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Ghezzi C, Ellingson BM, Lai A, Liu J, Barrio JR, Wright EM. Effect of Jardiance on glucose uptake into astrocytomas. J Neurooncol 2024; 169:437-444. [PMID: 39037688 DOI: 10.1007/s11060-024-04746-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 06/11/2024] [Indexed: 07/23/2024]
Abstract
PURPOSE SGLT2, the sodium glucose cotransporter two, is expressed in human pancreatic, prostate and brain tumors, and in a mouse cancer model SGLT2 inhibitors reduce tumor glucose uptake and growth. In this study we have measured the effect of a specific SGLT2 inhibitor, Jardiance® (Empagliflozin), on glucose uptake into astrocytomas in patients. METHODS We have used a specific SGLT glucose tracer, α-methyl-4-[18F]fluoro-4-deoxy-α-D-glucopyranoside (Me4FDG), and Positron Emission Tomography (PET) to measure glucose uptake. Four of five patients enrolled had WHO grade IV glioblastomas, and one had a low grade WHO Grade II astrocytoma. Two dynamic brain PET scans were conducted on each patient, one before and one after treatment with a single oral dose of Jardiance, a specific SGLT2 inhibitor. As a control, we also determined the effect of oral Jardiance on renal SGLT2 activity. RESULTS In all five patients an oral dose (25 or 100 mg) of Jardiance reduced Me4FDG tumor accumulation, highly significant inhibition in four, and inhibited SGLT2 activity in the kidney. CONCLUSIONS These initial experiments show that SGLT2 is a functional glucose transporter in astocytomas, and Jardiance inhibited glucose uptake, a drug approved by the FDA to treat type 2 diabetes mellitus (T2DM), heart failure, and renal failure. We suggest that clinical trials be initiated to determine whether Jardiance reduces astrocytoma growth in patients.
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Affiliation(s)
- Chiara Ghezzi
- Department of Physiology, The David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095-1751, USA
| | - Benjamin M Ellingson
- Department of Radiological Sciences, The David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Albert Lai
- Department of Neurology, The David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Jie Liu
- Department of Molecular and Medical Pharmacology, The David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Jorge R Barrio
- Department of Molecular and Medical Pharmacology, The David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Ernest M Wright
- Department of Physiology, The David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095-1751, USA.
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2
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Castello A, Castellani M, Florimonte L, Ciccariello G, Mansi L, Lopci E. PET radiotracers in glioma: a review of clinical indications and evidence. Clin Transl Imaging 2022. [DOI: 10.1007/s40336-022-00523-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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3
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Cicone F, Galldiks N, Papa A, Langen KJ, Cascini GL, Minniti G. Repeated amino acid PET imaging for longitudinal monitoring of brain tumors. Clin Transl Imaging 2022. [DOI: 10.1007/s40336-022-00504-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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4
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Ninatti G, Sollini M, Bono B, Gozzi N, Fedorov D, Antunovic L, Gelardi F, Navarria P, Politi LS, Pessina F, Chiti A. Preoperative [11C]methionine PET to personalize treatment decisions in patients with lower-grade gliomas. Neuro Oncol 2022; 24:1546-1556. [PMID: 35171292 PMCID: PMC9435504 DOI: 10.1093/neuonc/noac040] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND PET with radiolabelled amino acids is used in the preoperative evaluation of patients with glial neoplasms. This study aimed to assess the role of [ 11C]methionine (MET) PET in assessing molecular features, tumour extent, and prognosis in newly-diagnosed lower-grade gliomas (LGGs) surgically treated. METHODS 153 patients with a new diagnosis of grade 2/3 glioma who underwent surgery at our Institution and were imaged preoperatively using [ 11C]MET PET/CT were retrospectively included. [ 11C]MET PET images were qualitatively and semiquantitatively analyzed using tumour-to-background ratio (TBR). Progression-free survival (PFS) rates were estimated using the Kaplan-Meier method and Cox proportional-hazards regression was used to test the association of clinicopathological and imaging data to PFS. RESULTS Overall, 111 lesions (73%) were positive, while thirty-two (21%) and ten (6%) were isometabolic and hypometabolic at [ 11C]MET PET, respectively. [ 11C]MET uptake was more common in oligodendrogliomas than IDH-mutant astrocytomas (87% vs 50% of cases, respectively). Among [ 11C]MET-positive gliomas, grade 3 oligodendrogliomas had the highest median TBRmax (3.22). In 25% of patients, PET helped to better delineate tumour margins compared to MRI only. In IDH-mutant astrocytomas, higher TBRmax values at [ 11C]MET PET were independent predictors of shorter PFS. CONCLUSIONS This work highlights the role of preoperative [ 11C]MET PET in estimating the type, assessing tumour extent, and predicting biological behaviour and prognosis of LGGs. Our findings support the implementation of [ 11C]MET PET in routine clinical practice to better manage these neoplasms.
