Your browser doesn't support javascript.
loading
A numerical framework for interstitial fluid pressure imaging in poroelastic MRE.
Tan, Likun; McGarry, Matthew D J; Van Houten, Elijah E W; Ji, Ming; Solamen, Ligin; Zeng, Wei; Weaver, John B; Paulsen, Keith D.
Afiliación
  • Tan L; Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, United States of America.
  • McGarry MDJ; Department of Biomedical Engineering, Columbia University, New York, NY 10027, United States of America.
  • Van Houten EEW; Department of Mechanical Engineering, University de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada.
  • Ji M; Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States of America.
  • Solamen L; Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, United States of America.
  • Zeng W; Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, United States of America.
  • Weaver JB; Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, United States of America.
  • Paulsen KD; Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756 United States of America.
PLoS One ; 12(6): e0178521, 2017.
Article en En | MEDLINE | ID: mdl-28586393
A numerical framework for interstitial fluid pressure imaging (IFPI) in biphasic materials is investigated based on three-dimensional nonlinear finite element poroelastic inversion. The objective is to reconstruct the time-harmonic pore-pressure field from tissue excitation in addition to the elastic parameters commonly associated with magnetic resonance elastography (MRE). The unknown pressure boundary conditions (PBCs) are estimated using the available full-volume displacement data from MRE. A subzone-based nonlinear inversion (NLI) technique is then used to update mechanical and hydrodynamical properties, given the appropriate subzone PBCs, by solving a pressure forward problem (PFP). The algorithm was evaluated on a single-inclusion phantom in which the elastic property and hydraulic conductivity images were recovered. Pressure field and material property estimates had spatial distributions reflecting their true counterparts in the phantom geometry with RMS errors around 20% for cases with 5% noise, but degraded significantly in both spatial distribution and property values for noise levels > 10%. When both shear moduli and hydraulic conductivity were estimated along with the pressure field, property value error rates were as high as 58%, 85% and 32% for the three quantities, respectively, and their spatial distributions were more distorted. Opportunities for improving the algorithm are discussed.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Líquido Extracelular / Diagnóstico por Imagen de Elasticidad Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Líquido Extracelular / Diagnóstico por Imagen de Elasticidad Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos