Background: To develop a diagnostic tree analysis (DTA) model based on demographical information and conventional MRI for differential diagnosis of adult pilocytic astrocytomas (PAs) and high-grade gliomas (HGGs; World Health Organization grade III-IV). Methods: A total of 357 adult patients with pathologically confirmed PA (n = 65) and HGGs (n = 292) who underwent conventional MRI were included. The patients were randomly divided into training (n = 250) and validation (n = 107) datasets to assess the diagnostic performance of the DTA model. The DTA model was created using a classification and regression tree algorithm on the basis of demographical and MRI findings. Results: In the DTA model, tumor location (on cerebellum, brainstem, hypothalamus, optic nerve, or ventricle), cystic mass with mural nodule appearance, presence of infiltrative growth, and major axis (cutoff value, 2.9 cm) were significant predictors for differential diagnosis of adult PAs and HGGs. The AUC, accuracy, sensitivity, and specificity were 0.94 (95% confidence interval 0.86–1.00), 96.2%, 89.5%, and 97.7%, respectively, in the test set. The accuracy of the DTA model was significantly higher than the no-information rate in the test (96.2 % vs 85.0%, P < 0.001) set. Conclusion: The DTA model based on MRI findings may be useful for differential diagnosis of adult PA and HGGs.
|Journal||European Journal of Radiology|
|Publication status||Published - 2021 Oct|
Bibliographical noteFunding Information:
This research received funding from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies & Future Planning (2020R1A2C1003886). This research was also supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1I1A1A01071648).
© 2021 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging