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A linear algorithm of the reference region model for DCE-MRI is robust and relaxes requirements for temporal resolution.
Cárdenas-Rodríguez, Julio; Howison, Christine M; Pagel, Mark D.
Afiliação
  • Cárdenas-Rodríguez J; Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, USA.
Magn Reson Imaging ; 31(4): 497-507, 2013 May.
Article em En | MEDLINE | ID: mdl-23228309
ABSTRACT
Dynamic contrast enhanced MRI (DCE-MRI) has utility for improving clinical diagnoses of solid tumors, and for evaluating the early responses of anti-angiogenic chemotherapies. The Reference Region Model (RRM) can improve the clinical implementation of DCE-MRI by substituting the contrast enhancement of muscle for the Arterial Input Function that is used in traditional DCE-MRI methodologies. The RRM is typically fitted to experimental results with a non-linear least squares algorithm. This report demonstrates that this algorithm produces inaccurate and imprecise results when DCE-MRI results have low SNR or slow temporal resolution. To overcome this limitation, a linear least-squares algorithm has been derived for the Reference Region Model. This new algorithm improves accuracy and precision of fitting the Reference Region Model to DCE-MRI results, especially for voxel-wise analyses. This linear algorithm is insensitive to injection speeds, and has 300- to 8000-fold faster calculation speed relative to the non-linear algorithm. The linear algorithm produces more accurate results for over a wider range of permeabilities and blood volumes of tumor vasculature. This new algorithm, termed the Linear Reference Region Model, has strong potential to improve clinical DCE-MRI evaluations.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Neoplasias Experimentais Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2013 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Neoplasias Experimentais Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2013 Tipo de documento: Article