fMRI-Targeted High-Angular Resolution Diffusion MR Tractography to Identify Functional Language Tracts in Healthy Controls and Glioma Patients: Frontiers in Neuroscience

F. Sanvito, E. Caverzasi, M. Riva, K.M. Jordan, V. Blasi, P. Scifo, A. Iadanza, S.A. Crespi, S. Cirillo, A. Casarotti, A. Leonetti, G. Puglisi, M. Grimaldi, L. Bello, M.L. Gorno-Tempini, R.G. Henry, A. Falini, A. Castellano

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Background: MR Tractography enables non-invasive preoperative depiction of language subcortical tracts, which is crucial for the presurgical work-up of brain tumors; however, it cannot evaluate the exact function of the fibers. Purpose: A systematic pipeline was developed to combine tractography reconstruction of language fiber bundles, based on anatomical landmarks (Anatomical-T), with language fMRI cortical activations. A fMRI-targeted Tractography (fMRI-T) was thus obtained, depicting the subsets of the anatomical tracts whose endpoints are located inside a fMRI activation. We hypothesized that fMRI-T could provide additional functional information regarding the subcortical structures, better reflecting the eloquent white matter structures identified intraoperatively. Methods: Both Anatomical-T and fMRI-T of language fiber tracts were performed on 16 controls and preoperatively on 16 patients with left-hemisphere brain tumors, using a q-ball residual bootstrap algorithm based on High Angular Resolution Diffusion Imaging (HARDI) datasets (b = 3000 s/mm2; 60 directions); fMRI ROIs were obtained using picture naming, verbal fluency, and auditory verb generation tasks. In healthy controls, normalized MNI atlases of fMRI-T and Anatomical-T were obtained. In patients, the surgical resection of the tumor was pursued by identifying eloquent structures with intraoperative direct electrical stimulation mapping and extending surgery to the functional boundaries. Post-surgical MRI allowed to identify Anatomical-T and fMRI-T non-eloquent portions removed during the procedure. Results: MNI Atlases showed that fMRI-T is a subset of Anatomical-T, and that different task-specific fMRI-T involve both shared subsets and task-specific subsets – e.g., verbal fluency fMRI-T strongly involves dorsal frontal tracts, consistently with the phonogical-articulatory features of this task. A quantitative analysis in patients revealed that Anatomical-T removed portions of AF-SLF and IFOF were significantly greater than verbal fluency fMRI-T ones, suggesting that fMRI-T is a more specific approach. In addition, qualitative analyses showed that fMRI-T AF-SLF and IFOF predict the exact functional limits of resection with increased specificity when compared to Anatomical-T counterparts, especially the superior frontal portion of IFOF, in a subcohort of patients. Conclusion: These results suggest that performing fMRI-T in addition to the ‘classic’ Anatomical-T may be useful in a preoperative setting to identify the ‘high-risk subsets’ that should be spared during the surgical procedure. © Copyright © 2020 Sanvito, Caverzasi, Riva, Jordan, Blasi, Scifo, Iadanza, Crespi, Cirillo, Casarotti, Leonetti, Puglisi, Grimaldi, Bello, Gorno-Tempini, Henry, Falini and Castellano.
Original languageEnglish
Article number225
JournalFront. Neurosci.
Publication statusPublished - 2020


  • brain tumor
  • fMRI
  • high angular resolution diffusion imaging
  • language network
  • presurgical brain mapping
  • task-fMRI
  • tractography
  • adult
  • algorithm
  • Article
  • auditory system examination
  • brain mapping
  • cancer surgery
  • clinical article
  • cohort analysis
  • controlled study
  • diffusion tensor imaging
  • electrostimulation
  • female
  • functional magnetic resonance imaging
  • glioma
  • human
  • image reconstruction
  • intraoperative period
  • language
  • male
  • prediction
  • preoperative period
  • quantitative analysis
  • task performance
  • white matter


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