Tractography methods and findings in brain tumors and traumatic brain injury

Yeh, Fang‐Cheng; Irimia, Andrei; Bastos, Dhiego Chaves de Almeida; Golby, Alexandra J.

doi:10.1016/j.neuroimage.2021.118651

Cited by 36 publications

(31 citation statements)

References 227 publications

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“…For example, the connection probabilities between IFOF and insula regions (e.g., Pol1 and 52) were just due to IFOF passing by, and further histology validation is needed. On top of these limitations, the included tracts were also subject to errors such as trajectory deviation, premature termination, and incorrect routing, as discussed in a recent review 54 . Although multiple strategies have been leveraged to reduce false connections, we cannot rule out possible errors in the current form of the tract-to-region connectome.…”

Section: Discussionmentioning

confidence: 99%

Population-based tract-to-region connectome of the human brain and its hierarchical topology

Yeh

2022

Nat Commun

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Connectome maps region-to-region connectivities but does not inform which white matter pathways form the connections. Here we constructed a population-based tract-to-region connectome to fill this information gap. The constructed connectome quantifies the population probability of a white matter tract innervating a cortical region. The results show that ~85% of the tract-to-region connectome entries are consistent across individuals, whereas the remaining (~15%) have substantial individual differences requiring individualized mapping. Further hierarchical clustering on cortical regions revealed dorsal, ventral, and limbic networks based on the tract-to-region connective patterns. The clustering results on white matter bundles revealed the categorization of fiber bundle systems in the association pathways. This tract-to-region connectome provides insights into the connective topology between cortical regions and white matter bundles. The derived hierarchical relation further offers a categorization of gray and white matter structures.

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Section: Discussionmentioning

confidence: 99%

Population-based tract-to-region connectome of the human brain and its hierarchical topology

Yeh

2022

Nat Commun

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“…demyelination, axonal injury, inflammation or necrosis. 90 , 91 However, these metrics may be affected by several factors 90 , 91 and they might be less sensitive to distinguish specific types of WM impairments. 90 , 91 The majority of our cohort with glioblastomas (GBMs; 77 patients) are characterized by diffuse infiltration into the normal brain.…”

Section: Discussionmentioning

confidence: 99%

“… 90 , 91 However, these metrics may be affected by several factors 90 , 91 and they might be less sensitive to distinguish specific types of WM impairments. 90 , 91 The majority of our cohort with glioblastomas (GBMs; 77 patients) are characterized by diffuse infiltration into the normal brain. We observed the greatest elevation in values along the CST in relation to ADC, which could be explained by GBMs’ frequently developing within the WM and spreading throughout the brain along fibres, 92 and limited diffusion because of their tissue properties.…”

Section: Discussionmentioning

confidence: 99%

Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract

Shams

Wang

Roine

et al. 2022

Brain Communications

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Along tract statistics enables white matter characterization using various diffusion MRI (dMRI) metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology, and function. Here, we aim at assessing the clinical utility of dMRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumor patients suffering from either left or right supratentorial, unilateral World Health Organization (WHO) grade II, III & IV gliomas with a mean age of 53.51 ± 16.32 years. 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping dMRI differences were detected in the superior portion of the tracts’ profiles. Fractional anisotropy and fiber density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of dMRI tract profiles (e.g., mean, standard deviation, kurtosis, and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy, and 77% area under the curve. We found that apparent diffusion coefficient, fractional anisotropy, and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumor WHO grade, tumor location, gender, and resting motor threshold did not affect the model’s performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumor-related microstructural white matter changes in the prediction of functional deficits.

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“…Lastly, while our study condition was strictly intraoperative, based on our findings together with those from preoperative settings ( Albi et al, 2018 , Irfanoglu et al, 2012 , Merhof et al, 2007 , Treiber et al, 2016 ), and expert opinions ( Essayed et al, 2017 , Yang et al, 2021 , Yeh et al, 2021 ), we strongly advocate incorporating EPI distortion correction for all preoperative tractography processing workflows used for presurgical planning. This is particularly imperative in the semi-acute and elective surgical settings where data acquisition and processing time is less of an issue, compared to acute surgical settings.…”

Section: Discussionmentioning

confidence: 87%

Assessment of intraoperative diffusion EPI distortion and its impact on estimation of supratentorial white matter tract positions in pediatric epilepsy surgery

Yang

Chen

Alexander

et al. 2022

NeuroImage: Clinical

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Tractography methods and findings in brain tumors and traumatic brain injury

Cited by 36 publications

References 227 publications

Population-based tract-to-region connectome of the human brain and its hierarchical topology

Population-based tract-to-region connectome of the human brain and its hierarchical topology

Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract

Assessment of intraoperative diffusion EPI distortion and its impact on estimation of supratentorial white matter tract positions in pediatric epilepsy surgery

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