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Open Access Green as soon as Postprint is submitted to ZB.
Personalised estimation of the arterial input function for improved pharmacokinetic modelling of colorectal cancer using dceMRI.
Lect. Notes Comput. Sc. 8198 LNCS, 126-135 (2013)
dceMRI is becoming a key modality for tumour characterisation and monitoring of response to therapy, because of the ability to identify the underlying tumour physiology. Pharmacokinetic (PK) models relate the contrast enhancement seen in dceMRI to physiological parameters but require accurate measurement of the AIF, the time-dependant contrast concentration in blood plasma. In this study, a novel method is introduced that overcomes the challenges of direct AIF measurement, by automatically estimating the AIF from the tumour tissue. This approach was evaluated on synthetic data (10% noise) and achieved a relative error in Ktrans and kep of 11.8±3.5% and 25.7±4.7 %, respectively, compared to 41 ±15 % and 60 ±32 % using a population model. The method improved the fit of the PK model to clinical colorectal cancer cases, was stable for independent regions in the tumour, and showed improved localisation of the PK parameters. This demonstrates that personalised AIF estimation can lead to more accurate PK modelling.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Arterial Input Function ; Dcemri ; Pharmacokinetic Modelling
ISSN (print) / ISBN
0302-9743
e-ISSN
1611-3349
Quellenangaben
Volume: 8198 LNCS,
Pages: 126-135
Publisher
Springer
Publishing Place
Berlin [u.a.]
Non-patent literature
Publications
Institute(s)
Institute for Machine Learning in Biomed Imaging (IML)