Diffusion tensor imaging of the median nerve at 3.0 T using different MR scanners: Agreement of FA and ADC measurements

Department of Radiology, University Hospital, Raemistrasse 100, Zurich, 8091, Switzerland. Electronic address: .
European journal of radiology (Impact Factor: 2.16). 06/2013; 82(10). DOI: 10.1016/j.ejrad.2013.05.011
Source: PubMed

ABSTRACT OBJECTIVE: To assess the agreement of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of the median nerve on 3.0T MR scanners from different vendors. MATERIALS AND METHODS: IRB approved study including 16 healthy volunteers (9 women; mean age 30.6±5.3 years). Diffusion tensor imaging (DTI) of the dominant wrist was performed on three 3.0T MR scanners (GE, Siemens, Philips) using similar imaging protocols and vendor-proprietary hard- and software. Intra-, inter-reader and inter-vendor agreements were assessed. RESULTS: ICCs for intra-/inter-reader agreements ranged from 0.843-0.970/0.846-0.956 for FA, and 0.840-0.940/0.726-0.929 for ADC, respectively. ANOVA analysis identified significant differences for FA/ADC measurements among vendors (p<0.001/p<0.01, respectively). Overall mean values for FA were 0.63 (SD±0.1) and 0.999x10(-3)mm(2)/s (SD±0.134x10(-3)) for ADC. A significant negative measurement bias was found for FA values from the GE scanner (-0.05 and -0.07) and for ADC values from the Siemens scanner (-0.053 and -0.063x10(-3)mm(2)/s) as compared to the remainder vendors CONCLUSION: FA and ADC values of the median nerve obtained on different 3.0T MR scanners differ significantly, but are in comparison to the standard deviation of absolute values small enough to not have an impact on larger group studies or when substantial diffusion changes can be expected. However, caution is warranted in an individual patient when interpreting diffusion values from different scanner acquisitions.

1 Follower
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.
    PLoS ONE 03/2014; 9(3):e92069. DOI:10.1371/journal.pone.0092069 · 3.53 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: MR imaging of peripheral nerves, typically referred to as MR neurography, is a rapidly evolving technique that currently is drawing huge attention, both in research and in clinical settings. Both training and experience are necessary to detect the sometimes subtle findings and to avoid misinterpretation of abnormalities. This review article is intended to help radiologists with image evaluation and interpretation. Typical pitfalls are discussed as well as strategies to avoid them. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
    Seminars in musculoskeletal radiology 04/2015; 19(2):94-102. DOI:10.1055/s-0035-1546301 · 0.95 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this study was to evaluate whether anterior cruciate ligament (ACL) and ACL graft could be imaged using diffusion tensor imaging (DTI) and to provide the DTI metrics for ACL and grafts. Magnetic resonance imaging and DTI were performed in 40 healthy volunteers and 15 patients with ACL reconstruction. Fiber tracking and other postprocessing steps were performed on the workstation. The fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of ACL and grafts were determined. The courses of ACL and grafts were analyzed quantitatively using FA and ADC, and tractography illustrated nicely the 3-dimensional courses of the fiber bundles and corresponded well to the known anatomy. There was no significant difference in the mean FA and ADC values of the sexes. Diffusion tensor imaging can be used to image and visualize the structure of ACL and ACL grafts.
    Journal of computer assisted tomography 03/2014; DOI:10.1097/RCT.0000000000000078 · 1.60 Impact Factor