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Perfusion kinetics in human brain tumor with DCE-MRI derived model and CFD analysis.

To access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1016/j.jbiomech.2017.05.017 Byline: A. Bhandari (a), A. Bansal (b), A. Singh (c,d), N. Sinha [nsinha@iitk.ac.in] (a,*) Keywords Voxelized model; Human brain tumor; Arterial... Full description

Journal Title: Journal of biomechanics July 5, 2017, Vol.59, pp.80-89
Main Author: Bhandari, A
Other Authors: Bansal, A , Singh, A , Sinha, N
Format: Electronic Article Electronic Article
Language: English
Subjects:
CFD
Ifp
Ifv
ID: E-ISSN: 1873-2380 ; DOI: 10.1016/j.jbiomech.2017.05.017
Link: http://search.proquest.com/docview/1910796995/?pq-origsite=primo
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title: Perfusion kinetics in human brain tumor with DCE-MRI derived model and CFD analysis.
format: Article
creator:
  • Bhandari, A
  • Bansal, A
  • Singh, A
  • Sinha, N
subjects:
  • Algorithms–Diagnostic Imaging
  • Biological Transport–Metabolism
  • Brain Neoplasms–Pharmacokinetics
  • Contrast Media–Physiology
  • Extracellular Fluid–Methods
  • Humans–Methods
  • Kinetics–Methods
  • Magnetic Resonance Imaging–Methods
  • Models, Biological–Methods
  • Perfusion–Methods
  • Porosity–Methods
  • Pressure–Methods
  • Contrast Media
  • Arterial Input Function
  • CFD
  • Dce-Mri
  • Human Brain Tumor
  • Ifp
  • Ifv
  • Perfusion
ispartof: Journal of biomechanics, July 5, 2017, Vol.59, pp.80-89
description: To access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1016/j.jbiomech.2017.05.017 Byline: A. Bhandari (a), A. Bansal (b), A. Singh (c,d), N. Sinha [nsinha@iitk.ac.in] (a,*) Keywords Voxelized model; Human brain tumor; Arterial input function; Perfusion; IFP; IFV; Tracer transport; DCE-MRI; CFD Abstract Cancer is one of the leading causes of death all over the world. Among the strategies that are used for cancer treatment, the effectiveness of chemotherapy is often hindered by factors such as irregular and non-uniform uptake of drugs inside tumor. Thus, accurate prediction of drug transport and deposition inside tumor is crucial for increasing the effectiveness of chemotherapeutic treatment. In this study, a computational model of human brain tumor is developed that incorporates dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data into a voxelized porous media model. The model takes into account realistic transport and perfusion kinetics parameters together with realistic heterogeneous tumor vasculature and accurate arterial input function (AIF), which makes it patient specific. The computational results for interstitial fluid pressure (IFP), interstitial fluid velocity (IFV) and tracer concentration show good agreement with the experimental results. The computational model can be extended further for predicting the deposition of chemotherapeutic drugs in tumor environment as well as selection of the best chemotherapeutic drug for a specific patient. Author Affiliation: (a) Department of Mechanical Engineering, Indian Institute of Technology, Kanpur 208016, India (b) Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee 247677, India (c) Centre for Biomedical Engineering, Indian Institute of Technology, Delhi 110016, India (d) Department of Biomedical Engineering, All India Institute of Medical Sciences, Delhi 110016, India * Corresponding author. Article History: Accepted 18 May 2017
language: eng
source:
identifier: E-ISSN: 1873-2380 ; DOI: 10.1016/j.jbiomech.2017.05.017
fulltext: fulltext
issn:
  • 18732380
  • 1873-2380
url: Link


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titlePerfusion kinetics in human brain tumor with DCE-MRI derived model and CFD analysis.
creatorBhandari, A ; Bansal, A ; Singh, A ; Sinha, N
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identifierE-ISSN: 1873-2380 ; DOI: 10.1016/j.jbiomech.2017.05.017
subjectAlgorithms–Diagnostic Imaging ; Biological Transport–Metabolism ; Brain Neoplasms–Pharmacokinetics ; Contrast Media–Physiology ; Extracellular Fluid–Methods ; Humans–Methods ; Kinetics–Methods ; Magnetic Resonance Imaging–Methods ; Models, Biological–Methods ; Perfusion–Methods ; Porosity–Methods ; Pressure–Methods ; Contrast Media ; Arterial Input Function ; CFD ; Dce-Mri ; Human Brain Tumor ; Ifp ; Ifv ; Perfusion
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descriptionTo access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1016/j.jbiomech.2017.05.017 Byline: A. Bhandari (a), A. Bansal (b), A. Singh (c,d), N. Sinha [nsinha@iitk.ac.in] (a,*) Keywords Voxelized model; Human brain tumor; Arterial input function; Perfusion; IFP; IFV; Tracer transport; DCE-MRI; CFD Abstract Cancer is one of the leading causes of death all over the world. Among the strategies that are used for cancer treatment, the effectiveness of chemotherapy is often hindered by factors such as irregular and non-uniform uptake of drugs inside tumor. Thus, accurate prediction of drug transport and deposition inside tumor is crucial for increasing the effectiveness of chemotherapeutic treatment. In this study, a computational model of human brain tumor is developed that incorporates dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data into a voxelized porous media model. The model takes into account realistic transport and perfusion kinetics parameters together with realistic heterogeneous tumor vasculature and accurate arterial input function (AIF), which makes it patient specific. The computational results for interstitial fluid pressure (IFP), interstitial fluid velocity (IFV) and tracer concentration show good agreement with the experimental results. The computational model can be extended further for predicting the deposition of chemotherapeutic drugs in tumor environment as well as selection of the best chemotherapeutic drug for a specific patient. Author Affiliation: (a) Department of Mechanical Engineering, Indian Institute of Technology, Kanpur 208016, India (b) Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee 247677, India (c) Centre for Biomedical Engineering, Indian Institute of Technology, Delhi 110016, India (d) Department of Biomedical Engineering, All India Institute of Medical Sciences, Delhi 110016, India * Corresponding author. Article History: Accepted 18 May 2017
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