Skip to main content
SpringerLink
Log in

Exploring ASL perfusion MRI as a substitutive modality for 18F-FDG PET in determining the laterality of mesial temporal lobe epilepsy

  • Original Article
  • Published:
Neurological Sciences Aims and scope Submit manuscript

Abstract

Objective

The aim of this investigation was to determine whether a correlation could be discerned between perfusion acquired through ASL MRI and metabolic data acquired via 18F-fluorodeoxyglucose (18F-FDG) PET in mesial temporal lobe epilepsy (mTLE).

Methods

ASL MRI and 18F-FDG PET data were gathered from 22 mTLE patients. Relative cerebral blood flow (rCBF) asymmetry index (AIs) were measured using ASL MRI, and standardized uptake value ratio (SUVr) maps were obtained from 18F-FDG PET, focusing on bilateral vascular territories and key bitemporal lobe structures (amygdala, hippocampus, and parahippocampus). Intra-group comparisons were carried out to detect hypoperfusion and hypometabolism between the left and right brain hemispheres for both rCBF and SUVr in right and left mTLE. Correlations between the two AIs computed for each modality were examined.

Results

Significant correlations were observed between rCBF and SUVr AIs in the middle temporal gyrus, superior temporal gyrus, and hippocampus. Significant correlations were also found in vascular territories of the distal posterior, intermediate anterior, intermediate middle, proximal anterior, and proximal middle cerebral arteries. Intra-group comparisons unveiled significant differences in rCBF and SUVr between the left and right brain hemispheres for right mTLE, while hypoperfusion and hypometabolism were infrequently observed in any intracranial region for left mTLE.

Conclusion

The study’s findings suggest promising concordance between hypometabolism estimated by 18F-FDG PET and hypoperfusion determined by ASL perfusion MRI. This raises the possibility that, with prospective technical enhancements, ASL perfusion MRI could be considered an alternative modality to 18F-FDG PET in the future.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability

The data will be available by sending request to the corresponding author, for integration into large cohort studies and meta data analyses.

References

  1. Perucca P, Scheffer IE, Kiley M (2018) The management of epilepsy in children and adults. Med J Aust 208(5):226–233

    Article  PubMed  Google Scholar 

  2. Sisodiya SM et al (2022) The ENIGMA-Epilepsy working group: mapping disease from large data sets. Hum Brain Mapp 43(1):113–128

    Article  Google Scholar 

  3. Nazem-Zadeh M-R et al (2016) MEG coherence and DTI connectivity in mTLE. Brain Topogr 29(4):598–622

    Article  PubMed  PubMed Central  Google Scholar 

  4. Mahmoudi F et al (2018) Data mining MR image features of select structures for lateralization of mesial temporal lobe epilepsy. PLoS ONE 13(8):e0199137

    Article  PubMed  PubMed Central  Google Scholar 

  5. Fallahi A et al (2022) Comparison of multimodal findings on epileptogenic side in temporal lobe epilepsy using self-organizing maps. Magn Reson Mater Phys, Biol Med 35(2):249–266

    Article  Google Scholar 

  6. Mobarakeh NM et al (2019) The use of proton MR spectroscopy in epilepsy: a methodological review. Front Biomed Technol 6(1):1–21

    Google Scholar 

  7. Tomás J et al (2019) The predictive value of hypometabolism in focal epilepsy: a prospective study in surgical candidates. Eur J Nucl Med Mol Imaging 46(9):1806–1816

    Article  PubMed  Google Scholar 

  8. Steinbrenner M et al (2022) Utility of 18F-fluorodeoxyglucose positron emission tomography in presurgical evaluation of patients with epilepsy: A multicenter study. Epilepsia 63(5):1238–1252

    Article  CAS  PubMed  Google Scholar 

  9. Sone D et al (2019) Similar and differing distributions between 18F-FDG-PET and arterial spin labeling imaging in temporal lobe epilepsy. Front Neurol 10:318

    Article  PubMed  PubMed Central  Google Scholar 

  10. Rahimzadeh H et al (2023) Alteration of intracranial blood perfusion in temporal lobe epilepsy, an arterial spin labeling study. Heliyon 9(4):e14854

    Article  PubMed  PubMed Central  Google Scholar 

  11. Fan AP et al (2019) Identifying hypoperfusion in moyamoya disease with arterial spin labeling and an [15O]-water positron emission tomography/magnetic resonance imaging normative database. Stroke 50(2):373–380

    Article  PubMed  PubMed Central  Google Scholar 

  12. Zaharchuk G, Fan A, Gulaka P, Guo J, Poston, K., Greicius M, ...,  Zeineh M (2017l) Early uptake Amyloid PET imaging correlates strongly with cerebral blood flow based on arterial spin labeling MRI: a simultaneous PET/MRI study. In: Journal of Cerebral Blood Flow and Metabolism, vol 37. 2455 TELLER RD, THOUSAND OAKS, CA 91320 USA: SAGE PUBLICATIONS INC, pp 224-225.

