Hiroyuki Tatekawa1,2,3,4, Hiroyuki Uetani2,5, Akifumi Hagiwara1,2,6,4, Shadfar Bahri7, Catalina Raymond1,2,4, Albert Lai8,9, Timothy F Cloughesy8,9, Phioanh L Nghiemphu8,9, Linda M Liau8,10, Whitney B Pope2, Noriko Salamon2, Benjamin M Ellingson11,12,13,14. 1. UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. 2. Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. 3. Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan. 4. Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, USA. 5. Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan. 6. Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan. 7. Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA. 8. UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. 9. Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. 10. Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. 11. UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. bellingson@mednet.ucla.edu. 12. Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. bellingson@mednet.ucla.edu. 13. UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. bellingson@mednet.ucla.edu. 14. Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, USA. bellingson@mednet.ucla.edu.
Abstract
OBJECTIVE: The association of overall survival (OS) with tumor burden, including contrast enhanced (CE) volume on CE T1-weighted images, fluid-attenuated inversion recovery (FLAIR) hyperintense volume, and 3, 4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) hypermetabolic volume, in isocitrate dehydrogenase (IDH) wild-type gliomas remains unclear. This study aimed to assess the association between biological tumor burden in pre- and post-operative status and OS in IDH wild-type gliomas, and evaluated which volume was the best predictor of OS. METHODS: Thirty-four patients with treatment-naïve IDH wild-type gliomas (WHO grade II 6, III 15, IV 13) were retrospectively included. Three pre-operative tumor regions of interest (ROIs) were segmented based on the CE, FLAIR hyperintense, and FDOPA hypermetabolic regions. Resected ROIs were segmented from the post-operative images. Residual CE, FLAIR hyperintense, and FDOPA hypermetabolic ROIs were created by subtracting resected ROIs from pre-operative ROIs. Cox regression analysis was conducted to investigate the association of OS with the volume of each ROI, and Akaike information criterion was used to assess the fitness. RESULTS: Residual CE volume had a significant association with OS [hazard ratio (HR) = 1.26, p = 0.039], but this effect disappeared when controlling for tumor grade. Residual FDOPA hypermetabolic volume best fit the regression model and was significantly associated with OS (HR = 1.18, p = 0.008), even when controlling for tumor grade. FLAIR hyperintense volume showed no significant association with OS. CONCLUSION: Residual FDOPA hypermetabolic burden predicted OS for IDH wild-type gliomas, regardless of the tumor grade. Furthermore, removing hypermetabolic and CE regions may improve the prognosis.
OBJECTIVE: The association of overall survival (OS) with tumor burden, including contrast enhanced (CE) volume on CE T1-weighted images, fluid-attenuated inversion recovery (FLAIR) hyperintense volume, and 3, 4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) hypermetabolic volume, in isocitrate dehydrogenase (IDH) wild-type gliomas remains unclear. This study aimed to assess the association between biological tumor burden in pre- and post-operative status and OS in IDH wild-type gliomas, and evaluated which volume was the best predictor of OS. METHODS: Thirty-four patients with treatment-naïve IDH wild-type gliomas (WHO grade II 6, III 15, IV 13) were retrospectively included. Three pre-operative tumor regions of interest (ROIs) were segmented based on the CE, FLAIR hyperintense, and FDOPA hypermetabolic regions. Resected ROIs were segmented from the post-operative images. Residual CE, FLAIR hyperintense, and FDOPA hypermetabolic ROIs were created by subtracting resected ROIs from pre-operative ROIs. Cox regression analysis was conducted to investigate the association of OS with the volume of each ROI, and Akaike information criterion was used to assess the fitness. RESULTS: Residual CE volume had a significant association with OS [hazard ratio (HR) = 1.26, p = 0.039], but this effect disappeared when controlling for tumor grade. Residual FDOPA hypermetabolic volume best fit the regression model and was significantly associated with OS (HR = 1.18, p = 0.008), even when controlling for tumor grade. FLAIR hyperintense volume showed no significant association with OS. CONCLUSION: Residual FDOPA hypermetabolic burden predicted OS for IDH wild-type gliomas, regardless of the tumor grade. Furthermore, removing hypermetabolic and CE regions may improve the prognosis.
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