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Dynamic contrast-enhanced MRI of orbital and anterior visual pathway lesions.
Magnetic Resonance Imaging 2018 September
PURPOSE: The accurate diagnosis of orbital and anterior visual pathway lesions has clinical significance. We determined whether dynamic contrast-enhanced MRI could differentiate benign from malignant lesions and compared model-independent and model-dependent methods of data analysis.
METHODS: We retrospectively reviewed dynamic contrast-enhanced MRI studies of 37 enhancing orbital and anterior visual pathway lesions. The data were processed using model-independent analysis and model-dependent analysis using a 2-compartment pharmacokinetic model. The time-signal intensity curve and semiquantitative parameters from the model-independent method (area under the curve [AUC] after the initial 60, 90, and 120 s; time to peak; maximum signal enhancement ratio; maximum slope of increase; and washout ratio) and the quantitative parameters from the model-dependent method (Ktrans , kep , and ve ) were derived for comparison with pathologic diagnoses.
RESULTS: The time-signal intensity curves demonstrated different perfusion characteristics and were classified into 4 types. All the lesions that demonstrated curve types 1 and 4 were benign, while type 3 lesions were significantly associated with malignancy (P = 0.001). AUC60 , AUC90 , AUC120 , and kep were significantly lower in benign lesions than in malignant lesions (P = 0.020, 0.018, 0.015, and 0.018, respectively). Receiver operating characteristic analysis indicated that AUC120 yielded the best diagnostic accuracy (area under the curve, 0.80; 95% CI, 0.64-0.96) in differentiating between benign and malignant lesions.
CONCLUSIONS: Dynamic contrast-enhanced MRI is useful in evaluating orbital and anterior visual pathway lesions. The model-independent analysis method is equivalent to the model-dependent method in differentiating benign from malignant lesions.
METHODS: We retrospectively reviewed dynamic contrast-enhanced MRI studies of 37 enhancing orbital and anterior visual pathway lesions. The data were processed using model-independent analysis and model-dependent analysis using a 2-compartment pharmacokinetic model. The time-signal intensity curve and semiquantitative parameters from the model-independent method (area under the curve [AUC] after the initial 60, 90, and 120 s; time to peak; maximum signal enhancement ratio; maximum slope of increase; and washout ratio) and the quantitative parameters from the model-dependent method (Ktrans , kep , and ve ) were derived for comparison with pathologic diagnoses.
RESULTS: The time-signal intensity curves demonstrated different perfusion characteristics and were classified into 4 types. All the lesions that demonstrated curve types 1 and 4 were benign, while type 3 lesions were significantly associated with malignancy (P = 0.001). AUC60 , AUC90 , AUC120 , and kep were significantly lower in benign lesions than in malignant lesions (P = 0.020, 0.018, 0.015, and 0.018, respectively). Receiver operating characteristic analysis indicated that AUC120 yielded the best diagnostic accuracy (area under the curve, 0.80; 95% CI, 0.64-0.96) in differentiating between benign and malignant lesions.
CONCLUSIONS: Dynamic contrast-enhanced MRI is useful in evaluating orbital and anterior visual pathway lesions. The model-independent analysis method is equivalent to the model-dependent method in differentiating benign from malignant lesions.
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