6523 Automatic Bolus Analysis for DCE-MRI Using Radial Golden-Angle Stack-of-stars GRE Imaging

Robert Grimm, Li Feng, Christoph Forman,Jana Hutter,Berthold Kiefer,Joachim Hornegger, Tobias Block

semanticscholar(2012)

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摘要
INTRODUCTION: In clinical 3D Dynamic Contrast-Enhanced MRI (DCE-MRI) of the abdomen, multiple phases of perfusion (pre-contrast, arterial, venous, delayed phases) are captured subsequently in breath-hold scans. Novel imaging and reconstruction techniques such as GRASP promise DCEMRI at a temporal resolution of only few seconds from a single, continuous image acquisition. This reduces the requirements on bolus-timing accuracy and can thereby significantly simplify the imaging workflow. However, the technique also has two disadvantages that have not been addressed so far: First, it cannot be combined with conventional bolus detection techniques to monitor the contrast agent (CA) bolus. Because the reconstruction is computationally so intensive that dynamic images are computed with significant delay, no direct visual feedback is available after the scan. Second, the resulting 4D images that can comprise more than 100 time-steps impose a significant amount of data that cannot yet be adequately visualized or analyzed with most clinical imaging software. Identifying the few critical phases of perfusion in the time series requires manual interaction from the radiologist, or carefully tuned, application-specific segmentation algorithms. Here, we propose a parameter-free method to automatically extract a bolus time curve from raw k-space data acquired with a radial stack-of-stars GRE sequence. It can be used to display statistics about the CA bolus right after the scan, as well as to automatically pick time frames at important stages of perfusion. Because the approach is k-space-based, the temporal accuracy is not limited by the reconstructed images.
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