Frank F J Simonis1, Alessandro Sbrizzi2, Ellis Beld3, Jan J W Lagendijk3, Cornelis A T van den Berg3. 1. Department of Radiotherapy, Imaging Division, University Medical Center Utrecht, Utrecht, the Netherlands. F.F.J.Simonis@umcutrecht.nl. 2. Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands. 3. Department of Radiotherapy, Imaging Division, University Medical Center Utrecht, Utrecht, the Netherlands.
Abstract
PURPOSE: Dynamic contrast enhanced (DCE) imaging is a widely used technique in oncologic imaging. An essential prerequisite for obtaining quantitative values from DCE-MRI is the determination of the arterial input function (AIF). However, it is very challenging to accurately estimate the AIF using MR. A comprehensive model, which uses complex data instead of either magnitude or phase, was developed to improve AIF estimation. THEORY AND METHODS: The model was first applied to simulated data. Subsequently, the accuracy of the estimated contrast agent concentration was validated in a phantom. Finally the method was applied to existing DCE scans of 13 prostate cancer patients. RESULTS: The complex signal method combines the complementary strengths of the magnitude and phase method, increasing the precision and accuracy of concentration estimation in simulated and phantom data. The in vivo AIFs show a good agreement between arterial voxels (standard deviation in the peak and tail equal 0.4 mM and 0.12 mM, respectively). Furthermore, the dynamic behavior closely followed the AIF obtained with DCE-CT in the same patients (mean correlation coefficient: 0.92). CONCLUSION: By using the complex signal, the AIF estimation becomes more accurate and precise. This might enable patient specific AIFs, thereby improving the quantitative values obtained from DCE-MRI. Magn Reson Med 76:1236-1245, 2016.
PURPOSE: Dynamic contrast enhanced (DCE) imaging is a widely used technique in oncologic imaging. An essential prerequisite for obtaining quantitative values from DCE-MRI is the determination of the arterial input function (AIF). However, it is very challenging to accurately estimate the AIF using MR. A comprehensive model, which uses complex data instead of either magnitude or phase, was developed to improve AIF estimation. THEORY AND METHODS: The model was first applied to simulated data. Subsequently, the accuracy of the estimated contrast agent concentration was validated in a phantom. Finally the method was applied to existing DCE scans of 13 prostate cancerpatients. RESULTS: The complex signal method combines the complementary strengths of the magnitude and phase method, increasing the precision and accuracy of concentration estimation in simulated and phantom data. The in vivo AIFs show a good agreement between arterial voxels (standard deviation in the peak and tail equal 0.4 mM and 0.12 mM, respectively). Furthermore, the dynamic behavior closely followed the AIF obtained with DCE-CT in the same patients (mean correlation coefficient: 0.92). CONCLUSION: By using the complex signal, the AIF estimation becomes more accurate and precise. This might enable patient specific AIFs, thereby improving the quantitative values obtained from DCE-MRI. Magn Reson Med 76:1236-1245, 2016.
Authors: Yi Guo; Sajan Goud Lingala; Yannick Bliesener; R Marc Lebel; Yinghua Zhu; Krishna S Nayak Journal: Magn Reson Med Date: 2017-09-14 Impact factor: 4.668
Authors: Anneloes de Boer; Tim Leiner; Eva E Vink; Peter J Blankestijn; Cornelis A T van den Berg Journal: Magn Reson Med Date: 2017-11-13 Impact factor: 4.668
Authors: Edzo M E Klawer; Petra J van Houdt; Frank F J Simonis; Cornelis A T van den Berg; Floris J Pos; Stijn W T P J Heijmink; Sofie Isebaert; Karin Haustermans; Uulke A van der Heide Journal: Magn Reson Med Date: 2019-01-17 Impact factor: 4.668