Tracking motor and language eloquent white matter pathways with intraoperative fiber tracking versus preoperative tractography adjusted by intraoperative MRI–based elastic fusion

Wei ZhangDepartments of Neurosurgery and

Search for other papers by Wei Zhang in
Current site
Google Scholar
PubMed
Close
 MD
,
Sebastian IlleDepartments of Neurosurgery and

Search for other papers by Sebastian Ille in
Current site
Google Scholar
PubMed
Close
 MD
,
Maximilian SchwendnerDepartments of Neurosurgery and

Search for other papers by Maximilian Schwendner in
Current site
Google Scholar
PubMed
Close
 MD
,
Benedikt WiestlerDiagnostic and Interventional Neuroradiology, Technical University of Munich School of Medicine, Munich, Germany

Search for other papers by Benedikt Wiestler in
Current site
Google Scholar
PubMed
Close
 MD
,
Bernhard MeyerDepartments of Neurosurgery and

Search for other papers by Bernhard Meyer in
Current site
Google Scholar
PubMed
Close
 MD
, and
Sandro M. KriegDepartments of Neurosurgery and

Search for other papers by Sandro M. Krieg in
Current site
Google Scholar
PubMed
Close
 MD, MBA
Restricted access

Purchase Now

USD  $45.00

JNS + Pediatrics - 1 year subscription bundle (Individuals Only)

USD  $515.00

JNS + Pediatrics + Spine - 1 year subscription bundle (Individuals Only)

USD  $612.00
USD  $45.00
USD  $515.00
USD  $612.00
Print or Print + Online Sign in

OBJECTIVE

Preoperative fiber tracking (FT) enables visualization of white matter pathways. However, the intraoperative accuracy of preoperative image registration is reduced due to brain shift. Intraoperative FT is currently considered the standard of anatomical accuracy, while intraoperative imaging can also be used to correct and update preoperative data by intraoperative MRI (ioMRI)–based elastic fusion (IBEF). However, the use of intraoperative tractography is restricted due to the need for additional acquisition of diffusion imaging in addition to scanner limitations, quality factors, and setup time. Since IBEF enables compensation for brain shift and updating of preoperative FT, the aim of this study was to compare intraoperative FT with IBEF of preoperative FT.

METHODS

Preoperative MRI (pMRI) and ioMRI, both including diffusion tensor imaging (DTI) data, were acquired between February and November 2018. Anatomy-based DTI FT of the corticospinal tract (CST) and the arcuate fascicle (AF) was reconstructed at various fractional anisotropy (FA) values on pMRI and ioMRI, respectively. The intraoperative DTI FT, as a baseline tractography, was fused with original preoperative FT and IBEF-compensated FT, processes referred to as rigid fusion (RF) and elastic fusion (EF), respectively. The spatial overlap index (Dice coefficient [DICE]) and distances of surface points (average surface distance [ASD]) of fused FT before and after IBEF were analyzed and compared in operated and nonoperated hemispheres.

RESULTS

Seventeen patients with supratentorial brain tumors were analyzed. On the operated hemisphere, the overlap index of pre- and intraoperative FT of the CST by DICE significantly increased by 0.09 maximally after IBEF. A significant decrease by 0.5 mm maximally in the fused FT presented by ASD was observed. Similar improvements were found in IBEF-compensated FT, for which AF tractography on the tumor hemispheres increased by 0.03 maximally in DICE and decreased by 1.0 mm in ASD.

CONCLUSIONS

Preoperative tractography after IBEF is comparable to intraoperative tractography and can be a reliable alternative to intraoperative FT.

ABBREVIATIONS

AF = arcuate fascicle; ASD = average surface distance; CST = corticospinal tract; DICE = Dice coefficient; DTI = diffusion tensor imaging; EF = elastic fusion; FA = fractional anisotropy; FAT = FA threshold; FEM = finite element modeling; FT = fiber tracking; GNO = group of nonoperated hemispheres; GO = group of operated hemispheres; IBEF = ioMRI-based EF; ioMRI = intraoperative MRI; MFL = minimum fiber length; pMRI = preoperative MRI; RF = rigid fusion; ROI = region of interest.
  • Collapse
  • Expand

Illustration from Di Somma et al. (pp 1187–1190). Published with permission from Glia Media | Artist: Martha Headworth, MS.

