Vishal Patil1, Glyn Johnson. 1. Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, 660 First Avenue, New York, New York 10016, USA. Vishal.Patil@nyumc.org
Abstract
PURPOSE: Quantification of perfusion measurements using dynamic, susceptibility-weighted contrast-enhanced (DSC) MRI depends on estimating the size and shape of the tracer bolus. Typically, the bolus is described as a gamma variate function (GV) fitted to the bolus portion of tracer concentration time curve (CTC). However, the last point to fit is arbitrary which can lead to considerable variation in the fitted curve in the presence of noise. In this technical note, we present a model which takes into account recirculation explicitly and fits robustly to the entire CTC in the presence of noise. METHODS: Signal data measurements from ten DSC MRI patients were fitted with our new model and a GV function using four different methods of estimating the end of the bolus. Estimates of the area under the curves (AUC) and first moments (FMs) of the bolus were compared at different noise levels. RESULTS: The new model gave errors similar to or smaller than those of the most effective methods for fitting a GV. CONCLUSIONS: The single compartment recirculation (SCR) model is the most robust fitting technique with respect to noise both for bias and variability.
PURPOSE: Quantification of perfusion measurements using dynamic, susceptibility-weighted contrast-enhanced (DSC) MRI depends on estimating the size and shape of the tracer bolus. Typically, the bolus is described as a gamma variate function (GV) fitted to the bolus portion of tracer concentration time curve (CTC). However, the last point to fit is arbitrary which can lead to considerable variation in the fitted curve in the presence of noise. In this technical note, we present a model which takes into account recirculation explicitly and fits robustly to the entire CTC in the presence of noise. METHODS: Signal data measurements from ten DSC MRI patients were fitted with our new model and a GV function using four different methods of estimating the end of the bolus. Estimates of the area under the curves (AUC) and first moments (FMs) of the bolus were compared at different noise levels. RESULTS: The new model gave errors similar to or smaller than those of the most effective methods for fitting a GV. CONCLUSIONS: The single compartment recirculation (SCR) model is the most robust fitting technique with respect to noise both for bias and variability.
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