An extended reference region model for DCE-MRI that accounts for plasma volume

被引:9
|
作者
Ahmed, Zaki [1 ,2 ]
Levesque, Ives R. [1 ,2 ,3 ]
机构
[1] McGill Univ, Med Phys Unit, Montreal, PQ, Canada
[2] McGill Univ, Dept Phys, Montreal, PQ, Canada
[3] McGill Univ, Hlth Ctr, Res Inst, Montreal, PQ, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
cancer; dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI); perfusion; pharmacokinetics; reference region model; tracer kinetic modeling; ARTERIAL INPUT FUNCTION; CONTRAST-ENHANCED MRI; TEMPORAL SAMPLING REQUIREMENTS; PHARMACOKINETIC PARAMETERS; KINETIC-PARAMETERS; TRACER KINETICS; BREAST-CANCER; PERFUSION MRI; BRAIN-TUMORS; RESOLUTION;
D O I
10.1002/nbm.3924
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
The reference region model (RRM) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides pharmacokinetic parameters without requiring the arterial input function. A limitation of the RRM is that it assumes that the blood plasma volume in the tissue of interest is zero, but this is often not true in highly vascularized tissues, such as some tumours. This study proposes an extended reference region model (ERRM) to account for tissue plasma volume. Furthermore, ERRM was combined with a two-fit approach to reduce the number of fitting parameters, and this was named the constrained ERRM (CERRM). The accuracy and precision of RRM, ERRM and CERRM were evaluated in simulations covering a range of parameters, noise and temporal resolutions. These models were also compared with the extended Tofts model (ETM) on in vivo glioblastoma multiforme data. In simulations, RRM overestimated under noiseless conditions. In comparison, ERRM and CERRM were both accurate, with CERRM showing better precision when noise was included. On in vivo data, CERRM provided maps that had the highest agreement with ETM, whilst also being robust at temporal resolutions as poor as 30s. ERRM can provide pharmacokinetic parameters without an arterial input function in tissues with non-negligible where RRM provides inaccurate estimates. The two-fit approach, named CERRM, further improves on the accuracy and precision of ERRM.
引用
收藏
页数:13
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