  • 1

    Bello L, Gambini A, Castellano A, et al. Motor and language DTI fiber tracking combined with intraoperative subcortical mapping for surgical removal of gliomas. Neuroimage. 2008;39(1):369382.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Leclercq D, Duffau H, Delmaire C, et al. Comparison of diffusion tensor imaging tractography of language tracts and intraoperative subcortical stimulations. J Neurosurg. 2010;112(3):503511.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    Gerard IJ, Kersten-Oertel M, Petrecca K, Sirhan D, Hall JA, Collins DL. Brain shift in neuronavigation of brain tumors: a review. Med Image Anal. 2017;35:403420.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Khalid MT, Allen JC Jr, King NKK, et al. Characterization of pyramidal tract shift in high-grade glioma resection. World Neurosurg. 2017;107:612622.

  • 5

    Nimsky C, Ganslandt O, Hastreiter P, et al. Intraoperative diffusion-tensor MR imaging: shifting of white matter tracts during neurosurgical procedures—initial experience. Radiology. 2005;234(1):218225.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Bayer S, Maier A, Ostermeier M, Fahrig R. Intraoperative imaging modalities and compensation for brain shift in tumor resection surgery. Int J Biomed Imaging. 2017;2017:6028645.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Maesawa S, Fujii M, Nakahara N, Watanabe T, Wakabayashi T, Yoshida J. Intraoperative tractography and motor evoked potential (MEP) monitoring in surgery for gliomas around the corticospinal tract. World Neurosurg. 2010;74(1):153161.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8

    Ostrý S, Belšan T, Otáhal J, Beneš V, Netuka D. Is intraoperative diffusion tensor imaging at 3.0T comparable to subcortical corticospinal tract mapping? Neurosurgery. 2013;73(5):797807.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Javadi SA, Nabavi A, Giordano M, Faghihzadeh E, Samii A. Evaluation of diffusion tensor imaging-based tractography of the corticospinal tract: a correlative study with intraoperative magnetic resonance imaging and direct electrical subcortical stimulation. Neurosurgery. 2017;80(2):287299.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Nimsky C. Intraoperative acquisition of fMRI and DTI. Neurosurg Clin N Am. 2011;22(2):26977.ix.

  • 11

    Münnich T, Klein J, Hattingen E, et al. Tractography verified by intraoperative magnetic resonance imaging and subcortical stimulation during tumor resection near the corticospinal tract. Oper Neurosurg (Hagerstown). 2019;16(2):197210.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Nimsky C, Ganslandt O, Merhof D, Sorensen AG, Fahlbusch R. Intraoperative visualization of the pyramidal tract by diffusion-tensor-imaging-based fiber tracking. Neuroimage. 2006;30(4):12191229.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Kuhnt D, Bauer MH, Nimsky C. Brain shift compensation and neurosurgical image fusion using intraoperative MRI: current status and future challenges. Crit Rev Biomed Eng. 2012;40(3):175185.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Romano A, D’Andrea G, Calabria LF, et al. Pre- and intraoperative tractographic evaluation of corticospinal tract shift. Neurosurgery. 2011;69(3):696705.

  • 15

    Negwer C, Hiepe P, Meyer B, Krieg SM. Elastic fusion enables fusion of intraoperative magnetic resonance imaging data with preoperative neuronavigation data. World Neurosurg. 2020;142:e223e228.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Ille S, Schroeder A, Wagner A, et al. Intraoperative MRI-based elastic fusion for anatomically accurate tractography of the corticospinal tract: correlation with intraoperative neuromonitoring and clinical status. Neurosurg Focus. 2021;50(1):E9.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Ille S, Schwendner M, Zhang W, Schroeder A, Meyer B, Krieg SM. Tractography for subcortical resection of gliomas is highly accurate for motor and language function: ioMRI-based elastic fusion disproves the severity of brain shift. Cancers (Basel). 2021;13(8):1787.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18

