany. 4. Siemens Healthcare GmbH, Erlangen, Germany.
Abstract
PURPOSE: To assess the effect of different population-averaged arterial-input-functions (pAIF) on pharmacokinetic parameters from dynamic contrast-enhanced MRI (DCE-MRI) and their diagnostic accuracy regarding the detection of potentially malignant prostate lesions. MATERIALS AND METHODS: 66 male patients (age 65.4±10.8y) with suspected prostate cancer underwent multiparametric MRI of the prostate including T2-w, DWI-w and DCE-MRI sequences at a 3T MRI scanner. All detected lesions were categorized based on ACR PI-RADS version 2 and divided into 2 groups (A: PI-RADS ≤3, n=32; B: PI-RADS >3, n=34). In each DCE-MRI dataset, pharmacokinetic parameters (Ktrans, Kep and ve) and goodness of fit (chi(2)) were generated using the Tofts model with 3 different pAIFs (fast, intermediate, slow) as provided by a commercially available postprocessing software. Pharmacokinetic parameters, their diagnostic accuracies and model fits were compared for the 3 pAIFs. RESULTS: Ktrans, Kep and ve differed significantly among the 3 pAIFs (all p<.001). Ktrans and Kep were significantly higher in group B compared to group A (all p<.001). For chi(2), lowest results (representing highest goodness of fit) were found for intermediate pAIF (chi(2) 0.073). ROC analyses revealed comparable diagnostic accuracies for the different pAIFs, which were high for Ktrans and Kep and low for ve. CONCLUSION: Choosing various pAIF types causes a high variability in pharmacokinetic parameter estimates. Therefore, it is of great importance to consider this as potential artifact and thus keep AIF type selection constant in DCE-MRI studies.
PURPOSE: To assess the effect of different population-averaged arterial-input-functions (pAIF) on pharmacokinetic parameters from dynamic contrast-enhanced MRI (DCE-MRI) and their diagnostic accuracy regarding the detection of potentially malignant prostate lesions. MATERIALS AND METHODS: 66 male patients (age 65.4±10.8y) with suspected prostate cancer underwent multiparametric MRI of the prostate including T2-w, DWI-w and DCE-MRI sequences at a 3T MRI scanner. All detected lesions were categorized based on ACR PI-RADS version 2 and divided into 2 groups (A: PI-RADS ≤3, n=32; B: PI-RADS >3, n=34). In each DCE-MRI dataset, pharmacokinetic parameters (Ktrans, Kep and ve) and goodness of fit (chi(2)) were generated using the Tofts model with 3 different pAIFs (fast, intermediate, slow) as provided by a commercially available postprocessing software. Pharmacokinetic parameters, their diagnostic accuracies and model fits were compared for the 3 pAIFs. RESULTS: Ktrans, Kep and ve differed significantly among the 3 pAIFs (all p<.001). Ktrans and Kep were significantly higher in group B compared to group A (all p<.001). For chi(2), lowest results (representing highest goodness of fit) were found for intermediate pAIF (chi(2) 0.073). ROC analyses revealed comparable diagnostic accuracies for the different pAIFs, which were high for Ktrans and Kep and low for ve. CONCLUSION: Choosing various pAIF types causes a high variability in pharmacokinetic parameter estimates. Therefore, it is of great importance to consider this as potential artifact and thus keep AIF type selection constant in DCE-MRI studies.
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