Deep grey nuclei automated assessment in acute-subacute phase of middle cerebral artery cortical stroke helps predict the 3-month outcome

在急性期和亚急性期,对大脑中动脉皮质卒中患者深部灰质核团进行自动评估有助于预测3个月预后。

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Abstract

Background: Stroke induces both focal and remote brain alterations, including early degeneration of deep grey nuclei (DGN). This study evaluates whether volumetric and diffusion changes in DGN during the acute-subacute phase after cortical middle cerebral artery (MCA) stroke can predict 3-month functional outcome. Methods: In this retrospective study, consecutive patients ≥ 18 years with first acute-subacute cortical MCA stroke (< 21 days) who underwent 3T MRI including DWI and T1-MP-RAGE imaging between 2018 and 2020 were included. Demographic variables, cardiovascular risk factors, time from stroke onset, and functional outcome were collected. DGN volumes were automatically quantified using the MorphoBox application and normalized as Z-scores. ADC values were extracted by applying segmented DGN onto the ADC map. Infarct volume was manually segmented. Ipsilateral–contralateral differences and asymmetry indices were computed. Multivariable regression analyses were performed to identify predictors of 3-month modified Rankin Scale (mRS) delta. Results: A total of 153 patients (69.3 ± 15.3 years; 85 men) were included. Mean infarct volume was 8.3 ± 20.5 mL. Ipsilateral thalamic (p = 0.001) and caudate (p = 0.006) Z-scores were significantly lower than contralateral values. Thalamic Z-score difference was associated with infarct volume (β = 0.27 [0.12, 0.42], p = 0.001). Thalamic ADC differences were also associated with time from stroke onset (F = 6.55 [3, 148], p = 0.0003). Finally, putaminal Z-score asymmetry (β = − 0.24 [–0.44, − 0.04], p = 0.021) and thalamic ADC asymmetry (β = 0.24 [0.04, 0.44], p = 0.021) independently predicted 3-month mRS delta. Conclusion: Early volumetric and diffusion alterations in deep grey nuclei occur in the acute-subacute phase after cortical MCA stroke and are associated with infarct burden and time from onset. These remote changes can predict short-term functional outcome.

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