Skip to main content
SpringerLink
Log in

Shortened cerebral circulation time correlates with seizures in brain arteriovenous malformation: a cross-sectional quantitative digital subtraction angiography study

  • Neuro
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

Seizure is the most common clinical presentation in patients with nonhemorrhagic brain arteriovenous malformations (BAVMs) and it influences their quality of life. Angioarchitectural analysis of the seizure risk for BAVMs is subjective and does not consider hemodynamics. This study aimed to investigate the angioarchitectural and hemodynamic factors that may be associated with seizure in patients with BAVMs.

Methods

From 2011 to 2019, 104 patients with supratentorial BAVMs without previous hemorrhage or treatment were included and grouped according to the initial presentation of seizure. Their angiograms and MRI results were analyzed for morphological characteristics and quantitative digital subtraction angiography (QDSA) parameters. Modified cerebral circulation time (mCCT) was defined as the difference between the bolus arrival time of the ipsilateral cavernous internal carotid artery and the parietal vein on lateral DSA. Logistic regression analysis was performed to estimate the odds ratio (OR) for BAVMs presenting with seizure.

Results

The seizure group had shorter mCCT (1.98 s vs. 2.44 s, p = 0.005) and more BAVMs with temporal location (45% vs. 30.8%, p = 0.013), neoangiogenesis (55% vs. 33%, p = 0.03), and long draining veins (95% vs. 72%, p = 0.004) than did the nonseizure group. Shorter mCCT (OR: 3.4, p = 0.02), temporal location (OR: 13.4, p < 0.001), and neoangiogenesis (OR: 4.7, p = 0.013) were independently associated with higher risks of seizure, after adjustments for age, gender, BAVM volume, and long draining vein.

Conclusions

Shorter mCCT, temporal location, and neoangiogenesis were associated with epileptic BAVMs. QDSA can objectively evaluate hemodynamic changes in epileptic BAVMs.

Key Points

• Quantitative digital subtraction angiography may be used to evaluate the hemodynamic differences between brain arteriovenous malformations presenting with and without seizure.

• BAVMs with temporal location, neoangiogenesis, and shortened cerebral circulation time were more likely to present with seizure.

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
Fig. 4

Similar content being viewed by others

Abbreviations

BAT:

Bolus arrival time

BAVM:

Brain arteriovenous malformation

CCT:

Cerebral circulation time

DSA:

Digital subtraction angiography

mCCT:

Modified cerebral circulation time

MRA:

MR angiography

MRI:

Magnetic resonance imaging

QDSA:

Quantitative DSA

ROI:

Region of interest

References

  1. Al-Shahi R, Warlow C (2001) A systematic review of the frequency and prognosis of arteriovenous malformations of the brain in adults. Brain 124:1900–1926

    Article  CAS  Google Scholar 

  2. Josephson CB, Bhattacharya JJ, Counsell CE et al (2012) Seizure risk with AVM treatment or conservative management: prospective, population-based study. Neurology 79:500–507

    Article  CAS  Google Scholar 

  3. Tong X, Wu J, Lin F et al (2016) The effect of age, sex, and lesion location on initial presentation in patients with brain arteriovenous malformations. World Neurosurg 87:598–606

    Article  Google Scholar 

  4. Abecassis IJ, Xu DS, Batjer HH, Bendok BR (2014) Natural history of brain arteriovenous malformations: a systematic review. Neurosurg Focus 37:E7

    Article  Google Scholar 

  5. Soldozy S, Norat P, Yagmurlu K et al (2020) Arteriovenous malformation presenting with epilepsy: a multimodal approach to diagnosis and treatment. Neurosurg Focus 48:E17

    Article  Google Scholar 

  6. Hoh BL, Chapman PH, Loeffler JS, Carter BS, Ogilvy CS (2002) Results of multimodality treatment for 141 patients with brain arteriovenous malformations and seizures: factors associated with seizure incidence and seizure outcomes. Neurosurgery 51:303–309 discussion 309-311

    Article  Google Scholar 

  7. Chen CJ, Shabo LM, Ding D et al (2019) Seizure presentation in patients with brain arteriovenous malformations treated with stereotactic radiosurgery: a multicenter study. World Neurosurg 126:e634–e640

    Article  Google Scholar 

  8. Ding D, Starke RM, Quigg M et al (2015) Cerebral arteriovenous malformations and epilepsy, part 1: predictors of seizure presentation. World Neurosurg 84:645–652

    Article  Google Scholar 

  9. Sun Y, Tian RF, Li AM, Liu XG, Chen J, Shi H (2016) Unruptured epileptogenic brain arteriovenous malformations. Turk Neurosurg 26:341–346

    PubMed  Google Scholar 

  10. Zhang Y, Yan P, Liang F, Ma C, Liang S, Jiang C (2019) Predictors of epilepsy presentation in unruptured brain arteriovenous malformations: a quantitative evaluation of location and radiomics features on T2-weighted imaging. World Neurosurg 125:e1008–e1015

    Article  Google Scholar 

  11. Benson JC, Chiu S, Flemming K, Nasr DM, Lanzino G, Brinjikji W (2020) MR characteristics of unruptured intracranial arteriovenous malformations associated with seizure as initial clinical presentation. J Neurointerv Surg 12:186–191

    Article  Google Scholar 

  12. Shankar JJ, Menezes RJ, Pohlmann-Eden B, Wallace C, terBrugge K, Krings T (2013) Angioarchitecture of brain AVM determines the presentation with seizures: proposed scoring system. AJNR Am J Neuroradiol 34:1028–1034

    Article  CAS  Google Scholar 

  13. Galletti F, Costa C, Cupini LM et al (2014) Brain arteriovenous malformations and seizures: an Italian study. J Neurol Neurosurg Psychiatry 85:284–288

    Article  CAS  Google Scholar 

  14. Jiang P, Lv X, Wu Z et al (2011) Characteristics of brain arteriovenous malformations presenting with seizures without acute or remote hemorrhage. Neuroradiol J 24:886–888

    Article  CAS  Google Scholar 

  15. Turjman F, Massoud TF, Sayre JW, Vinuela F, Guglielmi G, Duckwiler G (1995) Epilepsy associated with cerebral arteriovenous malformations: a multivariate analysis of angioarchitectural characteristics. AJNR Am J Neuroradiol 16:345–350

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Garcin B, Houdart E, Porcher R et al (2012) Epileptic seizures at initial presentation in patients with brain arteriovenous malformation. Neurology 78:626–631

    Article  CAS  Google Scholar 

  17. Mast H, Mohr JP, Osipov A et al (1995) 'Steal' is an unestablished mechanism for the clinical presentation of cerebral arteriovenous malformations. Stroke 26:1215–1220

    Article  CAS  Google Scholar 

  18. Shakur SF, Brunozzi D, Hussein AE et al (2018) Validation of cerebral arteriovenous malformation hemodynamics assessed by DSA using quantitative magnetic resonance angiography: preliminary study. J Neurointerv Surg 10:156–161

    Article  Google Scholar 

  19. Hu YS, Lee CC, Wu HM et al (2020) Stagnant venous outflow predicts brain arteriovenous malformation obliteration after gamma knife radiosurgery without prior intervention. Neurosurgery 87:338–347

    Article  Google Scholar 

  20. Lin TM, Yang HC, Lee CC et al (2019) Stasis index from hemodynamic analysis using quantitative DSA correlates with hemorrhage of supratentorial arteriovenous malformation: a cross-sectional study. J Neurosurg 132:1574–1582

    Article  Google Scholar 

  21. Scheffer IE, Berkovic S, Capovilla G et al (2017) ILAE classification of the epilepsies: position paper of the ILAE Commission for Classification and Terminology. Epilepsia 58:512–521

    Article  Google Scholar 

  22. Guo WY, Nordell B, Karlsson B et al (1993) Target delineation in radiosurgery for cerebral arteriovenous malformations. Assessment of the value of stereotaxic MR imaging and MR angiography. Acta Radiol 34:457–463

    Article  CAS  Google Scholar 

  23. Lin CJ, Hung SC, Guo WY et al (2012) Monitoring peri-therapeutic cerebral circulation time: a feasibility study using color-coded quantitative DSA in patients with steno-occlusive arterial disease. AJNR Am J Neuroradiol 33:1685–1690

    Article  CAS  Google Scholar 

  24. Greitz T (1956) A radiologic study of the brain circulation by rapid serial angiography of the carotid artery. Acta Radiol Suppl:1–123

  25. Todaka T, Hamada J, Kai Y, Morioka M, Ushio Y (2003) Analysis of mean transit time of contrast medium in ruptured and unruptured arteriovenous malformations: a digital subtraction angiographic study. Stroke 34:2410–2414

    Article  Google Scholar 

  26. Joint Writing Group of the Technology Assessment Committee American Society of I, Therapeutic N, Joint Section on Cerebrovascular Neurosurgery a Section of the American Association of Neurological S et al (2001) Reporting terminology for brain arteriovenous malformation clinical and radiographic features for use in clinical trials. Stroke 32:1430–1442

    Article  Google Scholar 

  27. Shakur SF, Amin-Hanjani S, Mostafa H, Charbel FT, Alaraj A (2015) Hemodynamic characteristics of cerebral arteriovenous malformation feeder vessels with and without aneurysms. Stroke 46:1997–1999

    Article  Google Scholar 

  28. Hu YS, Lin TM, Wu HM et al (2021) Stagnant venous outflow in ruptured arteriovenous malformations revealed by delayed quantitative digital subtraction angiography. Eur J Radiol 134:109455