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Affiliation(s)
- Gaia Ninatti
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy
| | - Martina Sollini
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Beatrice Bono
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Noemi Gozzi
- Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Daniil Fedorov
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy
| | - Lidija Antunovic
- Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Fabrizia Gelardi
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Pierina Navarria
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Letterio S Politi
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Federico Pessina
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Neurosurgery Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
| | - Arturo Chiti
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele - Milan, Italy.,Diagnostic Imaging Department, IRCCS Humanitas Research Hospital, Via Manzoni, Rozzano - Milan, Italy
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5
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Nakajo K, Uda T, Kawashima T, Terakawa Y, Ishibashi K, Tsuyuguchi N, Tanoue Y, Nagahama A, Uda H, Koh S, Sasaki T, Ohata K, Kanemura Y, Goto T. Maximum 11C-methionine PET uptake as a prognostic imaging biomarker for newly diagnosed and untreated astrocytic glioma. Sci Rep 2022; 12:546. [PMID: 35017570 PMCID: PMC8752605 DOI: 10.1038/s41598-021-04216-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 12/15/2021] [Indexed: 12/26/2022] Open
Abstract
This study aimed whether the uptake of amino tracer positron emission tomography (PET) can be used as an additional imaging biomarker to estimate the prognosis of glioma. Participants comprised 56 adult patients with newly diagnosed and untreated World Health Organization (WHO) grade II-IV astrocytic glioma who underwent surgical excision and were evaluated by 11C-methionine PET prior to the surgical excision at Osaka City University Hospital from July 2011 to March 2018. Clinical and imaging studies were retrospectively reviewed based on medical records at our institution. Preoperative Karnofsky Performance Status (KPS) only influenced progression-free survival (hazard ratio [HR] 0.20; 95% confidence interval [CI] 0.10-0.41, p < 0.0001), whereas histology (anaplastic astrocytoma: HR 5.30, 95% CI 1.23-22.8, p = 0.025; glioblastoma: HR 11.52, 95% CI 2.27-58.47, p = 0.0032), preoperative KPS ≥ 80 (HR 0.23, 95% CI 0.09-0.62, p = 0.004), maximum lesion-to-contralateral normal brain tissue (LN max) ≥ 4.03 (HR 0.24, 95% CI 0.08-0.71, p = 0.01), and isocitrate dehydrogenase (IDH) status (HR 14.06, 95% CI 1.81-109.2, p = 0.011) were factors influencing overall survival (OS) in multivariate Cox regression. OS was shorter in patients with LN max ≥ 4.03 (29.3 months) than in patients with LN max < 4.03 (not reached; p = 0.03). OS differed significantly between patients with IDH mutant/LN max < 4.03 and patients with IDH mutant/LN max ≥ 4.03. LN max using 11C-methionine PET may be used in prognostic markers for newly identified and untreated WHO grade II-IV astrocytic glioma.
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Affiliation(s)
- Kosuke Nakajo
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan.
| | - Takehiro Uda
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Toshiyuki Kawashima
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Yuzo Terakawa
- Department of Neurosurgery, Hokkaido Ohno Memorial Hospital, Hokkaido, Japan
| | - Kenichi Ishibashi
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
- Department of Neurosurgery, Osaka City General Hospital, Osaka, Japan
| | - Naohiro Tsuyuguchi
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
- Department of Neurosurgery, Kinki University Graduate School of Medicine, Osaka, Japan
| | - Yuta Tanoue
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Atsufumi Nagahama
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Hiroshi Uda
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Saya Koh
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Tsuyoshi Sasaki
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Kenji Ohata
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
| | - Yonehiro Kanemura
- Departments of Biomedical Research and Innovation, Institute for Clinical Research, National Hospital Organization Osaka National Hospital, Osaka, Japan
- Department of Neurosurgery, National Hospital Organization Osaka National Hospital, Osaka, Japan
| | - Takeo Goto
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan
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Abstract
This article reviews recent advances in the use of standard and advanced imaging techniques for diagnosis and treatment of central nervous system (CNS) tumors, including glioma and brain metastasis. Following the recent transition from a histology-based approach in classifying CNS tumors to one that integrates histology with the molecular information of tumor, the approaches for imaging CNS tumors have also been adapted to this new framework. Some challenges related to the diagnosis and treatment of CNS tumors, such as differentiating tumor from treatment-related imaging changes, require further progress to implement advanced imaging for clinical use.
