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

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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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References

  1. Wang Y, Liu S, Fan X, Li S, Wang R, Wang L, Ma J, Jiang T, Ma W (2015) Age-associated brain regions in gliomas: a volumetric analysis. J Neurooncol 123:299–306. https://doi.org/10.1007/s11060-015-1798-x

    Article  CAS  PubMed  Google Scholar 

  2. Ren X, Cui X, Lin S, Wang J, Jiang Z, Sui D, Li J, Wang Z (2012) Co-deletion of chromosome 1p/19q and IDH1/2 mutation in glioma subsets of brain tumors in Chinese patients. PLoS ONE 7:e32764. https://doi.org/10.1371/journal.pone.0032764

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Stockhammer F, Misch M, Helms HJ, Lengler U, Prall F, von Deimling A, Hartmann C (2012) IDH1/2 mutations in WHO grade II astrocytomas associated with localization and seizure as the initial symptom. Seizure 21:194–197. https://doi.org/10.1016/j.seizure.2011.12.007

    Article  PubMed  Google Scholar 

  4. Paldor I, Pearce FC, Drummond KJ, Kaye AH (2016) Frontal glioblastoma multiforme may be biologically distinct from non-frontal and multilobar tumors. J Clin Neurosci 34:128–132. https://doi.org/10.1016/j.jocn.2016.05.017

    Article  CAS  PubMed  Google Scholar 

  5. Zhang J, Yao L, Peng S, Fang Y, Tang R, Liu J (2019) Correlation between glioma location and preoperative seizures: a systematic review and meta-analysis. Neurosurg Rev 42:603–618. https://doi.org/10.1007/s10143-018-1014-5

    Article  PubMed  Google Scholar 

  6. Smith JS, Chang EF, Lamborn KR, Chang SM, Prados MD, Cha S, Tihan T, Vandenberg S, McDermott MW, Berger MS (2008) Role of extent of resection in the long-term outcome of low-grade hemispheric gliomas. J Clin Oncol 26:1338–1345. https://doi.org/10.1200/JCO.2007.13.9337

    Article  PubMed  Google Scholar 

  7. Bilello M, Akbari H, Da X, Pisapia JM, Mohan S, Wolf RL, O’Rourke DM, Martinez-Lage M, Davatzikos C (2016) Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma. Neuroimage Clin 12:34–40. https://doi.org/10.1016/j.nicl.2016.03.007

    Article  PubMed  PubMed Central  Google Scholar 

  8. Roux A, Roca P, Edjlali M, Sato K, Zanello M, Dezamis E, Gori P, Lion S, Fleury A, Dhermain F, Meder JF, Chretien F, Lechapt E, Varlet P, Oppenheim C, Pallud J (2019) MRI atlas of IDH wild-type supratentorial glioblastoma: probabilistic maps of phenotype, management, and outcomes. Radiology 293:633–643. https://doi.org/10.1148/radiol.2019190491

    Article  PubMed  Google Scholar 

  9. Ellingson BM, Cloughesy TF, Pope WB, Zaw TM, Phillips H, Lalezari S, Nghiemphu PL, Ibrahim H, Naeini KM, Harris RJ, Lai A (2012) Anatomic localization of O6-methylguanine DNA methyltransferase (MGMT) promoter methylated and unmethylated tumors: a radiographic study in 358 de novo human glioblastomas. Neuroimage 59:908–916. https://doi.org/10.1016/j.neuroimage.2011.09.076

    Article  CAS  PubMed  Google Scholar 

  10. Ellingson BM, Lai A, Harris RJ, Selfridge JM, Yong WH, Das K, Pope WB, Nghiemphu PL, Vinters HV, Liau LM, Mischel PS, Cloughesy TF (2013) Probabilistic radiographic atlas of glioblastoma phenotypes. AJNR Am J Neuroradiol 34:533–540. https://doi.org/10.3174/ajnr.A3253

