Fiber visualization for preoperative glioma assessment: Tractography versus local connectivity mapping

Schult, Thomas; Hauser, Till‐Karsten; Klose, Uwe; Hurth, Helene; Ehricke, Hans-Heino

doi:10.1371/journal.pone.0226153

Cited by 8 publications

(12 citation statements)

References 49 publications

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“…Tractography is a technique to measure the strength of the white matter (WM) connection by tracking the fiber pathway connecting different brain regions. However, directly performing tractography on the brain with a tumor may cause tracking failure or artifacts, e.g., an unrealistic belt of fibers surrounding the tumor 24 . To bypass the need to perform tractography on the lesioned brain, previous studies proposed to generate a template from healthy controls for tract localization, and the strength of WM connection was then robustly estimated by comparing patients to healthy controls 25, 26 .…”

Section: Resultsmentioning

confidence: 99%

“…Directly performing tractography in the lesioned brain may cause artefacts, e.g., an unrealistic belt of fibers surrounding the tumor core. (27),(28) Previous evidence shows that the white matter integrity in glioma patients can be quantitatively assessed using the fractional anisotropy (FA), a robust measure derived from dMRI, after applying the deformable nonlinear registration (29–31). Further studies showed that the tract integrity of the lesioned brain can be estimated by using the tract templates derived from healthy controls (32–34), and the alignment-invariant tract representation (FA skeleton) generated using the tract-based spatial statistics (TBSS) (35).…”

Section: Methodsmentioning

confidence: 99%

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Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients

Wei

Cui

et al. 2021

Preprint

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Background: Glioblastoma is characterized by extensive invasion into brain parenchymal tissue through white matter tracts. Systematically quantifying invasion, however, is limited by the conventional imaging tools, and could potentially be achieved by a structural connectome approach. Methods: Two prospective patient cohorts of newly diagnosed glioblastoma were included for network construction. A fiber template was firstly derived by employing probabilistic tractography on healthy subjects. Through performing tract-based spatial statistics in patients and age-matched controls, the connectivity strength of each fiber was estimated in patients for network construction. Contrast-enhancing and non-enhancing tumors were segmented and overlaid to the network to identify connectome disruption in lesion and distant areas. The connectome disruption probabilities were calculated across all patients. Disruption indices and network topological features were examined using survival models. Results: Compared to healthy controls, patient networks demonstrated lower clustering coefficient, but higher characteristic path length (each P < 0.001). Higher distant area disruption (HR = 1.43, P = 0.027) and characteristic path length (HR = 1.59, P = 0.031) were associated with worse survival, while higher clustering coefficient (HR = 0.59, P = 0.016) was associated with prolonged survival. Conclusion: The occult invasion in glioblastoma could be identified and quantified using structural connectome, which may confer benefits to precise patient management.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients

Wei

Cui

et al. 2021

Preprint

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“…Amongst these methods, constrained spherical deconvolution (CSD) (25) has been shown to improve the assessment of complex, intra-voxel fiber configuration significantly. Thus, fiber-tracking procedures based on advanced DWI methods allow a more accurate estimation of complex fiber architectures (7) and are increasingly used for planning the extent of resection in brain tumors adjacent to eloquent areas (23,(26)(27)(28)(29)(30)(31)(32).…”

Section: Introductionmentioning

confidence: 99%

Alterations in white matter fiber density associated with structural MRI and metabolic PET lesions following multimodal therapy in glioma patients

