Multiparametric MRI texture analysis in prediction of glioma biomarker status: Added value of MR diffusion

Shingo Kihira, Nadejda M. Tsankova, Adam Bauer, Yu Sakai, Keon Mahmoudi, Nicole Zubizarreta, Jane Houldsworth, Fahad Khan, Noriko Salamon, Adilia Hormigo, Kambiz Nael

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Background. Early identification of glioma molecular phenotypes can lead to understanding of patient prognosis and treatment guidance. We aimed to develop a multiparametric MRI texture analysis model using a combination of conventional and diffusion MRI to predict a wide range of biomarkers in patients with glioma. Methods. In this retrospective study, patients were included if they (1) had diagnosis of gliomas with known IDH1, EGFR, MGMT, ATRX, TP53, and PTEN status from surgical pathology and (2) had preoperative MRI including FLAIR, T1c+ and diffusion for radiomic texture analysis. Statistical analysis included logistic regression and receiveroperating characteristic (ROC) curve analysis to determine the optimal model for predicting glioma biomarkers. A comparative analysis between ROCs (conventional only vs conventional + diffusion) was performed. Results. From a total of 111 patients included, 91 (82%) were categorized to training and 20 (18%) to test datasets. Constructed cross-validated model using a combination of texture features from conventional and diffusion MRI resulted in overall AUC/accuracy of 1/79% for IDH1, 0.99/80% for ATRX, 0.79/67% for MGMT, and 0.77/66% for EGFR. The addition of diffusion data to conventional MRI features significantly (P < .05) increased predictive performance for IDH1, MGMT, and ATRX. The overall accuracy of the final model in predicting biomarkers in the test group was 80% (IDH1), 70% (ATRX), 70% (MGMT), and 75% (EGFR). Conclusion. Addition of MR diffusion to conventional MRI features provides added diagnostic value in preoperative determination of IDH1, MGMT, and ATRX in patients with glioma.

Original languageEnglish
Article numbervdab051
JournalNeuro-Oncology Advances
Volume3
Issue number1
DOIs
StatePublished - 1 Jan 2021

Keywords

  • Glioma
  • MR diffusion
  • multiparametric MRI
  • radiogenomics
  • texture analysis

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