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Article in English | WPRIM (Western Pacific) | ID: wpr-228631

ABSTRACT

OBJECTIVE: To analyze different fluid-fluid level features between benign and malignant bone tumors on magnetic resonance imaging (MRI). MATERIALS AND METHODS: This study was approved by the hospital ethics committee. We retrospectively analyzed 47 patients diagnosed with benign (n = 29) or malignant (n = 18) bone tumors demonstrated by biopsy/surgical resection and who showed the intratumoral fluid-fluid level on pre-surgical MRI. The maximum length of the largest fluid-fluid level and the ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane were investigated for use in distinguishing benign from malignant tumors using the Mann-Whitney U-test and a receiver operating characteristic (ROC) analysis. Fluid-fluid level was categorized by quantity (multiple vs. single fluid-fluid level) and by T1-weighted image signal pattern (high/low, low/high, and undifferentiated), and the findings were compared between the benign and malignant groups using the chi2 test. RESULTS: The ratio of the maximum length of the largest fluid-fluid level to the maximum length of bone tumors in the sagittal plane that allowed statistically significant differentiation between benign and malignant bone tumors had an area under the ROC curve of 0.758 (95% confidence interval, 0.616-0.899). A cutoff value of 41.5% (higher value suggests a benign tumor) had sensitivity of 73% and specificity of 83%. CONCLUSION: The ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane may be useful to differentiate benign from malignant bone tumors.


Subject(s)
Adolescent , Adult , Aged , Child , Female , Humans , Male , Middle Aged , Young Adult , Area Under Curve , Bone Neoplasms/diagnosis , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Precancerous Conditions/diagnosis , ROC Curve , Retrospective Studies , Sensitivity and Specificity , Statistics, Nonparametric
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