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kratochwil C, Combs SE, Leotta K, Afshar-Oromieh A, Rieken S, Debus J, Haberkorn U, Giesel FL (2014) Intra-individual comparison of (1)(8)F-FET and (1)(8)F-DOPA in PET imaging of recurrent brain tumors. Neuro Oncol 16:434–440. https://doi.org/10.1093/neuonc/not199

    Article  CAS  PubMed  Google Scholar 

  12. Poulsen SH, Urup T, Grunnet K, Christensen IJ, Larsen VA, Jensen ML, Af Rosenschold PM, Poulsen HS, Law I (2017) The prognostic value of FET PET at radiotherapy planning in newly diagnosed glioblastoma. Eur J Nucl Med Mol Imaging 44:373–381. https://doi.org/10.1007/s00259-016-3494-2

    Article  CAS  PubMed  Google Scholar 

  13. Villani V, Carapella CM, Chiaravalloti A, Terrenato I, Piludu F, Vidiri A, Schillaci O, Floris R, Marzi S, Fabi A, Pace A (2015) The role of PET [18F]FDOPA in evaluating low-grade glioma. Anticancer Res 35:5117–5122

    CAS  PubMed  Google Scholar 

  14. Patel CB, Fazzari E, Chakhoyan A, Yao J, Raymond C, Nguyen H, Manoukian J, Nguyen N, Pope W, Cloughesy TF, Nghiemphu PL, Czernin J, Lai A, Ellingson BM (2018) (18)F-FDOPA PET and MRI characteristics correlate with degree of malignancy and predict survival in treatment-naive gliomas: a cross-sectional study. J Neurooncol 139:399–409. https://doi.org/10.1007/s11060-018-2877-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Verger A, Metellus P, Sala Q, Colin C, Bialecki E, Taieb D, Chinot O, Figarella-Branger D, Guedj E (2017) IDH mutation is paradoxically associated with higher (18)F-FDOPA PET uptake in diffuse grade II and grade III gliomas. Eur J Nucl Med Mol Imaging 44:1306–1311. https://doi.org/10.1007/s00259-017-3668-6

    Article  CAS  PubMed  Google Scholar 

  16. Ginet M, Zaragori T, Marie PY, Roch V, Gauchotte G, Rech F, Blonski M, Lamiral Z, Taillandier L, Imbert L, Verger A (2020) Integration of dynamic parameters in the analysis of (18)F-FDopa PET imaging improves the prediction of molecular features of gliomas. Eur J Nucl Med Mol Imaging 47:1381–1390. https://doi.org/10.1007/s00259-019-04509-y

    Article  CAS  PubMed  Google Scholar 

  17. Naslund O, Smits A, Forander P, Laesser M, Bartek J Jr, Gempt J, Liljegren A, Daxberg EL, Jakola AS (2018) Amino acid tracers in PET imaging of diffuse low-grade gliomas: a systematic review of preoperative applications. Acta Neurochir (Wien) 160:1451–1460. https://doi.org/10.1007/s00701-018-3563-3

    Article  Google Scholar 

  18. Kertels O, Kessler AF, Mihovilovic MI, Stolzenburg A, Linsenmann T, Samnick S, Brandlein S, Monoranu CM, Ernestus RI, Buck AK, Lohr M, Lapa C (2019) Prognostic value of O-(2-[(18)F]Fluoroethyl)-L-tyrosine PET/CT in newly diagnosed WHO 2016 Grade II and III glioma. Mol Imaging Biol 21:1174–1181. https://doi.org/10.1007/s11307-019-01357-y

    Article  CAS  PubMed  Google Scholar 

  19. Isal S, Gauchotte G, Rech F, Blonski M, Planel S, Chawki MB, Karcher G, Marie PY, Taillandier L, Verger A (2018) A high (18)F-FDOPA uptake is associated with a slow growth rate in diffuse Grade II-III gliomas. Br J Radiol 91:20170803. https://doi.org/10.1259/bjr.20170803

    Article  PubMed  PubMed Central  Google Scholar 

  20. Cicone F, Carideo L, Scaringi C, Arcella A, Giangaspero F, Scopinaro F, Minniti G (2019) (18)F-DOPA uptake does not correlate with IDH mutation status and 1p/19q co-deletion in glioma. Ann Nucl Med 33:295–302. https://doi.org/10.1007/s12149-018-01328-3

