@article{OttRosengarthDoenitzetal., author = {Ott, Christian and Rosengarth, Katharina and Doenitz, Christian and Hoehne, Julius and Wendl, Christina and Dodoo-Schittko, Frank and Lang, Elmar Wolfgang and Schmidt, Nils Ole and Goldhacker, Markus}, title = {Preoperative Assessment of Language Dominance through Combined Resting-State and Task-Based Functional Magnetic Resonance Imaging}, series = {Journal of personalized medicine}, volume = {11}, journal = {Journal of personalized medicine}, number = {12}, publisher = {MDPI}, doi = {10.3390/jpm11121342}, abstract = {Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years, the resting-state fMRI (RS-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Twenty patients suffering from brain lesions close to supposed language-relevant cortical areas were included. RS-fMRI and task-based (TB-fMRI) were performed for the purpose of preoperative language assessment. TB-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language-critical and language-supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the TB-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice index. Thereby, the RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. In general, the results suggest that determining language dominance in the human brain is feasible both with TB-fMRI and RS-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.}, language = {en} } @misc{OttRosengarthDoenitzetal., author = {Ott, Christian and Rosengarth, K. and Doenitz, Christian and Hoehne, Julius and Wendl, C. and Dodoo-Schittko, Frank and Lang, Elmar Wolfgang and Schmidt, Nils Ole and Goldhacker, Markus}, title = {Preoperative assessment of language dominance through combined resting-state and task-based functional magnetic resonance imaging}, series = {Brain and Spine}, volume = {1}, journal = {Brain and Spine}, number = {Suppl. 2}, publisher = {Elsevier}, doi = {10.1016/j.bas.2021.100523}, abstract = {Background: Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years the resting-state fMRI (rs-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Methods: Twenty patients suffering from brain lesions close to supposed language relevant cortical areas were included. Rs-fMRI and task-based (tb-fMRI) were performed for the purpose of preoperative language assessment. Tb-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language critical and language supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the tb-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice-index. Results: The RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. Conclusion: In general, the results suggest that determining language dominance in the human brain is feasible both with tb-fMRI and rs-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.}, language = {en} } @article{DeuterHajBrawanskietal., author = {Deuter, Daniel and Haj, Amer and Brawanski, Alexander and Krenkel, Lars and Schmidt, Nils Ole and Doenitz, Christian}, title = {Fast simulation of hemodynamics in intracranial aneurysms for clinical use}, series = {Acta Neurochirurgica}, volume = {167}, journal = {Acta Neurochirurgica}, publisher = {Springer}, doi = {10.1007/s00701-025-06469-9}, pages = {14}, abstract = {BACKGROUND: A widely accepted tool to assess hemodynamics, one of the most important factors in aneurysm pathophysiology, is Computational Fluid Dynamics (CFD). As current workflows are still time consuming and difficult to operate, CFD is not yet a standard tool in the clinical setting. There it could provide valuable information on aneurysm treatment, especially regarding local risks of rupture, which might help to optimize the individualized strategy of neurosurgical dissection during microsurgical aneurysm clipping. METHOD: We established and validated a semi-automated workflow using 3D rotational angiographies of 24 intracranial aneurysms from patients having received aneurysm treatment at our centre. Reconstruction of vessel geometry and generation of volume meshes was performed using AMIRA 6.2.0 and ICEM 17.1. For solving ANSYS CFX was used. For validational checks, tests regarding the volumetric impact of smoothing operations, the impact of mesh sizes on the results (grid convergence), geometric mesh quality and time tests for the time needed to perform the workflow were conducted in subgroups. RESULTS: Most of the steps of the workflow were performed directly on the 3D images requiring no programming experience. The workflow led to final CFD results in a mean time of 22 min 51.4 s (95\%-CI 20 min 51.562 s-24 min 51.238 s, n = 5). Volume of the geometries after pre-processing was in mean 4.46\% higher than before in the analysed subgroup (95\%-CI 3.43-5.50\%). Regarding mesh sizes, mean relative aberrations of 2.30\% (95\%-CI 1.51-3.09\%) were found for surface meshes and between 1.40\% (95\%-CI 1.07-1.72\%) and 2.61\% (95\%-CI 1.93-3.29\%) for volume meshes. Acceptable geometric mesh quality of volume meshes was found. CONCLUSIONS: We developed a semi-automated workflow for aneurysm CFD to benefit from hemodynamic data in the clinical setting. The ease of handling opens the workflow to clinicians untrained in programming. As previous studies have found that the distribution of hemodynamic parameters correlates with thin-walled aneurysm areas susceptible to rupture, these data might be beneficial for the operating neurosurgeon during aneurysm surgery, even in acute cases.}, language = {en} }