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Color-encoded distance visualization of cranial nerve-vessel contacts

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Visualization of pathological contact between cranial nerves and vascular structures at the surface of the brainstem is important for diagnosis and treatment of neurovascular compression (NVC) syndromes. We developed a method for improved visualization of this abnormality.

Methods

Distance fields were computed using preoperative MRI scans of individuals with NVC syndromes to support the topological representation of brainstem surface structures with quantitative information. Polygonal models of arteries, cranial nerves and the brainstem were generated using segmented T2 weighted MR data. After color-coding the polygonal models with the respective distances, enhanced color visualization of vessel-nerve locations with possible contacts was achieved.

Results

The proposed method was implemented and applied to surgical planning in a dozen cases of NVC syndrome. Two selected cases were chosen to demonstrate the feasibility and subjective improvement provided by our visualization technique. Expert neurosurgeons found the improvement valuable and useful for these cases.

Conclusion

Color-encoded distance information significantly improves the perceptibility of potential nerve-vessel contacts. This method contributes to a better understanding of the complex anatomical situation at the surface of the brainstem and assists in planning of surgery.

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References

  1. Akimoto H, Nagaoka T, Nariai T, Takada Y, Ohno K, Yoshino N (2002) Preoperative evaluation of neurovascular compression in patients with trigeminal neuralgia by use of three-dimensional reconstruction from two types of high-resolution magnetic resonance imaging. Neurosurgery 51(4): 956–961

    Article  PubMed  Google Scholar 

  2. Barker FG II, Jannetta PJ, Bissonette DJ, Shields PT, Larkins MV, Jho HD (1995) Microvascular decompression for hemifacial spasm. J Neurosurg 82: 201–210

    Article  PubMed  Google Scholar 

  3. Boecher-Schwarz HG, Bruehl K, Kessel G, Guenthner M, Perneczky A, Stoeter P (1998) Sensitivity and specificity of MRA in the diagnosis of neurovascular compression in patients with trigeminal neuralgia: a correlation of MRA and surgical findings. Neuroradiology 40: 88–95

    Article  CAS  PubMed  Google Scholar 

  4. De Ridder D, Moller A, Verlooy J, Cornelissen M, De Ridder L (2002) Is the root entry/exit zone important in microvascular compression syndromes?. Neurosurgery 51: 427–434

    Article  PubMed  Google Scholar 

  5. Dijkstra EW (1959) A note on two problems in connexion with graphs. Numerische Mathematik 1: 269–271

    Article  Google Scholar 

  6. Hadwiger M, Sigg C, Scharsach H, Bühler K, Gross M (2005) Real-time ray-casting and advanced shading of discrete isosurfaces. Comput Graph Forum 24(3): 303–312

    Article  Google Scholar 

  7. Hastreiter P, Naraghi R, Tomandl B, Bauer M, Fahlbusch R (2002) 3D-Visualization and registration for neurovascular compression syndrome analysis. MICCAI 396–403

  8. Hastreiter P, Naraghi R, Tomandl B, Bonk A, Fahlbusch R (2003) Analysis and 3-dimensional visualization of neurovascular compression syndromes. Acad Radiol 10(12): 1369–1379

    Article  PubMed  Google Scholar 

  9. Hastreiter P, Vega-Higuera F, Tomandl B, Fahlbusch R, Naraghi R (2004) Advanced and standardized evaluation of neurovascular compression syndromes. SPIE Med Imaging 5367: 267–274

    Google Scholar 

  10. Jannetta PJ (1967) Arterial compression of the trigeminal nerve at the pons in patients with trigeminal neuralgia. J Neurosurg 26(1): 159–162

    Article  PubMed  Google Scholar 

  11. Jannetta PJ (1980) Neurovascular compression in cranial nerve and systemic disease. Ann Surg 192: 518–525

    Article  CAS  PubMed  Google Scholar 

  12. Kin T, Oyama H, Kamada K, Aoki S, Ohtomo K, Saito N (2009) Prediction of surgical view of neurovascular decompression using interactive computer graphics. Neurosurgery 65(1): 121–128

    Article  PubMed  Google Scholar 

  13. Kobbelt L, Campagna S, Vorsatz J, Seidel H-P (1998) Interactive multi-resolution modeling on arbitrary meshes. SIGGRAPH 105–114

  14. Krüger J, Westermann R (2003) Acceleration techniques for GPU-based volume rendering. IEEE Vis 287–292

  15. Lorensen WE, Cline HE (1987) Marching cubes: a high resolution 3D surface construction algorithm. SIGGRAPH 163–169

  16. McLaughlin MR, Jannetta PJ, Clyde BL, Subach BR, Comey CH, Resnick DK (1999) Microvascular decompression of cranial nerves: lessons learned after 4,400 operations. J Neurosurg 90: 1–8