    Article  CAS  PubMed  Google Scholar 

  21. Oughourlian TC, Yao J, Schlossman J, Raymond C, Ji M, Tatekawa H, Salamon N, Pope WB, Czernin J, Nghiemphu PL, Lai A, Cloughesy TF, Ellingson BM (2020) Rate of change in maximum (18)F-FDOPA PET uptake and non-enhancing tumor volume predict malignant transformation and overall survival in low-grade gliomas. J Neurooncol 147:135–145. https://doi.org/10.1007/s11060-020-03407-w

    Article  PubMed  PubMed Central  Google Scholar 

  22. 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 (2020) Voxel-wise and patient-wise correlation of 18F-FDOPA PET, rCBV, and ADC in treatment-naïve diffuse gliomas with different molecular subtypes. J Nucl Med 62:319–325

    Article  Google Scholar 

  23. 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 (2020) Multiparametric MR-PET measurements in hypermetabolic regions reflect differences in molecular status and tumor grade in treatment-naïve diffuse gliomas. J Neurooncol 149:337–346. https://doi.org/10.1007/s11060-020-03613-6

    Article  PubMed  Google Scholar 

  24. Bishop A, Satyamurthy N, Bida G, Hendry G, Phelps M, Barrio JR (1996) Proton irradiation of [18O]O2: production of [18F]F2 and [18F]F2 + [18F] OF2. Nucl Med Biol 23:189–199. https://doi.org/10.1016/0969-8051(95)02037-3

    Article  CAS  PubMed  Google Scholar 

  25. Namavari M, Bishop A, Satyamurthy N, Bida G, Barrio JR (1992) Regioselective radiofluorodestannylation with [18F]F2 and [18F]CH3COOF: a high yield synthesis of 6-[18F]Fluoro-L-dopa. Int J Rad Appl Instrum A 43:989–996. https://doi.org/10.1016/0883-2889(92)90217-3

    Article  CAS  PubMed  Google Scholar 

  26. Kinahan PE, Townsend DW, Beyer T, Sashin D (1998) Attenuation correction for a combined 3D PET/CT scanner. Med Phys 25:2046–2053. https://doi.org/10.1118/1.598392

    Article  CAS  PubMed  Google Scholar 

  27. Nuyts J, Michel C, Dupont P (2001) Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations. IEEE Trans Med Imaging 20:365–375. https://doi.org/10.1109/42.925290

    Article  CAS  PubMed  Google Scholar 

  28. Thie JA (2004) Understanding the standardized uptake value, its methods, and implications for usage. J Nucl Med 45:1431–1434

    PubMed  Google Scholar 

  29. Chen W, Silverman DH, Delaloye S, Czernin J, Kamdar N, Pope W, Satyamurthy N, Schiepers C, Cloughesy T (2006) 18F-FDOPA PET imaging of brain tumors: comparison study with 18F-FDG PET and evaluation of diagnostic accuracy. J Nucl Med 47:904–911

    CAS  PubMed  Google Scholar 

  30. Ellingson BM, Kim HJ, Woodworth DC, Pope WB, Cloughesy JN, Harris RJ, Lai A, Nghiemphu PL, Cloughesy TF (2014) Recurrent glioblastoma treated with bevacizumab: contrast-enhanced T1-weighted subtraction maps improve tumor delineation and aid prediction of survival in a multicenter clinical trial. Radiology 271:200–210. https://doi.org/10.1148/radiol.13131305

    Article  PubMed  Google Scholar 

  31. Tran AN, Lai A, Li S, Pope WB, Teixeira S, Harris RJ, Woodworth DC, Nghiemphu PL, Cloughesy TF, Ellingson BM (2014) Increased sensitivity to radiochemotherapy in IDH1 mutant glioblastoma as demonstrated by serial quantitative MR volumetry. Neuro Oncol 16:414–420. https://doi.org/10.1093/neuonc/not198

