. 2021 May;152(3):573-582.

doi: 10.1007/s11060-021-03730-w. Epub 2021 Mar 11.

Preferential tumor localization in relation to ¹⁸F-FDOPA uptake for lower-grade gliomas

Hiroyuki Tatekawa^{1

2

3}, Hiroyuki Uetani², Akifumi Hagiwara^{1

2

4}, Jingwen Yao^{1

2

5}, Talia C Oughourlian^{1

2

6}, Issei Ueda², Catalina Raymond^{1

2}, Albert Lai^{7

8}, Timothy F Cloughesy^{7

8}, Phioanh L Nghiemphu^{7

8}, Linda M Liau^{7

9}, Shadfar Bahri¹⁰, Whitney B Pope², Noriko Salamon², Benjamin M Ellingson^{11

12

13

14

15}

Affiliations

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.

PMID: 33704629
PMCID: PMC8221401
DOI: 10.1007/s11060-021-03730-w

Preferential tumor localization in relation to ¹⁸F-FDOPA uptake for lower-grade gliomas

Hiroyuki Tatekawa et al. J Neurooncol. 2021 May.

. 2021 May;152(3):573-582.

doi: 10.1007/s11060-021-03730-w. Epub 2021 Mar 11.

Authors

Affiliations

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.

PMID: 33704629
PMCID: PMC8221401
DOI: 10.1007/s11060-021-03730-w

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.

Keywords: Analysis of differential involvement; FDOPA PET; Lower-grade glioma; Radiographic atlas.

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Conflict of interest statement

Conflicts of interest

Ellingson—Advisory Board— Hoffman La-Roche; Siemens; Nativis; Medicenna; MedQIA; Bristol-Myers Squibb; Imaging Endpoints; Agios. Paid Consultant—Nativis; MedQIA; Siemens; Hoffman La-Roche; Imaging Endpoints; Medicenna; Agios. Grant Funding—Hoffman La-Roche; Siemens; Agios; Janssen. Ellingson also holds a patent on this technology (US Patent #15/577,664; International PCT/US2016/034886). Cloughesy—Advisory Board—Roche/Genentech, Amgen, Tocagen, NewGen, LPath, Proximagen, Celgene, Vascular Biogenics Ltd, Insys, Agios, Cortice Bioscience, Pfizer, Human Longevity, BMS, Merck, Notable Lab, MedQIA.

Figures

**Fig. 1**
Overview of post-processing of MR and PET images. FLAIR and FDOPA images, as well as FLAIR hyperintense ROIs, are registered to the post-contrast T1-weighted images for each patient. Each registered ROI is applied to the corresponding PET images, and maximum nSUV and biological tumor volume within the ROI are calculated. Each registered ROI is then registered to a T1-weighted brain atlas (MNI152) using SPM12. The registered ROI in the left hemisphere is flipped to the right hemisphere in the MNI space. All ROIs in the MNI space are superimposed to create a voxel-wise frequency map for each group

**Fig. 2**
Atlas of tumor locations. Voxel-wise frequency of tumor occurrence for FDOPA hypometabolic (n = 14, nSUV_max < 1) and hypermetabolic LGGs (n = 37, nSUV_max > 1). a) Frequency of tumor occurrence for FDOPA hypometabolic LGG patients. b) Frequency of tumor occurrence for FDOPA hypermetabolic LGG patients. Note: All ROIs in the left hemisphere are flipped to the right hemisphere

**Fig. 3**
ADIFFI statistical analysis isolates two spatially distinct clusters. ADIFFI statistical analysis illustrates a) a significant cluster occurring in the frontal lobe for FDOPA hypometabolic LGGs (nSUV_max < 1), and b) a significant cluster occurring at a high frequency in the insular to putamen for FDOPA hypermetabolic LGGs (nSUV_max > 1)

**Fig. 4**
The Kaplan-Meier plots and log-rank test show significant differences in overall survival between FDOPA hypometabolic and hypermetabolic LGGs

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Preferential tumor localization in relation to ¹⁸F-FDOPA uptake for lower-grade gliomas

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Preferential tumor localization in relation to ¹⁸F-FDOPA uptake for lower-grade gliomas

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