European Radiology

, Volume 26, Issue 7, pp 2233–2241 | Cite as

Parotid gland tumours: MR tractography to assess contact with the facial nerve

  • Arnaud Attyé
  • Alexandre Karkas
  • Irène Troprès
  • Matthieu Roustit
  • Adrian Kastler
  • Georges Bettega
  • Laurent Lamalle
  • Félix Renard
  • Christian Righini
  • Alexandre Krainik
Head and Neck

Abstract

Objectives

To assess the feasibility of intraparotid facial nerve (VIIn) tractographic reconstructions in estimating the presence of a contact between the VIIn and the tumour, in patients requiring surgical resection of parotid tumours.

Methods

Patients underwent MR scans with VIIn tractography calculated with the constrained spherical deconvolution model. The parameters of the diffusion sequence were: b-value of 1000 s/mm2; 32 directions; voxel size: 2 mm isotropic; scan time: 9’31’. The potential contacts between VIIn branches and tumours were estimated with different initial fractional anisotropy (iFA) cut-offs compared to surgical data. Surgeons were blinded to the tractography reconstructions and identified both nerves and contact with tumours using nerve stimulation and reference photographs.

Results

Twenty-six patients were included in this study and the mean patient age was 55.2 years. Surgical direct assessment of VIIn allowed identifying 0.1 as the iFA threshold with the best sensitivity to detect tumour contact. In all patients with successful VIIn identification by tractography, surgeons confirmed nerve courses as well as lesion location in parotid glands. Mean VIIn branch FA values were significantly lower in cases with tumour contact (t-test; p ≤ 0.01).

Conclusions

This study showed the feasibility of intraparotid VIIn tractography to identify nerve contact with parotid tumours.

Key points

Diffusion imaging is an efficient method for highlighting the intraparotid VIIn.

Visualization of the VIIn may help to better manage patients before surgery.

We bring new insights to future trials for patients with VIIn dysfunction.

We aimed to provide radio-anatomical references for further studies.

Keywords

Diffusion tractography Parotid gland Facial nerve Magnetic resonance imaging Salivary gland neoplasms 

