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Khan MA, Fares H, Ghayvat H, Brunner IC, Puthusserypady S, Razavi B, Lansberg M, Poon A, Meador KJ. A systematic review on functional electrical stimulation based rehabilitation systems for upper limb post-stroke recovery. Front Neurol 2023; 14:1272992. [PMID: 38145118 PMCID: PMC10739305 DOI: 10.3389/fneur.2023.1272992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
Background Stroke is one of the most common neurological conditions that often leads to upper limb motor impairments, significantly affecting individuals' quality of life. Rehabilitation strategies are crucial in facilitating post-stroke recovery and improving functional independence. Functional Electrical Stimulation (FES) systems have emerged as promising upper limb rehabilitation tools, offering innovative neuromuscular reeducation approaches. Objective The main objective of this paper is to provide a comprehensive systematic review of the start-of-the-art functional electrical stimulation (FES) systems for upper limb neurorehabilitation in post-stroke therapy. More specifically, this paper aims to review different types of FES systems, their feasibility testing, or randomized control trials (RCT) studies. Methods The FES systems classification is based on the involvement of patient feedback within the FES control, which mainly includes "Open-Loop FES Systems" (manually controlled) and "Closed-Loop FES Systems" (brain-computer interface-BCI and electromyography-EMG controlled). Thus, valuable insights are presented into the technological advantages and effectiveness of Manual FES, EEG-FES, and EMG-FES systems. Results and discussion The review analyzed 25 studies and found that the use of FES-based rehabilitation systems resulted in favorable outcomes for the stroke recovery of upper limb functional movements, as measured by the FMA (Fugl-Meyer Assessment) (Manually controlled FES: mean difference = 5.6, 95% CI (3.77, 7.5), P < 0.001; BCI-controlled FES: mean difference = 5.37, 95% CI (4.2, 6.6), P < 0.001; EMG-controlled FES: mean difference = 14.14, 95% CI (11.72, 16.6), P < 0.001) and ARAT (Action Research Arm Test) (EMG-controlled FES: mean difference = 11.9, 95% CI (8.8, 14.9), P < 0.001) scores. Furthermore, the shortcomings, clinical considerations, comparison to non-FES systems, design improvements, and possible future implications are also discussed for improving stroke rehabilitation systems and advancing post-stroke recovery. Thus, summarizing the existing literature, this review paper can help researchers identify areas for further investigation. This can lead to formulating research questions and developing new studies aimed at improving FES systems and their outcomes in upper limb rehabilitation.
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Affiliation(s)
- Muhammad Ahmed Khan
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
- Department of Electrical Engineering, Stanford University, Palo Alto, CA, United States
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Hoda Fares
- Department of Electrical, Electronic, Telecommunication Engineering and Naval Architecture (DITEN), University of Genoa, Genoa, Italy
| | - Hemant Ghayvat
- Department of Computer Science, Linnaeus University, Växjö, Sweden
| | | | | | - Babak Razavi
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
| | - Maarten Lansberg
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
| | - Ada Poon
- Department of Electrical Engineering, Stanford University, Palo Alto, CA, United States
| | - Kimford Jay Meador
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
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Seim C, Chen B, Han C, Vacek D, Lowber A, Lansberg M, Okamura AM. Daily Vibrotactile Stimulation Exhibits Equal or Greater Spasticity Relief Than Botulinum Toxin in Stroke. Arch Phys Med Rehabil 2023; 104:1565-1572. [PMID: 37149017 DOI: 10.1016/j.apmr.2023.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 02/22/2023] [Accepted: 03/27/2023] [Indexed: 05/08/2023]
Abstract
OBJECTIVE To test the feasibility and efficacy of the VibroTactile Stimulation (VTS) Glove, a wearable device that provides VTS to the impaired limb to reduce spastic hypertonia. DESIGN Prospective 2-arm intervention study-including 1 group of patients who use Botulinum toxin (BTX-A) for spasticity and 1 group of patients who do not use BTX-A. SETTING Participants were recruited through rehabilitation and neurology clinics. PARTICIPANTS Patients with chronic stroke (N=20; mean age=54 years, mean time since stroke=6.9 years). Patients who were previously receiving the standard of care (BTX-A injection) were eligible to participate and started the intervention 12 weeks after their last injection. INTERVENTION Participants were instructed to use the VTS Glove for 3 hours daily, at home or during everyday activities, for 8 weeks. MAIN OUTCOME MEASURES Spasticity was assessed with the Modified Ashworth Scale and the Modified Tardieu Scale at baseline and then at 2-week intervals for 12 weeks. Primary outcomes were the difference from baseline and at week 8 (end of VTS Glove use) and week 12 (4 weeks after stopping VTS Glove use). Patients who were receiving BTX-A were also assessed during the 12 weeks preceding the start of VTS Glove use to monitor the effect of BTX-A on spastic hypertonia. Range of motion and participant feedback were also studied. RESULTS A clinically meaningful difference in spastic hypertonia was found during and after daily VTS Glove use. Modified Ashworth and Modified Tardieu scores were reduced by an average of 0.9 (P=.0014) and 0.7 (P=.0003), respectively, at week 8 of daily VTS Glove use, and by 1.1 (P=.00025) and 0.9 (P=.0001), respectively, 1 month after stopping VTS Glove use. For participants who used BTX-A, 6 out of 11 showed greater change in Modified Ashworth ratings during VTS Glove use (mean=-1.8 vs mean=-1.6 with BTX-A) and 8 out of 11 showed their lowest level of symptoms during VTS Glove use (vs BTX-A). CONCLUSIONS Daily stimulation from the VTS Glove provides relief of spasticity and hypertonia. For more than half of the participants who had regularly used BTX-A, the VTS Glove provided equal or greater symptom relief.
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Affiliation(s)
- Caitlyn Seim
- Department of Mechanical Engineering, Stanford University, Stanford, CA.
| | - Bingxian Chen
- Department of Bioengineering, Stanford University, Stanford, CA
| | - Chuzhang Han
- Department of Mechanical Engineering, Stanford University, Stanford, CA
| | - David Vacek
- Department of Mechanical Engineering, Stanford University, Stanford, CA
| | - Alexis Lowber
- Department of Computer Science, Stanford University, Stanford, CA
| | - Maarten Lansberg
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA
| | - Allison M Okamura
- Department of Mechanical Engineering, Stanford University, Stanford, CA
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Vasquez ED, Simpson CS, Zhou G, Lansberg M, Okamura AM. Evaluation of a Passive Wearable Device for Post-Stroke Shoulder Abduction Support. IEEE Int Conf Rehabil Robot 2023; 2023:1-6. [PMID: 37941216 DOI: 10.1109/icorr58425.2023.10304815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Post-stroke upper extremity function can be improved by devices that support shoulder abduction. However, many of these devices provide limited assistance in activities of daily living due to their complexity and encumbrance. We developed and evaluated a passive, lightweight (0.6 kg) wearable device consisting of an aluminum frame and elastic bands attached to a posture vest to aid in shoulder abduction. The number and thickness of bands can be adjusted to provide supportive forces to the affected arm. We measured reachable workspace area and Wolf Motor Function Test (WMFT) performance in people with a history of stroke (n = 11) with and without the wearable. The device increased workspace area in 6 participants and improved average WMFT functional and timing scores in 7 and 12 tasks, respectively, out of 16 total tasks. On average, participants increased their arm motion within 20 cm of shoulder level by 22.4% and decreased their hand's average distance from trunk by 15.2%, both improvements in the device case.
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Seim C, Chen B, Han C, Vacek D, Wu LS, Lansberg M, Okamura A. Relief of post-stroke spasticity with acute vibrotactile stimulation: controlled crossover study of muscle and skin stimulus methods. Front Hum Neurosci 2023; 17:1206027. [PMID: 37706171 PMCID: PMC10497102 DOI: 10.3389/fnhum.2023.1206027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 08/02/2023] [Indexed: 09/15/2023] Open
Abstract
Background Prior work suggests that vibratory stimulation can reduce spasticity and hypertonia. It is unknown which of three predominant approaches (stimulation of the spastic muscle, antagonist muscle, or cutaneous regions) most reduces these symptoms. Objective Determine which vibrotactile stimulation approach is most effective at reducing spastic hypertonia among post-stroke patients. Methods Sham-controlled crossover study with random assignment of condition order in fourteen patients with post-stroke hand spasticity. All patients were studied in four conditions over four visits: three stimulation conditions and a sham control. The primary outcome measure was the Modified Ashworth Scale, and the secondary outcome measure was the Modified Tardieu Scale measured manually and using 3D motion capture. For each condition, measures of spastic hypertonia were taken at four time points: baseline, during stimulation, after stimulation was removed, and after a gripping exercise. Results A clinically meaningful difference in spastic hypertonia was found during and after cutaneous stimulation of the hand. Modified Ashworth and Modified Tardieu scores were reduced by a median of 1.1 (SD = 0.84, p = 0.001) and 0.75 (SD = 0.65, p = 0.003), respectively, during cutaneous stimulation, and by 1.25 (SD = 0.94, p = 0.001) and 0.71 (SD = 0.67, p = 0.003), respectively, at 15 min after cutaneous stimulation. Symptom reductions with spastic muscle stimulation and antagonist muscle stimulation were non-zero but not significant. There was no change with sham stimulation. Conclusions Cutaneous vibrotactile stimulation of the hand provides significant reductions in spastic hypertonia, compared to muscle stimulation. Clinical trial registration www.ClinicalTrials.gov, identifier: NCT03814889.
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Affiliation(s)
- Caitlyn Seim
- Stanford University Department of Mechanical Engineering, Stanford, CA, United States
| | - Bingxian Chen
- Stanford University Department of Bioengineering, Stanford, CA, United States
| | - Chuzhang Han
- Stanford University Department of Mechanical Engineering, Stanford, CA, United States
| | - David Vacek
- Stanford University Department of Mechanical Engineering, Stanford, CA, United States
| | - Laura Song Wu
- Stanford University Department of Mechanical Engineering, Stanford, CA, United States
| | - Maarten Lansberg
- Stanford University Department of Neurology and Neurological Sciences, Stanford, CA, United States
| | - Allison Okamura
- Stanford University Department of Mechanical Engineering, Stanford, CA, United States
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Nazari-Farsani S, Yu Y, Duarte Armindo R, Lansberg M, Liebeskind DS, Albers G, Christensen S, Levin CS, Zaharchuk G. Predicting final ischemic stroke lesions from initial diffusion-weighted images using a deep neural network. Neuroimage Clin 2023; 37:103278. [PMID: 36481696 PMCID: PMC9727698 DOI: 10.1016/j.nicl.2022.103278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/20/2022] [Accepted: 11/30/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND For prognosis of stroke, measurement of the diffusion-perfusion mismatch is a common practice for estimating tissue at risk of infarction in the absence of timely reperfusion. However, perfusion-weighted imaging (PWI) adds time and expense to the acute stroke imaging workup. We explored whether a deep convolutional neural network (DCNN) model trained with diffusion-weighted imaging obtained at admission could predict final infarct volume and location in acute stroke patients. METHODS In 445 patients, we trained and validated an attention-gated (AG) DCNN to predict final infarcts as delineated on follow-up studies obtained 3 to 7 days after stroke. The input channels consisted of MR diffusion-weighted imaging (DWI), apparent diffusion coefficients (ADC) maps, and thresholded ADC maps with values less than 620 × 10-6 mm2/s, while the output was a voxel-by-voxel probability map of tissue infarction. We evaluated performance of the model using the area under the receiver-operator characteristic curve (AUC), the Dice similarity coefficient (DSC), absolute lesion volume error, and the concordance correlation coefficient (ρc) of the predicted and true infarct volumes. RESULTS The model obtained a median AUC of 0.91 (IQR: 0.84-0.96). After thresholding at an infarction probability of 0.5, the median sensitivity and specificity were 0.60 (IQR: 0.16-0.84) and 0.97 (IQR: 0.93-0.99), respectively, while the median DSC and absolute volume error were 0.50 (IQR: 0.17-0.66) and 27 ml (IQR: 7-60 ml), respectively. The model's predicted lesion volumes showed high correlation with ground truth volumes (ρc = 0.73, p < 0.01). CONCLUSION An AG-DCNN using diffusion information alone upon admission was able to predict infarct volumes at 3-7 days after stroke onset with comparable accuracy to models that consider both DWI and PWI. This may enable treatment decisions to be made with shorter stroke imaging protocols.
