HHS Public Access Author manuscript Author Manuscript
Ann Biomed Eng. Author manuscript; available in PMC 2017 May 01. Published in final edited form as: Ann Biomed Eng. 2016 May ; 44(5): 1524–1537. doi:10.1007/s10439-015-1449-6.
Inter-Operator Dependence of Magnetic Resonance ImageBased Computational Fluid Dynamics Prediction of Cerebrospinal Fluid Motion in the Cervical Spine
Author Manuscript
Bryn A. Martin1,*, Theresia I. Yiallourou2,*, Soroush Heidari Pahlavian3, Suraj Thyagaraj3, Alexander C. Bunck4, Francis Loth3, Daniel B. Sheffer5, Jan Robert Kröger4, and Nikolaos Stergiopulos2 1Neurophysiological
Imaging and Modeling Laboratory, Department of Biological Engineering, The University of Idaho, ID, U.S.A 2Laboratory of Hemodynamics and Cardiovascular Technology, École Polytechnique Fédérale de Lausanne, Switzerland 3Conquer Chiari Research Center, Department of Mechanical Engineering, The University of Akron, OH, U.S.A 4Department of Radiology, University Hospital of Cologne, Germany, and with the Department of Clinical Radiology, University of Muenster, Germany 5Department of Biomedical Engineering, The University of Akron, OH, U.S.A
Abstract Author Manuscript Author Manuscript
For the first time, inter-operator dependence of MRI based computational fluid dynamics (CFD) modeling of cerebrospinal fluid (CSF) in the cervical spinal subarachnoid space (SSS) is evaluated. In vivo MRI flow measurements and anatomy MRI images were obtained at the cervico-medullary junction of a healthy subject and a Chiari I malformation patient. 3D anatomies of the SSS were reconstructed by manual segmentation by four independent operators for both cases. CFD results were compared at nine axial locations along the SSS in terms of hydrodynamic and geometric parameters. Intraclass correlation (ICC) assessed the inter-operator agreement for each parameter over the axial locations and coefficient of variance (CV) compared the percentage of variance for each parameter between the operators. Greater operator dependence was found for the patient (0.19
Ann Biomed Eng. Author manuscript; available in PMC 2017 May 01. Published in final edited form as: Ann Biomed Eng. 2016 May ; 44(5): 1524–1537. doi:10.1007/s10439-015-1449-6.
Inter-Operator Dependence of Magnetic Resonance ImageBased Computational Fluid Dynamics Prediction of Cerebrospinal Fluid Motion in the Cervical Spine
Author Manuscript
Bryn A. Martin1,*, Theresia I. Yiallourou2,*, Soroush Heidari Pahlavian3, Suraj Thyagaraj3, Alexander C. Bunck4, Francis Loth3, Daniel B. Sheffer5, Jan Robert Kröger4, and Nikolaos Stergiopulos2 1Neurophysiological
Imaging and Modeling Laboratory, Department of Biological Engineering, The University of Idaho, ID, U.S.A 2Laboratory of Hemodynamics and Cardiovascular Technology, École Polytechnique Fédérale de Lausanne, Switzerland 3Conquer Chiari Research Center, Department of Mechanical Engineering, The University of Akron, OH, U.S.A 4Department of Radiology, University Hospital of Cologne, Germany, and with the Department of Clinical Radiology, University of Muenster, Germany 5Department of Biomedical Engineering, The University of Akron, OH, U.S.A
Abstract Author Manuscript Author Manuscript
For the first time, inter-operator dependence of MRI based computational fluid dynamics (CFD) modeling of cerebrospinal fluid (CSF) in the cervical spinal subarachnoid space (SSS) is evaluated. In vivo MRI flow measurements and anatomy MRI images were obtained at the cervico-medullary junction of a healthy subject and a Chiari I malformation patient. 3D anatomies of the SSS were reconstructed by manual segmentation by four independent operators for both cases. CFD results were compared at nine axial locations along the SSS in terms of hydrodynamic and geometric parameters. Intraclass correlation (ICC) assessed the inter-operator agreement for each parameter over the axial locations and coefficient of variance (CV) compared the percentage of variance for each parameter between the operators. Greater operator dependence was found for the patient (0.19
