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Output details

11 - Computer Science and Informatics

Imperial College London

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Output 2 of 201 in the submission

Article title

A Bayesian Hierarchical Model for the Analysis of a Longitudinal Dynamic Contrast-Enhanced MRI Oncology Study

Type

D - Journal article

DOI

10.1002/mrm.21807

Title of journal

Magnetic Resonance in Medicine

Article number

Volume number

Issue number

First page of article

163

ISSN of journal

0740-3194

Year of publication

2009

URL

Number of additional authors

Additional information

<33>This is in collaborative with industry (GSK), focussing on kinetic modelling for dynamic contrast enhanced MRI using mixed-effect models that are more suitable for longitudinal studies, which are essential for cancer patient follow-ups for assessing the efficacy of therapeutic regimes. Hypothesis testing at the study level for an overall treatment effect is made possible and the method is validated with a breast cancer study, where the subjects were imaged before and after two cycles of chemotherapy, demonstrating the clinical potential of this method to longitudinal oncology studies. The 1st author obtained a professorship at the highly rated Ludwig-Maximilians-University in Germany.

Interdisciplinary

Yes

Cross-referral requested

Research group

C - Visual Information Processing

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract