Mapping glioblastoma-induced neurological deficits: a brain atlas - Yun, Yeong Chul; Wolf, Sabine; Holz, Katharina; Garhöfer, Freya; Hohmann, Anja; Vollmuth, Philipp; Lövblad, Karl-Olof; Bendszus, Martin; Schlemmer, Heinz-Peter; Sahm, Felix; Heiland, Sabine; Wick, Wolfgang; et al. (Clinical neurology and neurosurgery, 2025)
Background - Identifying radiological characteristics and brain regions associated with neurological deficits in glioblastoma patients can improve diagnostic evaluation and understanding of the disease’s impact on neurological function. - Methods - The retrospective study included 527 newly diagnosed glioblastoma patients. Eligibility criteria included pathologically confirmed IDH-wild type glioblastoma, availability of pre- and post-contrast MRIs, and detailed neurological examination reports. Contrast-enhancing tumors (CET) and non-contrast-enhancing lesions (NEL) were segmented from 3 Tesla MRI scans. Lesion volumes from patients without neurological deficits compared with symptomatic patients using either the Mann-Whitney test or Kruskal-Wallis test. Voxel-wise lesion-symptom mapping was conducted using Fisher-exact-test followed by random permutation analysis (ADIFFI) to identify brain regions with higher occurrences of deficit-associated lesions. - Results - Location of CET and NEL within the brain were associated with specific neurological deficits. Larger CET and NEL volumes were associated with increased neurological deficits (CET: rs = 0.15, p=0.0006; NEL: rs = 0.22, p<0.0001). Lesion volumes were smaller in patients without neurological deficits (CET: 4.97±0.69ml vs. 20.0±0.9ml, p<0.0001). Epilepsy-associated lesions were also smaller (CET: 4.59±0.55ml vs. 22.0±0.9ml, p<0.0001). - Conclusion - The study highlights that neurological and epilepsy status at pre-treatment provide estimates of glioblastoma lesion volumes and locations. The correlation between lesion volumes and neurological deficits underscores the significance of comprehensive radiological assessments in glioblastoma patients. These findings support the use of detailed lesion-symptom mapping to guide clinical management and prognosis evaluation in glioblastoma.