Utilizing Quantitative Analysis of CSF Volume from Clinical T1-Weighted MRI to Predict Thrombectomy Outcomes.

BACKGROUND AND PURPOSE: Endovascular thrombectomy (EVT) is the standard for acute ischemic stroke from large vessel occlusion, but post-EVT functional independence varies. Brain atrophy, linked to higher cerebrospinal fluid volume (CSFV), may affect outcomes. Baseline CSFV could predict EVT benefit by assessing brain health. We aimed to quantify total CSFV from clinical T1-weighted (w) magnetic resonance imaging (MRI) to assess global brain atrophy and its association with functional outcomes following successful EVT.

METHODS

We performed a retrospective analysis of patients achieving thrombolysis-in-cerebral-infarction ≥2b revascularization via prospectively maintained single-institution stroke thrombectomy registry (n = 432) between 2015 and 2021. We included 214 patients (mean age 67.5 ± 14.6, 49% female) with acceptable quality MRI within 14 days of EVT and available modified Rankin-scale (mRS) at 90 days post EVT. Clinical T1w images were transformed into high-resolution images using the convolutional neural-network SynthSR. FreeSurfer software was then used to estimate total cranial CSFV. To correct for head size, percentage of CSFV to intracranial volume was used.

RESULTS

Baseline CSFV% significantly predicted 90-day mRS in an ordinal regression model adjusted for baseline mRS (p < 0.001). Further modeling was performed to account for age, sex, 24-h National-Institutes-Health-Stroke-Scale (NIHSS), smoking history, prior stroke, hypertension, congestive heart failure, hemoglobin-A1c, atrial fibrillation, and Alberta-Stroke-Program-Early-CT-Score (ASPECTS). Total CSFV% remained an independent predictor of 90-day mRS (p = 0.012). CSFV% did not significantly predict the occurrence of any type of hemorrhagic transformation in a logistic regression model.

CONCLUSIONS

Increased CSFV% correlates with poorer functional outcomes post EVT. Total CSFV% may serve as a useful imaging biomarker for clinicians determining patient prognostication prior to EVT.