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Characterizing Peritumoral Tissue Using Free Water Elimination in Clinical DTI

Authors :
Abdol Aziz Ould Ismail
Drew Parker
Moises Hernandez-Fernandez
Steven Brem
Simon Alexander
Ofer Pasternak
Emmanuel Caruyer
Ragini Verma
Section for Biomedical Image Analysis (SBIA)
Perelman School of Medicine
University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia]
University of Pennsylvania [Philadelphia]
Synaptive Medical Inc
Departments of Psychiatry and Radiology [Boston]
Brigham and Women's Hospital [Boston]
Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA)
Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1)
Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)
Vision, Action et Gestion d'informations en Santé (VisAGeS)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA)
Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1)
University of Pennsylvania-University of Pennsylvania
University of Pennsylvania
Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)
Caruyer, Emmanuel
Source :
MICCAI 2018-21st International Conference on Medical Image Computing and Computer Assisted Intervention ; Workshop : Brain Lesion, MICCAI 2018-21st International Conference on Medical Image Computing and Computer Assisted Intervention ; Workshop : Brain Lesion, Sep 2018, Granada, Spain. pp.1-9, HAL
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

International audience; Finding an accurate microstructural characterization of the peritumoral region is essential to distinguish between edema and infiltration, enabling the distinction between tumor types, and to improve tractography in this region. Characterization of healthy versus pathological tissue is a key concern when modeling tissue microstructure in the peritumoral area, which is muddled by the presence of free water (e.g., edema). Although diffusion MRI (dMRI) is being used to obtain the microstructural characterization of tissue, most methods are based on advanced dMRI acquisition schemes that are infeasible in the clinical environment, which predominantly uses diffusion tensor imaging (DTI), and are mostly for healthy tissue. In this paper, we propose a novel approach for microstructural characterization of peritumoral tissue, that involves multi-compartment modeling and a robust free water elimination (FWE) method to improve the estimation of free water in both healthy and pathological tissue. As FWE requires the fitting of two compartments, it is an ill-posed problem in DTI acquisitions. Solving this problem requires an optimization routine, which in turn relies on an initialization step for finding a solution, which we optimally choose to model the presence of edema and infiltration unlike existing schemes. We have validated the method extensively on simulated data, and applied it to data from brain tumor patients to demonstrate the improvement in tractography in the peritumoral region, which is important for surgical planning.

Details

Language :
English
Database :
OpenAIRE
Journal :
MICCAI 2018-21st International Conference on Medical Image Computing and Computer Assisted Intervention ; Workshop : Brain Lesion, MICCAI 2018-21st International Conference on Medical Image Computing and Computer Assisted Intervention ; Workshop : Brain Lesion, Sep 2018, Granada, Spain. pp.1-9, HAL
Accession number :
edsair.dedup.wf.001..40c1745e53d0ef722bd70206eaed094c