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Affiliation(s)
| | - Yannan Yu
- Department of Radiology, Stanford University, CA, USA; Internal Medicine Department, University of Massachusetts Memorial Medical Center, University of Massachusetts, Boston, USA
| | - Rui Duarte Armindo
- Department of Radiology, Stanford University, CA, USA; Department of Neuroradiology, Hospital Beatriz Ângelo, Loures, Lisbon, Portugal
| | | | - David S Liebeskind
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | | | | | - Craig S Levin
- Department of Radiology, Stanford University, CA, USA
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Zera KA, Bidoki N, Nassar H, Drag L, Mlynash M, Osborn E, Musabbir M, Kim DE, Mendez M, Lansberg M, Aghaeepour N, Buckwalter MS. Proteomics reveals associations between inflammation and chronic depression in a prospective study of post‐stroke cognition. Alzheimers Dement 2022. [DOI: 10.1002/alz.064301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Winkelmeier L, Broocks G, Kniep H, Geest V, Reinwald J, Meyer L, van Horn N, Guenego A, Zeleňák K, Albers GW, Lansberg M, Sporns P, Wintermark M, Fiehler J, Heit JJ, Faizy TD. Venous Outflow Profiles Are Linked to Clinical Outcomes in Ischemic Stroke Patients with Extensive Baseline Infarct. J Stroke 2022; 24:372-382. [PMID: 36221940 PMCID: PMC9561220 DOI: 10.5853/jos.2022.01046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/09/2022] [Indexed: 11/11/2022] Open
Abstract
Background and Purpose The benefit of endovascular thrombectomy (EVT) treatment is still unclear in stroke patients presenting with extensive baseline infarct. The use of additional imaging biomarkers could improve clinical outcome prediction and individualized EVT selection in this vulnerable cohort. We hypothesized that cerebral venous outflow (VO) may be associated with functional outcomes in patients with low Alberta Stroke Program Early CT Score (ASPECTS).Methods We conducted a retrospective multicenter cohort study of patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). Extensive baseline infarct was defined by an ASPECTS of ≤5 on admission computed tomography (CT). VO profiles were assessed on admission CT angiography using the Cortical Vein Opacification Score (COVES). Favorable VO was defined as COVES ≥3. Multivariable logistic regression was used to determine the association between cerebral VO and good clinical outcomes (90-day modified Rankin Scale score of ≤3).Results A total of 98 patients met the inclusion criteria. Patients with extensive baseline infarct and favorable VO achieved significantly more often good clinical outcomes compared to patients with unfavorable VO (45.5% vs. 10.5%, P<0.001). Higher COVES were strongly associated with good clinical outcomes (odds ratio, 2.17; 95% confidence interval, 1.15 to 4.57; P=0.024), independent of ASPECTS, National Institutes of Health Stroke Scale, and success of EVT.Conclusions Cerebral VO profiles are associated with good clinical outcomes in AIS-LVO patients with extensive baseline infarct. VO profiles could serve as a useful additional imaging biomarker for treatment selection and outcome prediction in low ASPECTS patients.
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Affiliation(s)
- Laurens Winkelmeier
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Correspondence: Laurens Winkelmeier Department of Neuroradiology, University Medical Center HamburgEppendorf, Martinistraße 52, 20251 Hamburg, Germany Tel: +49-152-2283-0918 Fax: +49-(0)40-7410-54640 E-mail:
| | - Gabriel Broocks
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Helge Kniep
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Vincent Geest
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonathan Reinwald
- Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Lukas Meyer
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Noel van Horn
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Adrien Guenego
- Department of Neuroradiology, Erasme Medical Center, Brussels, Belgium
| | - Kamil Zeleňák
- Department of Radiology, Jessenius Faculty of Medicine in Martin Clinic of Radiology, Comenius University in Bratislava, Martin, Slovakia
| | - Gregory W. Albers
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | - Maarten Lansberg
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | - Peter Sporns
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Diagnostic and Interventional Neuroradiology, University Medical Hospital Basel, Basel, Switzerland
| | - Max Wintermark
- Department of Neuroradiology, MD Andersen Cancer Center, Houston, TX, USA
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jeremy J. Heit
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Tobias D. Faizy
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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de Havenon A, Petersen N, Wolcott Z, Goldstein E, Delic A, Sheibani N, Anadani M, Sheth KN, Lansberg M, Turan T, Prabhakaran S. Effect of dihydropyridine calcium channel blockers on blood pressure variability in the SPRINT trial: a treatment effects approach. J Hypertens 2022; 40:462-469. [PMID: 34694261 DOI: 10.1097/hjh.0000000000003033] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Increased visit-to-visit blood pressure variability (vvBPV) has negative effects on multiple organ systems. Prior research has suggested that dihydropyridine calcium channel blockers (CCB) may reduce vvBPV, which we attempted to verify in a high-quality dataset with robust statistical methodology. METHODS We performed a post hoc analysis of the SPRINT trial and included participants who were on a dihydropyridine CCB either 0 or 100% of follow-up study visits. The primary outcome was vvBPV, defined as residual standard deviation (rSD) of SBP from month 6 until study completion. We estimated the average treatment effect of the treated (ATET) after augmented inverse-probability-weighting (AIPW) matching. RESULTS Of the 9361 participants enrolled in SPRINT, we included 5020, of whom 1959 were on a dihydropyridine CCB and 3061 were not; mean age was 67.4 ± 9.2 years, 34.5% were men, 65.9% were white, 49.4% were randomized to intensive blood pressure control, and the rSD was 10.1 ± 4.0 mmHg. Amlodipine represented greater than 95% of dihydropyridine CCB use. After AIPW matching of demographics and other antihypertensive medications, the ATET estimation for participants on a dihydropyridine CCB was an rSD that was 2.05 mmHg lower (95% CI -3.19 to -0.91). We did not find that other antihypertensive medications classes decreased vvBPV, and several increased it. CONCLUSION In the SPRINT trial, consistent use of a dihydropyridine CCB was associated with a 2 mmHg reduction in vvBPV. The implication of this hypothesis-generating finding in a high-quality dataset is that future trials to reduce vvBPV could consider using dihydropyridine CCBs.
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Affiliation(s)
- Adam de Havenon
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | - Nils Petersen
- Department of Neurology, Yale University, New Haven, Connecticut
| | - Zoe Wolcott
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | - Eric Goldstein
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | - Alen Delic
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | - Nazanin Sheibani
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | - Mohammad Anadani
- Department of Neurology, Washington University, St Louis, Missouri
| | - Kevin N Sheth
- Department of Neurology, Yale University, New Haven, Connecticut
| | - Maarten Lansberg
- Department of Neurology, Stanford University, Stanford, California
| | - Tanya Turan
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina
| | - Shyam Prabhakaran
- Department of Neurology, University of Chicago, Chicago, Illinois, USA
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Wouters A, Robben D, Christensen S, Marquering HA, Roos YB, van Oostenbrugge RJ, van Zwam WH, Dippel DW, Majoie CB, Schonewille WJ, van der Lugt A, Lansberg M, Albers GW, Suetens P, Lemmens R. Prediction of Stroke Infarct Growth Rates by Baseline Perfusion Imaging. Stroke 2022; 53:569-577. [PMID: 34587794 PMCID: PMC8792202 DOI: 10.1161/strokeaha.121.034444] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND PURPOSE Computed tomography perfusion imaging allows estimation of tissue status in patients with acute ischemic stroke. We aimed to improve prediction of the final infarct and individual infarct growth rates using a deep learning approach. METHODS We trained a deep neural network to predict the final infarct volume in patients with acute stroke presenting with large vessel occlusions based on the native computed tomography perfusion images, time to reperfusion and reperfusion status in a derivation cohort (MR CLEAN trial [Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands]). The model was internally validated in a 5-fold cross-validation and externally in an independent dataset (CRISP study [CT Perfusion to Predict Response to Recanalization in Ischemic Stroke Project]). We calculated the mean absolute difference between the predictions of the deep learning model and the final infarct volume versus the mean absolute difference between computed tomography perfusion imaging processing by RAPID software (iSchemaView, Menlo Park, CA) and the final infarct volume. Next, we determined infarct growth rates for every patient. RESULTS We included 127 patients from the MR CLEAN (derivation) and 101 patients of the CRISP study (validation). The deep learning model improved final infarct volume prediction compared with the RAPID software in both the derivation, mean absolute difference 34.5 versus 52.4 mL, and validation cohort, 41.2 versus 52.4 mL (P<0.01). We obtained individual infarct growth rates enabling the estimation of final infarct volume based on time and grade of reperfusion. CONCLUSIONS We validated a deep learning-based method which improved final infarct volume estimations compared with classic computed tomography perfusion imaging processing. In addition, the deep learning model predicted individual infarct growth rates which could enable the introduction of tissue clocks during the management of acute stroke.
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Affiliation(s)
- Anke Wouters
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium,Department of Neurosciences, Experimental Neurology, KU Leuven – University of Leuven, Leuven, Belgium.,Center for Brain & Disease Research, Laboratory of Neurobiology, VIB, Leuven, Belgium,Department of Neurology, Academic Medical Center, Amsterdam, Netherlands
| | - David Robben
- Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium,Medical Image Computing (MIC), ESAT-PSI, Department of Electrical Engineering, KU Leuven, Leuven, Belgium,Icometrix, Leuven, Belgium
| | | | - Henk A. Marquering
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, Netherlands,Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, Netherlands
| | - Yvo B.W.E.M. Roos
- Department of Neurology, Academic Medical Center, Amsterdam, Netherlands
| | - Robert J. van Oostenbrugge
- Department of Neurology, Maastricht University Medical Center and Cardiovascular Research Institute (CARIM), Maastricht, Netherlands
| | - Wim H. van Zwam
- Department of Radiology, Maastricht University Medical Center and Cardiovascular Research Institute (CARIM), Maastricht, Netherlands
| | - Diederik W.J. Dippel
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Charles B.L.M. Majoie
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, Netherlands
| | - Wouter J. Schonewille
- Department of Neurology, St. Antonius Hospital, Nieuwegein, and University Medical Center Utrecht, Utrecht
| | - Aad van der Lugt
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | | | | | - Paul Suetens
- Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium,Medical Image Computing (MIC), ESAT-PSI, Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | - Robin Lemmens
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium,Department of Neurosciences, Experimental Neurology, KU Leuven – University of Leuven, Leuven, Belgium.,Center for Brain & Disease Research, Laboratory of Neurobiology, VIB, Leuven, Belgium
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Rolle CE, Baumer FM, Jordan JT, Berry K, Garcia M, Monusko K, Trivedi H, Wu W, Toll R, Buckwalter MS, Lansberg M, Etkin A. Mapping causal circuit dynamics in stroke using simultaneous electroencephalography and transcranial magnetic stimulation. BMC Neurol 2021; 21:280. [PMID: 34271872 PMCID: PMC8283835 DOI: 10.1186/s12883-021-02319-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 05/16/2021] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Motor impairment after stroke is due not only to direct tissue loss but also to disrupted connectivity within the motor network. Mixed results from studies attempting to enhance motor recovery with Transcranial Magnetic Stimulation (TMS) highlight the need for a better understanding of both connectivity after stroke and the impact of TMS on this connectivity. This study used TMS-EEG to map the causal information flow in the motor network of healthy adult subjects and define how stroke alters these circuits. METHODS Fourteen stroke patients and 12 controls received TMS to two sites (bilateral primary motor cortices) during two motor tasks (paretic/dominant hand movement vs. rest) while EEG measured the cortical response to TMS pulses. TMS-EEG based connectivity measurements were derived for each hemisphere and the change in connectivity (ΔC) between the two motor tasks was calculated. We analyzed if ΔC for each hemisphere differed between the stroke and control groups or across TMS sites, and whether ΔC correlated with arm function in stroke patients. RESULTS Right hand movement increased connectivity in the left compared to the right hemisphere in controls, while hand movement did not significantly change connectivity in either hemisphere in stroke. Stroke patients with the largest increase in healthy hemisphere connectivity during paretic hand movement had the best arm function. CONCLUSIONS TMS-EEG measurements are sensitive to movement-induced changes in brain connectivity. These measurements may characterize clinically meaningful changes in circuit dynamics after stroke, thus providing specific targets for trials of TMS in post-stroke rehabilitation.