Abbreviations

VIIn

Facial nerve

CF

Cervicofacial branch

TF

Temporofacial branch

DTI

Diffusion tensor imaging

CSD

Constrained spherical deconvolution

FA

Fractional anisotropy

bFFE

Balanced fast field echo

ROI

Region of interest

FND

Facial nerve division

ODF

Orientation density function

SNR

Signal to noise ratio

SH

Spherical harmonic

IAC

Internal auditory canal

DW

Diffusion-weighted imaging

References

  1. 1.
    Guntinas-Lichius O, Klussmann JP, Wittekindt C, Stennert E (2006) Parotidectomy for benign parotid disease at a university teaching hospital: outcome of 963 operations. Laryngoscope 116:534–540CrossRefPubMedGoogle Scholar
  2. 2.
    Gaillard C, Périé S, Susini B, St Guily JL (2005) Facial nerve dysfunction after parotidectomy: the role of local factors. Laryngoscope 115:287–291CrossRefPubMedGoogle Scholar
  3. 3.
    Qin Y, Zhang J, Li P, Wang Y (2011) 3D double-echo steady-state with water excitation MR imaging of the intraparotid facial nerve at 1.5T: a pilot study. AJNR Am J Neuroradiol 32:1167–1172CrossRefPubMedGoogle Scholar
  4. 4.
    Li C, Li Y, Zhang D et al (2012) 3D-FIESTA MRI at 3 T demonstrating branches of the intraparotid facial nerve, parotid ducts and relation with benign parotid tumours. Clin Radiol 67:1078–1082CrossRefPubMedGoogle Scholar
  5. 5.
    Farquharson S, Tournier J-D, Calamante F et al (2013) White matter fiber tractography: why we need to move beyond DTI. J Neurosurg 118:1367–1377CrossRefPubMedGoogle Scholar
  6. 6.
    Tournier J-D, Calamante F, Gadian DG, Connelly A (2004) Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage 23:1176–1185CrossRefPubMedGoogle Scholar
  7. 7.
    Tournier J-D, Calamante F, Connelly A (2007) Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage 35:1459–1472CrossRefPubMedGoogle Scholar
  8. 8.
    Calamante F, Oh S-H, Tournier J-D et al (2013) Super-resolution track-density imaging of thalamic substructures: comparison with high-resolution anatomical magnetic resonance imaging at 7.0T. Hum Brain Mapp 34:2538–2548CrossRefPubMedGoogle Scholar
  9. 9.
    Calamante F, Tournier J-D, Kurniawan ND et al (2012) Super-resolution track-density imaging studies of mouse brain: comparison to histology. Neuroimage 59:286–296CrossRefPubMedGoogle Scholar
  10. 10.
    Tournier J-D, Yeh C-H, Calamante F et al (2008) Resolving crossing fibres using constrained spherical deconvolution: validation using diffusion-weighted imaging phantom data. Neuroimage 42:617–625CrossRefPubMedGoogle Scholar
  11. 11.
    Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174CrossRefPubMedGoogle Scholar
  12. 12.
    Kwak HH, Park HD, Youn KH et al (2004) Branching patterns of the facial nerve and its communication with the auriculotemporal nerve. Surg Radiol Anat 26:494–500CrossRefPubMedGoogle Scholar
  13. 13.
    Davis RA, Anson BJ, Budinger JM, Kurth LR (1956) Surgical anatomy of the facial nerve and parotid gland based upon a study of 350 cervicofacial halves. Surg Gynecol Obstet 102:385–412PubMedGoogle Scholar
  14. 14.
    Salame K, Ouaknine GER, Arensburg B, Rochkind S (2002) Microsurgical anatomy of the facial nerve trunk. Clin Anat 15:93–99CrossRefPubMedGoogle Scholar
  15. 15.
    Roundy N, Delashaw JB, Cetas JS (2012) Preoperative identification of the facial nerve in patients with large cerebellopontine angle tumors using high-density diffusion tensor imaging. J Neurosurg 116:697–702CrossRefPubMedGoogle Scholar
  16. 16.
    Taoka T, Hirabayashi H, Nakagawa H et al (2006) Displacement of the facial nerve course by vestibular schwannoma: preoperative visualization using diffusion tensor tractography. J Magn Reson Imaging 24:1005–1010CrossRefPubMedGoogle Scholar
  17. 17.
    Righini CA, Petrossi J, Reyt E, Atallah I (2014) An original submandibular approach technique sparing the cervical branch of the facial nerve. Eur Ann Otorhinolaryngol Head Neck Dis 131:143–146CrossRefPubMedGoogle Scholar
  18. 18.
    Conturo TE, Lori NF, Cull TS et al (1999) Tracking neuronal fiber pathways in the living human brain. Proc Natl Acad Sci U S A 96:10422–10427CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Descoteaux M, Deriche R, Knösche TR, Anwander A (2009) Deterministic and probabilistic tractography based on complex fibre orientation distributions. IEEE Trans Med Imaging 28:269–286CrossRefPubMedGoogle Scholar
  20. 20.
    Jones DK (2004) The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn Reson Med 51:807–815CrossRefPubMedGoogle Scholar
  21. 21.
    Hodaie M, Chen DQ, Quan J, Laperriere N (2012) Tractography delineates microstructural changes in the trigeminal nerve after focal radiosurgery for trigeminal neuralgia. PLoS ONE 7:e32745CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Budzik J-F, Balbi V, Verclytte S et al (2014) Diffusion tensor imaging in musculoskeletal disorders. Radiographics 34:E56–E72CrossRefPubMedGoogle Scholar
  23. 23.
    Rotshenker S (2011) Wallerian degeneration: the innate-immune response to traumatic nerve injury. J Neuroinflammation 8:109CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Khalil C, Hancart C, Le Thuc V et al (2008) Diffusion tensor imaging and tractography of the median nerve in carpal tunnel syndrome: preliminary results. Eur Radiol 18:2283–2291CrossRefPubMedGoogle Scholar
  25. 25.
    Barcelo C, Faruch M, Lapègue F et al (2013) 3-T MRI with diffusion tensor imaging and tractography of the median nerve. Eur Radiol 23:3124–3130CrossRefPubMedGoogle Scholar
  26. 26.
    Guggenberger R, Markovic D, Eppenberger P et al (2012) Assessment of median nerve with MR neurography by using diffusion-tensor imaging: normative and pathologic diffusion values. Radiology 265:194–203CrossRefPubMedGoogle Scholar
  27. 27.
    Breitenseher JB, Kranz G, Hold A et al (2015) MR neurography of ulnar nerve entrapment at the cubital tunnel: a diffusion tensor imaging study. Eur Radiol 25:1911–1918CrossRefPubMedGoogle Scholar
  28. 28.
    Jengojan S, Kovar F, Breitenseher J et al (2015) Acute radial nerve entrapment at the spiral groove: detection by DTI-based neurography. Eur Radiol 25:1678–1683CrossRefPubMedGoogle Scholar
  29. 29.
    Tournier J-D, Calamante F, Connelly A (2013) Determination of the appropriate b value and number of gradient directions for high-angular-resolution diffusion-weighted imaging. NMR Biomed 26:1775–1786CrossRefPubMedGoogle Scholar
  30. 30.
    Pannek K, Mathias JL, Bigler ED et al (2011) The average pathlength map: a diffusion MRI tractography-derived index for studying brain pathology. Neuroimage 55:133–141CrossRefPubMedGoogle Scholar
  31. 31.
    Willats L, Raffelt D, Smith RE et al (2014) Quantification of track-weighted imaging (TWI): characterisation of within-subject reproducibility and between-subject variability. Neuroimage 87:18–31CrossRefPubMedGoogle Scholar
  32. 32.
    Chang H-C, Juan C-J, Chiu H-C et al (2014) Effects of gender, age, and body mass index on fat contents and apparent diffusion coefficients in healthy parotid glands: an MRI evaluation. Eur Radiol 24:2069–2076CrossRefPubMedGoogle Scholar
  33. 33.
    Smith RE, Tournier J-D, Calamante F, Connelly A (2015) The effects of SIFT on the reproducibility and biological accuracy of the structural connectome. Neuroimage 104:253–265CrossRefPubMedGoogle Scholar
  34. 34.
    Smith RE, Tournier J-D, Calamante F, Connelly A (2013) SIFT: spherical-deconvolution informed filtering of tractograms. Neuroimage 67:298–312CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2015

