Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms

被引:66
|
作者
Tax, Chantal M. W. [1 ]
Grussu, Francesco [2 ,3 ]
Kaden, Enrico [3 ]
Ning, Lipeng [4 ]
Rudrapatna, Umesh [1 ]
Evans, C. John [1 ]
St-Jean, Samuel [5 ]
Leemans, Alexander [5 ]
Koppers, Simon [6 ,7 ,8 ]
Merhof, Dorit [8 ]
Ghosh, Aurobrata [3 ]
Tanno, Ryutaro [3 ,9 ]
Alexander, Daniel C. [3 ]
Zappala, Stefano [1 ]
Charron, Cyril [1 ]
Kusmia, Slawomir [1 ]
Linden, David E. J. [1 ]
Jones, Derek K. [1 ,10 ]
Veraart, Jelle [11 ,12 ]
机构
[1] Cardiff Univ, Sch Psychol, CUBRIC, Cardiff, S Glam, Wales
[2] UCL, Fac Brain Sci, UCL Queen Sq Inst Neurol, Queen Sq MS Ctr, London, England
[3] UCL, Dept Comp Sci, Ctr Med Image Comp, London, England
[4] Harvard Med Sch, Boston, MA 02115 USA
[5] Univ Med Ctr Utrecht, Image Sci Inst, Dept Radiol, Utrecht, Netherlands
[6] Univ Penn, Dept Radiol, Philadelphia, PA 19104 USA
[7] Childrens Hosp Philadelphia, Philadelphia, PA 19104 USA
[8] Rhein Westfal TH Aachen, Inst Imaging & Comp Vis, Aachen, Germany
[9] Microsoft Res Cambridge, Machine Intelligence & Percept Grp, Cambridge, England
[10] Australian Catholic Univ, Mary McKillop Inst Hlth Res, Melbourne, Vic, Australia
[11] NYU, New York, NY USA
[12] Univ Antwerp, Dept Phys, Imec Vis Lab, Antwerp, Belgium
基金
英国惠康基金; 英国工程与自然科学研究理事会; 比利时弗兰德研究基金会;
关键词
LINEAR LEAST-SQUARES; ROBUST ESTIMATION; MULTISITE; BRAIN; SIGNAL; REGISTRATION; DISTORTIONS; PARAMETERS; ARTIFACTS; MATRIX;
D O I
10.1016/j.neuroimage.2019.01.077
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Diffusion MRI is being used increasingly in studies of the brain and other parts of the body for its ability to provide quantitative measures that are sensitive to changes in tissue microstructure. However, inter-scanner and inter-protocol differences are known to induce significant measurement variability, which in turn jeopardises the ability to obtain 'truly quantitative measures' and challenges the reliable combination of different datasets. Combining datasets from different scanners and/or acquired at different time points could dramatically increase the statistical power of clinical studies, and facilitate multi-centre research. Even though careful harmonisation of acquisition parameters can reduce variability, inter-protocol differences become almost inevitable with improvements in hardware and sequence design over time, even within a site. In this work, we present a benchmark diffusion MRI database of the same subjects acquired on three distinct scanners with different maximum gradient strength (40, 80, and 300 mT/m), and with 'standard' and 'state-of-the-art' protocols, where the latter have higher spatial and angular resolution. The dataset serves as a useful testbed for method development in cross-scanner/cross-protocol diffusion MRI harmonisation and quality enhancement. Using the database, we compare the performance of five different methods for estimating mappings between the scanners and protocols. The results show that cross-scanner harmonisation of single-shell diffusion data sets can reduce the variability between scanners, and highlight the promises and shortcomings of today's data harmonisation techniques.
引用
收藏
页码:285 / 299
页数:15
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