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Affiliation(s)
- Camarin E Rolle
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, MC: 5797, Stanford, CA, 94305-5797, USA.,Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.,Sierra-Pacific Mental Illness Research, Education, and Clinical Centers (MIRECC), Palo Alto Veterans Health Care Administration, Palo Alto, CA, USA
| | - Fiona M Baumer
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.,Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Joshua T Jordan
- Department of Psychiatry, University of California At San Francisco, San Francisco, CA, USA
| | - Ketura Berry
- School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Madelleine Garcia
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Karen Monusko
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, MC: 5797, Stanford, CA, 94305-5797, USA
| | - Hersh Trivedi
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, MC: 5797, Stanford, CA, 94305-5797, USA
| | - Wei Wu
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, MC: 5797, Stanford, CA, 94305-5797, USA.,Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.,Sierra-Pacific Mental Illness Research, Education, and Clinical Centers (MIRECC), Palo Alto Veterans Health Care Administration, Palo Alto, CA, USA
| | - Russell Toll
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, MC: 5797, Stanford, CA, 94305-5797, USA.,Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.,Sierra-Pacific Mental Illness Research, Education, and Clinical Centers (MIRECC), Palo Alto Veterans Health Care Administration, Palo Alto, CA, USA
| | - Marion S Buckwalter
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.,Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Maarten Lansberg
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, MC: 5797, Stanford, CA, 94305-5797, USA. .,Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA. .,Sierra-Pacific Mental Illness Research, Education, and Clinical Centers (MIRECC), Palo Alto Veterans Health Care Administration, Palo Alto, CA, USA.
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11
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Yaghi S, Raz E, Dehkharghani S, Riina H, McTaggart R, Jayaraman M, Prabhakaran S, Liebeskind DS, Khatri P, Mac Grory B, Al-Mufti F, Lansberg M, Albers G, de Havenon A. Penumbra Consumption Rates Based on Time-to-Maximum Delay and Reperfusion Status: A Post Hoc Analysis of the DEFUSE 3 Trial. Stroke 2021; 52:2690-2693. [PMID: 34157865 DOI: 10.1161/strokeaha.120.033806] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE In patients with acute large vessel occlusion, the natural history of penumbral tissue based on perfusion time-to-maximum (Tmax) delay is not well established in relation to late-window endovascular thrombectomy. In this study, we sought to evaluate penumbra consumption rates for Tmax delays in patients with large vessel occlusion evaluated between 6 and 16 hours from last known normal. METHODS This is a post hoc analysis of the DEFUSE 3 trial (The Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke), which included patients with an acute ischemic stroke due to anterior circulation occlusion within 6 to 16 hours of last known normal. The primary outcome is percentage penumbra consumption, defined as (24-hour magnetic resonance imaging infarct volume-baseline core infarct volume)/(Tmax 6 or 10 s volume-baseline core volume). We stratified the cohort into 4 categories based on treatment modality and Thrombolysis in Cerebral Infarction (TICI score; untreated, TICI 0-2a, TICI 2b, and TICI3) and calculated penumbral consumption rates in each category. RESULTS We included 141 patients, among whom 68 were untreated. In the untreated versus TICI 3 patients, a median (interquartile range) of 53.7% (21.2%-87.7%) versus 5.3% (1.1%-14.6%) of penumbral tissue was consumed based on Tmax >6 s (P<0.001). In the same comparison for Tmax>10 s, we saw a difference of 165.4% (interquartile range, 56.1%-479.8%) versus 25.7% (interquartile range, 3.2%-72.1%; P<0.001). Significant differences were not demonstrated between untreated and TICI 0-2a patients for penumbral consumption based on Tmax >6 s (P=0.52) or Tmax >10 s (P=0.92). CONCLUSIONS Among extended window endovascular thrombectomy patients, Tmax >10-s mismatch volume may comprise large volumes of salvageable tissue, whereas nearly half the Tmax >6-s mismatch volume may remain viable in untreated patients at 24 hours.
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Affiliation(s)
- Shadi Yaghi
- Department of Neurology (S.Y., R.M., M.J.), Brown University, Providence, RI
| | - Eytan Raz
- Department of Radiology (E.R., S.D.), NYU Langone Health
| | - Seena Dehkharghani
- Department of Radiology (E.R., S.D.), NYU Langone Health.,Department of Neurology (S.D.), NYU Langone Health
| | - Howard Riina
- Department of Neurosurgery (H.R.), NYU Langone Health
| | - Ryan McTaggart
- Department of Neurology (S.Y., R.M., M.J.), Brown University, Providence, RI.,Department of Radiology (R.M., M.J.), Brown University, Providence, RI.,Department of Neurosurgery (R.M., M.J.), Brown University, Providence, RI
| | - Mahesh Jayaraman
- Department of Neurology (S.Y., R.M., M.J.), Brown University, Providence, RI.,Department of Radiology (R.M., M.J.), Brown University, Providence, RI.,Department of Neurosurgery (R.M., M.J.), Brown University, Providence, RI
| | | | - David S Liebeskind
- Department of Neurology, University of California at Los Angeles (D.S.L.)
| | - Pooja Khatri
- Department of Neurology, University of Cincinnati, OH (P.K.)
| | - Brian Mac Grory
- Department of Neurology, Duke University, Durham, NC (B.M.G.)
| | - Fawwaz Al-Mufti
- Department of Neurology, New York Medical College, Valhalla (F.A.-M.)
| | - Maarten Lansberg
- Department of Neurology, Stanford University, San Francisco, CA (M.L., G.A.)
| | - Gregory Albers
- Department of Neurology, Stanford University, San Francisco, CA (M.L., G.A.)
| | - Adam de Havenon
- Department of Neurology, University of Utah, Salt Lake City (A.d.H.)
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12
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Sarraj A, Grotta J, Albers GW, Hassan AE, Blackburn S, Day A, Sitton C, Abraham M, Cai C, Dannenbaum M, Pujara D, Hicks W, Budzik R, Vora N, Arora A, Alenzi B, Tekle WG, Kamal H, Mir O, Barreto AD, Lansberg M, Gupta R, Martin-Schild S, Savitz S, Tsivgoulis G. Clinical and Neuroimaging Outcomes of Direct Thrombectomy vs Bridging Therapy in Large Vessel Occlusion: Analysis of the SELECT Cohort Study. Neurology 2021; 96:e2839-e2853. [PMID: 33875560 PMCID: PMC8205460 DOI: 10.1212/wnl.0000000000012063] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 03/11/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate the comparative safety and efficacy of direct endovascular thrombectomy (dEVT) compared to bridging therapy (BT; IV tissue plasminogen activator + EVT) and to assess whether BT potential benefit relates to stroke severity, size, and initial presentation to EVT vs non-EVT center. METHODS In a prospective multicenter cohort study of imaging selection for endovascular thrombectomy (Optimizing Patient Selection for Endovascular Treatment in Acute Ischemic Stroke [SELECT]), patients with anterior circulation large vessel occlusion (LVO) presenting to EVT-capable centers within 4.5 hours from last known well were stratified into BT vs dEVT. The primary outcome was 90-day functional independence (modified Rankin Scale [mRS] score 0-2). Secondary outcomes included a shift across 90-day mRS grades, mortality, and symptomatic intracranial hemorrhage. We also performed subgroup analyses according to initial presentation to EVT-capable center (direct vs transfer), stroke severity, and baseline infarct core volume. RESULTS We identified 226 LVOs (54% men, mean age 65.6 ± 14.6 years, median NIH Stroke Scale [NIHSS] score 17, 28% received dEVT). Median time from arrival to groin puncture did not differ in patients with BT when presenting directly (dEVT 1.43 [interquartile range (IQR) 1.13-1.90] hours vs BT 1.58 [IQR 1.27-2.02] hours, p = 0.40) or transferred to EVT-capable centers (dEVT 1.17 [IQR 0.90-1.48] hours vs BT 1.27 [IQR 0.97-1.87] hours, p = 0.24). BT was associated with higher odds of 90-day functional independence (57% vs 44%, adjusted odds ratio [aOR] 2.02, 95% confidence interval [CI] 1.01-4.03, p = 0.046) and functional improvement (adjusted common OR 2.06, 95% CI 1.18-3.60, p = 0.011) and lower likelihood of 90-day mortality (11% vs 23%, aOR 0.20, 95% CI 0.07-0.58, p = 0.003). No differences in any other outcomes were detected. In subgroup analyses, patients with BT with baseline NIHSS scores <15 had higher functional independence likelihood compared to those with dEVT (aOR 4.87, 95% CI 1.56-15.18, p = 0.006); this association was not evident for patients with NIHSS scores ≥15 (aOR 1.05, 95% CI 0.40-2.74, p = 0.92). Similarly, functional outcomes improvements with BT were detected in patients with core volume strata (ischemic core <50 cm3: aOR 2.10, 95% CI 1.02-4.33, p = 0.044 vs ischemic core ≥50 cm3: aOR 0.41, 95% CI 0.01-16.02, p = 0.64) and transfer status (transferred: aOR 2.21, 95% CI 0.93-9.65, p = 0.29 vs direct to EVT center: aOR 1.84, 95% CI 0.80-4.23, p = 0.15). CONCLUSIONS BT appears to be associated with better clinical outcomes, especially with milder NIHSS scores, smaller presentation core volumes, and those who were "dripped and shipped." We did not observe any potential benefit of BT in patients with more severe strokes. TRIAL REGISTRATION INFORMATION ClinicalTrials.gov Identifier: NCT02446587. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that for patients with ischemic stroke from anterior circulation LVO within 4.5 hours from last known well, BT compared to dEVT leads to better 90-day functional outcomes.
