RATIONALE AND OBJECTIVES: The purpose of this study was to integrate contrast material kinetic and architectural data from magnetic resonance (MR) images and to assess the improvement in diagnostic accuracy. MATERIALS AND METHODS: MR imaging data from a diagnostic cohort of 100 patients (50 malignant and 50 benign cases) were analyzed. RESULTS: Qualitative classification of the enhancement curve was the most predictive kinetic feature. Receiver operating characteristic (ROC) curves were calculated for the architectural model alone and for the architectural model combined with the qualitative kinetic classification. The results demonstrated a statistically significant increase in ROC area (P = .03) of the combined model compared with that of the architectural model alone. CONCLUSION: The addition of qualitative classification of the time-signal intensity curve to an architectural interpretation model results in significant improvement in model performance as measured by the area under the ROC curve.
RATIONALE AND OBJECTIVES: The purpose of this study was to integrate contrast material kinetic and architectural data from magnetic resonance (MR) images and to assess the improvement in diagnostic accuracy. MATERIALS AND METHODS: MR imaging data from a diagnostic cohort of 100 patients (50 malignant and 50 benign cases) were analyzed. RESULTS: Qualitative classification of the enhancement curve was the most predictive kinetic feature. Receiver operating characteristic (ROC) curves were calculated for the architectural model alone and for the architectural model combined with the qualitative kinetic classification. The results demonstrated a statistically significant increase in ROC area (P = .03) of the combined model compared with that of the architectural model alone. CONCLUSION: The addition of qualitative classification of the time-signal intensity curve to an architectural interpretation model results in significant improvement in model performance as measured by the area under the ROC curve.
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