et al. 2022

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BackgroundIn glioma patients, multimodality therapy and recurrent tumor can lead to structural brain tissue damage characterized by pathologic findings in MR and PET imaging. However, little is known about the impact of different types of damage on the fiber architecture of the affected white matter.Patients and methodsThis study included 121 pretreated patients (median age, 52 years; ECOG performance score, 0 in 48%, 1-2 in 51%) with histomolecularly characterized glioma (WHO grade IV glioblastoma, n=81; WHO grade III anaplastic astrocytoma, n=28; WHO grade III anaplastic oligodendroglioma, n=12), who had a resection, radiotherapy, alkylating chemotherapy, or combinations thereof. After a median follow-up time of 14 months (range, 1-214 months), anatomic MR and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET images were acquired on a 3T hybrid PET/MR scanner. Post-therapeutic findings comprised resection cavities, regions with contrast enhancement or increased FET uptake and T2/FLAIR hyperintensities. Local fiber density was determined from high angular-resolution diffusion-weighted imaging and advanced tractography methods. A cohort of 121 healthy subjects selected from the 1000BRAINS study matched for age, gender and education served as a control group.ResultsLesion types differed in both affected tissue volumes and relative fiber densities compared to control values (resection cavities: median volume 20.9 mL, fiber density 16% of controls; contrast-enhanced lesions: 7.9 mL, 43%; FET uptake areas: 30.3 mL, 49%; T2/FLAIR hyperintensities: 53.4 mL, 57%, p<0.001). In T2/FLAIR-hyperintense lesions caused by peritumoral edema due to recurrent glioma (n=27), relative fiber density was as low as in lesions associated with radiation-induced gliosis (n=13, 48% vs. 53%, p=0.17). In regions with pathologically increased FET uptake, local fiber density was inversely related (p=0.005) to the extent of uptake. Total fiber loss associated with contrast-enhanced lesions (p=0.006) and T2/FLAIR hyperintense lesions (p=0.013) had a significant impact on overall ECOG score.ConclusionsThese results suggest that apart from resection cavities, reduction in local fiber density is greatest in contrast-enhancing recurrent tumors, but total fiber loss induced by edema or gliosis has an equal detrimental effect on the patients’ performance status due to the larger volume affected.

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“…Preoperative white matter (WM) fibers visualization and quantitative assessment of tissue organization in patients with brain pathology can assist in the selection of surgical approach and setting maximum boundaries for the extent of lesion resection while preserving function. 1 – 3 …”

Section: Introductionmentioning

confidence: 99%

Utilizing the TractSeg Tool for Automatic Corticospinal Tract Segmentation in Patients With Brain Pathology

Moshe

Bashat

Hananis

et al. 2022

Technol Cancer Res Treat

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Purpose: White-matter tract segmentation in patients with brain pathology can guide surgical planning and can be used for tissue integrity assessment. Recently, TractSeg was proposed for automatic tract segmentation in healthy subjects. The aim of this study was to assess the use of TractSeg for corticospinal-tract (CST) segmentation in a large cohort of patients with brain pathology and to evaluate its consistency in repeated measurements. Methods: A total of 649 diffusion-tensor-imaging scans were included, of them: 625 patients and 24 scans from 12 healthy controls (scanned twice for consistency assessment). Manual CST labeling was performed in all cases, and by 2 raters for the healthy subjects. Segmentation results were evaluated based on the Dice score. In order to evaluate consistency in repeated measurements, volume, Fractional Anisotropy (FA), and Mean Diffusivity (MD) values were extracted and correlated for the manual versus automatic methods. Results: For the automatic CST segmentation Dice scores of 0.63 and 0.64 for the training and testing datasets were obtained. Higher consistency between measurements was detected for the automatic segmentation, with between measurements correlations of volume = 0.92/0.65, MD = 0.94/0.75 for the automatic versus manual segmentation. Conclusions: The TractSeg method enables automatic CST segmentation in patients with brain pathology. Superior measurements consistency was detected for the automatic in comparison to manual fiber segmentation, which indicates an advantage when using this method for clinical and longitudinal studies.

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Fiber visualization for preoperative glioma assessment: Tractography versus local connectivity mapping

Cited by 8 publications

References 49 publications

Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients

Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients

Alterations in white matter fiber density associated with structural MRI and metabolic PET lesions following multimodal therapy in glioma patients

Utilizing the TractSeg Tool for Automatic Corticospinal Tract Segmentation in Patients With Brain Pathology

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