    Article  Google Scholar 

  29. Shellikeri S, Bai H, Setser RM, Hurst RW, Cahill AM (2020) Association of intracranial arteriovenous malformation embolization with more rapid rate of perfusion in the peri-nidal region on color-coded quantitative digital subtraction angiography. J Neurointerv Surg 12:902–905

    Article  Google Scholar 

  30. Fiehler J, Illies T, Piening M et al (2009) Territorial and microvascular perfusion impairment in brain arteriovenous malformations. AJNR Am J Neuroradiol 30:356–361

    Article  CAS  Google Scholar 

  31. Guglielmi G (2006) Electrical models in the analysis of hemodynamic characteristics of arteriovenous malformations. Part 1: baseline measurements. Interv Neuroradiol 12:9–15

    Article  CAS  Google Scholar 

  32. Sato S, Kodama N, Sasaki T, Matsumoto M, Ishikawa T (2004) Perinidal dilated capillary networks in cerebral arteriovenous malformations. Neurosurgery 54:163–168 discussion 168-170

    Article  Google Scholar 

  33. Attia W, Tada T, Hongo K et al (2003) Microvascular pathological features of immediate perinidal parenchyma in cerebral arteriovenous malformations: giant bed capillaries. J Neurosurg 98:823–827

    Article  Google Scholar 

  34. Lv S, Guo ZN, Jin H et al (2018) Compromised dynamic cerebral autoregulation in patients with epilepsy. Biomed Res Int 2018:6958476

    PubMed  PubMed Central  Google Scholar 

  35. Teng MMH, Chang FC, Lin CJ, Chiang L, Hong JS, Kao YH (2016) Peritherapeutic hemodynamic changes of carotid stenting evaluated with quantitative DSA in patients with carotid stenosis. AJNR Am J Neuroradiol 37:1883–1888

    Article  CAS  Google Scholar 

  36. Narsinh KH, Mueller K, Nelson J et al (2020) Interrater reliability in the measurement of flow characteristics on Color-Coded Quantitative DSA of brain AVMs. AJNR Am J Neuroradiol 41:2303–2310

    Article  CAS  Google Scholar 

  37. Chen KK, Guo WY, Yang HC et al (2017) Application of time-resolved 3D digital subtraction angiography to plan cerebral arteriovenous malformation radiosurgery. AJNR Am J Neuroradiol 38:740–746

    Article  Google Scholar 

  38. Wu CX, Zang ZX, Hong T et al (2021) Signal intensity ratio of draining vein on silent MR angiography as an indicator of high-flow arteriovenous shunt in brain arteriovenous malformation. Eur Radiol. https://doi.org/10.1007/s00330-021-08170-8

  39. Aristova M, Vali A, Ansari SA et al (2019) Standardized evaluation of cerebral arteriovenous malformations using flow distribution network graphs and dual-venc 4D Flow MRI. J Magn Reson Imaging 50:1718–1730

    Article  Google Scholar 

Download references

Acknowledgements

We sincerely thank Hsin-Yi Huang (Biostatistics Task Force, Taipei Veterans General Hospital) for statistical assistance.

Funding

This study has received funding from the Taipei Veterans General Hospital (V110C-056) and the Ministry of Science and Technology (MOST 109-2628-B-010-014-MY2).

Author information

Authors and Affiliations

  1. Department of Radiology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Rd., Beitou District, Taipei City, Taiwan

    Jing Kai Loo, Yong-Sin Hu, Te-Ming Lin, Chung-Jung Lin, Jiing-Feng Lirng, Hsiu-Mei Wu, Chao-Bao Luo & Wan-Yuo Guo

  2. School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

    Jing Kai Loo, Yong-Sin Hu, Te-Ming Lin, Chung-Jung Lin, Jiing-Feng Lirng, Hsiu-Mei Wu, Huai-Che Yang, Cheng-Chia Lee, Chao-Bao Luo & Wan-Yuo Guo

  3. Department of Radiology, Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan

    Yong-Sin Hu

  4. Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan

    Huai-Che Yang & Cheng-Chia Lee

Authors
  1. Jing Kai Loo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong-Sin Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Te-Ming Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chung-Jung Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jiing-Feng Lirng
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hsiu-Mei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Huai-Che Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Cheng-Chia Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Chao-Bao Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Wan-Yuo Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chung-Jung Lin.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Chung-Jung Lin.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Hsin-Yi Huang (Biostatistics Task Force, Taipei Veterans General Hospital) kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• cross-sectional study

• performed at one institution

Additional information

Publisher’s note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Loo, J.K., Hu, YS., Lin, TM. et al. Shortened cerebral circulation time correlates with seizures in brain arteriovenous malformation: a cross-sectional quantitative digital subtraction angiography study. Eur Radiol 32, 5402–5412 (2022). https://doi.org/10.1007/s00330-022-08690-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-022-08690-x

Keywords

Search

Navigation