OBJECTIVE: We determined the most accurate criteria for predicting malignancy of masses in the parotid gland using magnetization transfer ratios. SUBJECTS AND METHODS: Lesion-to-muscle magnetization transfer ratios obtained with a spoiled gradient-recalled acquisition in a steady state sequence with a 1-kHz off-resonance pulse were measured in 72 parotid masses (52 benign lesions, 20 malignant tumors). Various MR imaging findings and lesion-to-muscle magnetization transfer ratios were simultaneously assessed using a logistic model to determine the useful factors for predicting malignancy. We also studied the clinical usage of magnetization transfer ratios. RESULTS: Of the MR imaging findings, poorly defined margins showed the highest accuracy, 81%, with 60% sensitivity and 88% specificity. Of the lesion-to-muscle magnetization transfer ratios, a ratio of greater than 0.71 was most accurate (85%), with 90% sensitivity and 83% specificity. All four recurrent tumors and 10 (91%) of 11 secondary tumors were correctly diagnosed using the magnetization transfer ratio analysis. The logistic model revealed that the margin characteristics (p = 0.084) and lesion-to-muscle magnetization transfer ratios (p < 0.001) were statistically significant predictors for malignancy. A combined criteria of poorly defined margins and a lesion-to-muscle magnetization transfer ratio of greater than 0.71 raised the accuracy to 86% and specificity to 96%, but the sensitivity decreased to 60%. CONCLUSION: A combination of MR imaging findings and lesion-to-muscle magnetization transfer ratios was the most accurate predictor of malignancy.
OBJECTIVE: We determined the most accurate criteria for predicting malignancy of masses in the parotid gland using magnetization transfer ratios. SUBJECTS AND METHODS: Lesion-to-muscle magnetization transfer ratios obtained with a spoiled gradient-recalled acquisition in a steady state sequence with a 1-kHz off-resonance pulse were measured in 72 parotid masses (52 benign lesions, 20 malignant tumors). Various MR imaging findings and lesion-to-muscle magnetization transfer ratios were simultaneously assessed using a logistic model to determine the useful factors for predicting malignancy. We also studied the clinical usage of magnetization transfer ratios. RESULTS: Of the MR imaging findings, poorly defined margins showed the highest accuracy, 81%, with 60% sensitivity and 88% specificity. Of the lesion-to-muscle magnetization transfer ratios, a ratio of greater than 0.71 was most accurate (85%), with 90% sensitivity and 83% specificity. All four recurrent tumors and 10 (91%) of 11 secondary tumors were correctly diagnosed using the magnetization transfer ratio analysis. The logistic model revealed that the margin characteristics (p = 0.084) and lesion-to-muscle magnetization transfer ratios (p < 0.001) were statistically significant predictors for malignancy. A combined criteria of poorly defined margins and a lesion-to-muscle magnetization transfer ratio of greater than 0.71 raised the accuracy to 86% and specificity to 96%, but the sensitivity decreased to 60%. CONCLUSION: A combination of MR imaging findings and lesion-to-muscle magnetization transfer ratios was the most accurate predictor of malignancy.