Authors and Affiliations

  • Arnaud Attyé
    • 1
    • 2
    • 3
    • 9
  • Alexandre Karkas
    • 4
  • Irène Troprès
    • 2
    • 3
    • 5
  • Matthieu Roustit
    • 6
  • Adrian Kastler
    • 1
    • 2
    • 3
  • Georges Bettega
    • 7
  • Laurent Lamalle
    • 2
    • 3
    • 5
  • Félix Renard
    • 3
  • Christian Righini
    • 4
    • 8
  • Alexandre Krainik
    • 1
    • 2
    • 3
  1. 1.Department of Neuroradiology and MRIGrenoble University Hospital – SFR RMN NeurosciencesGrenobleFrance
  2. 2.Inserm, US 17GrenobleFrance
  3. 3.University Grenoble Alpes, IRMaGeGrenobleFrance
  4. 4.Department of Otolaryngology-Head and Neck SurgeryUniversity Hospital of GrenobleGrenobleFrance
  5. 5.CNRS, UMS 3552GrenobleFrance
  6. 6.Department of StatisticsUniversity Hospital of GrenobleGrenobleFrance
  7. 7.Department of Maxillofacial SurgeryUniversity Hospital of GrenobleGrenobleFrance
  8. 8.Albert Bonniot InstituteGrenobleFrance
  9. 9.Neuroradiology and MR UnitCS 10217- Grenoble University HospitalGrenobleFrance

Personalised recommendations