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Affiliation(s)
- Amrou Sarraj
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece.
| | - James Grotta
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Gregory W Albers
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Ameer E Hassan
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Spiros Blackburn
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Arthur Day
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Clark Sitton
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Michael Abraham
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Chunyan Cai
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Mark Dannenbaum
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Deep Pujara
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - William Hicks
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Ronald Budzik
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Nirav Vora
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Ashish Arora
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Bader Alenzi
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Wondwossen G Tekle
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Haris Kamal
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Osman Mir
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Andrew D Barreto
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Maarten Lansberg
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Rishi Gupta
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Sheryl Martin-Schild
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Sean Savitz
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
| | - Georgios Tsivgoulis
- From the Departments of Neurology (A.S., J.G., D.P., H.K., A.D.B.), Neurosurgery (S.B., A.D., M.D.), Radiology (C.S.), and Clinical and Translational Science (C.C.), University of Texas at Houston; Department of Neurology (G.W.A., M.L.), Stanford University, CA; Department of Neurology (A.E.H., W.G.T.), University of Texas Rio Grande Valley, Harlingen; Department of Neurology (M.A.), Kansas University Medical Center, Kansas City; Department of Neurology (W.H., R.B., N.V.), OhioHealth-Riverside Methodist Hospital, Columbus; Cone Health (A.A.), Greensboro, NC; Department of Neurology (B.A.), St. Vincent Mercy Health Medical Center, Toledo, OH; Department of Neurology (O.M.), New York University Langone Health, New York; Department of Neurology (R.G.), WellStar Health System, Atlanta, GA; Department of Neurology (S.M.-S.), Touro Infirmary and New Orleans East Hospital, LA; Department of Neurology (S.S.), Institute for Stroke and Cerebrovascular Diseases-UTHealth, Houston; University of Tennessee Health Science Center (G.T.), Memphis; and Second Department of Neurology (G.T.), National & Kapodistrian University of Athens, Greece
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de Havenon A, Johnston SC, Easton JD, Kim AS, Sheth KN, Lansberg M, Tirschwell D, Mistry E, Yaghi S. Evaluation of Systolic Blood Pressure, Use of Aspirin and Clopidogrel, and Stroke Recurrence in the Platelet-Oriented Inhibition in New TIA and Minor Ischemic Stroke Trial. JAMA Netw Open 2021; 4:e2112551. [PMID: 34086033 PMCID: PMC8178708 DOI: 10.1001/jamanetworkopen.2021.12551] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
IMPORTANCE Elevated systolic blood pressure (SBP) after acute ischemic stroke and transient ischemic attack (TIA) is associated with future stroke risk. OBJECTIVE To explore the association of dual antiplatelet therapy (DAPT) with stroke recurrence among patients with acute ischemic stroke and TIA with or without elevated baseline SBP. DESIGN, SETTING, AND PARTICIPANTS This cohort study performed a post hoc subgroup analysis of the Platelet-Oriented Inhibition in New TIA and Minor Ischemic Stroke (POINT) trial, which was a multicenter trial conducted from 2010 to 2018 at 269 sites in 10 countries in North America, Europe, Australia, and New Zealand. Patients enrolled in POINT with available blood pressure and outcome data were included in this cohort. Statistical analysis was performed from November 2020 to January 2021. EXPOSURES Baseline SBP less than 140 mm Hg vs greater than or equal to 140 mm Hg and the interaction term of SBP (<140 mm Hg vs ≥140 mm Hg) × treatment group (aspirin vs DAPT). MAIN OUTCOMES AND MEASURES The primary outcome was ischemic stroke during 90 days of follow-up. The statistical analysis fit Cox proportional hazards models adjusted for patient age, race, premorbid hypertension, diabetes, and final diagnosis of the qualifying event (stroke vs TIA). RESULTS Among 4781 patients in the cohort, the mean (SD) age was 64.6 (13.1) years; 2142 (44.8%) were male individuals, 3487 (72.9%) were White individuals, and 266 (5.6%) had a primary outcome of ischemic stroke during follow-up. There were 946 patients (19.8%) with baseline SBP less than 140 mm Hg and 3835 (80.2%) with SBP greater than or equal to 140 mm Hg. The interaction term (SBP × treatment) was significant (P for interaction = .03). In the subgroup of patients with SBP less than 140 mm Hg, the hazard ratio (HR) of DAPT vs aspirin alone for ischemic stroke was 0.36 (95% CI, 0.18-0.72; P = .004), whereas the HR in the subgroup with SBP greater than or equal to 140 mm Hg was 0.79 (95% CI, 0.60-1.02; P = .08). When evaluating the outcome of ischemic stroke within 7 days of randomization, the interaction term was significant (P for interaction = .02), and the HR for patients with DAPT with SBP less than 140 mm Hg was 0.19 (95% CI, 0.07-0.55; P = .002). CONCLUSIONS AND RELEVANCE In the POINT trial, patients with SBP less than 140 mm Hg at presentation received a greater benefit from 90 days of DAPT than those with higher baseline SBP, particularly for reduction of early ischemic stroke recurrence. Additional research is needed to replicate these findings and potentially test whether mild SBP reduction and DAPT within 12 hours of stroke onset lowers early risk of stroke recurrence.
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Affiliation(s)
| | | | - J. Donald Easton
- Department of Neurology, University of California, San Francisco
| | - Anthony S. Kim
- Department of Neurology, University of California, San Francisco
| | - Kevin N. Sheth
- Department of Neurology, Yale University, New Haven, Connecticut
| | - Maarten Lansberg
- Department of Neurology, Stanford University, Stanford, California
| | | | - Eva Mistry
- Department of Neurology, Vanderbilt University, Nashville, Tennessee
| | - Shadi Yaghi
- Department of Neurology, New York University, New York
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14
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Sarraj A, Mlynash M, Heit J, Pujara D, Lansberg M, Marks M, Albers GW. Clinical Outcomes and Identification of Patients With Persistent Penumbral Profiles Beyond 24 Hours From Last Known Well: Analysis From DEFUSE 3. Stroke 2021; 52:838-849. [PMID: 33563012 DOI: 10.1161/strokeaha.120.031147] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke 3) infarct volumes at 24 hours did not significantly differ in the endovascular thrombectomy (EVT) versus medical management (MM) only groups. We hypothesized that this was due to underestimation of the final infarct volume among patients with persistent penumbral tissue 24 hours after randomization that subsequently progressed to infarction. We sought to assess the clinical outcomes in patients with persistent penumbral profile >24 hours from last known well and identify them based on the Persistent Penumbra Index (PPI, time-to-maximum of the residue function >6 s perfusion lesion divided by diffusion-weighted magnetic resonance imaging lesion volume on 24-hour postrandomization imaging). METHODS Patients were stratified into those with a 24-hour postrandomization penumbral (PPI>1) versus a nonpenumbral (PPI≤1) profile. The primary outcome was 90-day-modified Rankin Scale. RESULTS One hundred eighty-two patients were randomized (EVT: 92, MM: 90). Twenty-four-hour postrandomization time-to-maximum of the residue function and infarct volumes were assessable for 144 (EVT: 75, MM: 69). Infarct volumes did not differ between EVT and MM (median [interquartile range] mL: 35.0 [17.6-81.6] versus 41.0 [25.4-106.2], P=0.185). Thirty-two patients had persistent penumbral profile (PPI>1), of these 29 (91%) received MM. PPI was 0 (0-0.07) for EVT, and 0.77 (0.23-1.79) for MM, P<0.001. Patients with clinical-imaging mismatch (more severe strokes and smaller infarct volumes) were more likely to have persistent penumbral profile (PPI>1; adjusted odds ratio, 1.20 [1.11-1.30] for every 1-point National Institutes of Health Stroke Scale-increment and adjusted odds ratio, 0.977 [0.964-0.990] for every 10 cc smaller infarct volume, P<0.001). Patients with nonpenumbral profile (PPI≤1) had higher odds of achieving functional independence (39% versus 9%; adjusted odds ratio, 9.9[95% CI, 2.3-42.8], P=0.002), a trend towards lower mortality (12% versus 34%, P=0.002; adjusted odds ratio, 0.34 [95% CI, 0.11-1.03], P=0.057) and early clinical improvement (24-hour National Institutes of Health Stroke Scale-decrease ≥8 points or 0-1): 29% vs 9%, P=0.034) which persisted at discharge and 90-day follow-up. For a given volume, patients with PPI≤1 had significantly higher likelihood of functional independence as compared to those with PPI>1. CONCLUSIONS Patients with persistent penumbral profile who have salvageable tissue beyond 24 hours from last known well can be identified by PPI and clinical-imaging mismatch. They have a poor prognosis and may benefit from very late window reperfusion therapies. Clinical trials in these patients are warranted. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02586415.
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Affiliation(s)
- Amrou Sarraj
- Department of Neurology, University of Texas Health Science Center at Houston (A.S., D.P.)
| | - Michael Mlynash
- Departments of Neurology and Neurological Sciences (M. Mlynash, J.H., M.L., G.W.A.)
| | - Jeremy Heit
- Departments of Neurology and Neurological Sciences (M. Mlynash, J.H., M.L., G.W.A.)
| | - Deep Pujara
- Department of Neurology, University of Texas Health Science Center at Houston (A.S., D.P.)
| | - Maarten Lansberg
- Departments of Neurology and Neurological Sciences (M. Mlynash, J.H., M.L., G.W.A.)
| | - Michael Marks
- Department of Diagnostic Radiology, Stanford University School of Medicine, Stanford, CA (M. Marks)
| | - Gregory W Albers
- Departments of Neurology and Neurological Sciences (M. Mlynash, J.H., M.L., G.W.A.)
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15
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Dehkharghani S, Lansberg M, Venkatsubramanian C, Cereda C, Lima F, Coelho H, Rocha F, Qureshi A, Haerian H, Mont'Alverne F, Copeland K, Heit J. High-Performance Automated Anterior Circulation CT Angiographic Clot Detection in Acute Stroke: A Multireader Comparison. Radiology 2021; 298:665-670. [PMID: 33434110 DOI: 10.1148/radiol.2021202734] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background Identification of large vessel occlusion (LVO) is critical to the management of acute ischemic stroke and prerequisite to endovascular therapy in recent trials. Increasing volumes and data complexity compel the development of fast, reliable, and automated tools for LVO detection to facilitate acute imaging triage. Purpose To investigate the performance of an anterior circulation LVO detection platform in a large mixed sample of individuals with and without LVO at cerebrovascular CT angiography (CTA). Materials and Methods In this retrospective analysis, CTA data from recent cerebrovascular trials (CRISP [ClinicalTrials.gov NCT01622517] and DASH) were enriched with local repositories from 11 worldwide sites to balance demographic and technical variables in LVO-positive and LVO-negative examinations. CTA findings were reviewed independently by two neuroradiologists from different institutions for intracranial internal carotid artery (ICA) or middle cerebral artery (MCA) M1 LVO; these observers were blinded to all clinical variables and outcomes. An automated analysis platform was developed and tested for prediction of LVO presence and location relative to reader consensus. Discordance between readers with respect to LVO presence or location was adjudicated by a blinded tertiary reader at a third institution. Sensitivity, specificity, and receiver operating characteristics were assessed by an independent statistician, and subgroup analyses were conducted. Prespecified performance thresholds were set at a lower bound of the 95% CI of sensitivity and specificity of 0.8 or greater at mean times to notification of less than 3.5 minutes. Results A total of 217 study participants (mean age, 64 years ± 16 [standard deviation]; 116 men; 109 with positive findings of LVO) were evaluated. Prespecified performance thresholds were exceeded (sensitivity, 105 of 109 [96%; 95% CI: 91, 99]; specificity, 106 of 108 [98%; 95% CI: 94, 100]). Sensitivity and specificity estimates across age, sex, location, and vendor subgroups exceeded 90%. The area under the receiver operating characteristic curve was 99% (95% CI: 97, 100). Mean processing and notification time was 3 minutes 18 seconds. Conclusion The results confirm the feasibility of fast automated high-performance detection of intracranial internal carotid artery and middle cerebral artery M1 occlusions. © RSNA, 2021 See also the editorial by Kloska in this issue.
