title: The Accuracy of ADC Measurements in Liver Is Improved by a Tailored and Computationally Efficient Local-Rigid Registration Algorithm.
abstract: This study describes post-processing methodologies to reduce the effects of physiological motion in measurements of apparent diffusion coefficient (ADC) in the liver. The aims of the study are to improve the accuracy of ADC measurements in liver disease to support quantitative clinical characterisation and reduce the number of patients required for sequential studies of disease progression and therapeutic effects. Two motion correction methods are compared, one based on non-rigid registration (NRA) using freely available open source algorithms and the other a local-rigid registration (LRA) specifically designed for use with diffusion weighted magnetic resonance (DW-MR) data. Performance of these methods is evaluated using metrics computed from regional ADC histograms on abdominal image slices from healthy volunteers. While the non-rigid registration method has the advantages of being applicable on the whole volume and in a fully automatic fashion, the local-rigid registration method is faster while maintaining the integrity of the biological structures essential for analysis of tissue heterogeneity. Our findings also indicate that the averaging commonly applied to DW-MR images as part of the acquisition protocol should be avoided if possible.
authors.affiliation: Centre for Imaging Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: Hossein
authors.initials: H
authors.lastname: Ragheb
authors.affiliation: Centre for Imaging Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: Neil A
authors.initials: NA
authors.lastname: Thacker
authors.affiliation: Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC, University Medical Centre Rotterdam, Netherlands.
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Guyader
authors.affiliation: Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC, University Medical Centre Rotterdam, Netherlands.
authors.forename: Stefan
authors.initials: S
authors.lastname: Klein
authors.affiliation: Cancer Research UK Imaging Centre, Institute of Cancer Research and Royal Marsden Hospital, Downs Road, Sutton, Surrey, United Kingdom.
authors.forename: Nandita M
authors.initials: NM
authors.lastname: deSouza
authors.affiliation: The Wolfson Molecular Imaging Centre, Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: Alan
authors.initials: A
authors.lastname: Jackson
mesh_terms: D000465:Algorithms; D066264:Datasets as Topic; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000473:pathology*; D008107:Liver Diseases / Q000473:pathology; D009038:Motion; D011522:Protons; D015203:Reproducibility of Results
chemical_list: D011522:Protons