Nicole Wake1, Hersh Chandarana2, Henry Rusinek3, Koji Fujimoto4, Linda Moy3, Daniel K Sodickson2, Sungheon Gene Kim2. 1. Center for Advanced Imaging Innovation and Research (CAI2R), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, United States; Sackler Institute of Graduate Biomedical Sciences, NYU School of Medicine, New York, NY, United States. Electronic address: nicole.wake@nyumc.org. 2. Center for Advanced Imaging Innovation and Research (CAI2R), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, United States; Sackler Institute of Graduate Biomedical Sciences, NYU School of Medicine, New York, NY, United States. 3. Center for Advanced Imaging Innovation and Research (CAI2R), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, United States. 4. Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University, Kyoto, Japan.
Abstract
INTRODUCTION: Pharmacokinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) data are sensitive to acquisition and post-processing techniques, which makes it difficult to compare results obtained using different methods. In particular, one of the most important factors affecting estimation of model parameters is how to convert MRI signal intensities to contrast agent concentration. The purpose of our study was to quantitatively compare a linear signal-to-concentration conversion (LC) as an approximation and a non-linear conversion (NLC) based on the MRI signal equation, in terms of the accuracy and precision of the pharmacokinetic parameters in T1-weighted DCE-MRI. MATERIALS AND METHODS: Numerical simulation studies were conducted to compare LC and NLC in terms of the accuracy and precision in contrast kinetic parameter estimation, and to evaluate their dependency on flip angle (FA), pre-contrast T1 (T10) and arterial input function (AIF). In addition, the effect of the conversion method on the diagnostic accuracy was evaluated with 36 breast lesions (19 benign and 17 malignant). RESULTS: The transfer rate (Ktrans) estimated using LC and measured AIF (mAIF) were up to 38% higher than the true Ktrans values, while the LC Ktrans estimates with the presumed AIF (pAIF) were up to 7% lower than the true Ktrans values, when FA = 45°. When using a small FA, such as 12°, the LC Ktrans with pAIF had least sensitivity to the error in T10 compared to the Ktrans estimated using LC with mAIF, and NLC with pAIF or mAIF. The breast DCE-MRI study showed that both LC and NLC Ktrans were significantly different (p < 0.05) between the malignant and benign lesions. The effect size between benign and malignant values as measured by Cohen's d was 1.06 for LC Ktrans and 1.02 for NLC Ktrans. CONCLUSION: The present study results show that, when precontrast T1 measurement is not available and a low FA is used for DCE-MRI, the uncertainty in the contrast kinetic parameter estimation can be reduced by using the LC method with pAIF, without compromising the diagnostic accuracy.
INTRODUCTION: Pharmacokinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) data are sensitive to acquisition and post-processing techniques, which makes it difficult to compare results obtained using different methods. In particular, one of the most important factors affecting estimation of model parameters is how to convert MRI signal intensities to contrast agent concentration. The purpose of our study was to quantitatively compare a linear signal-to-concentration conversion (LC) as an approximation and a non-linear conversion (NLC) based on the MRI signal equation, in terms of the accuracy and precision of the pharmacokinetic parameters in T1-weighted DCE-MRI. MATERIALS AND METHODS: Numerical simulation studies were conducted to compare LC and NLC in terms of the accuracy and precision in contrast kinetic parameter estimation, and to evaluate their dependency on flip angle (FA), pre-contrast T1 (T10) and arterial input function (AIF). In addition, the effect of the conversion method on the diagnostic accuracy was evaluated with 36 breast lesions (19 benign and 17 malignant). RESULTS: The transfer rate (Ktrans) estimated using LC and measured AIF (mAIF) were up to 38% higher than the true Ktrans values, while the LC Ktrans estimates with the presumed AIF (pAIF) were up to 7% lower than the true Ktrans values, when FA = 45°. When using a small FA, such as 12°, the LC Ktrans with pAIF had least sensitivity to the error in T10 compared to the Ktrans estimated using LC with mAIF, and NLC with pAIF or mAIF. The breast DCE-MRI study showed that both LC and NLC Ktrans were significantly different (p < 0.05) between the malignant and benign lesions. The effect size between benign and malignant values as measured by Cohen's d was 1.06 for LC Ktrans and 1.02 for NLC Ktrans. CONCLUSION: The present study results show that, when precontrast T1 measurement is not available and a low FA is used for DCE-MRI, the uncertainty in the contrast kinetic parameter estimation can be reduced by using the LC method with pAIF, without compromising the diagnostic accuracy.
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