Skip to main content

Advertisement

SpringerLink
Log in

Quantitative assessment of microstructural evolution of intracranial aneurysm wall by vessel wall imaging

  • Diagnostic Neuroradiology
  • Published:
Neuroradiology Aims and scope Submit manuscript

Abstract

Purpose

This study aimed to evaluate new quantitative parameters of aneurysm wall enhancement (AWE) on magnetic resonance vessel wall imaging (VWI) in differentiating between the stable and evolving unruptured intracranial aneurysms (UIAs).

Methods

Thirty-eight consecutive patients with UIAs (27 stable and 11 evolving) underwent VWI with contrast-enhanced 3D T1 volume isotropic turbo spin echo acquisition. The voxel-based enhancement maps were created using pre- and post-contrast images. The aneurysmal lumen with signal suppression by black-blood method was segmented. Then, one voxel outer and inner layers of the lumen contour were automatically segmented. The shape features of the aneurysms and AWE of the two layers were compared between stable and evolving groups.

Results

The shape features, including aneurysm volume, surface, and compacity were significantly different between the stable and evolving groups (P = 0.024, 0.028, and 0.033, respectively). Stable and evolving groups also differed significantly in the AWE at the union of outer and inner layers of the aneurysm wall (P = 0.0082) but not in that of the outer or inner layer alone. Multivariate logistic regression analysis revealed significant differences in aneurysm volume, surface, and AWE at the union of outer and inner layers between the two groups (P = 0.0029, 0.0092, and 0.0033, respectively). Receiver operating characteristics curve analysis revealed that the area under the curve of the logistic regression model was 0.89.

Conclusion

Quantitative combined analysis of aneurysm shape features and AWE of the union of outer and inner layers were effective for differentiating between stable and evolving UIAs.

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

Abbreviations

AWE:

Aneurysm wall enhancement

UIA:

Unruptured intracranial aneurysm

VISTA:

Volume isotropic turbo spin echo acquisition

VWI:

Vessel wall imaging

References

  1. Vlak MH, Algra A, Brandenburg R, Rinkel GJ (2011) Prevalence of unruptured intracranial aneurysms, with emphasis on sex, age, comorbidity, country, and time period: a systematic review and meta-analysis. Lancet Neurol 10:626–636

    Article  Google Scholar 

  2. The UCAS Japan Investigators (2012) The Natural course of unruptured cerebral aneurysms in a Japanese cohort. N Engl J Med 366:2474–2482

    Article  Google Scholar 

  3. Algra AM, Lindgren A, Vergouwen MDI et al (2019) Procedural clinical complications, case-fatality risks, and risk factors in endovascular and neurosurgical treatment of unruptured intracranial aneurysms: a systematic review and meta-analysis. JAMA Neurol 76:282

    Article  Google Scholar 

  4. Greving JP, Wermer MJH, Brown RD et al (2014) Development of the PHASES score for prediction of risk of rupture of intracranial aneurysms: a pooled analysis of six prospective cohort studies. Lancet Neurol 13:59–66

    Article  Google Scholar 

  5. Tominari S, Morita A, Ishibashi T et al (2015) Prediction model for 3-year rupture risk of unruptured cerebral aneurysms in Japanese patients: cerebral aneurysm rupture risk. Ann Neurol 77:1050–1059

    Article  Google Scholar 

  6. Brinjikji W, Zhu Y-Q, Lanzino G et al (2016) Risk factors for growth of intracranial aneurysms: a systematic review and meta-analysis. AJNR Am J Neuroradiol 37:615–620

    Article  CAS  Google Scholar 

  7. Inoue T, Shimizu H, Fujimura M et al (2012) Annual rupture risk of growing unruptured cerebral aneurysms detected by magnetic resonance angiography: Clinical article. JNS 117:20–25

    Article  Google Scholar 

  8. Omodaka S, Endo H, Niizuma K et al (2019) Circumferential wall enhancement in evolving intracranial aneurysms on magnetic resonance vessel wall imaging. J Neurosurg 131:1262–1268

