NIMG-83. MULTIMODAL PET/MRI RADIOMICS AND CLINICAL PARAMETERS FOR OVERALL SURVIVAL PREDICTION IN PATIENTS WITH IDH WILDTYPE GLIOBLASTOMA. (14th November 2022)
- Record Type:
- Journal Article
- Title:
- NIMG-83. MULTIMODAL PET/MRI RADIOMICS AND CLINICAL PARAMETERS FOR OVERALL SURVIVAL PREDICTION IN PATIENTS WITH IDH WILDTYPE GLIOBLASTOMA. (14th November 2022)
- Main Title:
- NIMG-83. MULTIMODAL PET/MRI RADIOMICS AND CLINICAL PARAMETERS FOR OVERALL SURVIVAL PREDICTION IN PATIENTS WITH IDH WILDTYPE GLIOBLASTOMA
- Authors:
- Gutsche, Robin
Bauer, Elena
Kocher, Martin
Werner, Jan-Michael
Fink, Gereon
Shah, Nadim
Langen, Karl-Josef
Galldiks, Norbert
Lohmann, Philipp - Abstract:
- Abstract: BACKGROUND: Currently, most radiomics studies on survival prediction in brain tumor patients are based on MRI only. The goal of our study was to evaluate multimodal radiomics derived from amino acid PET/MRI and clinical parameters for survival prediction in patients with newly diagnosed IDH wildtype glioblastoma. METHODS: Sixty-three patients with newly diagnosed IDH wildtype glioblastoma were evaluated retrospectively. At initial diagnosis, all patients underwent structural MRI and O-(2-[ 18 F]fluoroethyl)-L-tyrosine (FET) PET. Tumor volumes were automatically segmented using a deep learning-based tool followed by visual inspection. Predefined and deep radiomics features were extracted from both imaging modalities. Feature repeatability analyses and feature selection were performed to avoid overfitting. Cox regression models for overall survival were built from clinical parameters such as age or the extent of resection, radiomics features, and combinations thereof, and finally validated using 5-fold cross-validation. Further evaluation of the model in an external test dataset is ongoing. RESULTS: The median overall survival was 12 months (range, 0-64 months). Higher age and larger FET PET tumor volumes were significantly correlated with shorter overall survival (age, r=-0.39, p< 0.001; volume, r=-0.31, p< 0.05). Models solely based on predefined FET PET or MRI radiomics features showed a similar mean concordance index (C-index) as the model based on clinicalAbstract: BACKGROUND: Currently, most radiomics studies on survival prediction in brain tumor patients are based on MRI only. The goal of our study was to evaluate multimodal radiomics derived from amino acid PET/MRI and clinical parameters for survival prediction in patients with newly diagnosed IDH wildtype glioblastoma. METHODS: Sixty-three patients with newly diagnosed IDH wildtype glioblastoma were evaluated retrospectively. At initial diagnosis, all patients underwent structural MRI and O-(2-[ 18 F]fluoroethyl)-L-tyrosine (FET) PET. Tumor volumes were automatically segmented using a deep learning-based tool followed by visual inspection. Predefined and deep radiomics features were extracted from both imaging modalities. Feature repeatability analyses and feature selection were performed to avoid overfitting. Cox regression models for overall survival were built from clinical parameters such as age or the extent of resection, radiomics features, and combinations thereof, and finally validated using 5-fold cross-validation. Further evaluation of the model in an external test dataset is ongoing. RESULTS: The median overall survival was 12 months (range, 0-64 months). Higher age and larger FET PET tumor volumes were significantly correlated with shorter overall survival (age, r=-0.39, p< 0.001; volume, r=-0.31, p< 0.05). Models solely based on predefined FET PET or MRI radiomics features showed a similar mean concordance index (C-index) as the model based on clinical parameters (C-indices, 0.68±0.04; 0.64±0.03; and 0.69±0.08, respectively). Multimodal radiomics based on predefined and deep features yielded improved C-indices of 0.75±0.06 and 0.72±0.09, respectively. A model based on multimodal radiomics and clinical parameters achieved the best prognostic performance (C-index, 0.80±0.04). CONCLUSION: Our results suggest an added clinical value of multimodal FET PET/MRI radiomics with clinical parameters for the non-invasive survival prediction in patients with IDH wildtype glioblastoma. … (more)
- Is Part Of:
- Neuro-oncology. Volume 24(2022)Supplement 7
- Journal:
- Neuro-oncology
- Issue:
- Volume 24(2022)Supplement 7
- Issue Display:
- Volume 24, Issue 7 (2022)
- Year:
- 2022
- Volume:
- 24
- Issue:
- 7
- Issue Sort Value:
- 2022-0024-0007-0000
- Page Start:
- vii184
- Page End:
- vii184
- Publication Date:
- 2022-11-14
- Subjects:
- Brain Neoplasms -- Periodicals
Brain -- Tumors -- Periodicals
Brain -- Cancer -- Periodicals
Nervous system -- Cancer -- Periodicals
616.99481 - Journal URLs:
- http://neuro-oncology.dukejournals.org/ ↗
http://neuro-oncology.oxfordjournals.org/ ↗
http://www.oxfordjournals.org/content?genre=journal&issn=1522-8517 ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/neuonc/noac209.701 ↗
- Languages:
- English
- ISSNs:
- 1522-8517
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.288000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24899.xml