Improved repeatability of dynamic contrast‐enhanced MRI using the complex MRI signal to derive arterial input functions: a test‐retest study in prostate cancer patients

Purpose The arterial input function (AIF) is a major source of uncertainty in tracer kinetic (TK) analysis of dynamic contrast‐enhanced (DCE)‐MRI data. The aim of this study was to investigate the repeatability of AIFs extracted from the complex signal and of the resulting TK parameters in prostate...

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Veröffentlicht in:Magnetic resonance in medicine Jg. 81; H. 5; S. 3358 - 3369
Hauptverfasser: Klawer, Edzo M.E., van Houdt, Petra J., Simonis, Frank F.J., van den Berg, Cornelis A.T., Pos, Floris J., Heijmink, Stijn W.T.P.J., Isebaert, Sofie, Haustermans, Karin, van der Heide, Uulke A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Wiley Subscription Services, Inc 01.05.2019
John Wiley and Sons Inc
Schlagworte:
Aged
Algorithms
arterial input function
Biopsy
Coefficient of variation
complex signal
Computer Simulation
Contrast Media - administration & dosage
Data acquisition
dynamic contrast‐enhanced MRI
Full Papers—Computer Processing and Modeling
Humans
Image Interpretation, Computer-Assisted - methods
Image Processing, Computer-Assisted
Kinetics
Magnetic Resonance Imaging
Male
Middle Aged
Models, Statistical
Patients
Prostate cancer
Prostatic Neoplasms - diagnostic imaging
Quantitative analysis
repeatability
Reproducibility
Reproducibility of Results
tracer kinetic analysis
repeatability
prostate cancer
complex signal
arterial input function
tracer kinetic analysis
dynamic contrast-enhanced MRI
ISSN:0740-3194, 1522-2594, 1522-2594
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Zusammenfassung:Purpose The arterial input function (AIF) is a major source of uncertainty in tracer kinetic (TK) analysis of dynamic contrast‐enhanced (DCE)‐MRI data. The aim of this study was to investigate the repeatability of AIFs extracted from the complex signal and of the resulting TK parameters in prostate cancer patients. Methods Twenty‐two patients with biopsy‐proven prostate cancer underwent a 3T MRI exam twice. DCE‐MRI data were acquired with a 3D spoiled gradient echo sequence. AIFs were extracted from the magnitude of the signal (AIFMAGN), phase (AIFPHASE), and complex signal (AIFCOMPLEX). The Tofts model was applied to extract Ktrans, kep and ve. Repeatability of AIF curve characteristics and TK parameters was assessed with the within‐subject coefficient of variation (wCV). Results The wCV for peak height and full width at half maximum for AIFCOMPLEX (7% and 8%) indicated an improved repeatability compared to AIFMAGN (12% and 12%) and AIFPHASE (12% and 7%). This translated in lower wCV values for Ktrans (11%) with AIFCOMPLEX in comparison to AIFMAGN (24%) and AIFPHASE (15%). For kep, the wCV was 16% with AIFMAGN, 13% with AIFPHASE, and 13% with AIFCOMPLEX. Conclusion Repeatability of AIFPHASE and AIFCOMPLEX is higher than for AIFMAGN, resulting in a better repeatability of TK parameters. Thus, use of either AIFPHASE or AIFCOMPLEX improves the robustness of quantitative analysis of DCE‐MRI in prostate cancer.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0740-3194
1522-2594
1522-2594
DOI:10.1002/mrm.27646