Dynamic contrast-enhanced MRI: Study of inter-software accuracy and reproducibility using simulated and clinical data.
J Magn Reson Imaging
; 43(6): 1288-300, 2016 06.
Article
em En
| MEDLINE
| ID: mdl-26687041
PURPOSE: To test the reproducibility and accuracy of pharmacokinetic parameter measurements on five analysis software packages (SPs) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), using simulated and clinical data. MATERIALS AND METHODS: This retrospective study was Institutional Review Board-approved. Simulated tissues consisted of pixel clusters of calculated dynamic signal changes for combinations of Tofts model pharmacokinetic parameters (volume transfer constant [K(trans) ], extravascular extracellular volume fraction [ve ]), longitudinal relaxation time (T1 ). The clinical group comprised 27 patients treated for rectal cancer, with 36 3T DCE-MR scans performed between November 2012 and February 2014, including dual-flip-angle T1 mapping and a dynamic postcontrast T1 -weighted, 3D spoiled gradient-echo sequence. The clinical and simulated images were postprocessed with five SPs to measure K(trans) , ve , and the initial area under the gadolinium curve (iAUGC). Modified Bland-Altman analysis was conducted, intraclass correlation coefficients (ICCs) and within-subject coefficients of variation were calculated. RESULTS: Thirty-one examinations from 23 patients were of sufficient technical quality and postprocessed. Measurement errors were observed on the simulated data for all the pharmacokinetic parameters and SPs, with a bias ranging from -0.19 min(-1) to 0.09 min(-1) for K(trans) , -0.15 to 0.01 for ve , and -0.65 to 1.66 mmol.L(-1) .min for iAUGC. The ICC between SPs revealed moderate agreement for the simulated data (K(trans) : 0.50; ve : 0.67; iAUGC: 0.77) and very poor agreement for the clinical data (K(trans) : 0.10; ve : 0.16; iAUGC: 0.21). CONCLUSION: Significant errors were found in the calculated DCE-MRI pharmacokinetic parameters for the perfusion analysis SPs, resulting in poor inter-software reproducibility. J. Magn. Reson. Imaging 2016;43:1288-1300.
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Base de dados:
MEDLINE
Assunto principal:
Compostos Organometálicos
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Software
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Imageamento por Ressonância Magnética
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Interpretação de Imagem Assistida por Computador
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Neoplasias Renais
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Meglumina
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Modelos Biológicos
Tipo de estudo:
Diagnostic_studies
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Evaluation_studies
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Observational_studies
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Prognostic_studies
Limite:
Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article