Thrombectomy for Large‐Vessel Occlusion With Pretreatment Intracranial Hemorrhage

Background Many patients treated with endovascular thrombectomy (EVT) in clinical practice would not have qualified for inclusion in the initial clinical trials demonstrating benefit for EVT, yet likely will benefit from reperfusion. One such subset for which data are sparse is patients with emergent large‐vessel occlusion and concomitant intracranial hemorrhage (ICH). The objective of this report is to document patients who underwent thrombectomy for large‐vessel occlusion in the presence of concomitant ICH and evaluate their clinical characteristics and outcomes. Methods We retrospectively reviewed prospectively collected patient records at 4 comprehensive stroke centers from 2012 to 2019. Patients were identified who had pre‐EVT ICH. Data collected included baseline patient demographics and laboratory values, stroke characteristics, ICH radiographic variables, antiplatelet/anticoagulant/thrombolytic medication use, and procedural factors. The primary safety outcome was any worsening of ICH on neuroimaging obtained 24 hours after EVT. Results Eight patients were identified who underwent thrombectomy with concomitant ICH. The mean age was 71.9 years (range, 37–90). Median National Institutes of Health Stroke Scale score was 25 (interquartile range, 16.5–28.8), and 5 (63%) received tissue plasminogen activator. All patients underwent EVT and had mTICI2B or greater reperfusion. In 7 patients (88%), the initial ICH remained stable on postprocedure imaging. In 1 patient who received intravenous antiplatelet agents during thrombectomy, the hemorrhagic transformation was radiographically increased but without clinical correlate or mass effect. Conclusions In a multi‐institution evaluation of 8 patients with ICH at the time of thrombectomy, 1 patient had radiographic worsening of hemorrhage, and no patient experienced clinical worsening related to hemorrhage progression. These findings suggest that thrombectomy may be safe in this population

Porous Substrates Promote Endothelial Migration at the Expense of Fibronectin Fibrillogenesis

Porous substrates have gained increased usage in cell studies and tissue mimetic applications because they can partition distinct cell types while still allowing important biochemical crosstalk. In the presented work, we investigated how porous substrates with micron and submicron features influence early cell migration and the associated ECM establishment, which can critically affect the rate of cell coverage on the substrate and the ensuing tissue organization. We showed through time-lapse microscopy that cell speed and migratory distance on membranes with 0.5 μm pores were nearly 2-fold of those observed on nonporous membranes, while values on membranes with 3.0 μm pores fell in between. Although the cell directionality ratio and the persistence time was unaffected by the presence of pores, the cells did exhibit directionality preferences based on the hexagonal pore patterning. Fibronectin fibrillogenesis exhibited a distinct inverse relationship to cell speed, as the fibrils formed on the nonporous control were significantly longer than those on both types of porous substrates. We further confirmed on a per cell basis that there is a negative correlation between fibronectin fibril length and cell speed. The observed trade-off between early cell coverage and ECM establishment thus warrants consideration in the selection or the engineering of the ideal porous substrate for tissue mimetic applications and may help guide future cell studies

Membrane Pore Spacing Can Modulate Endothelial Cell–Substrate and Cell–Cell Interactions

Mechanical cues and substrate interaction affect the manner in which cells adhere, spread, migrate and form tissues. With increased interest in tissue-on-a-chip and coculture systems utilizing porous membranes, it is important to understand the role of disrupted surfaces on cellular behavior. Using a transparent glass membrane with defined pore geometries, we investigated endothelial fibronectin fibrillogenesis and formation of focal adhesions as well as development of intercellular junctions. Cells formed fewer focal adhesions and had shorter fibronectin fibrils on porous membranes compared to nonporous controls, which was similar to cell behavior on continuous soft substrates with Young’s moduli 7 orders of magnitude lower than glass. Additionally, porous membranes promoted enhanced cell–cell interactions as evidenced by earlier formation of tight junctions. These findings suggest that porous membranes with discontinuous surfaces promote reduced cell–matrix interactions similarly to soft substrates and may enhance tissue and barrier formation

Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans.