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Affiliation(s)
- Raymond Y Huang
- Department of Neuroradiology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Whitney B Pope
- Radiology, Section of Neuroradiology, Brain Tumor Imaging, UCLA Medical Center, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California-Los Angeles, 924 Westwood Boulevard, Suite 615, Los Angeles, CA 90024, USA; Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, 924 Westwood Boulevard, Suite 615, Los Angeles, CA 90024, USA
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7
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Tatekawa H, Uetani H, Hagiwara A, Bahri S, Raymond C, Lai A, Cloughesy TF, Nghiemphu PL, Liau LM, Pope WB, Salamon N, Ellingson BM. Worse prognosis for IDH wild-type diffuse gliomas with larger residual biological tumor burden. Ann Nucl Med 2021; 35:1022-1029. [PMID: 34121166 DOI: 10.1007/s12149-021-01637-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 05/27/2021] [Indexed: 10/21/2022]
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.
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Affiliation(s)
- Hiroyuki Tatekawa
- UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
- Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, USA
| | - Hiroyuki Uetani
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
- Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, USA
| | - Shadfar Bahri
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, USA
| | - Albert Lai
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Linda M Liau
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Whitney B Pope
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Noriko Salamon
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
- Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, USA.
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8
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Tatekawa H, Uetani H, Hagiwara A, Yao J, Oughourlian TC, Ueda I, Raymond C, Lai A, Cloughesy TF, Nghiemphu PL, Liau LM, Bahri S, Pope WB, Salamon N, Ellingson BM. Preferential tumor localization in relation to 18F-FDOPA uptake for lower-grade gliomas. J Neurooncol 2021; 152:573-582. [PMID: 33704629 DOI: 10.1007/s11060-021-03730-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 03/01/2021] [Indexed: 11/28/2022]
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.
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Affiliation(s)
- Hiroyuki Tatekawa
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Hiroyuki Uetani
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Jingwen Yao
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia C Oughourlian
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Issei Ueda
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Albert Lai
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Linda M Liau
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Shadfar Bahri
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- 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. .,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. .,Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, CA, USA. .,Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA. .,UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
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9
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Maximum Uptake and Hypermetabolic Volume of 18F-FDOPA PET Estimate Molecular Status and Overall Survival in Low-Grade Gliomas: A PET and MRI Study. Clin Nucl Med 2020; 45:e505-e511. [PMID: 33031233 DOI: 10.1097/rlu.0000000000003318] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE We evaluated F-FDOPA PET and MRI characteristics in association with the molecular status and overall survival (OS) in a large number of low-grade gliomas (LGGs). METHODS Eighty-six patients who underwent F-FDOPA PET and MRI and were diagnosed with new or recurrent LGGs were retrospectively evaluated with respect to their isocitrate dehydrogenase (IDH) and 1p19q status (10 IDH wild type, 57 mutant, 19 unknown; 1p19q status in IDH mutant: 20 noncodeleted, 37 codeleted). After segmentation of the hyperintense area on fluid-attenuated inversion recovery image (FLAIRROI), the following were calculated: normalized SUVmax (nSUVmax) of F-FDOPA relative to the striatum, F-FDOPA hypermetabolic volume (tumor-to-striatum ratios >1), FLAIRROI volume, relative cerebral blood volume, and apparent diffusion coefficient within FLAIRROI. Receiver operating characteristic curve and Cox regression analyses were performed. RESULTS PET and MRI metrics combined with age predicted the IDH mutation and 1p19q codeletion statuses with sensitivities of 73% and 76% and specificities of 100% and 94%, respectively. Significant correlations were found between OS and the IDH mutation status (hazard ratio [HR] = 4.939), nSUVmax (HR = 2.827), F-FDOPA hypermetabolic volume (HR = 1.048), and FLAIRROI volume (HR = 1.006). The nSUVmax (HR = 151.6) for newly diagnosed LGGs and the F-FDOPA hypermetabolic volume (HR = 1.038) for recurrent LGGs demonstrated significant association with OS. CONCLUSIONS Combining F-FDOPA PET and MRI with age proved useful for predicting the molecular status in patients with LGGs, whereas the nSUVmax and F-FDOPA hypermetabolic volume may be useful for prognostication.