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Affiliation(s)
- Seena Dehkharghani
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Maarten Lansberg
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Chitra Venkatsubramanian
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Carlo Cereda
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Fabricio Lima
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Henrique Coelho
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Felipe Rocha
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Abid Qureshi
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Hafez Haerian
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Francisco Mont'Alverne
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Karen Copeland
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
| | - Jeremy Heit
- From the Department of Radiology, New York University Langone Medical Center, 660 First Ave, 2nd Floor, New York, NY 10016 (S.D.); Department of Neurology, Stanford University Hospital, Stanford, Calif (M.L., C.V., J.H.); Department of Neurology, Ente Ospedaliero Cantonale, Lugano, Switzerland (C.C.); Departments of Neurology (F.L., H.C., F.R.) and Radiology (F.M.), Hospital Geral de Fortaleza, Fortaleza, Brazil; Department of Neurology, Kansas University Medical Center, Kansas City, Kan (A.Q.); LifeBridge, Baltimore, Md (H.H.); and Boulder Statistics, Boulder, Colo (K.C.)
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16
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Sarraj A, Hassan AE, Grotta J, Blackburn S, Day A, Abraham M, Sitton C, Dannenbaum M, Cai C, Pujara D, Hicks W, Vora N, Budzik R, Shaker F, Arora A, Riascos RF, Kamal H, Martin-Schild S, Lansberg M, Gupta R, Albers GW. Early Infarct Growth Rate Correlation With Endovascular Thrombectomy Clinical Outcomes: Analysis From the SELECT Study. Stroke 2020; 52:57-69. [PMID: 33280550 DOI: 10.1161/strokeaha.120.030912] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Time elapsed from last-known well (LKW) and baseline imaging results are influential on endovascular thrombectomy (EVT) outcomes. METHODS In a prospective multicenter cohort study of imaging selection for endovascular thrombectomy (SELECT [Optimizing Patient's Selection for Endovascular Treatment in Acute Ischemic Stroke], the early infarct growth rate (EIGR) was defined as ischemic core volume on perfusion imaging (relative cerebral blood flow<30%) divided by the time from LKW to imaging. The optimal EIGR cutoff was identified by maximizing the sum of the sensitivity and specificity to correlate best with favorable outcome and to improve its the predictability. Patients were stratified into slow progressors if EIGR<cutoff and fast progressors if EIGR≥the optimal cutoff. Good collaterals were defined on computed tomography perfusion as a hypoperfusion intensity ratio <0.4 and on computed tomography angiography as collateral score >2. The primary outcome was 90-day functional independence (modified Rankin Scale score =0-2). RESULTS Of 445 consented, 361 (285 EVT, 76 medical management only) patients met the study inclusion criteria. The optimal EIGR was <10 mL/h; 200 EVT patients were slow and 85 fast progressors. Fast progressors had a higher median National Institutes of Health Stroke Scale (19 versus 15, P<0.001), shorter time from LKW to groin puncture (180 versus 266 minutes, P<0.001). Slow progressors had better collaterals on computed tomography perfusion: hypoperfusion intensity ratio (adjusted odds ratio [aOR]: 5.11 [2.43-10.76], P<0.001) and computed tomography angiography: collaterals-score (aOR: 4.43 [1.83-10.73], P=0.001). EIGR independently correlated with functional independence after EVT, adjusting for age, National Institutes of Health Stroke Scale, time LKW to groin puncture, reperfusion (modified Thrombolysis in Cerebral Infarction score of ≥2b), IV-tPA (intravenous tissue-type plasminogen activator), and transfer status (aOR: 0.78 [0.65-0.94], P=0.01). Slow progressors had higher functional independence rates (121 [61%] versus 30 [35%], P<0.001) and had 3.5 times the likelihood of achieving modified Rankin Scale score =0-2 with EVT (aOR=2.94 [95% CI, 1.53-5.61], P=0.001) as compared to fast progressors, who had substantially worse clinical outcomes both in early and late time window. The odds of good outcome decreased by 14% for each 5 mL/h increase in EIGR (aOR, 0.87 [0.80-0.94], P<0.001) and declined more rapidly in fast progressors. CONCLUSIONS The EIGR strongly correlates with both collateral status and clinical outcomes after EVT. Fast progressors demonstrated worse outcomes when receiving EVT beyond 6 hours of stroke onset as compared to those who received EVT within 6 hours. Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT02446587.
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Affiliation(s)
- Amrou Sarraj
- Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston
| | - Ameer E Hassan
- Neurology, University of Texas Rio Grande Valley, Harlingen (A.E.H.)
| | - James Grotta
- Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston
| | - Spiros Blackburn
- Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston
| | - Arthur Day
- Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston
| | - Michael Abraham
- Department of Neurology, University of Kansas Medical Center (M.A.)
| | - Clark Sitton
- Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston
| | - Mark Dannenbaum
- Department of Neurosurgery (S.B., A.D., M.D.), The University of Texas at Houston
| | - Chunyan Cai
- Division of Clinical and Translational Science (C.C.), The University of Texas at Houston
| | - Deep Pujara
- Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston
| | - William Hicks
- Department of Neurology, OhioHealth - Riverside Methodist Hospital, Columbus (W.H., N.V., R.B.)
| | - Nirav Vora
- Department of Neurology, OhioHealth - Riverside Methodist Hospital, Columbus (W.H., N.V., R.B.)
| | - Ronald Budzik
- Department of Neurology, OhioHealth - Riverside Methodist Hospital, Columbus (W.H., N.V., R.B.)
| | - Faris Shaker
- Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston
| | | | - Roy F Riascos
- Department of Radiology (C.S., R.F.R.), The University of Texas at Houston
| | - Haris Kamal
- Department of Neurology (A.S., J.G., D.P., F.S., H.K.), The University of Texas at Houston
| | - Sheryl Martin-Schild
- Department of Neurology, Touro Infirmary and New Orleans East Hospital (S.M.-S.)
| | | | - Rishi Gupta
- Department of Neurology, WellStar Health System, Atlanta (R.G.)
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17
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Sarraj A, Hassan AE, Grotta J, Sitton C, Cutter G, Cai C, Chen PR, Imam B, Pujara D, Arora A, Reddy S, Parsha K, Riascos RF, Vora N, Abraham M, Edgell R, Hellinger F, Haussen DC, Blackburn S, Kamal H, Barreto AD, Martin‐Schild S, Lansberg M, Gupta R, Savitz S, Albers GW. Correction to: “Optimizing Patient Selection for Endovascular Treatment in Acute Ischemic Stroke (
SELECT
): A Prospective Multicenter Cohort Study of Imaging Selection”. Ann Neurol 2020; 88:1056-1057. [DOI: 10.1002/ana.25843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 07/06/2020] [Accepted: 07/07/2020] [Indexed: 11/12/2022]
Affiliation(s)
- Amrou Sarraj
- Neurology The University of Texas at Houston Houston TX
| | - Ameer E. Hassan
- Neurology University of Texas Rio Grande Valley Harlingen TX
| | - James Grotta
- Neurology The University of Texas at Houston Houston TX
| | - Clark Sitton
- Radiology The University of Texas at Houston Houston TX
| | - Gary Cutter
- Biostatistics The University of Alabama at Birmingham School of Public Health Birmingham AL
| | - Chunyan Cai
- Clinical and Translational Science The University of Texas at Houston Houston TX
| | - Peng R. Chen
- Neurosurgery The University of Texas at Houston Houston TX
| | - Bita Imam
- Neurology The University of Texas at Houston Houston TX
| | - Deep Pujara
- Neurology The University of Texas at Houston Houston TX
| | | | - Sujan Reddy
- Neurology The University of Texas at Houston Houston TX
| | | | - Roy F Riascos
- Radiology The University of Texas at Houston Houston TX
| | - Nirav Vora
- Neurology OhioHealth ‐ Riverside Methodist Hospital Columbus OH
| | - Michael Abraham
- Neurology University of Kansas Medical Center Kansas City MO
| | | | | | | | | | - Haris Kamal
- Neurology The University of Texas at Houston Houston TX
| | | | | | | | | | - Sean Savitz
- Neurology The University of Texas at Houston Houston TX
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18
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Moshayedi P, Liebeskind DS, Jadhav A, Jahan R, Lansberg M, Sharma L, Nogueira RG, Saver JL. Decision-Making Visual Aids for Late, Imaging-Guided Endovascular Thrombectomy for Acute Ischemic Stroke. J Stroke 2020; 22:377-386. [PMID: 33053953 PMCID: PMC7568977 DOI: 10.5853/jos.2019.03503] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 06/22/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND AND PURPOSE Speedy decision-making is important for optimal outcomes from endovascular thrombectomy (EVT) for acute ischemic stroke (AIS). Figural decision aids facilitate rapid review of treatment benefits and harms, but have not yet been developed for late-presenting patients selected for EVT based on multimodal computed tomography or magnetic resonance imaging. METHODS For combined pooled study-level randomized trial (DAWN and DEFUSE 3) data, as well as each trial singly, 100 person-icon arrays (Kuiper-Marshall personographs) were generated showing beneficial and adverse effects of EVT for patients with AIS and large vessel occlusion using automated (algorithmic) and expert-guided joint outcome table specification. RESULTS Among imaging-selected patients 6 to 24 hours from last known well, for the full 7-category modified Rankin Scale (mRS), EVT had number needed to treat to benefit 1.9 (interquartile range [IQR], 1.9 to 2.1) and number needed to harm 40.0 (IQR, 29.2 to 58.3). Visual displays of treatment effects among 100 patients showed that, with EVT: 52 patients have better disability outcome, including 32 more achieving functional independence (mRS 0 to 2); three patients have worse disability outcome, including one more experiencing severe disability or death (mRS 5 to 6), mediated by symptomatic intracranial hemorrhage and infarct in new territory. Similar features were present in person-icon figures based on a 6-level mRS (levels 5 and 6 combined) rather than 7-level mRS, and based on the DAWN trial alone and DEFUSE 3 trial alone. CONCLUSIONS Personograph visual decision aids are now available to rapidly educate patients, family, and healthcare providers regarding benefits and risks of EVT for late-presenting, imaging-selected AIS patients.
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Affiliation(s)
- Pouria Moshayedi
- Department of Neurology and Comprehensive Stroke Center, University of California Los Angeles, Los Angeles, CA, USA
| | - David S Liebeskind
- Department of Neurology and Comprehensive Stroke Center, University of California Los Angeles, Los Angeles, CA, USA
| | - Ashutosh Jadhav
- Department of Neurology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Reza Jahan
- Department of Radiology and Comprehensive Stroke Center, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Latisha Sharma
- Department of Neurology and Comprehensive Stroke Center, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Jeffrey L Saver
- Department of Neurology and Comprehensive Stroke Center, University of California Los Angeles, Los Angeles, CA, USA
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19
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Seifert-Held T, Eberhard K, Christensen S, Hofer E, Enzinger C, Albers GW, Lansberg M. Circle of Willis variants are not associated with thrombectomy outcomes. Stroke Vasc Neurol 2020; 6:310-313. [PMID: 33046661 PMCID: PMC8258040 DOI: 10.1136/svn-2020-000491] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/03/2020] [Accepted: 09/09/2020] [Indexed: 11/23/2022] Open
Abstract
Background The circle of Willis (COW) is part of the brain collateral system. The absence of COW segments may affect functional outcome in patients with ischaemic stroke undergoing endovascular therapy. Methods In 182 patients in the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution 2 Study and the CT Perfusion to Predict Response to Recanalisation in Ischaemic Stroke Project, COW anatomy was evaluated on postinterventional magnetic resonance angiography. The absence of the posterior communicating artery or the first segments of posterior or anterior cerebral arteries ipsilateral to the ischaemic infarction was rated as an incomplete COW. Logistic regression was applied to evaluate an association with the patients’ modified Rankin scale (mRS) at 90 days after stroke Results An incomplete ipsilateral COW was not predictive of the patients’ mRS at 90 days after stroke. Significant associations were shown for the patients’ baseline National Institutes of Health Stroke Scale (NIHSS), age and reperfusion status. The effect size suggests that a significant association of an incomplete COW with the mRS at 90 days may be obtained in cohorts of more than 3000 patients. Conclusions Compared with the established predictors NIHSS, age and reperfusion status, an incomplete COW is not associated with functional outcome after endovascular therapy.