Background After severe traumatic brain injury (sTBI), physicians use long-term prognostication to guide acute clinical care yet struggle to predict outcomes in comatose patients. Purpose To develop and evaluate a prognostic model combining deep learning of head CT scans and clinical information to predict long-term outcomes after sTBI. Materials and Methods This was a retrospective analysis of two prospectively collected databases. The model-building set included 537 patients (mean age, 40 years ± 17 [SD]; 422 men) from one institution from November 2002 to December 2018. Transfer learning and curriculum learning were applied to a convolutional neural network using admission head CT to predict mortality and unfavorable outcomes (Glasgow Outcomes Scale scores 1-3) at 6 months. This was combined with clinical input for a holistic fusion model. The models were evaluated using an independent internal test set and an external cohort of 220 patients with sTBI (mean age, 39 years ± 17; 166 men) from 18 institutions in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study from February 2014 to April 2018. The models were compared with the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model and the predictions of three neurosurgeons. Area under the receiver operating characteristic curve (AUC) was used as the main model performance metric. Results The fusion model had higher AUCs than did the IMPACT model in the prediction of mortality (AUC, 0.92 [95% CI: 0.86, 0.97] vs 0.80 [95% CI: 0.71, 0.88]; P < .001) and unfavorable outcomes (AUC, 0.88 [95% CI: 0.82, 0.94] vs 0.82 [95% CI: 0.75, 0.90]; P = .04) on the internal data set. For external TRACK-TBI testing, there was no evidence of a significant difference in the performance of any models compared with the IMPACT model (AUC, 0.83; 95% CI: 0.77, 0.90) in the prediction of mortality. The Imaging model (AUC, 0.73; 95% CI: 0.66-0.81; P = .02) and the fusion model (AUC, 0.68; 95% CI: 0.60, 0.76; P = .02) underperformed as compared with the IMPACT model (AUC, 0.83; 95% CI: 0.77, 0.89) in the prediction of unfavorable outcomes. The fusion model outperformed the predictions of the neurosurgeons. Conclusion A deep learning model of head CT and clinical information can be used to predict 6-month outcomes after severe traumatic brain injury. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Haller in this issue

Thrombectomy for Large‐Vessel Occlusion With Pretreatment Intracranial Hemorrhage

Background Many patients treated with endovascular thrombectomy (EVT) in clinical practice would not have qualified for inclusion in the initial clinical trials demonstrating benefit for EVT, yet likely will benefit from reperfusion. One such subset for which data are sparse is patients with emergent large‐vessel occlusion and concomitant intracranial hemorrhage (ICH). The objective of this report is to document patients who underwent thrombectomy for large‐vessel occlusion in the presence of concomitant ICH and evaluate their clinical characteristics and outcomes. Methods We retrospectively reviewed prospectively collected patient records at 4 comprehensive stroke centers from 2012 to 2019. Patients were identified who had pre‐EVT ICH. Data collected included baseline patient demographics and laboratory values, stroke characteristics, ICH radiographic variables, antiplatelet/anticoagulant/thrombolytic medication use, and procedural factors. The primary safety outcome was any worsening of ICH on neuroimaging obtained 24 hours after EVT. Results Eight patients were identified who underwent thrombectomy with concomitant ICH. The mean age was 71.9 years (range, 37–90). Median National Institutes of Health Stroke Scale score was 25 (interquartile range, 16.5–28.8), and 5 (63%) received tissue plasminogen activator. All patients underwent EVT and had mTICI2B or greater reperfusion. In 7 patients (88%), the initial ICH remained stable on postprocedure imaging. In 1 patient who received intravenous antiplatelet agents during thrombectomy, the hemorrhagic transformation was radiographically increased but without clinical correlate or mass effect. Conclusions In a multi‐institution evaluation of 8 patients with ICH at the time of thrombectomy, 1 patient had radiographic worsening of hemorrhage, and no patient experienced clinical worsening related to hemorrhage progression. These findings suggest that thrombectomy may be safe in this population

Biographies of international women leaders in neurosurgery

We received so many biographies of women neurosurgery leaders for this issue that only a selection could be condensed here. In all of them, the essence of a leader shines through. Many are included as “first” of their country or color or other achievement. All of them are included as outstanding—in clinical, academic, and organized neurosurgery. Two defining features are tenacity and service. When faced with shocking discrimination, or numbing indifference, they ignored it or fought valiantly. When choosing their life’s work, they chose service, often of the most neglected—those with pain, trauma, and disability. These women inspire and point the way to a time when the term “women leaders” as an exception is unnecessary