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10
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Somme F, Bender L, Namer IJ, Noël G, Bund C. Usefulness of 18F-FDOPA PET for the management of primary brain tumors: a systematic review of the literature. Cancer Imaging 2020; 20:70. [PMID: 33023662 PMCID: PMC7541204 DOI: 10.1186/s40644-020-00348-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 09/21/2020] [Indexed: 11/30/2022] Open
Abstract
Contrast-enhanced magnetic resonance imaging is currently the standard of care in the management of primary brain tumors, although certain limitations remain. Metabolic imaging has proven useful for an increasing number of indications in oncology over the past few years, most particularly 18F-FDG PET/CT. In neuro-oncology, 18F-FDG was insufficient to clearly evaluate brain tumors. Amino-acid radiotracers such as 18F-FDOPA were then evaluated in the management of brain diseases, notably tumoral diseases. Even though European guidelines on the use of amino-acid PET in gliomas have been published, it is crucial that future studies standardize acquisition and interpretation parameters. The aim of this article was to systematically review the potential effect of this metabolic imaging technique in numerous steps of the disease: primary and recurrence diagnosis, grading, local and systemic treatment assessment, and prognosis. A total of 41 articles were included and analyzed in this review. It appears that 18F-FDOPA PET holds promise as an effective additional tool in the management of gliomas. More consistent prospective studies are still needed.
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Affiliation(s)
- François Somme
- Nuclear medicine Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France.
| | - Laura Bender
- Oncology Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France
| | - Izzie Jacques Namer
- Nuclear medicine Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France
- Strasbourg University, Unistra/CNRS UMR 7237, Strasbourg, France
| | - Georges Noël
- Radiotherapy Department, Paul Strauss Comprehensive Cancer Center, 3, rue de la porte de l'hôpital, F-67065, Strasbourg, France
- Strasbourg University, CNRS, IPHC UMR 7178, Centre Paul Strauss, UNICANCER, F-67000, Strasbourg, France
| | - Caroline Bund
- Nuclear medicine Department, Hautepierre University Hospital, 1, rue Molière, F-67000, Strasbourg, France
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11
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Tatekawa H, Hagiwara A, Uetani H, Yao J, Oughourlian TC, Bahri S, Wang C, Raymond C, Lai A, Cloughesy TF, Nghiemphu PL, Liau LM, Pope WB, Salamon N, Ellingson BM. Multiparametric MR-PET measurements in hypermetabolic regions reflect differences in molecular status and tumor grade in treatment-naïve diffuse gliomas. J Neurooncol 2020; 149:337-346. [PMID: 32929644 DOI: 10.1007/s11060-020-03613-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 08/31/2020] [Indexed: 01/28/2023]
Abstract
PURPOSE To assess whether hypermetabolically-defined regions of interest (ROIs) on 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) could be used to evaluate physiological features and whether there are measurable differences between molecular subtypes and tumor grades. METHODS Sixty-eight treatment-naïve glioma patients who underwent FDOPA PET and magnetic resonance imaging (MRI) were retrospectively included. Fluid-attenuated inversion recovery hyperintense regions (FLAIRROI) were segmented. FDOPA hypermetabolic regions (FDOPAROI, tumor-to-striatum ratios > 1) within FLAIRROI were extracted. Normalized maximum standardized uptake value (nSUVmax), volume of each ROI, and median relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) within FLAIRROI or FDOPAROI were calculated. Imaging metrics were compared using Students t or Mann-Whitney U tests. Area under the curve (AUC) of receiver-operating characteristic curves were used to determine whether imaging metrics within FLAIRROI or FDOPAROI can discriminate different molecular statuses or grades. RESULTS Using either FLAIRROI or FDOPAROI, the nSUVmax and rCBV were significantly higher and the ADC was lower in isocitrate dehydrogenase (IDH) wild-type than mutant gliomas, and in higher-grade gliomas (HGGs) than lower-grade gliomas (LGGs). The FDOPAROI volume was significantly higher in 1p19q codeleted than non-codeleted gliomas, and in HGGs than LGGs. Although not significant, imaging metrics extracted by FDOPAROI discriminated molecular status and tumor grade more accurately than those extracted by FLAIRROI (AUC of IDH status, 0.87 vs. 0.82; 1p19q status, 0.78 vs. 0.73; grade, 0.87 vs. 0.76). CONCLUSION FDOPA hypermetabolic ROI may extract useful imaging features of gliomas, which can illuminate biological differences between different molecular status or tumor grades.
