Arterial input function estimation compensating for inflow and partial voluming in dynamic contrast-enhanced MRI

被引:0
|
作者
Tseng, Chih-Hsien [1 ,2 ,3 ,4 ,5 ,6 ]
Nagtegaal, Martijn A. [1 ,7 ]
van Osch, Matthias J. P. [2 ,3 ,4 ,5 ,6 ,7 ]
Jaspers, Jaap [3 ,4 ,5 ,6 ,8 ]
Romero, Alejandra Mendez [3 ,4 ,5 ,6 ,8 ]
Wielopolski, Piotr [9 ]
Smits, Marion [2 ,9 ,10 ]
Vos, Frans M. [1 ,2 ,3 ,4 ,5 ,6 ,9 ]
机构
[1] Delft Univ Technol, Dept Imaging Phys, Lorentzweg 1, NL-2628 CJ Delft, Netherlands
[2] Med Delta, Delft, Netherlands
[3] Erasmus MC, HollandPTC Consortium, Rotterdam, Netherlands
[4] Holland Proton Therapy Ctr, Delft, Netherlands
[5] Leiden Univ, Med Ctr, Leiden, Netherlands
[6] Delft Univ Technol, Delft, Netherlands
[7] Leiden Univ, CJ Gorter MRI Ctr, Med Ctr, Dept Radiol, Leiden, Netherlands
[8] Univ Med Ctr Rotterdam, Erasmus MC Canc Inst, Dept Radiotherapy, Rotterdam, Netherlands
[9] Univ Med Ctr Rotterdam, Dept Radiol & Nucl Med, Erasmus MC, Rotterdam, Netherlands
[10] Univ Med Ctr Rotterdam, Erasmus MC Canc Inst, Brain Tumour Ctr, Rotterdam, Netherlands
关键词
arterial input function; DCE MRI; inflow effect; partial volume effect; KINETIC-PARAMETERS; PERFUSION MRI; BLOOD; QUANTIFICATION; VARIABILITY; ACQUISITION; TISSUE; YIELD;
D O I
10.1002/nbm.5225
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Both inflow and the partial volume effect (PVE) are sources of error when measuring the arterial input function (AIF) in dynamic contrast-enhanced (DCE) MRI. This is relevant, as errors in the AIF can propagate into pharmacokinetic parameter estimations from the DCE data. A method was introduced for flow correction by estimating and compensating the number of the perceived pulse of spins during inflow. We hypothesized that the PVE has an impact on concentration-time curves similar to inflow. Therefore, we aimed to study the efficiency of this method to compensate for both effects simultaneously. We first simulated an AIF with different levels of inflow and PVE contamination. The peak, full width at half-maximum (FWHM), and area under curve (AUC) of the reconstructed AIFs were compared with the true (simulated) AIF. In clinical data, the PVE was included in AIFs artificially by averaging the signal in voxels surrounding a manually selected point in an artery. Subsequently, the artificial partial volume AIFs were corrected and compared with the AIF from the selected point. Additionally, corrected AIFs from the internal carotid artery (ICA), the middle cerebral artery (MCA), and the venous output function (VOF) estimated from the superior sagittal sinus (SSS) were compared. As such, we aimed to investigate the effectiveness of the correction method with different levels of inflow and PVE in clinical data. The simulation data demonstrated that the corrected AIFs had only marginal bias in peak value, FWHM, and AUC. Also, the algorithm yielded highly correlated reconstructed curves over increasingly larger neighbourhoods surrounding selected arterial points in clinical data. Furthermore, AIFs measured from the ICA and MCA produced similar peak height and FWHM, whereas a significantly larger peak and lower FWHM was found compared with the VOF. Our findings indicate that the proposed method has high potential to compensate for PVE and inflow simultaneously. The corrected AIFs could thereby provide a stable input source for DCE analysis. The partial volume effect (PVE) exerts a relatively equivalent impact as the inflow effect does on arterial input function (AIF) measurement in DCE MRI. We propose a compensatory approach, addressing PVE and inflow correction simultaneously by estimating the perceived pulse number of protons implicitly. This method adeptly reconstructs the AIF with minimal bias, as demonstrated in simulations and clinical datasets. While the venous output function (VOF) from the superior sagittal sinus is a contemplated alternative in clinic, our findings reveal significant dispersion-induced differences between the VOF and AIF in DCE MRI. image
引用
收藏
页数:14
相关论文
共 50 条
  • [31] Estimating the arterial input function using two reference tissues in dynamic contrast-enhanced MRI studies: Fundamental concepts and simulations
    Yang, C
    Karczmar, GS
    Medved, M
    Stadler, WM
    MAGNETIC RESONANCE IN MEDICINE, 2004, 52 (05) : 1110 - 1117
  • [32] Impact of the arterial input function on microvascularization parameter measurements using dynamic contrast-enhanced ultrasonography
    Gauthier, Marianne
    Pitre-Champagnat, Stephanie
    Tabarout, Farid
    Leguerney, Ingrid
    Polrot, Melanie
    Lassau, Nathalie
    WORLD JOURNAL OF RADIOLOGY, 2012, 4 (07): : 291 - 301
  • [33] Pharmacokinetic modeling of dynamic contrast-enhanced MRI using a reference region and input function tail
    Ahmed, Zaki
    Levesque, Ives R.
    MAGNETIC RESONANCE IN MEDICINE, 2020, 83 (01) : 286 - 298
  • [34] Use of Cardiac Output to Improve Measurement of Input Function in Quantitative Dynamic Contrast-Enhanced MRI
    Zhang, Jeff L.
    Rusinek, Henry
    Bokacheva, Louisa
    Chen, Qun
    Storey, Pippa
    Lee, Vivian S.
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2009, 30 (03) : 656 - 665
  • [35] Dynamic Contrast-Enhanced MRI in Mice at High Field: Estimation of the Arterial Input Function Can Be Achieved by Phase Imaging (vol 71, pg 544, 2014)
    Fruytier, Anne-Catherine
    Magat, Julie
    Jordan, Benedicte
    Cron, Greg
    Colliez, Florence
    Gallez, Bernard
    MAGNETIC RESONANCE IN MEDICINE, 2014, 72 (02) : 602 - 602
  • [36] Improving the Arterial Input Function in Dynamic Contrast Enhanced MRI by Fitting the Signal in the Complex Plane
    Simonis, Frank F. J.
    Sbrizzi, Alessandro
    Beld, Ellis
    Lagendijk, Jan J. W.
    van den Berg, Cornelis A. T.
    MAGNETIC RESONANCE IN MEDICINE, 2016, 76 (04) : 1236 - 1245
  • [37] The Effect of Blood Inflow and B1-Field Inhomogeneity on Measurement of the Arterial Input Function in Axial 3D Spoiled Gradient Echo Dynamic Contrast-Enhanced MRI
    Roberts, Caleb
    Little, Ross
    Watson, Yvonne
    Zhao, Sha
    Buckley, David L.
    Parker, Geoff J. M.
    MAGNETIC RESONANCE IN MEDICINE, 2011, 65 (01) : 108 - 119
  • [38] Impact of Arterial Input Function Selection on the Accuracy of Dynamic Contrast-Enhanced MRI Quantitative Analysis for the Diagnosis of Clinically Significant Prostate Cancer
    Azahaf, Mustapha
    Haberley, Marc
    Betrouni, Nacim
    Ernst, Olivier
    Behal, Helene
    Duhamel, Alain
    Ouzzane, Adil
    Puech, Philippe
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2016, 43 (03) : 737 - 749
  • [39] Feasibility of using limited-population-based arterial input function for pharmacokinetic modeling of osteosarcoma dynamic contrast-enhanced MRI data
    Wang, Ya
    Huang, Wei
    Panicek, David A.
    Schwartz, Lawrence H.
    Koutcher, Jason A.
    MAGNETIC RESONANCE IN MEDICINE, 2008, 59 (05) : 1183 - 1189
  • [40] Dynamic contrast-enhanced MRI using Gd-DTPA: Interindividual variability of the arterial input function and consequences for the assessment of kinetics in tumors
    Port, RE
    Knopp, MV
    Brix, G
    MAGNETIC RESONANCE IN MEDICINE, 2001, 45 (06) : 1030 - 1038