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Affiliation(s)
| | - Katharina Eberhard
- Core Facility Computational Bioanalytics, Center for Medical Research, Medical University of Graz, Graz, Austria
| | - Soren Christensen
- Department of Neurology & Neurological Sciences, Stanford University, Stanford, California, USA
| | - Edith Hofer
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Gregory W Albers
- Department of Neurology & Neurological Sciences, Stanford University, Stanford, California, USA
| | - Maarten Lansberg
- Department of Neurology & Neurological Sciences, Stanford University, Stanford, California, USA
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20
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Federau C, Christensen S, Scherrer N, Ospel JM, Schulze-Zachau V, Schmidt N, Breit HC, Maclaren J, Lansberg M, Kozerke S. Improved Segmentation and Detection Sensitivity of Diffusion-weighted Stroke Lesions with Synthetically Enhanced Deep Learning. Radiol Artif Intell 2020; 2:e190217. [PMID: 33937840 DOI: 10.1148/ryai.2020190217] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 04/23/2020] [Accepted: 05/06/2020] [Indexed: 11/11/2022]
Abstract
Purpose To compare the segmentation and detection performance of a deep learning model trained on a database of human-labeled clinical stroke lesions on diffusion-weighted (DW) images to a model trained on the same database enhanced with synthetic stroke lesions. Materials and Methods In this institutional review board-approved study, a stroke database of 962 cases (mean patient age ± standard deviation, 65 years ± 17; 255 male patients; 449 scans with DW positive stroke lesions) and a normal database of 2027 patients (mean age, 38 years ± 24; 1088 female patients) were used. Brain volumes with synthetic stroke lesions on DW images were produced by warping the relative signal increase of real strokes to normal brain volumes. A generic three-dimensional (3D) U-Net was trained on four different databases to generate four different models: (a) 375 neuroradiologist-labeled clinical DW positive stroke cases (CDB); (b) 2000 synthetic cases (S2DB); (c) CDB plus 2000 synthetic cases (CS2DB); and (d) CDB plus 40 000 synthetic cases (CS40DB). The models were tested on 20% (n = 192) of the cases of the stroke database, which were excluded from the training set. Segmentation accuracy was characterized using Dice score and lesion volume of the stroke segmentation, and statistical significance was tested using a paired two-tailed Student t test. Detection sensitivity and specificity were compared with labeling done by three neuroradiologists. Results The performance of the 3D U-Net model trained on the CS40DB (mean Dice score, 0.72) was better than models trained on the CS2DB (Dice score, 0.70; P < .001) or the CDB (Dice score, 0.65; P < .001). The deep learning model (CS40DB) was also more sensitive (91% [95% confidence interval {CI}: 89%, 93%]) than each of the three human readers (human reader 3, 84% [95% CI: 81%, 87%]; human reader 1, 78% [95% CI: 75%, 81%]; human reader 2, 79% [95% CI: 76%, 82%]), but was less specific (75% [95% CI: 72%, 78%]) than each of the three human readers (human reader 3, 96% [95% CI: 94%, 98%]; human reader 1, 92% [95% CI: 90%, 94%]; human reader 2, 89% [95% CI: 86%, 91%]). Conclusion Deep learning training for segmentation and detection of stroke lesions on DW images was significantly improved by enhancing the training set with synthetic lesions.Supplemental material is available for this article.© RSNA, 2020.
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Affiliation(s)
- Christian Federau
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Soren Christensen
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Nino Scherrer
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Johanna M Ospel
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Victor Schulze-Zachau
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Noemi Schmidt
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Hanns-Christian Breit
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Julian Maclaren
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Maarten Lansberg
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, ETH Zürich und University of Zürich, Gloriastrasse 35, 8092 Zürich, Switzerland (C.F., N. Scherrer, S.K.); Stanford Stroke Center, Department of Neurology, Stanford University, Stanford, Calif (S.C., J.M., M.L.); and Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland (J.O., V.S.Z., N. Schmidt, H.C.B.)
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22
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Pizzo E, Lobotesis K, Albers GW, Martin-Schild S, Hassan A, Abraham M, Vora N, Chen PR, Grotta JC, Sitton C, Blackburn S, Dannenbaum M, Cai C, Parsha K, Reddy S, Kamal H, Arora A, Pujara D, Imam B, Shaker F, Barreto AD, Hicks WJ, Riascos RF, Haussen D, Gupta R, Lansberg M, McCullough LD, Savitz SI, Sarraj A. Abstract 171: Endovascular Thrombectomy May Be Cost-Effective for Patients With Large Core Ischemic Strokes: A Cost-Utility Analysis From the SELECT Study. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Whether Endovascular Thrombectomy (EVT) is cost-effective in large ischemic core infarcts is unknown.
Methods:
In the prospective multicenter cohort study of imaging selection study (SELECT), large core was defined as CT ASPECTS < 6 or CTP ischemic core volume (rCBF<30%) ≥ 50 cc. A Markov model estimated costs, quality-adjusted life years (QALYs) and the Incremental Cost-effectiveness Ratio (ICER) of EVT compared to Medical Management (MM) over 20 years life expectancy. The lower and upper willingness to pay (WTP) per QALY were set at $50000 and $100000 and the Net Monetary Benefit (NMB) for EVT were calculated. A probabilistic sensitivity analysis (PSA) and cost-effectiveness acceptability curves (CEAC) assessed EVT cost-effective probability at WTP range values.
Results:
Of 361 enrolled, 105 had large core on CT or CTP (EVT 62, MM 43). 19 (31%) EVT patients achieved mRS 0-2 vs 6 (14%) MM (aOR: 3.27, 95% CI: 1.11-9.62;
P
= .03) with a shift towards better mRS (adj cOR: 2.12, 95% CI: 1.05-4.31,
P
= .04). Over 20 years EVT was associated with $26589 (C.I. $8672- $43978) incremental costs and a gain of 1.18 QALYs (C.I. 0.091- 2.2) per patient.
EVT could avert 75 deaths over a theoretical cohort of 1000 patients (MM 861 vs EVT 786) thus the ICER of EVT compared to MM was $22400 per QALY (CI. $10109 - $66140), which is <$50000/QALY, Tab 1.
EVT has a higher NMB compared to MM at the lower and upper WTP thresholds (EVT $86,3 and 271,4 million vs MM $53,6-$179,3 million), Tab 2.
The PSA confirmed the results (fig 1). The CEAC showed 94% and 97% cost-effectiveness probability of EVT at the lower and upper values respectively of the maximum WTP, fig 2.
EVT ICER in SELECT large core ($22400/QALY) was higher but still comparable to those in HERMES ($16882/QALY), DAWN ($7335/QALY) and DEFUSE3 ($14673/QALY), Tab 3.
Conclusion:
EVT may result in better outcomes and more lives saved in large core patients with higher QALYs, NMB and an acceptable ICER. The results were comparable to other EVT RCTs.
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Affiliation(s)
- Elena Pizzo
- Applied Health Rsch, Univ College London, London, United Kingdom
| | | | | | | | - Ameer Hassan
- Neurology, Univ of Texas Rio Grande Valley, Harlingen, TX
| | | | - Nirav Vora
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | - Peng R Chen
- Neurosurgery, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Clark Sitton
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | | | | | | | | | - Sujan Reddy
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Haris Kamal
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Deep Pujara
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Bita Imam
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Faris Shaker
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - William J Hicks
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | - Roy F Riascos
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Rishi Gupta
- Neurology, WellStar Health System, Marrietta, GA
| | | | | | - Sean I Savitz
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Amrou Sarraj
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
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23
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Sarraj A, Lansberg M, Marks MP, Mlynash M, Heit JJ, Savitz SI, Albers GW. Abstract WP15: Correlation of 24-Hour Infarct Volumes and Imaging Reperfusion With Functional Independence in DEFUSE 3. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
In DEFUSE 3, infarct volumes 24 hours after randomization did not significantly differ in EVT vs. medical management only (MM) groups. We hypothesized that this lack of difference was due underestimation of the final infarct volume among patients who had persistent penumbral tissue 24 hours after randomization that subsequently progressed to infarction. In this substudy, we evaluated if the 24 hr post-randomization DWI volumes correlated with functional independence.
Methods:
We correlated the 24-hr post-randomization DWI volumes and penumbral profiles with 90-day functional independence.
Results:
182 patients, 92 were randomized to EVT, 90 to MM. 24 hr post-randomization Tmax and DWI volume were assessable for 75 EVT and 69 MM. Infarct volumes at 24 hr follow-up did not differ between EVT and MM median (IQR) ml 35.0 (17.6-81.6) vs 41.0(25.4-106.2), P=0.185. Still, 24 hr infarct volumes independently correlated with 90 day functional independence: median (IQR) 30.3 ml (9.0-55.6) vs. 47.5 ml (25.4-132.3), aOR=0.93 (95%CI=0.89-0.98, P=0.004) for achieving functional independence vs. disability for each additional 5 ml of infarct volume after adjustment for baseline NIHSS, age, glucose, and treatment, figure 1. EVT resulted in higher rates of reperfusion (>90% reduction in Tmax>6 seconds at 24 hrs in 79% of EVT vs. 18% of MM, P<0.001). Patients who achieved successful reperfusion with no evidence of remaining penumbra had smaller 24- hr infarct volumes: 32.9 (17.6-67.0) vs. 59.3 (24.7-126.3), P=0.007), figure 2 and a higher odds of functional independence aOR=10.9, 95%CI 3.6-39.8, P<0.001, compared to those who had remaining penumbral tissue, figure 3.
Conclusion:
24 hr- post randomization infarct volumes independently correlated with functional independence in DEFUSE 3. Patients who had complete reperfusion had smaller follow-up infarct volumes and a higher odds of functional independence as compared to those with persistent penumbral mismatch.
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Affiliation(s)
- Amrou Sarraj
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | | | | | | | - Sean I Savitz
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
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24
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Sarraj A, Hassan A, Grotta JC, Sitton C, Blackburn S, Abraham M, Chen PR, Vora N, Pujara D, Cai C, Parsha K, Reddy S, Kamal H, Arora A, Imam B, Hicks WJ, Shaker F, Barreto AD, Riascos RF, Haussen D, Martin-Schild S, Gupta R, Lansberg M, Savitz SI, Albers GW. Abstract 129: Endovascular Thrombectomy Potential Benefits in Isolated M2 Occlusions Are Related to Stroke Severity and Penumbral Mismatch Deficit: A Secondary Analysis From the SELECT Study. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
The efficacy of endovascular thrombectomy (EVT) in M2 occlusions is uncertain.
