Differences in tumour heterogeneity based on dynamic contrast-enhanced MRI between tumour and peritumoural stroma for predicting Ki-67 status of invasive ductal carcinoma

Discrimination between microcystic meningioma and atypical meningioma using whole-lesion apparent diffusion coefficient histogram analysis

AIM

To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in discriminating microcystic meningioma (MCM) from atypical meningioma (AM).

MATERIALS AND METHODS

Clinical and preoperative MRI data of 20 patients with MCM and 26 patients with AM were analysed retrospectively. Whole-lesion apparent diffusion coefficient (ADC) histogram analysis was performed on each patient's lesion to obtain histogram parameters, including mean, variance, skewness, kurtosis, the 1st (ADCp1), 10th (ADCp10), 50th (ADCp50), 90th (ADCp90), and 99th (ADCp99) percentiles of ADC. The differences between the ADC histogram parameters of the two tumours were compared, and the receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of statistically significant parameters in distinguishing the two tumours.

RESULTS

The mean, ADCp1, ADCp10, ADCp50, and ADCp90 of MCM were greater than those of AM, and significant differences were observed in these parameters between MCM and AM (all p<0.05). ROC analysis showed that the mean had the highest area under the curve value (AUC) in distinguishing the two tumours (AUC = 0.852), when using 120.46 × 10^-6 mm²/s as the optimal threshold, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for discriminating the two groups were 84.6%, 75%, 80.4%, 81.5%, and 78.9%, respectively.

CONCLUSION

Histogram analysis based on whole-lesion ADC maps was useful for discriminating between MCM from AM preoperatively, with the mean being the most promising potential parameter.