## Abstract In previous papers relative signal intensity increase was used as a quantitative assessment parameter for contrast uptake in contrastenhanced MRI. However, relative signal intensity increase does not only reflect contrast uptake but depends also on tissue parameters (native __T__~1~ rel
Reproducibility assessment of a multiple reference tissue method for quantitative dynamic contrast enhanced–MRI analysis
✍ Scribed by Cheng Yang; Gregory S. Karczmar; Milica Medved; Aytekin Oto; Marta Zamora; Walter M. Stadler
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 632 KB
- Volume
- 61
- Category
- Article
- ISSN
- 0740-3194
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✦ Synopsis
Abstract
Bone metastases of 16 prostate cancer patients were scanned twice 1 week apart by dynamic contrast enhanced (DCE) –MRI at 2‐s resolution using a two‐dimensional gradient‐echo pulse sequence. With a multiple reference tissue method (MRTM), the local tissue arterial input function (AIF) was estimated using the contrast agent enhancement data from tumor subregions and muscle. The 32 individual AIFs estimated by the MRTM, which had considerable intra‐patient and inter‐patient variability, were similar to directly measured AIFs in the literature and using the MRTM AIFs in a pharmacokinetic model to derive estimated individual cardiac outputs provided physiologically reasonable results. The MRTM individual AIFs gave better fits with smaller sum of squared errors and equally reproducible estimate of kinetic parameters compared with a previous reported population AIF measured from remote arteries. The individual MRTM AIFs were also used to obtain a mean local tissue AIF for the unique population of this study, which further improved the reproducibility of the estimated kinetic parameters. The MRTM can be applied to DCE‐MRI studies of bone metastases from prostate cancers to provide an AIF from which reproducible quantitative DCE‐MRI parameters can be derived, thus help standardize DCE‐MRI studies in cancer patients. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
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