Your browser doesn't support javascript.
loading
The Potential Use of Radiomics with Pre-Radiation Therapy MR Imaging in Predicting Risk of Pseudoprogression in Glioblastoma Patients.
Baine, Michael; Burr, Justin; Du, Qian; Zhang, Chi; Liang, Xiaoying; Krajewski, Luke; Zima, Laura; Rux, Gerard; Zhang, Chi; Zheng, Dandan.
Afiliação
  • Baine M; Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
  • Burr J; Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
  • Du Q; Department of Biological Science, University of Nebraska Lincoln, Lincoln, NE 68588, USA.
  • Zhang C; Department of Biological Science, University of Nebraska Lincoln, Lincoln, NE 68588, USA.
  • Liang X; Department of Radiation Oncology, University of Florida Proton Institute, Jacksonville, FL 32206, USA.
  • Krajewski L; Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
  • Zima L; Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
  • Rux G; Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
  • Zhang C; Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
  • Zheng D; Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
J Imaging ; 7(2)2021 Jan 28.
Article em En | MEDLINE | ID: mdl-34460616
Glioblastoma (GBM) is the most common adult glioma. Differentiating post-treatment effects such as pseudoprogression from true progression is paramount for treatment. Radiomics has been shown to predict overall survival and MGMT (methylguanine-DNA methyltransferase) promoter status in those with GBM. A potential application of radiomics is predicting pseudoprogression on pre-radiotherapy (RT) scans for patients with GBM. A retrospective review was performed with radiomic data analyzed using pre-RT MRI scans. Pseudoprogression was defined as post-treatment findings on imaging that resolved with steroids or spontaneously on subsequent imaging. Of the 72 patients identified for the study, 35 were able to be assessed for pseudoprogression, and 8 (22.9%) had pseudoprogression. A total of 841 radiomic features were examined along with clinical features. Receiver operating characteristic (ROC) analyses were performed to determine the AUC (area under ROC curve) of models of clinical features, radiomic features, and combining clinical and radiomic features. Two radiomic features were identified to be the optimal model combination. The ROC analysis found that the predictive ability of this combination was higher than using clinical features alone (mean AUC: 0.82 vs. 0.62). Additionally, combining the radiomic features with clinical factors did not improve predictive ability. Our results indicate that radiomics is potentially capable of predicting future development of pseudoprogression in patients with GBM using pre-RT MRIs.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Imaging Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Imaging Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos