Hiroyuki Tatekawa1,2,3, Hiroyuki Uetani2, Akifumi Hagiwara1,2,4, Jingwen Yao1,2,5, Talia C Oughourlian1,2,6, Issei Ueda2, Catalina Raymond1,2, Albert Lai7,8, Timothy F Cloughesy7,8, Phioanh L Nghiemphu7,8, Linda M Liau7,9, Shadfar Bahri10, Whitney B Pope2, Noriko Salamon2, Benjamin M Ellingson11,12,13,14,15. 1. UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA. 2. Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. 3. Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan. 4. Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan. 5. Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, CA, USA. 6. Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. 7. UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. 8. Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. 9. Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. 10. Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. 11. UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA. bellingson@mednet.ucla.edu. 12. Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu. 13. Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu. 14. Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu. 15. UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
Abstract
PURPOSE: Although tumor localization and 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas. METHODS: Fifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping. RESULTS: Superimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula. CONCLUSION: Radiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.
PURPOSE: Although tumor localization and 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas. METHODS: Fifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping. RESULTS: Superimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula. CONCLUSION: Radiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.
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