title: Quantitative fat and R2* mapping in vivo to measure lipid-rich necrotic core and intraplaque hemorrhage in carotid atherosclerosis.
abstract: The aim of this work was to quantify the extent of lipid-rich necrotic core (LRNC) and intraplaque hemorrhage (IPH) in atherosclerotic plaques.
  
  
  
  Patients scheduled for carotid endarterectomy underwent four-point Dixon and T1-weighted magnetic resonance imaging (MRI) at 3 Tesla. Fat and R2* maps were generated from the Dixon sequence at the acquired spatial resolution of 0.60 × 0.60 × 0.70 mm voxel size. MRI and three-dimensional (3D) histology volumes of plaques were registered. The registration matrix was applied to segmentations denoting LRNC and IPH in 3D histology to split plaque volumes in regions with and without LRNC and IPH.
  
  
  
  Five patients were included. Regarding volumes of LRNC identified by 3D histology, the average fat fraction by MRI was significantly higher inside LRNC than outside: 12.64 ± 0.2737% versus 9.294 ± 0.1762% (mean ± standard error of the mean [SEM]; P < 0.001). The same was true for IPH identified by 3D histology, R2* inside versus outside IPH was: 71.81 ± 1.276 s-1versus 56.94 ± 0.9095 s-1(mean ± SEM; P < 0.001). There was a strong correlation between the cumulative fat and the volume of LRNC from 3D histology (R2= 0.92) as well as between cumulative R2* and IPH (R2= 0.94).
  
  
  
  Quantitative mapping of fat and R2* from Dixon MRI reliably quantifies the extent of LRNC and IPH. Magn Reson Med 78:285-296, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
authors: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.|Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors: Sandeep
authors: S
authors: Koppal
authors: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.|Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.|SyntheticMR AB, Linköping, Sweden.
authors: Marcel
authors: M
authors: Warntjes
authors: School of Computing, University of Leeds, Leeds, United Kingdom.
authors: Jeremy
authors: J
authors: Swann
authors: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.|Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors: Petter
authors: P
authors: Dyverfeldt
authors: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.|Department of Radiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors: Johan
authors: J
authors: Kihlberg
authors: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.|KTH, Royal Institute of Technology, Stockholm, Sweden.
authors: Rodrigo
authors: R
authors: Moreno
authors: School of Computing, University of Leeds, Leeds, United Kingdom.
authors: Derek
authors: D
authors: Magee
authors: Division of Brain Sciences, Department of Medicine, Institute of Neurology, Imperial College, London, United Kingdom.
authors: Nicholas
authors: N
authors: Roberts
authors: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.|Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors: Helene
authors: H
authors: Zachrisson
authors: Department of Thoracic and Vascular Surgery, and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors: Claes
authors: C
authors: Forssell
authors: Department of Thoracic and Vascular Surgery, and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors: Toste
authors: T
authors: Länne
authors: Department of Pathology and Tumor Biology, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, United Kingdom.|Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
authors: Darren
authors: D
authors: Treanor
authors: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.|Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors: Ebo D
authors: ED
authors: de Muinck
mesh_terms: D000273:Adipose Tissue / Q000000981:diagnostic imaging / Q000378:metabolism* / Q000473:pathology*; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000378:metabolism; D002340:Carotid Artery Diseases / Q000000981:diagnostic imaging / Q000378:metabolism* / Q000473:pathology*; D006470:Hemorrhage / Q000000981:diagnostic imaging / Q000378:metabolism* / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D050356:Lipid Metabolism; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D057054:Molecular Imaging / Q000379:methods; D009336:Necrosis / Q000000981:diagnostic imaging / Q000378:metabolism / Q000473:pathology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted
chemical_list: D015415:Biomarkers
keywords: atherosclerosis; carotid artery; magnetic resonance imaging; quantitative mapping