    Article  CAS  PubMed  Google Scholar 

  32. Law I, Albert NL, Arbizu J, Boellaard R, Drzezga A, Galldiks N, la Fougere C, Langen KJ, Lopci E, Lowe V, McConathy J, Quick HH, Sattler B, Schuster DM, Tonn JC, Weller M (2019) Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [(18)F]FDG: version 1.0. Eur J Nucl Med Mol Imaging 46:540–557. https://doi.org/10.1007/s00259-018-4207-9

    Article  CAS  PubMed  Google Scholar 

  33. Bullmore ET, Suckling J, Overmeyer S, Rabe-Hesketh S, Taylor E, Brammer MJ (1999) Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Trans Med Imaging 18:32–42. https://doi.org/10.1109/42.750253

    Article  CAS  PubMed  Google Scholar 

  34. Parisot S, Darlix A, Baumann C, Zouaoui S, Yordanova Y, Blonski M, Rigau V, Chemouny S, Taillandier L, Bauchet L, Duffau H, Paragios N (2016) A probabilistic atlas of diffuse WHO Grade II glioma locations in the brain. PLoS ONE 11:e0144200. https://doi.org/10.1371/journal.pone.0144200

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Duffau H, Capelle L (2004) Preferential brain locations of low-grade gliomas. Cancer 100:2622–2626. https://doi.org/10.1002/cncr.20297

    Article  PubMed  Google Scholar 

  36. Krainik A, Lehéricy S, Duffau H, Vlaicu M, Poupon F, Capelle L, Cornu P, Clemenceau S, Sahel M, Valery CA, Boch AL, Mangin JF, Bihan DL, Marsault C (2001) Role of the supplementary motor area in motor deficit following medial frontal lobe surgery. Neurology 57:871–878. https://doi.org/10.1212/wnl.57.5.871

    Article  CAS  PubMed  Google Scholar 

  37. Lima GL, Zanello M, Mandonnet E, Taillandier L, Pallud J, Duffau H (2016) Incidental diffuse low-grade gliomas: from early detection to preventive neuro-oncological surgery. Neurosurg Rev 39:377–384. https://doi.org/10.1007/s10143-015-0675-6

    Article  PubMed  Google Scholar 

  38. Potts MB, Smith JS, Molinaro AM, Berger MS (2012) Natural history and surgical management of incidentally discovered low-grade gliomas. J Neurosurg 116:365–372. https://doi.org/10.3171/2011.9.JNS111068

    Article  PubMed  Google Scholar 

  39. Pallud J, Fontaine D, Duffau H, Mandonnet E, Sanai N, Taillandier L, Peruzzi P, Guillevin R, Bauchet L, Bernier V, Baron MH, Guyotat J, Capelle L (2010) Natural history of incidental World Health Organization grade II gliomas. Ann Neurol 68:727–733. https://doi.org/10.1002/ana.22106

    Article  PubMed  Google Scholar 

  40. Pallud J, Capelle L, Taillandier L, Badoual M, Duffau H, Mandonnet E (2013) The silent phase of diffuse low-grade gliomas. Is it when we missed the action? Acta Neurochir (Wien) 155:2237–2242. https://doi.org/10.1007/s00701-013-1886-7

    Article  Google Scholar 

  41. Unterrainer M, Schweisthal F, Suchorska B, Wenter V, Schmid-Tannwald C, Fendler WP, Schuller U, Bartenstein P, Tonn JC, Albert NL (2016) Serial 18F-FET PET imaging of primarily 18F-FET-negative glioma: does it make sense? J Nucl Med 57:1177–1182. https://doi.org/10.2967/jnumed.115.171033

    Article  CAS  PubMed  Google Scholar 

  42. Mishra A, John AP, Shukla D, Sathyaprabha TN, Devi BI (2018) Autonomic function in insular glioma: an exploratory study. World Neurosurg 118:e951–e955. https://doi.org/10.1016/j.wneu.2018.07.107

    Article  PubMed  Google Scholar 

  43. Almairac F, Duffau H, Herbet G (2018) Contralesional macrostructural plasticity of the insular cortex in patients with glioma: a VBM study. Neurology 91:e1902–e1908. https://doi.org/10.1212/WNL.0000000000006517

