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Improved reliability of perfusion estimation in dynamic susceptibility contrast MRI by using the arterial input function from dynamic contrast enhanced MRI
被引:0
|作者:
Tseng, Chih-Hsien
[1
,2
,3
,4
,5
,6
]
Jaspers, Jaap
[3
,4
,5
,6
,7
]
Romero, Alejandra Mendez
[3
,4
,5
,6
,7
]
Wielopolski, Piotr
[8
]
Smits, Marion
[2
,8
,9
]
van Osch, Matthias J. P.
[2
,3
,4
,5
,6
,10
]
Vos, Frans
[1
,2
,3
,4
,5
,6
,8
]
机构:
[1] Delft Univ Technol, Dept Imaging Phys, Lorentzweg 1, NL-2628 CJ Delft, Netherlands
[2] Med Delta, Delft, Netherlands
[3] Erasmus MC, Holland Proton Therapy Ctr Consortium, Rotterdam, Netherlands
[4] Holland Proton Therapy Ctr, Delft, Netherlands
[5] Leiden Univ, Med Ctr, Leiden, Netherlands
[6] Delft Univ Technol, Delft, Netherlands
[7] Univ Med Ctr Rotterdam, Erasmus MC Canc Inst, Dept Radiotherapy, Rotterdam, Netherlands
[8] Univ Med Ctr Rotterdam, Erasmus MC, Dept Radiol & Nucl Med, Rotterdam, Netherlands
[9] Univ Med Ctr Rotterdam, Erasmus MC Canc Inst, Brain Tumour Ctr, Rotterdam, Netherlands
[10] Leiden Univ, CJ Gorter MRI Ctr, Med Ctr, Dept Radiol, Leiden, Netherlands
关键词:
arterial input function;
cerebral blood flow;
cerebral blood volume;
dynamic contrast enhanced MRI;
dynamic susceptibility contrast MRI;
CEREBRAL-BLOOD-FLOW;
POSITRON-EMISSION-TOMOGRAPHY;
HIGH-RESOLUTION MEASUREMENT;
TRACER BOLUS PASSAGES;
AUTOMATIC SELECTION;
AGENT CONCENTRATION;
HIGH-GRADE;
VOLUME;
QUANTIFICATION;
OXYGEN;
D O I:
10.1002/nbm.5038
中图分类号:
Q6 [生物物理学];
学科分类号:
071011 ;
摘要:
The arterial input function (AIF) plays a crucial role in estimating quantitative perfusion properties from dynamic susceptibility contrast (DSC) MRI. An important issue, however, is that measuring the AIF in absolute contrast-agent concentrations is challenging, due to uncertainty in relation to the measured R-2(*)-weighted signal, signal depletion at high concentration, and partial-volume effects. A potential solution could be to derive the AIF from separately acquired dynamic contrast enhanced (DCE) MRI data. We aim to compare the AIF determined from DCE MRI with the AIF from DSC MRI, and estimated perfusion coefficients derived from DSC data using a DCE-driven AIF with perfusion coefficients determined using a DSC-based AIF. AIFs were manually selected in branches of the middle cerebral artery (MCA) in both DCE and DSC data in each patient. In addition, a semi-automatic AIF-selection algorithm was applied to the DSC data. The amplitude and full width at half-maximum of the AIFs were compared statistically using the Wilcoxon rank-sum test, applying a 0.05 significance level. Cerebral blood flow (CBF) was derived with different AIF approaches and compared further. The results showed that the AIFs extracted from DSC scans yielded highly variable peaks across arteries within the same patient. The semi-automatic DSC-AIF had significantly narrower width compared with the manual AIFs, and a significantly larger peak than the manual DSC-AIF. Additionally, the DCE-based AIF provided a more stable measurement of relative CBF and absolute CBF values estimated with DCE-AIFs that were compatible with previously reported values. In conclusion, DCE-based AIFs were reproduced significantly better across vessels, showed more realistic profiles, and delivered more stable and reasonable CBF measurements. The DCE-AIF can, therefore, be considered as an alternative AIF source for quantitative perfusion estimations in DSC MRI. DCE-based AIFs are reproduced significantly better across vessels and provide more stable relative CBF measurements, and can therefore improve the reliability of perfusion parameter estimations from DSC MRI. In addition, absolute CBF maps estimated with DCE-AIFs are highly correlated with previously reported values. The DCE-driven AIF can, therefore, be considered as an alternative AIF source when deriving absolute CBF in DSC MRI. image
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