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Affiliation(s)
- Hiroyuki Tatekawa
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Akifumi Hagiwara
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Hiroyuki Uetani
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Jingwen Yao
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA.,Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, USA
| | - Talia C Oughourlian
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA.,Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Shadfar Bahri
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Chencai Wang
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Catalina Raymond
- 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.,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Albert Lai
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Linda M Liau
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.,Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
| | - Whitney B Pope
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Noriko Salamon
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Benjamin M Ellingson
- 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. .,Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA. .,Department of Bioengineering, Henry Samueli School of Engineering, University of California Los Angeles, Los Angeles, USA. .,Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA. .,UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
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12
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Tatekawa H, Hagiwara A, Yao J, Oughourlian TC, Ueda I, Uetani H, Raymond C, Lai A, Cloughesy TF, Nghiemphu PL, Liau LM, Pope WB, Salamon N, Ellingson BM. Voxelwise and Patientwise Correlation of 18F-FDOPA PET, Relative Cerebral Blood Volume, and Apparent Diffusion Coefficient in Treatment-Naïve Diffuse Gliomas with Different Molecular Subtypes. J Nucl Med 2020; 62:319-325. [PMID: 32646876 DOI: 10.2967/jnumed.120.247411] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 06/11/2020] [Indexed: 11/16/2022] Open
Abstract
Our purpose was to identify correlations between 18F-fluorodihydroxyphenylalanine (18F-FDOPA) uptake and physiologic MRI, including relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC), in gliomas with different molecular subtypes and to evaluate their prognostic values. Methods: Sixty-eight treatment-naïve glioma patients who underwent 18F-FDOPA PET and physiologic MRI were retrospectively selected (36 with isocitrate dehydrogenase wild-type [IDHwt], 16 with mutant 1p/19q noncodeleted [IDHm-noncodel], and 16 with mutant codeleted [IDHm-codel]). Fluid-attenuated inversion recovery hyperintense areas were segmented and used as regions of interest. For voxelwise and patientwise analyses, Pearson correlation coefficients (r voxelwise and r patientwise) between the normalized SUV (nSUV), rCBV, and ADC were evaluated. Cox regression analysis was performed to investigate the associations between overall survival and r voxelwise, maximum or median nSUV, median rCBV, or median ADC. Results: For IDHwt and IDHm-noncodel gliomas, nSUV demonstrated significant positive correlations with rCBV (r voxelwise = 0.25 and 0.31, respectively; r patientwise = 0.50 and 0.70, respectively) and negative correlations with ADC (r voxelwise = -0.19 and -0.19, respectively; r patientwise = -0.58 and -0.61, respectively) in both voxelwise and patientwise analyses. IDHm-codel gliomas demonstrated a significant positive correlation between nSUV and ADC only in voxelwise analysis (r voxelwise = 0.18). In Cox regression analysis, r voxelwise between nSUV and rCBV (hazard ratio, 28.82) or ADC (hazard ratio, 0.085) had significant associations with overall survival for only IDHwt gliomas. Conclusion: IDHm-codel gliomas showed distinctive patterns of correlations between amino acid PET and physiologic MRI. Stronger correlations between nSUV and rCBV or ADC may result in a worse prognosis for IDHwt gliomas.
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Affiliation(s)
- Hiroyuki Tatekawa
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering, UCLA, Los Angeles, California
| | - Talia C Oughourlian
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California.,Neuroscience Interdepartmental Program, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Issei Ueda
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Hiroyuki Uetani
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Albert Lai
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, California; and
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, California; and
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, California; and
| | - Linda M Liau
- UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Neurosurgery, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Whitney B Pope
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Noriko Salamon
- Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, UCLA, Los Angeles, California .,Department of Radiological Science, David Geffen School of Medicine, UCLA, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering, UCLA, Los Angeles, California.,Neuroscience Interdepartmental Program, David Geffen School of Medicine, UCLA, Los Angeles, California.,UCLA Neuro-Oncology Program, David Geffen School of Medicine, UCLA, Los Angeles, California
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