Paper
13 March 2013 pCT derived arterial input function for improved pharmacokinetic analysis of longitudinal dceMRI for colorectal cancer
Monica Enescu, Manav Bhushan, Esme J. Hill, Jamie Franklin, Ewan M. Anderson, Ricky A. Sharma, Julia A. Schnabel
Author Affiliations +
Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86690L (2013) https://doi.org/10.1117/12.2007036
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Dynamic contrast-enhanced MRI is a dynamic imaging technique that is now widely used for cancer imaging. Changes in tumour microvasculature are typically quantified by pharmacokinetic modelling of the contrast uptake curves. Reliable pharmacokinetic parameter estimation depends on the measurement of the arterial input function, which can be obtained from arterial blood sampling, or extracted from the image data directly. However, arterial blood sampling poses additional risks to the patient, and extracting the input function from MR intensities is not reliable. In this work, we propose to compute a perfusion CT based arterial input function, which is then employed for dynamic contrast enhanced MRI pharmacokinetic parameter estimation. Here, parameter estimation is performed simultaneously with intra-sequence motion correction by using nonlinear image registration. Ktrans maps obtained with this approach were compared with those obtained using a population averaged arterial input function, i.e. Orton. The dataset comprised 5 rectal cancer patients, who had been imaged with both perfusion CT and dynamic contrast enhanced MRI, before and after the administration of a radiosensitising drug. Ktrans distributions pre and post therapy were computed using both the perfusion CT and the Orton arterial input function. Perfusion CT derived arterial input functions can be used for pharmacokinetic modelling of dynamic contrast enhanced MRI data, when perfusion CT images of the same patients are available. Compared to the Orton model, perfusion CT functions have the potential to give a more accurate separation between responders and non-responders.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Monica Enescu, Manav Bhushan, Esme J. Hill, Jamie Franklin, Ewan M. Anderson, Ricky A. Sharma, and Julia A. Schnabel "pCT derived arterial input function for improved pharmacokinetic analysis of longitudinal dceMRI for colorectal cancer", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86690L (13 March 2013); https://doi.org/10.1117/12.2007036
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KEYWORDS
Magnetic resonance imaging

Tissues

Modeling

Computed tomography

Cancer

Image registration

Motion estimation

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