  13. Guo J (2023) Robust dual-module velocity-selective arterial spin labeling (dm-VSASL) with velocity-selective saturation and inversion. Magn Reson Med 89(3):1026–1040

    Article  CAS  PubMed  Google Scholar 

  14. Guo J, Das S, Hernandez-Garcia L (2021) Comparison of velocity-selective arterial spin labeling schemes. Magn Reson Med 85(4):2027–2039

    Article  PubMed  Google Scholar 

  15. Rahimzadeh H et al (2019) An efficient framework for accurate arterial input selection in DSC-MRI of glioma brain tumors. J Biomed Phys Eng 9(1):69

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Lee DA et al (2021) Temporal lobe epilepsy with or without hippocampal sclerosis: structural and functional connectivity using advanced MRI techniques. J Neuroimaging 31(5):973–980

    Article  PubMed  Google Scholar 

  17. Zadeh HR, et al. (2017) Arterial input function selection in DSC-MRI of brain tumors using differential evaluation clustering method. In Proc. Intl. Soc. Mag. Reson. Med

  18. Musiek ES et al (2012) Direct comparison of FDG-PET and ASL-MRI in Alzheimer’s disease. Alzheimer’s Dementia 8(1):51

    Article  PubMed  Google Scholar 

  19. Wolf RL et al (2001) Detection of mesial temporal lobe hypoperfusion in patients with temporal lobe epilepsy by use of arterial spin labeled perfusion MR imaging. Am J Neuroradiol 22(7):1334–1341

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Lim Y-M et al (2008) Usefulness of pulsed arterial spin labeling MR imaging in mesial temporal lobe epilepsy. Epilepsy Res 82(2–3):183–189

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kojan M et al (2021) Arterial spin labeling is a useful MRI method for presurgical evaluation in MRI-negative focal epilepsy. Brain Topogr 34(4):504–510

    Article  PubMed  Google Scholar 

  22. Wang Y-H, et al. (2018) Comparison between simultaneously acquired arterial spin labeling and 18F-FDG PET in mesial temporal lobe epilepsy assisted by a PET/MR system and SEEG. NeuroImage: Clin 19: 824–830

  23. Horváth R et al (2008) Brain lateralization and seizure semiology: ictal clinical lateralizing signs. Ideggyogyaszati Szemle 61(7–8):231–237

    PubMed  Google Scholar 

  24. Marks WJ Jr, Laxer KD (1998) Semiology of temporal lobe seizures: value in lateralizing the seizure focus. Epilepsia 39(7):721–7264

    Article  PubMed  Google Scholar 

  25. Blair RD (2012) Temporal lobe epilepsy semiology. Epilepsy Res Treat 2012:751510. https://doi.org/10.1155/2012/751510

  26. Mani J (2014) Video electroencephalogram telemetry in temporal lobe epilepsy. Ann Indian Acad Neurol 17(Suppl 1):S45

    Article  PubMed  PubMed Central  Google Scholar 

  27. Chappell MA et al (2008) Variational Bayesian inference for a nonlinear forward model. IEEE Trans Signal Process 57(1):223–236

    Article  Google Scholar 

  28. Buxton RB et al (1998) A general kinetic model for quantitative perfusion imaging with arterial spin labeling. Magn Reson Med 40(3):383–396

    Article  CAS  PubMed  Google Scholar 

  29. Alsop DC et al (2015) Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med 73(1):102–116

    Article  PubMed  Google Scholar 

  30. Dolui S, et al. (2020) Arterial spin labeling versus 18F-FDG-PET to identify mild cognitive impairment. NeuroImage: Clin 25:102146

  31. Galazzo IB, et al. (2016) Cerebral metabolism and perfusion in MR-negative individuals with refractory focal epilepsy assessed by simultaneous acquisition of 18F-FDG PET and arterial spin labeling. NeuroImage: Clin 11: 648–657

  32. Verclytte S et al (2016) Cerebral hypoperfusion and hypometabolism detected by arterial spin labeling MRI and FDG-PET in early-onset Alzheimer’s disease. J Neuroimaging 26(2):207–212

    Article  PubMed  Google Scholar 

  33. Maldjian JA et al (2003) An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage 19(3):1233–1239

    Article  PubMed  Google Scholar 

  34.  Nazem-Zadeh M-R, Elisevich K, Soltanian-Zadeh H (2018) Development of multimodal neuroimaging models for lateralization of temporal lobe epilepsy In: 2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC), Stellenbosch, South Africa, pp 1–4.  https://doi.org/10.1109/SAIBMEC.2018.8408603

  35. Nazem-Zadeh MR, Elisevich KV, Schwalb JM, Bagher-Ebadian H, Mahmoudi F, Soltanian-Zadeh H (2014) Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models. Journal of the neurological sciences 347(1–2):107–118. https://doi.org/10.1016/j.jns.2014.09.029

