Abstract
Purpose: Histograms can be determined throughout tumors, relying partly on existing tumor microstructure knowledge and the sampling effect from area of interest analyses. We aimed to investigate the impact of ADC histogram parameters in discriminating medulloblastoma, ependymoma, and pilocytic astrocytoma.
Methods: This study received approval from the Institutional Ethics Review Committee of Children’s Hospital 02. Processes were conducted according to relevant laws and regulations, and requirements for written informed consent were fulfilled. The study involved 24 patients at Children’s Hospital 02 from February–December 2019. Group 1 included 12 children with medulloblastoma, group 2 included 5 with ependymoma, and group 3 included 7 with pilocytic astrocytoma. All patients underwent MRI followed by surgery or biopsy to obtain histopathological confirmations.
Results: Our analysis indicated that AUC, sensitivity, and specificity were 96.7%, 91.7%, and 100%, respectively when ADCkurtosis (cut-off point = 2.34) was taken to differentiate between medulloblastomas and ependymomas. To distinguish between medulloblastomas and pilocytic astrocytomas, the cut-off points of ADCmean, ADCmedian, ADCmax, ADCmin, rADCmean, rADCmax, and rADCmin of 0.985, 0.910, 1.305, 0.710, 1.349, 1.738, and 1.251, were taken respectively with AUC, sensitivity, and specificity elicited at 100%. To discriminate between ependymomas and pilocytic astrocytomas, the cut-off points of ADCmean, ADCmedian, ADCmax, ADCmin, rADCmean, rADCmedian, rADCmax and rADCmin were 1.010, 0.930, 1.270, 0.735, 1.346, 1.324, 1.676, and 1.273, respectively, with AUC, sensitivity, and specificity at 100%.
Conclusion: ADC histograms can facilitate differentiation among juvenile medulloblastoma, ependymoma, and pilocytic astrocytoma, providing reliable, objective evidence of tumor differentiation.
