Publication Type	Academic Article
Authors	Nguyen T, Zhang S, Gupta A, Zhao Y, Gauthier S, Wang Y
Journal	AJNR Am J Neuroradiol
Volume	39
Issue	5
Pagination	830-833
Date Published	03/08/2018
ISSN	1936-959X
Keywords	Algorithms, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Multiple Sclerosis
Abstract	We developed a robust automated algorithm called statistical detection of changes for detecting morphologic changes of multiple sclerosis lesions between 2 T2-weighted FLAIR brain images. Results from 30 patients showed that statistical detection of changes achieved significantly higher sensitivity and specificity (0.964, 95% CI, 0.823-0.994; 0.691, 95% CI, 0.612-0.761) than with the lesion-prediction algorithm (0.614, 95% CI, 0.410-0.784; 0.281, 95% CI, 0.228-0.314), while resulting in a 49% reduction in human review time (P = .007).
DOI	10.3174/ajnr.A5594
PubMed ID	29519791
PubMed Central ID	PMC5955764