Publication Details

AFRICAN RESEARCH NEXUS

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medicine

Relationship of temporal resolution to diagnostic performance for dynamic contrast enhanced MRI of the breast

Journal of Magnetic Resonance Imaging, Volume 30, No. 5, Year 2009

Purpose: To investigate the relationship between temporal resolution of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and classification of breast lesions as benign versus malignant. Materials and Methods: Patients underwent T1-weighted DCE MRI with 15 s/acquisition temporal resolution using 1.5 Tesla (n = 48) and 3.0T (n = 33) MRI scanners. Seventy-nine patients had pathologically proven diagnosis and 2 had 2 years follow-up showing no change in lesion size. The temporal resolution of DCE MRI was systematically reduced as a postprocessing step from 15 to 30, 45, and 60 s/acquisition by eliminating intermediate time points. Average wash-in and wash-out slopes, wash-out percentage changes, and kinetic curve shape (persistently enhancing, plateau, or wash-out) were compared for each temporal resolution. Logistic regression and receiver operating characteristic (ROC) curve analysis were used to compare kinetic parameters and diagnostic accuracy. Results: Sixty patients (74%) had malignant lesions and 21 patients (26%) had benign lesions. All temporal-resolution parameters significantly predicted benign versus malignant diagnosis (P < 0.05). However, 45 s/acquisition and higher temporal-resolution datasets showed higher accuracy than the 60 s/acquisition dataset by ROC curve analysis (0.72 versus 0.69 for average wash-in slope; 0.85 versus 0.82, for average wash-out slope; and 0.88 versus 0.80 for kinetic curve shape assessment, for 45 s/acquisition versus 60 s/acquisition temporal-resolution datasets, respectively (P = 0.027). Conclusion: DCE MRI data with at least 45-s temporal resolution maximized the agreement between the kinetic parameters and correct classification of benign versus malignant diagnosis. © 2009 Wiley-Liss, Inc.
Statistics
Citations: 175
Authors: 6
Affiliations: 3
Identifiers
Research Areas
Cancer
Study Design
Cohort Study