CNSC-05. MAPPING LANGUAGE PROCESSING IN SURGICAL GLIOMA PATIENTS

Abstract Previous work from our group has shown that the resection of white matter tracts localized by transcranial magnetic stimulation (TMS) predicts postoperative neurological deficits. Here we use advanced preoperative brain mapping along with formal language evaluations to localize the neuroanatomical underpinnings of language processing in surgical glioma patients. In patients who had TMS tracts resected, the resected portions (“tract-cavity segmentations”) were classified according to the functional outcome (“true positives”-corresponding deficit; “false positives”-no deficit) and normalized to MNI space. For patients who sustained long-term deficits, TMS tracts were segmented according to spatial overlap with normative tracts to create ROIs. Each normalized resection cavity (n=79) was analyzed for overlap with each ROI associated with postoperative deficits (n=8). The percentage of patients who had positive ROI resections that included TMS tracts versus patients who had positive ROI resections irrespective of TMS tracts were analyzed according to the percent who sustained deficits in each group. ROIs from all patients were summed to create a probabilistic atlas of functional white matter. “True positive” tract-cavity segmentations localized into dual anterior/posterior “hubs” and demonstrated significantly higher spatial association with normative tracts across three different measures (p<.05). 92% of patients who underwent ROI resections that included TMS tracts sustained long-term deficits while 34% of patients who underwent ROI resections irrespective of individualized mapping sustained deficits (p<.05). The probabilistic atlas of functional white matter demonstrated significantly higher voxel intensities within the white matter deep to the temporoparietal junction defined by the same posterior “hub” ROI from Figure 1 (p<.001). This study demonstrates that essential language processing localizes to ROIs within normative white matter tracts that require individualized mapping for surgical preservation. The white matter deep to the temporoparietal junction serves as a crucial hub for language-processing circuitry in glioma patients.

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Journal
Neuro-Oncology
Published
2024-11-01
DOI
https://doi.org/10.1093/neuonc/noae165.0161
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

CNSC-05. MAPPING LANGUAGE PROCESSING IN SURGICAL GLIOMA PATIENTS

Matthew Muir, Vinodh A. Kumar, Jeffrey I. Traylor, Ho-Ling Liu et al.
Neuro-Oncology
Radiomics and Machine Learning in Medical Imaging
article

CNSC-05. MAPPING LANGUAGE PROCESSING IN SURGICAL GLIOMA PATIENTS

Matthew Muir, Vinodh A. Kumar, Jeffrey I. Traylor, Ho-Ling Liu, Sujit S. Prabhu, Kyle R. Noll, Sarah Prinsloo
article en

Abstract

Abstract Previous work from our group has shown that the resection of white matter tracts localized by transcranial magnetic stimulation (TMS) predicts postoperative neurological deficits. Here we use advanced preoperative brain mapping along with formal language evaluations to localize the neuroanatomical underpinnings of language processing in surgical glioma patients. In patients who had TMS tracts resected, the resected portions (“tract-cavity segmentations”) were classified according to the functional outcome (“true positives”-corresponding deficit; “false positives”-no deficit) and normalized to MNI space. For patients who sustained long-term deficits, TMS tracts were segmented according to spatial overlap with normative tracts to create ROIs. Each normalized resection cavity (n=79) was analyzed for overlap with each ROI associated with postoperative deficits (n=8). The percentage of patients who had positive ROI resections that included TMS tracts versus patients who had positive ROI resections irrespective of TMS tracts were analyzed according to the percent who sustained deficits in each group. ROIs from all patients were summed to create a probabilistic atlas of functional white matter. “True positive” tract-cavity segmentations localized into dual anterior/posterior “hubs” and demonstrated significantly higher spatial association with normative tracts across three different measures (p<.05). 92% of patients who underwent ROI resections that included TMS tracts sustained long-term deficits while 34% of patients who underwent ROI resections irrespective of individualized mapping sustained deficits (p<.05). The probabilistic atlas of functional white matter demonstrated significantly higher voxel intensities within the white matter deep to the temporoparietal junction defined by the same posterior “hub” ROI from Figure 1 (p<.001). This study demonstrates that essential language processing localizes to ROIs within normative white matter tracts that require individualized mapping for surgical preservation. The white matter deep to the temporoparietal junction serves as a crucial hub for language-processing circuitry in glioma patients.

Neuro-OncologyVol. 26(Supplement_8)
The University of Texas MD Anderson Cancer Center (US), Southwestern Medical Center (US), The University of Texas Southwestern Medical Center (US)
Quality Education
Openalex Percentile: Top 67%
Radiomics and Machine Learning in Medical Imaging
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