    Article  Google Scholar 

  9. Matsushige T, Shimonaga K, Ishii D et al (2019) Vessel wall imaging of evolving unruptured intracranial aneurysms. Stroke 50:1891–1894

    Article  Google Scholar 

  10. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159

    Article  CAS  Google Scholar 

  11. Omodaka S, Endo H, Niizuma K et al (2016) Quantitative Assessment of circumferential enhancement along the wall of cerebral aneurysms using MR imaging. Am J Neuroradiol 37:1262–1266

    Article  CAS  Google Scholar 

  12. Nagahata S, Nagahata M, Obara M et al (2016) Wall enhancement of the intracranial aneurysms revealed by magnetic resonance vessel wall imaging using three-dimensional turbo spin-echo sequence with motion-sensitized driven-equilibrium: a sign of ruptured aneurysm? Clin Neuroradiol 26:277–283

    Article  CAS  Google Scholar 

  13. Matouk CC, Mandell DM, Günel M et al (2013) Vessel wall magnetic resonance imaging identifies the site of rupture in patients with multiple intracranial aneurysms. Neurosurgery 72:492–496

    Article  Google Scholar 

  14. Zhu C, Wang X, Eisenmenger L et al (2020) Wall enhancement on black-blood MRI is independently associated with symptomatic status of unruptured intracranial saccular aneurysm. Eur Radiol 30:6413–6420

    Article  Google Scholar 

  15. Vergouwen MDI, Backes D, van der Schaaf IC et al (2019) Gadolinium Enhancement of the aneurysm wall in unruptured intracranial aneurysms is associated with an increased risk of aneurysm instability: a follow-up study. AJNR Am J Neuroradiol 40:1112–1116

    Article  CAS  Google Scholar 

  16. Shimonaga K, Matsushige T, Ishii D et al (2018) Clinicopathological insights from vessel wall imaging of unruptured intracranial aneurysms. Stroke 49:2516–2519

    Article  Google Scholar 

  17. Larsen N, Flüh C, Saalfeld S et al (2020) Multimodal validation of focal enhancement in intracranial aneurysms as a surrogate marker for aneurysm instability. Neuroradiology 62:1627–1635

    Article  Google Scholar 

  18. Gariel F, Ben Hassen W, Boulouis G et al (2020) Increased wall enhancement during follow-up as a predictor of subsequent aneurysmal growth. Stroke 51:1868–1872

    Article  CAS  Google Scholar 

  19. Edjlali M, Guédon A, Ben Hassen W et al (2018) Circumferential thick enhancement at vessel wall MRI has high specificity for intracranial aneurysm instability. Radiology 289(1):181–187. https://doi.org/10.1148/radiol.2018172879

    Article  PubMed  Google Scholar 

  20. Stember JN, Chang P, Stember DM et al (2019) Convolutional neural networks for the detection and measurement of cerebral aneurysms on magnetic resonance angiography. J Digit Imaging 32:808–815

    Article  Google Scholar 

  21. Omodaka S, Endo H, Niizuma K et al (2018) Circumferential wall enhancement on magnetic resonance imaging is useful to identify rupture site in patients with multiple cerebral aneurysms. Neurosurgery 82:638–644

    Article  Google Scholar 

  22. Tsuji M, Ishikawa T, Ishida F et al (2017) Stagnation and complex flow in ruptured cerebral aneurysms: a possible association with hemostatic pattern. J Neurosurg 126:1566–1572

    Article  Google Scholar 

  23. Sugiyama S, Endo H, Niizuma K et al (2016) Computational hemodynamic analysis for the diagnosis of atherosclerotic changes in intracranial aneurysms: a proof-of-concept study using 3 cases harboring atherosclerotic and nonatherosclerotic aneurysms simultaneously. Comput Math Methods Med 2016:1–12

    Article  CAS  Google Scholar 

  24. Sugiyama S, Niizuma K, Nakayama T et al (2013) Relative residence time prolongation in intracranial aneurysms: a possible association with atherosclerosis. Neurosurgery 73:767–776

