Accuracy for detection of simulated lesions: Comparison of fluid-attenuated inversion-recovery, proton density-weighted, and T2-weighted synthetic brain MR imaging

Citation
Eh. Herskovits et al., Accuracy for detection of simulated lesions: Comparison of fluid-attenuated inversion-recovery, proton density-weighted, and T2-weighted synthetic brain MR imaging, AM J ROENTG, 176(5), 2001, pp. 1313-1318
Citations number
27
Categorie Soggetti
Radiology ,Nuclear Medicine & Imaging","Medical Research Diagnosis & Treatment
Journal title
AMERICAN JOURNAL OF ROENTGENOLOGY
ISSN journal
0361803X → ACNP
Volume
176
Issue
5
Year of publication
2001
Pages
1313 - 1318
Database
ISI
SICI code
0361-803X(200105)176:5<1313:AFDOSL>2.0.ZU;2-4
Abstract
OBJECTIVE. The objective of our study was to determine the effects of MR se quence (fluid-attenuated inversion-recovery [FLAIR], proton density-weighte d, and T2-weighted) and of lesion location an sensitivity and specificity o f lesion detection. MATERIALS AND METHODS. We generated FLAIR, proton density-weighted, and T2- weighted brain images with 3-mm lesions using published parameters for acut e multiple sclerosis plaques. Each image contained from zero to five lesion s that were distributed among cortical-subcortical, periventricular, and de ep white matter regions; on either side; and anterior or posterior in posit ion. We presented images of 540 lesions, distributed among 2592 image regio ns, to six neuroradiologists. We constructed a contingency table for image regions with lesions rind another for image regions without lesions (normal ). Each table included the following: the reviewer's number (1-6); the MR s equence; the side, position, and region of the lesion; and the reviewer's r esponse (lesion present or absent [normal]). We performed chi-square and lo g-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-lineal analysis cont ained an additional sequence-location interaction. The true-negative rate m odel 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 o f a wide range of pulse sequences and that allows us to spetify the locatio n, size, shape, and intrinsic characteristics of simulated lesions. We foun d 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.