Errors in Quantitative Image Analysis due to Platform-Dependent Image Scaling.
To evaluate the ability of various software (SW) tools used for quantitative image analysis to properly account for source-specific image scaling employed by magnetic resonance imaging manufacturers.



A series of gadoteridol-doped distilled water solutions (0%, 0.5%, 1%, and 2% volume concentrations) was prepared for manual substitution into one (of three) phantom compartments to create "variable signal," whereas the other two compartments (containing mineral oil and 0.25% gadoteriol) were held unchanged. Pseudodynamic images were acquired over multiple series using four scanners such that the histogram of pixel intensities varied enough to provoke variable image scaling from series to series. Additional diffusion-weighted images were acquired of an ice-water phantom to generate scanner-specific apparent diffusion coefficient (ADC) maps. The resulting pseudodynamic images and ADC maps were analyzed by eight centers of the Quantitative Imaging Network using 16 different SW tools to measure compartment-specific region-of-interest intensity.



Images generated by one of the scanners appeared to have additional intensity scaling that was not accounted for by the majority of tested quantitative image analysis SW tools. Incorrect image scaling leads to intensity measurement bias near 100%, compared to nonscaled images.



Corrective actions for image scaling are suggested for manufacturers and quantitative imaging community.
Department of Radiology, University of Michigan, Ann Arbor, MI.
Thomas L
TL
Chenevert
Department of Radiology, University of Michigan, Ann Arbor, MI.
Dariya I
DI
Malyarenko
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
David
D
Newitt
Oregon Health & Science University, Portland, OR.
Xin
X
Li
Oregon Health & Science University, Portland, OR.
Mohan
M
Jayatilake
Oregon Health & Science University, Portland, OR.
Alina
A
Tudorica
Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Andriy
A
Fedorov
Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Ron
R
Kikinis
Stanford University, Stanford, CA.
Tiffany Ting
TT
Liu
University of Washington, Seattle, WA.
Mark
M
Muzi
University of Pittsburgh, Pittsburgh, PA.
Matthew J
MJ
Oborski
University of Pittsburgh, Pittsburgh, PA.
Charles M
CM
Laymon
Institute of Imaging Science, Vanderbilt University, Nashville, TN.
Xia
X
Li
Institute of Imaging Science, Vanderbilt University, Nashville, TN.
Yankeelov
Y
Thomas
Massachusetts General Hospital, Boston, MA.
Kalpathy-Cramer
KC
Jayashree
University of Pittsburgh, Pittsburgh, PA.
James M
JM
Mountz
University of Washington, Seattle, WA.
Paul E
PE
Kinahan
Stanford University, Stanford, CA.
Daniel L
DL
Rubin
Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Fiona
F
Fennessy
Oregon Health & Science University, Portland, OR.
Wei
W
Huang
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
Nola
N
Hylton
Department of Radiology, University of Michigan, Ann Arbor, MI.
Brian D
BD
Ross