David A Broadbent1,2,3, John D Biglands1,2,3, David P Ripley1,3, David M Higgins4, John P Greenwood1,3, Sven Plein1,3, David L Buckley1,3. 1. Division of Biomedical Imaging, University of Leeds, Leeds, United Kingdom. 2. Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom. 3. Multidisciplinary Cardiovascular Research Centre, University of Leeds, Leeds, United Kingdom. 4. Philips Healthcare, Guildford, United Kingdom.
Abstract
PURPOSE: To compare methods designed to minimize or correct signal nonlinearity in quantitative myocardial dynamic contrast-enhanced (DCE) MRI. METHODS: DCE-MRI studies were simulated and data acquired in eight volunteers. Signal nonlinearity was corrected using either a dual-bolus approach or model-based correction using proton-density weighted imaging (conventional or dual-sequence acquisition) or T1 data (native or bookend). Scanning of healthy and infarcted myocardium at 3 T was simulated, including noise, saturation imperfection and T1 measurement error. Data were analyzed using model-based deconvolution with a one-compartment (mono-exponential) model. RESULTS: Substantial variation between methods was demonstrated in volunteers. In simulations the dual-bolus method proved stable for realistic levels of saturation efficiency but demonstrated bias due to residual nonlinearity. Model-based methods performed ideally in the absence of confounding error sources and were generally robust to noise or saturation imperfection, except for native T1 based correction which was highly sensitive to the latter. All methods demonstrated large variation in accuracy above an over-saturation level where baseline signal was nulled. For the dual-sequence approach this caused substantial bias at the saturation efficiencies observed in volunteers. CONCLUSION: The choice of nonlinearity correction method in myocardial DCE-MRI impacts on accuracy and precision of estimated parameters, particularly in the presence of nonideal saturation.
PURPOSE: To compare methods designed to minimize or correct signal nonlinearity in quantitative myocardial dynamic contrast-enhanced (DCE) MRI. METHODS: DCE-MRI studies were simulated and data acquired in eight volunteers. Signal nonlinearity was corrected using either a dual-bolus approach or model-based correction using proton-density weighted imaging (conventional or dual-sequence acquisition) or T1 data (native or bookend). Scanning of healthy and infarcted myocardium at 3 T was simulated, including noise, saturation imperfection and T1 measurement error. Data were analyzed using model-based deconvolution with a one-compartment (mono-exponential) model. RESULTS: Substantial variation between methods was demonstrated in volunteers. In simulations the dual-bolus method proved stable for realistic levels of saturation efficiency but demonstrated bias due to residual nonlinearity. Model-based methods performed ideally in the absence of confounding error sources and were generally robust to noise or saturation imperfection, except for native T1 based correction which was highly sensitive to the latter. All methods demonstrated large variation in accuracy above an over-saturation level where baseline signal was nulled. For the dual-sequence approach this caused substantial bias at the saturation efficiencies observed in volunteers. CONCLUSION: The choice of nonlinearity correction method in myocardial DCE-MRI impacts on accuracy and precision of estimated parameters, particularly in the presence of nonideal saturation.
Authors: Gaurav S Gulsin; Joseph Henson; Emer M Brady; Jack A Sargeant; Emma G Wilmot; Lavanya Athithan; Zin Z Htike; Anna-Marie Marsh; John D Biglands; Peter Kellman; Kamlesh Khunti; David Webb; Melanie J Davies; Thomas Yates; Gerry P McCann Journal: Diabetes Care Date: 2020-07-17 Impact factor: 19.112
Authors: James R J Foley; Ananth Kidambi; John D Biglands; Neil Maredia; Catherine J Dickinson; Sven Plein; John P Greenwood Journal: J Cardiovasc Magn Reson Date: 2017-11-06 Impact factor: 5.364