Abstract

Abstract OBJECTIVES Surgical resection of gliomas involving the supplementary motor area (SMA) frequently results in a symptom complex commonly described as „SMA syndrome“, which is characterized by transient contralateral akinesia and mutism. As factors potentially influencing the severity and duration of symptoms still remain elusive, we aim to further investigate potential predictors in a multicentric cohort of glioma patients. METHODS Fifty patients with gliomas located in the superior frontal gyrus from 3 centers were included in this retrospective study. Patients with injury of M1 and/or the corticospinal tract were excluded. Early postoperative motor outcome, the occurrence of mutism and duration of acute symptoms in days were assessed. The long-term outcome was assessed in follow-up examinations 3 months after surgery. Atlas-based lesion-symptom mapping was performed using postoperative MR imaging estimating surgical grey matter damage as well as white matter disconnection severity. Associations between functional outcome and imaging findings were analyzed using group tests and correlation analyses. RESULTS Median duration of symptoms in the cohort was 3 days (range: 1 – 42 days). Persistent deficits concerning fine motor movements and speech after initial recovery were found in 27 patients (54%). Disconnection of the central segment of the corpus callosum was associated with longer symptom duration (FDR corr. p < 0.05), while disconnection of the mid-posterior segment of the corpus callosum was associated with persistent deficits at follow-up (FDR corr. p < 0.05). CONCLUSIONS The present study shows a high variability regarding the recovery time of postoperative SMA syndrome and a high prevalence of persistent deficits in fine motor movements and speech after initial recovery of acute symptoms. The pivotal role of interhemispheric connectivity in the recovery process is reinforced. These findings will help neurosurgeons in patient consultation and provide a foundation for future studies aiming to establish prediction models of the SMA syndrome.

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