    Article  PubMed  Google Scholar 

  44. Capelle L, Fontaine D, Mandonnet E, Taillandier L, Golmard JL, Bauchet L, Pallud J, Peruzzi P, Baron MH, Kujas M, Guyotat J, Guillevin R, Frenay M, Taillibert S, Colin P, Rigau V, Vandenbos F, Pinelli C, Duffau H, French Reseau d’Etude des G (2013) Spontaneous and therapeutic prognostic factors in adult hemispheric World Health Organization Grade II gliomas: a series of 1097 cases: clinical article. J Neurosurg 118:1157–1168. https://doi.org/10.3171/2013.1.JNS121

    Article  PubMed  Google Scholar 

  45. Simpson JR, Horton J, Scott C, Curran WJ, Rubin P, Fischbach J, Isaacson S, Rotman M, Asbell SO, Nelson JS et al (1993) Influence of location and extent of surgical resection on survival of patients with glioblastoma multiforme: results of three consecutive Radiation Therapy Oncology Group (RTOG) clinical trials. Int J Radiat Oncol Biol Phys 26:239–244. https://doi.org/10.1016/0360-3016(93)90203-8

    Article  CAS  PubMed  Google Scholar 

  46. Sun T, Patoine C, Abu-Khalil A, Visvader J, Sum E, Cherry TJ, Orkin SH, Geschwind DH, Walsh CA (2005) Early asymmetry of gene transcription in embryonic human left and right cerebral cortex. Science 308:1794–1798. https://doi.org/10.1126/science.1110324

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Kumakura Y, Vernaleken I, Buchholz HG, Borghammer P, Danielsen E, Gründer G, Heinz A, Bartenstein P, Cumming P (2010) Age-dependent decline of steady state dopamine storage capacity of human brain: an FDOPA PET study. Neurobiol Aging 31:447–463. https://doi.org/10.1016/j.neurobiolaging.2008.05.005

    Article  CAS  PubMed  Google Scholar 

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Funding

Grant from the Society of Nuclear Medicine and Molecular Imaging (SNMMI) (Tatekawa); American Cancer Society (ACS) Research Scholar Grant (RSG-15-003-01-CCE) (Ellingson); American Brain Tumor Association (ABTA) Research Collaborators Grant (ARC1700002) (Ellingson); National Brain Tumor Society (NBTS) Research Grant (Ellingson, Cloughesy); NIH/NCI UCLA Brain Tumor SPORE (1P50CA211015-01A1) (Ellingson, Lai, Cloughesy, Nghiemphu); NIH/NCI (1R21CA223757-01) (Ellingson).

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Contributions

HT: study design, data analysis, drafting the manuscript, approving the final content. HU: study design, data analysis, revising the manuscript, approving the final content. AH: study design, data analysis, revising the manuscript, approving the final content. JY: study design, data analysis, revising the manuscript, approving the final content. TCO: study design, data analysis, revising the manuscript, approving the final content. IU: study design, data analysis, revising the manuscript, approving the final content. CR: data analysis, revising the manuscript, approving the final content. AL: data acquisition, revising the manuscript, approving the final content. TFC: data acquisition, revising the manuscript, approving the final content. PLN: data acquisition, revising the manuscript, approving the final content. LML: data acquisition, revising the manuscript, approving the final content. SB: study design, data analysis, revising the manuscript, approving the final content. WBP: study design, revising the manuscript, approving the final content. NS: study design, revising the manuscript, approving the final content. BME: study design, data analysis, revising the manuscript, approving the final content.

Corresponding author

Correspondence to Benjamin M. Ellingson.

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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.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants to have their imaging, clinical, and molecular data included in our research database (IRB IRB#10-000655).

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Tatekawa, H., Uetani, H., Hagiwara, A. et al. Preferential tumor localization in relation to 18F-FDOPA uptake for lower‐grade gliomas. J Neurooncol 152, 573–582 (2021). https://doi.org/10.1007/s11060-021-03730-w

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