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AJR 2001; 176:1313-1318
© American Roentgen Ray Society


Accuracy for Detection of Simulated Lesions

Comparison of Fluid-Attenuated Inversion-Recovery, Proton Density-Weighted, and T2-Weighted Synthetic Brain MR Imaging

Edward H. Herskovits1,2, Ryuta Itoh1,3 and Elias R. Melhem1,3,4

1 Division of Neuroradiology, The Johns Hopkins Medical Institutions, 600 N. Wolfe St., Baltimore, MD 21287-7619.
2 Department of Biostatistics, The Johns Hopkins School of Public Health, Baltimore, MD 21287.
3 The MR Perception Laboratory of The Kennedy Krieger Institute, Baltimore, MD 21287.
4 Department of Radiology, The Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287-2182.

OBJECTIVE. The objective of our study was to determine the effects of MR sequence (fluid-attenuated inversion-recovery [FLAIR], proton density-weighted, and T2-weighted) and of lesion location on sensitivity and specificity of lesion detection.

MATERIALS AND METHODS. We generated FLAIR, proton density-weighted, and T2-weighted brain images with 3-mm lesions using published parameters for acute multiple sclerosis plaques. Each image contained from zero to five lesions that were distributed among cortical-subcortical, periventricular, and deep white matter regions; on either side; and anterior or posterior in position. We presented images of 540 lesions, distributed among 2592 image regions, to six neuroradiologists. We constructed a contingency table for image regions with lesions and another for image regions without lesions (normal). Each table included the following: the reviewer's number (1-6); the MR sequence; the side, position, and region of the lesion; and the reviewer's response (lesion present or absent [normal]). We performed chisquare and log-linear analyses.

RESULTS. The FLAIR sequence yielded the highest true-positive rates (p < 0.001) and the highest true-negative rates (p < 0.001). Regions also differed in reviewers' true-positive rates (p < 0.001) and true-negative rates (p = 0.002). The true-positive rate model generated by log-linear analysis contained an additional sequence-location interaction. The true-negative rate model generated by log-linear analysis confirmed these associations, but no higher order interactions were added.

CONCLUSION. We developed software with which we can generate brain images of a wide range of pulse sequences and that allows us to specify the location, size, shape, and intrinsic characteristics of simulated lesions. We found that the use of FLAIR sequences increases detection accuracy for cortical-subcortical and periventricular lesions over that associated with proton density- and T2-weighted sequences.


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