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Measurement of MRI scanner performance with the ADNI phantom
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10.1118/1.3116776
/content/aapm/journal/medphys/36/6/10.1118/1.3116776
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/36/6/10.1118/1.3116776

Figures

Image of FIG. 1.
FIG. 1.

ADNI phantom. A photograph of the internal components of the ADNI phantom is shown. Each of the spheres is filled with a copper sulfate solution. The colored spheres contain differing solution concentrations. The small inset provides a detailed view of a single sphere and postcomponent. A triplanar view of a phantom image acquired with the MP-RAGE used in the ADNI protocol is also shown.

Image of FIG. 2.
FIG. 2.

Qualitative evaluation of geometric performance. Plots of sphere position (vertical axes) versus displacement (horizontal axes) in each cardinal direction provide qualitative image distortion information. All lengths are measured in mm, and the position origin is MR scanner isocenter.

Image of FIG. 3.
FIG. 3.

Calibration exercise. Sets of plots with data before (left) and after (right) an exercise in scanner calibration are shown. After calibration, the dependence of position residuals (the horizontal axes in the subplots) on position (the vertical axes in the subplots) was greatly reduced. The two obvious outlier points in the versus subplots were due to manufacturing defects and subsequently repaired.

Image of FIG. 4.
FIG. 4.

Construction variability. Histograms of normalized phantom size for the initial 66 production phantoms used in the ADNI study are shown.

Image of FIG. 5.
FIG. 5.

Nonlinearity estimates. The dependence of the residual radius distribution for different orders of polynomial displacement field is shown for a scan with 2D (left) and 3D (middle) gradient warping corrections. In these plots, each horizontal row contains a histogram of 160 residual radii for a deformation field of given polynomial order (which is indicated on the vertical axes). The sizes of the boxes in the plots are proportional to the density of points. The rightmost plot presents the standard deviation of the distributions for data with 2D warping correction (open stars) and for 3D warping correction (solid red circles).

Image of FIG. 6.
FIG. 6.

Longitudinal tracking of individual scanner from vendor 2 with phantom measurements. The left panel demonstrates scale factors along each cardinal axis. The right panels show the standard deviation of residual radius (nonlinearity). The system was recalibrated in early and mid-2006 as well as mid-2007 when the system underwent an upgrade. After the upgrade, the standard deviation of residual radius metric for nonlinearity was decreased.

Image of FIG. 7.
FIG. 7.

Longitudinal tracking of individual scanner from vendor 3 with phantom measurements. The left panel demonstrates scale factors along each cardinal axis. The right panels show the standard deviation of residual radius (nonlinearity). Prior to mid-2007, the protocol for this vendor was errantly distributed with autoshimming disabled, a fact reflected in the larger variation in the scale factors. Note that the vertical range for the scale factor time course is larger than for other dimensions.

Image of FIG. 8.
FIG. 8.

Summary of scanner performance for more than 2200 phantom scans. A pooled-variance approach is used to estimate the stability of gradient performance factoring out discrete changes generally due to scanner recalibration. Symbols are plotted at the mean scale value over all values, and error bars indicate the square root of the pooled variance. System number is an arbitrary enumeration. calibration appears less consistent across scanners for vendor 1 than for other vendors. The per scanner error bars for vendor 3 are much larger than for other vendors and other directions. Scanners from vendor 2 are from two different models and the data are clustered by model in the mean scale factors.

Image of FIG. 9.
FIG. 9.

Use of phantom measurements to correct within-scanner linear scaling changes in human images. Histograms of intrasubject coregistration scale factors from scanners with and without phantom-based voxel size adjustment are shown. The upper (lower) histograms are without (with) correction. Correction reduces the widths of the distributions. The vertical dashed lines are located at 1.00, the ideal intrasubject scale factor.

Image of FIG. 10.
FIG. 10.

Use of phantom measurements to perform absolute scaling of human images across scanner. Histograms of intrasubject coregistration scale factors for image pairs with one scan acquired at and the other at are shown. The upper (lower) histograms are without (with) correction. Correction reduces the widths of the distributions.

Tables

Generic image for table
TABLE I.

Summary statistics for the scale factors in each of the cardinal directions are shown under various experimental conditions. AS indicates that data were acquired with autoshim enabled; “no AS” indicates data from vendor 3 with autoshim errantly disabled in the distributed protocol. “Matched phantoms” indicates that each image pair contributing to the underlying distribution was corrected against the same phantom. All data were acquired with autoshim enabled.

Generic image for table
TABLE II.

Representative values for standard deviation of residuals (mm) for systems used in ADNI are presented. Entries for scanners requiring different levels of gradient warping correction are included. Right and wrong corrections indicate that postprocessing was done using the right and wrong gradient warping coefficients for the actual system.

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/content/aapm/journal/medphys/36/6/10.1118/1.3116776
2009-05-13
2014-04-19
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Measurement of MRI scanner performance with the ADNI phantom
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/36/6/10.1118/1.3116776
10.1118/1.3116776
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