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DOI: 10.1055/s-0039-1677864
Super-resolution Diffusion Tensor Imaging for Delineating the Facial Nerve in Patients with Vestibular Schwannoma
Funding Sources American Hearing Health Foundation.Publication History
16 October 2018
16 December 2018
Publication Date:
01 March 2019 (online)
Abstract
Objectives Predicting the course of cranial nerves (CNs) VII and VIII in the cerebellopontine angle on preoperative imaging for vestibular schwannoma (VS) may help guide surgical resection and reduce complications. Diffusion magnetic resonance imaging dMRI is commonly used for this purpose, but is limited by its resolution. We investigate the use of super-resolution reconstruction (SRR), where several different dMRIs are combined into one dataset. We hypothesize that SRR improves the visualization of the CN VII and VIII.
Design Retrospective case review.
Setting Tertiary referral center. SRR was performed on the basis of axial and parasagittal single-shot epiplanar diffusion tensor imaging on a 3.0-tesla MRI scanner.
Participants Seventeen adult patients with suspected neoplasms of the lateral skull base.
Main Outcome Measures We assessed separability of the two distinct nerves on fractional anisotropy (FA) maps, the tractography of the nerves through the cerebrospinal fluid (CSF), and FA in the CSF as a measure of noise.
Results SRR increases separability of the CN VII and VIII (16/17 vs. 0/17, p = 0.008). Mean FA of CSF surrounding the nerves is significantly lower in SRRs (0.07 ± 0.02 vs. 0.13 ± 0.03 [axial images]/0.14 ± 0.05 [parasagittal images], p = 0.00003/p = 0.00005). Combined scanning times (parasagittal and axial) used for SRR were shorter (8 minute 25 seconds) than a comparable high-resolution scan (15 minute 17 seconds).
Conclusion SRR improves the resolution of CN VII and VIII. The technique can be readily applied in the clinical setting, improving surgical counseling and planning in patients with VS.
Keywords
super-resolution - diffusion tensor imaging - tractography - facial nerve - vestibular schwannoma - cochlear nerveFinancial Disclosures
None.
* Contributed equally.
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References
- 1 Samii M, Gerganov V, Samii A. Improved preservation of hearing and facial nerve function in vestibular schwannoma surgery via the retrosigmoid approach in a series of 200 patients. J Neurosurg 2006; 105 (04) 527-535
- 2 Mikami T, Minamida Y, Yamaki T, Koyanagi I, Nonaka T, Houkin K. Cranial nerve assessment in posterior fossa tumors with fast imaging employing steady-state acquisition (FIESTA). Neurosurg Rev 2005; 28 (04) 261-266
- 3 Zhang Y, Mao Z, Wei P. , et al. Preoperative prediction of location and shape of facial nerve in patients with large vestibular schwannomas using diffusion tensor imaging-based fiber tracking. World Neurosurg 2017; 99: 70-78
- 4 Hilly O, Chen JM, Birch J. , et al. Diffusion tensor imaging tractography of the facial nerve in patients with cerebellopontine angle tumors. Otol Neurotol 2016; 37 (04) 388-393
- 5 Yoshino M, Abhinav K, Yeh F-C. , et al. Visualization of cranial nerves using high-definition fiber tractography. Neurosurgery 2016; 79 (01) 146-165
- 6 O'Donnell LJ, Westin C-F. An introduction to diffusion tensor image analysis. Neurosurg Clin N Am 2011; 22 (02) 185-196 , viii
- 7 Stejskal EO, Tanner JE. Spin diffusion measurements: Spin echoes in the presence of a time-dependent field gradient. J Chem Phys 1965; 42 (01) 288-292
- 8 Qin W, Yu CS, Zhang F. , et al. Effects of echo time on diffusion quantification of brain white matter at 1.5 T and 3.0 T. Magn Reson Med 2009; 61 (04) 755-760
- 9 Scherrer B, Gholipour A, Warfield SK. Super-resolution reconstruction to increase the spatial resolution of diffusion weighted images from orthogonal anisotropic acquisitions. Med Image Anal 2012; 16 (07) 1465-1476
- 10 Van Steenkiste G, Jeurissen B, Veraart J. , et al. Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations. Magn Reson Med 2016; 75 (01) 181-195
- 11 Ning L, Setsompop K, Michailovich O. , et al. A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging. Neuroimage 2016; 125: 386-400
- 12 Reeth EV, Tham IWK, Tan CH, Poh CL. Super-resolution in magnetic resonance imaging: a review. Concepts Magn Reson 2012; 40A (06) 306-325
- 13 Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 2002; 17 (02) 825-841
- 14 Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A. In vivo fiber tractography using DT-MRI data. Magn Reson Med 2000; 44 (04) 625-632
- 15 Roundy N, Delashaw JB, Cetas JS. Preoperative identification of the facial nerve in patients with large cerebellopontine angle tumors using high-density diffusion tensor imaging. J Neurosurg 2012; 116 (04) 697-702
- 16 Tu TW, Budde MD, Xie M. , et al. Phase-aligned multiple spin-echo averaging: a simple way to improve signal-to-noise ratio of in vivo mouse spinal cord diffusion tensor image. Magn Reson Imaging 2014; 32 (10) 1335-1343
- 17 Yoshino M, Kin T, Ito A. , et al. Feasibility of diffusion tensor tractography for preoperative prediction of the location of the facial and vestibulocochlear nerves in relation to vestibular schwannoma. Acta Neurochir (Wien) 2015; 157 (06) 939-946 , discussion 946
- 18 Azuma T, Kodama T, Yano T, Enzaki M, Nakamura M, Murata K. Optimal imaging parameters for readout-segmented EPI of the temporal bone. Magn Reson Med Sci 2015; 14 (02) 145-152