    Article  Google Scholar 

  25. Quan K, Song J, Yang Z et al (2019) Validation of wall enhancement as a new imaging biomarker of unruptured cerebral aneurysm. Stroke 50:1570–1573

    Article  Google Scholar 

  26. Khan MO, Toro Arana V, Rubbert C et al (2021) Association between aneurysm hemodynamics and wall enhancement on 3D vessel wall MRI. J Neurosurg 134:565–575

    Article  Google Scholar 

  27. Hokari M, Nakayama N, Nishihara H, Houkin K (2015) Pathological findings of saccular cerebral aneurysms—impact of subintimal fibrin deposition on aneurysm rupture. Neurosurg Rev 38:531–540

    Article  Google Scholar 

  28. Chalouhi N, Hoh BL, Hasan D (2013) Review of cerebral aneurysm formation, growth, and rupture. Stroke 44:3613–3622

    Article  Google Scholar 

  29. Sato T, Matsushige T, Chen B et al (2019) Wall contrast enhancement of thrombosed intracranial aneurysms at 7T MRI. AJNR Am J Neuroradiol 40:1106–1111

    Article  CAS  Google Scholar 

  30. McDonald RJ, McDonald JS, Kallmes DF et al (2017) Gadolinium deposition in human brain tissues after contrast-enhanced MR imaging in adult patients without intracranial abnormalities. Radiology 285:546–554

    Article  Google Scholar 

  31. Kleinloog R, Korkmaz E, Zwanenburg JJM et al (2014) Visualization of the aneurysm wall: a 7.0-tesla magnetic resonance imaging study. Neurosurgery 75:614–622

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank Hiroaki Shimizu and Kenichi Higuchi in Tohoku University for their kind support.

Author information

Authors and Affiliations

  1. Department of Neurosurgery, Tohoku University Graduate School of Medicine, Sendai, Japan

    Hidenori Endo, Shunsuke Omodaka & Teiji Tominaga

  2. Department of Neurosurgery, Kohnan Hospital, Sendai, Japan

    Hidenori Endo & Shunsuke Omodaka

  3. Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, Japan

    Naoko Mori, Shunji Mugikura & Kei Takase

  4. Division of Image Statistics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan

    Shunji Mugikura

  5. Department of Neurosurgical Engineering and Translational Neuroscience, Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan

    Kuniyasu Niizuma

  6. Department of Neurosurgical Engineering and Translational Neuroscience, Tohoku University Graduate School of Medicine, Sendai, Japan

    Kuniyasu Niizuma

Authors
  1. Hidenori Endo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Naoko Mori
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shunji Mugikura
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kuniyasu Niizuma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shunsuke Omodaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kei Takase
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Teiji Tominaga
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: [Naoko Mori], [Hidenori Endo]; methodology: [Shunji Mugikura], [Naoko Mori]; formal analysis and investigation: [Kuniyasu Niizuma], [Shunsuke Omodaka]; writing—original draft preparation: [Naoko Mori], [Hidenori Endo]; writing—review and editing: [Naoko Mori], [Teiji Tominaga]; Funding acquisition: [Naoko Mori]; resources: [Hidenori Endo], [Teiji Tominaga], [Kei Takase]; supervision: [Teiji Tominaga].

Corresponding author

Correspondence to Naoko Mori.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Ethics approval

This study was approved by the institutional review board. The requirement for informed consent for this study was waived because of its retrospective design.

Consent to participate

The requirement for informed consent for this study was waived because of its retrospective design.

Consent for publication

The requirement for informed consent for this study was waived because of its retrospective design.

Additional information

Publisher's note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 34 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Endo, H., Mori, N., Mugikura, S. et al. Quantitative assessment of microstructural evolution of intracranial aneurysm wall by vessel wall imaging. Neuroradiology 64, 1343–1350 (2022). https://doi.org/10.1007/s00234-021-02877-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00234-021-02877-7

Keywords

Search

Navigation