Methods:
In a prospective multicenter cohort study of imaging selection (SELECT), EVT outcomes were compared to medical managment (MM) in M2 occlusions. Further, we assessed for potential treatment benefit in patients with higher stroke severity (NIHSS) and a larger perfusion deficit on CTP (Tmax > 6 sec - ischemic core volume)The primary outcome was excellent outcome (mRS 0-1).
Results:
of 361 patients enrolled in SELECT, 87 had isolated M2 occlusion (EVT 59, MM 28). Baseline NIHSS median (IQR) (EVT 14 (10-20), MM 15 (9.5-19.5), p=0.72) and infarct volume rCBF<30% (EVT 7 (0-21) vs MM 18.5 (0-41.25), P=0.10). EVT was associated with higher rates of excellent outcomes (53% vs 21%, aOR:6.94, 95% CI=1.86-25.90, p=0.004) with a shift towards better mRS outcomes (adj cOR: 3.49, 95% CI=1.39-8.80, p=0.008), smaller final infarct volume (15.9 (2.7-48.0) vs 58 (24.3-141.9), P<0.001), and a reduction of neurological worsening (3% vs 22%, p=0.011), sICH (2% vs 21%, p=0.004), and mortality (5% vs 25%, p=0.011). Assessing outcomes in NIHSS strata; there was no significant increase in excellent outcomes rates in NIHSS ≤10 (EVT 65% vs MM 50%, aOR=1.59, 95% CI=0.21-12.01, p=0.65). In contrast, patients with NIHSS>10 had better outcomes with EVT (46%) vs MM (10%), aOR=11.39, 95% CI=1.80-72.11, p=0.01 as shown in figure 1. As perfusion deficit lesion size increased, the odds of achieving excellent outcomes was reduced (for each 10cc by 11%, aOR: 0.89, 95% CI=0.79-1.00, p=0.05). Excellent outcomes declined in patients with MM as perfusion deficit lesion size increased, yet in the EVT they were maintained as shown in figure 2. Similar results were obtained for mRS 0-2.
Conclusion:
EVT may result in better rates of excellent outcomes in isolated M2 occlusions, especially those with more severe strokes and larger perfusion deficits who are more likely to have worse outcomes without emergent reperfusion.
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Affiliation(s)
- Amrou Sarraj
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Ameer Hassan
- Neurology, Univ of Texas Rio Grande Valley, Harlingen, TX
| | | | - Clark Sitton
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | | | | | - Peng R Chen
- Neurosurgery, McGovern Med Sch at UTHealth, Houston, TX
| | - Nirav Vora
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | - Deep Pujara
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | | | - Sujan Reddy
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Haris Kamal
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Bita Imam
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - William J Hicks
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | - Faris Shaker
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Roy F Riascos
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | | | | | - Rishi Gupta
- Neurology, WellStar Health System, Marrietta, GA
| | | | - Sean I Savitz
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
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Rao V, Mlynash M, Christensen S, Yennu A, Kemp S, Zaharchuk G, Heit J, Marks M, Lansberg M, Albers G. Abstract WMP24: Collateral Status Contributes to Differences Between Observed and Predicted 24-Hour Infarct Volumes in DEFUSE 3. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wmp24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose:
We have previously shown that in the DEFUSE 3 trial, the infarct volume 24 hours after randomization was predicted by the union of the baseline core and the 24-hour Tmax>6s perfusion lesion. We determined if collateral robustness measured by the hypoperfusion intensity ratio (HIR) and cerebral blood volume index (CBV) accounts for the variance in infarct volume predictions.
Methods:
DEFUSE 3 patients underwent MRI with perfusion or CT perfusion at baseline and 24 hours after randomization. We used RAPID software to determine ischemic core and Tmax>6s lesion volumes as well as HIR and CBV Index at baseline and 24 hours. Patients were stratified by the difference between the predicted and the observed infarct volume at 24 hours. We compared baseline and follow-up HIR and CBV Index, as well as several other imaging and clinical outcomes in subgroups based on the accuracy of the infarct volume estimate.
Results:
Out of 123 eligible patients, 34 had 24-hour infarcts larger than predicted and these patients had less favorable collaterals (HIR 0.43 vs 0.32, p=0.006 and CBV Index 0.78 vs 0.85, p=0.001) at baseline, as well as at 24-hour follow-up (HIR 0.56 vs 0.07, p=0.004 and CBV Index 0.47 vs 0.73, p=0.006) compared to the 71 patients with more accurate infarct volume prediction. The remaining 18 patients had 24-hour infarct volumes smaller than predicted. These patients had similar baseline collateral scores but a more favorable CBV Index at 24 hours (0.81 vs 0.73, p=0.040) compared to patients with more accurate infarct prediction.
Conclusions:
Patients with 24-hour infarcts larger than predicted had evidence of less favorable baseline collaterals that fail within 24 hours, while patients with 24-hour infarcts smaller than predicted typically had favorable collaterals that persisted for at least 24 hours.
Clinical Trial Registration:
URL: http://www.clinicaltrials.gov. Unique identifier: NCT02586415
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Christensen S, Federau C, Maclaren J, Srivatsan A, Albers G, Lansberg M. Abstract TP64: Ischemic Stroke Lesion Identification in Non-Contrast CT Using Deep Learning. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.tp64] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Automatic measurement of the acute stroke lesion volume on DWI and CT-CBF has been used in recent late window trials. Despite non-contrast CT (NCCT) being the most widely used imaging modality in the acute stroke setting, quantification of acute stroke volumes on NCCT has not been employed in trials because of the difficulty outlining territory with very mild Hounsfield unit depression. Deep learning algorithms have been effective at solving many image processing tasks and may outperform human readers given enough training data. The goal of this study was to train and test a deep learning model on NCCT scans with synthetic stroke lesions and to determine the optimal model design.
Methods:
Training: 20 NCCT scans without acute stroke were combined with 20 DWI lesions using co-registration producing 400 non-contrast scans with lesions. The region of the NCCT that coincided with the DWI lesion was depressed by 2 Hounsfield units to simulate an acute infarct. An independent validation dataset of 100 cases was created in the same way. Two models were used: a standard “Unet” model and a symmetry-aware Unet model. The models were compared in terms of segmentation accuracy in the independent validation dataset.
Results:
Both the symmetry aware U-net and the standard U-net detected some part of the true lesion in 100% of the cases. The symmetry aware U-net was more sensitive, median [iqr], (45% [27-68] vs 17% [6-54], p<0.00001) but slightly less specific (98% [93-98] vs 99% [94-99], p<0.0008) than the standard U-net.
Conclusion:
The symmetry aware U-net shows great promise in detection of acute strokes on NCCT; lesions with Hounsfield unit depressions that are barely visible to the eye can be automatically segmented by this model. Additional training data and architectural enhancements are likely to improve the current spatial sensitivity to above 45%.
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27
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MacLellan A, Legault C, Parikh A, Lugo L, Kemp S, Mlynash M, Buckwalter M, Flavin K, Lansberg M. Abstract WP205: Home-Based Virtual Reality Therapy for Hand Recovery After Stroke. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Stroke is the leading cause of disability worldwide, with many stroke survivors having persistent upper limb functional impairment. Aside from therapist-directed rehabilitation, few efficacious recovery tools are available for use by stroke survivors in their own home. Game-based virtual reality systems have already shown promising results in therapist-supervised settings and may be suitable for home-based use.
Objective:
We aimed to assess the feasibility of unsupervised home-based use of a virtual reality device for hand rehabilitation in stroke survivors.
Methodology:
Twenty subacute/chronic stroke patients with upper extremity impairment were enrolled in this prospective single-arm study. Participants were instructed to use the Neofect Smart Glove 5 days per week for 8 weeks, in single sessions of 50 minutes or two 25-minute sessions daily. We measured (1) compliance to prescribed rehabilitation dose, (2) patient impression of the intervention, and (3) efficacy measures including the upper extremity Fugl-Meyer (UE-FM), the Jebsen-Taylor hand function test (JTHFT) and the Stroke Impact Scale (SIS).
Results:
Seven subjects (35%) met target compliance of 40 days use, and 6 subjects (30%) used the device for 20-39 days; there were no age or gender differences in use. Subjective patient experience was favorable, with ninety percent of subjects reporting satisfaction with their overall experience, and 80% reporting perceived improvement in hand function (figure 1). There was a mean improvement of 26.6±48.8 seconds in the JTHFT (
p
=0.03) and 16.1±15.3 points in the domain of the SIS that assesses hand function (
p
<0.01). There was a trend towards improvement in the UE-FM (2.2±5.5 points,
p
=0.10).
Conclusions:
A novel virtual reality gaming device is suitable for unsupervised use in stroke patients and may improve hand/arm function in subacute/chronic stroke patients. A large-scale randomized controlled trial is needed to confirm these results.
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Sarraj A, Lansberg M, Marks MP, Mlynash M, Heit JJ, Savitz SI, Albers GW. Abstract WMP12: Benefits of Thrombectomy Among Patients Who Did Not Achieve Functional Independence in DEFUSE 3. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wmp12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
While endovascular thrombectomy (EVT) patients may not achieve functional independence, they may avoid devastating outcomes as in profound disability/death.
Methods:
DEFUSE 3 patients who did not achieve mRS 0-2 were assessed for a shift towards reductions in severe (mRS 4-6) and profound (mRS 5-6) disability, mortality, length of stay (LOS) and increased rates of home/rehabilitation discharges.
Results:
126 of the 182 randomized in DEFUSE 3 did not achieve mRS 0-2 (EVT 51, MM 75). Baseline characteristics were similar. EVT was associated with a higher mRS 3 rate (28% vs 18%) and lower rates of severe (72% vs 82%) and profound disability (39% vs. 50%), EVT vs MM respectively, with a trend for a shift towards less disability aOR=1.6 (95%CI=0.9-3.2, P=0.138), figure 1. Mortality rates were numerically lower with EVT (25% vs 31, p=0.528). EVT patients had a trend for shorter LOS (8.6 (6.5-13.7) vs 9.3 (7.1-16.3) days, p=0.156) and increased rates of home/rehabilitation discharges 51% vs. 40%, p=0.224. Older age correlated independently with severe disability aOR=1.04 per year/age, (95%CI=1.01-1.07, p=0.023) as did more severe strokes, aOR per NIHSS point=1.07, 95%CI=0.99-1.15, P=0.096). Larger final infarct volumes had a trend towards severe disability in EVT aOR=1.005, 95%CI=0.996-1.013, p=0.257, but not in MM aOR=1.0 (95% CI 0.993-1.007, p=0.966). Lack of reperfusion (>90% Tmax>6 reduction) had a strong trend for severe disability in MM (83% in non-reperfusers vs. 50% for reperfusers), p=0.056, but not in EVT: 77% vs. 63%, p=0.484.
Conclusion:
In patients who did not achieve functional independence, EVT resulted in reduced rates of severe and profound disability, decreased length of stay and increased home and rehabilitation discharges. Older patients, more severe strokes and those who did not achieve reperfusion were more likely to have severe disability especially if not treated with EVT. EVT may result in avoiding severe disability in elderly patients.
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Affiliation(s)
- Amrou Sarraj
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | | | | | | | - Sean I Savitz
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
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29
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Drag L, Aghaeepour N, Mlynash M, Osborn E, Rah E, Buckwalter M, Lansberg M. Abstract WP190: Development of a Comprehensive Neuropsychological Battery to Assess Post-Stroke Cognitive Functioning. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
Cognitive outcomes vary widely following stroke and there is need for further research identifying the trajectory of post-stroke cognitive functioning. This requires a neuropsychological test battery that takes into account the unique challenges of testing cognition post-stroke (e.g., aphasia, hemiparesis) and that is relatively brief yet assesses cognition across multiple domains. The aim of this study was to develop such a battery and describe its characteristics.
