AI Summary & Key Takeaways
AI InsightADC10 has the potential to be the most significant parameter for predicting malignant orbital tumors.
📌 3 Key Takeaways
Abstract
We aimed to evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps for differentiating benign and malignant orbital tumors. METHODS Fifty-two patients with orbital tumors were enrolled from March 2013 to November 2014. Pretreatment diffusion-weighted imaging was performed on a 3T magnetic resonance scanner with b factors of 0 and 800 s/mm2 , and the corresponding ADC maps were generated. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including ADCmean, ADCmedian, standard deviation (SD), skewness, kurtosis, quartile, ADC10, ADC25, ADC75, and ADC90. Histogram parameter differences between benign and malignant orbital tumors were compared. The diagnostic value of each significant parameter in predicting malignant tumors was established. RESULTS Age, ADCmean, ADCmedian, quartile, kurtosis, ADC10, ADC25, ADC75, and ADC90 parameters were significantly different between benign and malignant orbital tumor groups, while gender, location, SD, and skewness were not significantly different. The best diagnostic performance in predicting malignant orbital tumors was achieved at the threshold of ADC10=0.990 (AUC, 0.997; sensitivity, 96.2%; specificity, 100%). CONCLUSION Histogram analysis of ADC maps holds promise for differentiating benign and malignant orbital tumors. ADC10 has the potential to be the most significant parameter for predicting malignant orbital tumors.