    Taylor PA, Alhamud A, van der Kouwe A, Saleh MG, Laughton B, Meintjes E. Assessing the performance of different DTI motion correction strategies in the presence of EPI distortion correction. Hum Brain Mapp. 2016;37(12):44054424.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Albi A, Meola A, Zhang F, et al. Image registration to compensate for EPI distortion in patients with brain tumors: an evaluation of tract-specific effects. J Neuroimaging. 2018;28(2):173182.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Gerhardt J, Sollmann N, Hiepe P, et al. Retrospective distortion correction of diffusion tensor imaging data by semi-elastic image fusion—evaluation by means of anatomical landmarks. Clin Neurol Neurosurg. 2019;183:105387.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Sollmann N, Negwer C, Ille S, et al. Feasibility of nTMS-based DTI fiber tracking of language pathways in neurosurgical patients using a fractional anisotropy threshold. J Neurosci Methods. 2016;267:4554.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Frey D, Strack V, Wiener E, Jussen D, Vajkoczy P, Picht T. A new approach for corticospinal tract reconstruction based on navigated transcranial stimulation and standardized fractional anisotropy values. Neuroimage. 2012;62(3):16001609.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Negwer C, Sollmann N, Ille S, et al. Language pathway tracking: comparing nTMS-based DTI fiber tracking with a cubic ROIs-based protocol. J Neurosurg. 2017;126(3):10061014.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    Rosenstock T, Giampiccolo D, Schneider H, et al. Specific DTI seeding and diffusivity-analysis improve the quality and prognostic value of TMS-based deterministic DTI of the pyramidal tract. Neuroimage Clin. 2017;16:276285.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Weiss C, Tursunova I, Neuschmelting V, et al. Improved nTMS- and DTI-derived CST tractography through anatomical ROI seeding on anterior pontine level compared to internal capsule. Neuroimage Clin. 2015;7:424437.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    Huang H, Zhang J, van Zijl PC, Mori S. Analysis of noise effects on DTI-based tractography using the brute-force and multi-ROI approach. Magn Reson Med. 2004;52(3):559565.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27

    Mori S, van Zijl PC. Fiber tracking: principles and strategies—a technical review. NMR Biomed. 2002;15(7-8):468480.

  • 28

    Giordano M, Nabavi A, Gerganov VM, et al. Assessment of quantitative corticospinal tract diffusion changes in patients affected by subcortical gliomas using common available navigation software. Clin Neurol Neurosurg. 2015;136:14.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Sollmann N, Wildschuetz N, Kelm A, et al. Associations between clinical outcome and navigated transcranial magnetic stimulation characteristics in patients with motor-eloquent brain lesions: a combined navigated transcranial magnetic stimulation-diffusion tensor imaging fiber tracking approach. J Neurosurg. 2018;128(3):800810.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    Glasser MF, Rilling JK. DTI tractography of the human brain’s language pathways. Cereb Cortex. 2008;18(11):24712482.

  • 31

    Catani M, Jones DK, ffytche DH. Perisylvian language networks of the human brain. Ann Neurol. 2005;57(1):816.

  • 32

    Riva M, Hiepe P, Frommert M, et al. Intraoperative computed tomography and finite element modelling for multimodal image fusion in brain surgery. Oper Neurosurg (Hagerstown). 2020;18(5):531541.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33

    Zou KH, Warfield SK, Bharatha A, et al. Statistical validation of image segmentation quality based on a spatial overlap index. Acad Radiol. 2004;11(2):178189.

  • 34

    Taha AA, Hanbury A. Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool. BMC Med Imaging. 2015;15:29.

  • 35

    Heimann T, van Ginneken B, Styner MA, et al. Comparison and evaluation of methods for liver segmentation from CT datasets. IEEE Trans Med Imaging. 2009;28(8):12511265.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36

    Fan X, Roberts DW, Olson JD, et al. Image updating for brain shift compensation during resection. Oper Neurosurg (Hagerstown). 2018;14(4):402411.

  • 37

    Luo M, Frisken SF, Weis JA, et al. Retrospective study comparing model-based deformation correction to intraoperative magnetic resonance imaging for image-guided neurosurgery. J Med Imaging (Bellingham). 2017;4(3):035003.

    • Search Google Scholar
    • Export Citation
  • 38

    Krivosheya D, Rao G, Tummala S, et al. Impact of multi-modality monitoring using direct electrical stimulation to determine corticospinal tract shift and integrity in tumors using the intraoperative MRI. J Neurol Surg A Cent Eur Neurosurg. 2021;82(4):375380.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39

    Vargas MI, Delavelle J, Kohler R, Becker CD, Lovblad K. Brain and spine MRI artifacts at 3Tesla. J Neuroradiol. 2009;36(2):7481.

  • 40

    Ginat DT, Swearingen B, Curry W, Cahill D, Madsen J, Schaefer PW. 3 Tesla intraoperative MRI for brain tumor surgery. J Magn Reson Imaging. 2014;39(6):13571365.

Metrics

All Time Past Year Past 30 Days
Abstract Views 1480 1480 61
Full Text Views 13110 13110 9
PDF Downloads 177 177 9
EPUB Downloads 0 0 0