    Article  CAS  PubMed  Google Scholar 

  17. Miller J, Acar F, Hamilton B, Burchiel K (2008) Preoperative visualization of neurovascular anatomy in trigeminal. J Neurosurg 108(3): 477–482

    Article  PubMed  Google Scholar 

  18. Mortensen EN, Barrett WA (1998) Interactive segmentation with intelligent scissors. Graph Models Image Process 60(5): 349–384

    Article  Google Scholar 

  19. Naraghi R, Hastreiter P, Tomandl B, Bonk A, Huk W, Fahlbusch R (2004) Three dimensional visualization of neurovascular relationship in the posterior fossa. Technique and clinical application. J Neurosurg 100(6): 1025–1035

    Article  PubMed  Google Scholar 

  20. Naraghi R, Tanrikulu L, Troescher-Weber R, Bischoff B, Hecht M, Buchfelder M, Hastreiter P (2007) Classification of neurovascular compression in typical hemifacial spasm: three-dimensional visualization of the facial and the vestibulocochlear nerves. J Neurosurg 107(6): 1154–1163

    Article  PubMed  Google Scholar 

  21. Ni S, Su W, Li X, Zeng Q, Liu Y, Zhu S, Wu C (2009) Enhanced three-dimensional fast spoiled gradient recalled MRI combined with magnetic resonance angiography for preoperative assessment of patients with trigeminal neuralgia. J Clin Neurosci 16(12): 1555–1559

    Article  PubMed  Google Scholar 

  22. Peker S, Dinçer A, Necmettin Pamir M. (2009) Vascular compression of the trigeminal nerve is a frequent finding in asymptomatic individuals: 3-T MR imaging of 200 trigeminal nerves using 3D CISS sequences. Acta Neurochir (Wien) 151(9): 1081–1088

    Article  Google Scholar 

  23. Raslan AM, DeJesus R, Berk C, Zacest A, Anderson JC, Burchiel KJ (2009) Sensitivity of high-resolution three-dimensional magnetic resonance angiography and three-dimensional spoiled-gradient recalled imaging in the prediction of neurovascular compression in patients with hemifacial spasm. J Neurosurg 111(4): 733–736

    Article  PubMed  Google Scholar 

  24. Satoh T, Omi M, Nabeshima M, Onoda K, Date I (2009) Severity analysis of neurovascular contact in patients with trigeminal neuralgia: assessment with the inner view of the 3D MR cisternogram and angiogram fusion imaging. Am J Neuroradiol 30(3): 603–607

    Article  CAS  PubMed  Google Scholar 

  25. Süßmuth J, Piazza A, Enders F, Naraghi R, Greiner G, Hastreiter P (2009) Analysis and visualization of nerve vessel contacts for neurovascular decompression. Bildverarbeitung für die Medizin (BVM) 21–25

  26. Takao T, Oishi M, Fukuda M, Ishida G, Sato M, Fujii Y (2008) Three-dimensional visualization of neurovascular compression: presurgical use of virtual endoscopy created from magnetic resonance imaging. Neurosurgery 63: 139–145

    Article  Google Scholar 

  27. Tanrikulu L, Hastreiter P, Troescher-Weber R, Buchfelder M, Naraghi R (2007) Intraoperative three-dimensional visualization in microvascular decompression. J Neurosurg 107(6): 1137–1143

    Article  PubMed  Google Scholar 

  28. Tessmann M, Eisenacher C, Enders F, Stamminger M, Hastreiter P (2008) GPU accelerated normalized mutual information and B-spline transformation. EG VCBM 117–124

  29. Vega-Higuera F, Hastreiter P, Fahlbusch R, Greiner G (2005) High performance volume splatting for visualization of neurovascular data. IEEE Vis 271–278

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Authors and Affiliations

  1. Informatik 9-Computer Graphics Group, University of Erlangen-Nuremberg, Am Wolfsmantel 33, 91058, Erlangen, Germany

    Jochen Süßmuth, Wassilios-Daniele Protogerakis, Alexander Piazza & Günther Greiner

  2. Department of Neurosurgery, University of Erlangen-Nuremberg, Erlangen, Germany

    Frank Enders, Ramin Naraghi & Peter Hastreiter

Authors
  1. Jochen Süßmuth
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  2. Wassilios-Daniele Protogerakis
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  3. Alexander Piazza
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  4. Frank Enders
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  5. Ramin Naraghi
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  6. Günther Greiner
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  7. Peter Hastreiter
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Corresponding author

Correspondence to Jochen Süßmuth.

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Süßmuth, J., Protogerakis, WD., Piazza, A. et al. Color-encoded distance visualization of cranial nerve-vessel contacts. Int J CARS 5, 647–654 (2010). https://doi.org/10.1007/s11548-010-0410-2

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  • DOI: https://doi.org/10.1007/s11548-010-0410-2

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