    Article  PubMed  PubMed Central  Google Scholar 

  36. Nelissen N et al (2006) Correlations of interictal FDG-PET metabolism and ictal SPECT perfusion changes in human temporal lobe epilepsy with hippocampal sclerosis. Neuroimage 32(2):684–695

    Article  CAS  PubMed  Google Scholar 

  37. Guo X et al (2015) Asymmetry of cerebral blood flow measured with three-dimensional pseudocontinuous arterial spin-labeling MR imaging in temporal lobe epilepsy with and without mesial temporal sclerosis. J Magn Reson Imaging 42(5):1386–1397

    Article  PubMed  Google Scholar 

  38. Rahimzadeh H, Kamkar H, Hoseini-Tabatabaei N, Mobarakeh NM, Habibabadi JM, Hashemi-Fesharaki SS, Nazem-Zadeh MR (2023) Alteration of intracranial blood perfusion in temporal lobe epilepsy, an arterial spin labeling study. Heliyon 9(4):e14854. https://doi.org/10.1016/j.heliyon.2023.e14854

  39. Jber M et al (2021) Temporal and extratemporal atrophic manifestation of temporal lobe epilepsy using voxel-based morphometry and corticometry: clinical application in lateralization of epileptogenic zone. Neurol Sci 42(8):3305–3325

    Article  PubMed  Google Scholar 

  40. Ahmadi ME et al (2009) Side matters: diffusion tensor imaging tractography in left and right temporal lobe epilepsy. Am J Neuroradiol 30(9):1740–1747

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Zhou X et al (2019) Disruption and lateralization of cerebellar–cerebral functional networks in right temporal lobe epilepsy: a resting-state fMRI study. Epilepsy Behav 96:80–86

    Article  PubMed  Google Scholar 

  42. Paldino MJ et al (2017) Comparison of the diagnostic accuracy of PET/MRI to PET/CT-acquired FDG brain exams for seizure focus detection: a prospective study. Pediatr Radiol 47(11):1500–1507

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to express their gratitude to the Iranian National Brain Mapping Laboratory (NBML), Tehran, Iran, for their invaluable assistance in data acquisition.

Funding

This work was financially supported by the Medical School of the Tehran University of Medical Sciences under Grant Number 98–3-101–45419, between the years 2019 and 2022.

Author information

Authors and Affiliations

  1. Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran

    Hossein Rahimzadeh, Hadi Kamkar, Neda Mohammadi-Mobarakeh & Mohammad-Reza Nazem-Zadeh

  2. Department of Biomedical Engineering and Medical Physics, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Hossein Rahimzadeh

  3. Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran

    Hadi Kamkar

  4. Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Pardis Ghafarian

  5. Medical School, Tehran University of Medical Sciences, Tehran, Iran

    Narges Hoseini-Tabatabaei

  6. Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran

    Neda Mohammadi-Mobarakeh & Mohammad-Reza Nazem-Zadeh

  7. Isfahan Neuroscience Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

    Jafar Mehvari-Habibabadi

  8. Pars Advanced and Minimally Invasive Medical Manners Research Center, Pars Hospital, Iran University of Medical Sciences, Tehran, Iran

    Seyed-Sohrab Hashemi-Fesharaki

  9. Department of Neuroscience, Monash University, Melbourne, Australia

    Mohammad-Reza Nazem-Zadeh

Authors
  1. Hossein Rahimzadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hadi Kamkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pardis Ghafarian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Narges Hoseini-Tabatabaei
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Neda Mohammadi-Mobarakeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jafar Mehvari-Habibabadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Seyed-Sohrab Hashemi-Fesharaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mohammad-Reza Nazem-Zadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad-Reza Nazem-Zadeh.

Ethics declarations

Ethical approval

The studies involving human participants were conducted in accordance with the ethical standards set by the institutional and/or national research committee. The research also adhered to the principles outlined in the 1964 Helsinki Declaration and its subsequent amendments, or comparable ethical standards.

Consent to participate

All individual participants included in the study provided informed consent.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Hossein Rahimzadeh and Hadi Kamkar equally contributed as co-first authors.

Appendix

Appendix

Tables 7, 8, 9, 10 and 11

Table 7 Patient characteristic and clinical data
Full size table
Table 8 Asymmetry index of perfusion data on AAL atlas
Full size table
Table 9 Asymmetry index of PET on AAL atlas
Full size table
Table 10 Asymmetry index of perfusion data on vascular territories
Full size table
Table 11 Asymmetry index of PET on vascular territories
Full size table

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rahimzadeh, H., Kamkar, H., Ghafarian, P. et al. Exploring ASL perfusion MRI as a substitutive modality for 18F-FDG PET in determining the laterality of mesial temporal lobe epilepsy. Neurol Sci 45, 2223–2243 (2024). https://doi.org/10.1007/s10072-023-07188-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10072-023-07188-8

Keywords

Search

Navigation