학술논문
Errors in Quantitative Image Analysis due to Platform-Dependent Image Scaling
Document Type
article
Author
Chenevert, Thomas L; Malyarenko, Dariya I; Newitt, David; Li, Xin; Jayatilake, Mohan; Tudorica, Alina; Fedorov, Andriy; Kikinis, Ron; Liu, Tiffany Ting; Muzi, Mark; Oborski, Matthew J; Laymon, Charles M; Li, Xia; Thomas, Yankeelov; Jayashree, Kalpathy-Cramer; Mountz, James M; Kinahan, Paul E; Rubin, Daniel L; Fennessy, Fiona; Huang, Wei; Hylton, Nola; Ross, Brian D
Source
Translational Oncology. 7(1)
Subject
Language
Abstract
PurposeTo 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.MethodsA 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.ResultsImages 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.ConclusionCorrective actions for image scaling are suggested for manufacturers and quantitative imaging community.