Ying Wu1,2, Hongyan Du3, Fiona
Malone1, Shawn Sidharthan1, Ann Ragin4,
Robert Edelman1,5
1Radiology, NorthShore University
HealthSystem, Evanston, IL, United States; 2Radiology , University
of Chicago; 3NorthShore University HealthSystem Research
Institute, IL, United States; 4Radiology, Northwestern University;
5Radiology, University of Chicago
This
investigation compared the standard manual region of interest approach with a
volume-of-interest analysis based on automated brain segmentation. Analysis based on automated VOI
successfully detected subtle changes in tissue contrast and was consistently
informative for MR sequence optimization. Results based on the standard ROI
approach were ambiguous in different brain regions and individuals, and
failed to document changes in image quality when scanning parameters were
alternated in MR sequence optimization. These findings demonstrate the
potential benefit of integrating advanced quantitative image analysis into
sequence development routines to improve efficiency and accuracy.