Prediction of Prognosis in Glioblastoma Using Radiomics Features of Dynamic Contrast-Enhanced MRI

• Published in: Korean journal of radiology Vol. 22; no. 9; pp. 1514 - 1524
• Main Authors: Pak, Elena, Choi, Kyu Sung, Choi, Seung Hong, Park, Chul-Kee, Kim, Tae Min, Park, Sung-Hye, Lee, Joo Ho, Lee, Soon-Tae, Hwang, Inpyeong, Yoo, Roh-Eul, Kang, Koung Mi, Yun, Tae Jin, Kim, Ji-Hoon, Sohn, Chul-Ho
• Format: Journal Article
• Language: English
• Published: Seoul The Korean Society of Radiology 01-09-2021; 대한영상의학회
• Subjects: Medical prognosis; Neuroimaging and Head & Neck; Permeability; Pharmacokinetics; Tumors; 방사선과학
• ISSN: 1229-6929; 2005-8330
• DOI: 10.3348/kjr.2020.1433

Objective To develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma. Materials and Methods One hundred and fifty patients (92 male [61.3%]; mean age ± standard deviation, 60.5 ± 13.5 years) with glioblastoma who underwent preoperative MRI were enrolled in the study. Six hundred and forty-two radiomic features were extracted from volume transfer constant (Ktrans), fractional volume of vascular plasma space (Vp), and fractional volume of extravascular extracellular space (Ve) maps of DCE MRI, wherein the regions of interest were based on both T1-weighted contrast-enhancing areas and non-enhancing T2 hyperintense areas. Using feature selection algorithms, salient radiomic features were selected from the 642 features. Next, a radiomics risk score was developed using a weighted combination of the selected features in the discovery set (n = 105); the risk score was validated in the validation set (n = 45) by investigating the difference in prognosis between the “radiomics risk score” groups. Finally, multivariable Cox regression analysis for progression-free survival was performed using the radiomics risk score and clinical variables as covariates. Results 16 radiomic features obtained from non-enhancing T2 hyperintense areas were selected among the 642 features identified. The radiomics risk score was used to stratify high- and low-risk groups in both the discovery and validation sets (both pp = 0.004 and hazard ratio, 0.34; p = 0.022, respectively). Conclusion We developed and validated the “radiomics risk score” from the features of DCE MRI based on non-enhancing T2 hyperintense areas for risk stratification of patients with glioblastoma. It was associated with progression-free survival independently of IDH mutation status.