Methods:
StrokeCog is a prospective longitudinal cohort study examining cognitive trajectories following stroke. A 60-minute neuropsychological battery including 10 tests (yielding 17 neuropsychological variables) was administered to 86 participants 6-12 months after stroke. Raw scores for each of the 17 variables were transformed to age-corrected z-scores. A pair-wise undirected Pearson correlation graph was created using all available variables to visualize the correlation network representing the variables and to identify the cognitive domains assessed by these variables.
Results:
Participants ranged in age from 26-87 (M = 63.85, SD = 12.58); 59% of the sample was male. Sixteen cognitive variables loaded onto five cognitive domains: memory, expressive language, processing speed, visuospatial functioning, and fine motor functioning. 62% of participants demonstrated impaired cognition in at least one domain with 22% demonstrating impairment in 2 or more domains. Memory and processing speed were most commonly impaired (45% and 53% of participants, respectively). Visuospatial functioning was least impacted (14% of participants).
Conclusions:
A comprehensive assessment of cognition in post-stroke patients can be obtained using a 60-minute cognitive test battery, allowing repeated annual assessments to elucidate cognitive trajectories post-stroke. The results show a high rate of cognitive impairment in at least one cognitive domain among the participants.
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Affiliation(s)
- Lauren Drag
- Stanford Univ Sch of Medicine, Palo Alto, CA
| | | | | | | | - Esther Rah
- Stanford Univ Sch of Medicine, Palo Alto, CA
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30
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Moshayedi P, Liebeskind D, Jadhav A, Jahan R, Lansberg M, Sharma L, Nogueira R, Saver J. Abstract TP54: Visual Aids for Patient, Family, and Physician Decision Making About Late Imaging-Guided Endovascular Thrombectomy for Acute Ischemic Stroke. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.tp54] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Speedy decision-making is helpful for optimal outcomes from endovascular thrombectomy (EVT) for acute ischemic stroke (AIS). Visual displays may facilitate rapid review of relevant outcomes with different courses of action, but have not yet been developed for late-presenting patients selected for EVT based on multimodal CT or MR imaging.
Methods:
From pooled, study-level randomized trial (DAWN and DEFUSE 3) data, 100 person-icon arrays (Kuiper-Marshall personographs) were generated showing beneficial and adverse effects of endovascular thrombectomy for patients with acute cerebral ischemia and large vessel occlusion using (1) automated (algorithmic) and (2) expert-guided joint outcome table specification.
Results:
Among imaging-selected patients 6-24 hours from last known well, for the full 7-category modified Rankin Scale (mRS), endovascular thrombectomy had number needed to treat to benefit 1.9 (IQR 1.9-2.1) and number needed to harm 40.0 (29.2-58.3). Visual displays of treatment effects among 100 patients showed that, with EVT: 52 patients have better disability outcome, including 32 more achieving functional independence (mRS 0-2); 3 patients have worse disability outcome, including 1 more experiencing severe disability or death (mRS 5-6), mediated by symptomatic intracranial hemorrhage and infarct in new territory. The person-icon figure integrated these outcomes, and early side-effects, in a single display (Figure). Similar features were present in person-icon figures based on a 6-level mRS (levels 5 and 6 combined) rather than 7-level mRS, and giving special emphasis to normal or near-normal outcome (mRS 0-1) rather than functional independence (mR 0-2).
Conclusion:
Personograph visual decision aids are now available to rapidly educate patients, family, and healthcare providers on the benefits and risks of late, imaging-guided endovascular thrombectomy therapies for acute ischemic stroke.
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Affiliation(s)
| | | | | | - Reza Jahan
- Radiology, Univ of California Los Angeles, Los Angeles, CA
| | | | - Latisha Sharma
- Neurology, Univ of California Los Angeles, Los Angeles, CA
| | | | - Jeffrey Saver
- Neurology, Univ of California Los Angeles, Los Angeles, CA
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31
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Yu Y, Xie Y, Gong E, thamm T, Ouyang J, Christensen S, Lansberg M, Albers G, Zaharchuk G. Abstract WP79: The Value of Pre-Training for Deep Learning Acute Stroke Triaging Models. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp79] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Objective:
We investigated if deep learning models are able to define the penumbra and ischemic core by comparing models from two training strategies (with and without pre-training) and clinical thresholding criteria (MRI parameter time-to-peak of the residue function [Tmax] and apparent diffusion coefficient [ADC]).
Methods:
We selected patients from two multicenter stroke trials, with baseline perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI) and 3-7 day T2-FLAIR. Based on reperfusion rate calculated from baseline and 24 hr PWI, patients were grouped into unknown (no 24 hr PWI scan), minimal (≤20%), partial (20%-80%), and major (≥80%) reperfusion. Attention-gated U-net structure was selected for training, with eight image channels from baseline PWI/DWI as inputs and the infarct lesion manually segmented on T2-FLAIR as ground truth. Two training strategies were used: (1) training two models separately in minimal and major reperfusion patients; (2) pre-training a model using patients with partial and unknown reperfusion, then fine-tuning two models using minimal and major reperfusion patients, respectively. Prediction was evaluated by Dice score coefficient (DSC), and lesion volume error at an optimal threshold. In minimal and major reperfusion patients, the deep learning models and Tmax and ADC thresholding were compared using paired sample Wilcoxon test.
Results:
182 patients were included (85 males, age 65±16 yrs, baseline NIHSS 15 IQR 10-19), with a breakdown of minimal/major/partial/unknown reperfusion status of 32/65/43/42 patients, respectively. The pre-training approach performed the best among all approaches (Table 1, Figure 1).
Conclusion:
Deep learning models to predict penumbra and ischemic core are best trained using general pre-training on a wide range of stroke cases followed by fine-tuning on the extreme cases. This method outperforms conventional DWI-PWI mismatch inspired thresholding approaches.
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32
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Sarraj A, Grotta JC, Lansberg M, Abraham M, Sitton C, Chen PR, Cai C, Pujara D, Blackburn S, Reddy S, Vora N, Haussen D, Parsha K, Kamal H, Imam B, Shaker F, Gupta R, Martin-Schild S, Hicks WJ, Arora A, Barreto AD, Riascos RF, Hassan A, Savitz SI, Albers GW. Abstract WP42: Stroke Severity and Size Modify the Association Between IV Thrombolysis and Outcomes Following Endovascular Thrombectomy. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp42] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Whether IV tPA has adjunctive benefit to endovascular thrombectomy (EVT) is unclear.
Methods:
In a prospective multicenter cohort study of imaging selection for EVT (SELECT), patients who received IV tPA vs. no IV tPA were compared stratified by stroke severity and ischemic core size (rCBF<30%).
Results:
Of 361 enrolled, 285 received EVT; 226 presented within 4.5 hrs, 162 (72%) received IV tPA. IV tPA patients had lower median ASPECTS (8 vs 9, p=0.007) and larger ischemic core size (11.4 (1.5-37) vs 3.9 (0-32.15), p=0.042, otherwise similar at baseline. There were no delays in EVT delivery associated with tPA: median time (IQR) from arrival to groin puncture 95.0 min (66.0, 118.0) tPA vs 81.5 (63.5, 107.5) no tPA, p=0.21. IV tPA use was associated with higher mRS 0-2 rates (57% vs 44%), aOR 2.02 (95% CI 1.01-4.03, p=0.046) after adjustment for baseline differences with a shift towards better outcomes on all mRS levels (cOR 2.06, 95% CI 1.18-3.59, p=0.01) with lower mortality (11% vs 22%, p=0.026) and similar sICH rates (and 6% vs 6%, p=1.0). In patients with NIHSS <15, IV tPA was associated with higher mRS 0-2 (tPA 83% vs no tPA 50%, aOR 4.53, 95%CI 1.48-13.80, p=0.008) with a shift towards better outcomes (adj cOR 5.44, 95% CI 2.16-13.70, p<0.001) while with NIHSS≥15 there was no adjunctive benefit of IV tPA (tPA 42% vs no tPA 38%, aOR 1.05, 95%CI 0.40-2.74, p=0.92) or shift (adj cOR: 1.32, 95% CI 0.61-2.86, p=0.48) with an interaction between IV tPA effect on EVT outcome with NIHSS (p=0.04) Fig A. Similarly, in ischemic core < 50 cc (62% vs. 46%, aOR 1.96, 95%CI 0.96-3.99, p=0.06; adj cOR 2.03, 95% CI 1.13-3.66, p=0.018) as compared to core ≥ 50cc (tPA 26% vs no tPA 25% P=1.0) with an interaction between IV tPA effect on EVT outcome with core size (p=0.037) Fig B.
Conclusion:
IV tPA did not result in thrombectomy delivery delays and may result in better outcomes. Patients with less severe strokes and smaller infarct size had a stronger association between the use of IV tPA and favorable outcomes.
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Affiliation(s)
- Amrou Sarraj
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | | | | | - Clark Sitton
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | - Peng R Chen
- Neurosurgery, McGovern Med Sch at UTHealth, Houston, TX
| | - Chunyan Cai
- Biostatistics, McGovern Med Sch at UTHealth, Houston, TX
| | - Deep Pujara
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Sujan Reddy
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Nirav Vora
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | | | | | - Haris Kamal
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Bita Imam
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Faris Shaker
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Rishi Gupta
- Neurology, WellStar Health System, Marrietta, GA
| | | | - William J Hicks
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | | | | | - Roy F Riascos
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | - Ameer Hassan
- Neurology, Univ of Texas Rio Grande Valley, Harlingen, TX
| | - Sean I Savitz
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
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Sarraj A, Chen PR, Hassan A, Grotta JC, Sitton C, Abraham M, Vora N, Blackburn S, Cai C, Pujara D, Reddy S, Parsha K, Imam B, Shaker F, Kamal H, Gupta R, Martin-Schild S, Hicks WJ, Arora A, Haussen D, Barreto AD, Riascos RF, Lansberg M, Savitz SI, Albers GW. Abstract TMP12: The Effect of Anesthesia Type on Endovascular Thrombectomy Outcomes is Modified by Stroke Size: A Secondary Analysis From the SELECT Study. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.tmp12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
The effect of anesthesia choice on endovascular thrombectomy (EVT) outcomes is unclear.
Methods:
In the prospective multicenter cohort study of imaging selection for EVT (SELECT), patients were stratified based on their anesthesia type into general anesthesia (GA) and conscious sedation (CS). EVT times and outcomes were compared. Further we assessed the impact of ischemic core size (rCBF<30%) on the correlation between anesthesia type and EVT outcomes.
Results:
Of 361 enrolled, 285 received EVT. 129 (45%%) received GA and 156 (54%) CS. The baseline characteristics were similar, except for presentation NIHSS (GA 17(13-21), CS 15(11-20), p=0.027) and ischemic core volume (GA 14.1 cc (0-38) vs CS 6.3(0-26.1), p=0.034). GA was associated with numerically longer arrival to GP times 92 (68—115) vs. 85(60-117) mins, p=0.58. After adjustment for baseline imbalances, patients who received CS had a shift toward better outcome (adj cOR 1.72, 95% CI=1.08-2.75, p=0.022) with higher functional independence rates 56.8% vs 48.8%, p=0.75. Furthermore, GA was associated with higher mortality rates (19% vs 9%, p=0.017), figure 1A.
In patients with core volume ≥ 50 cc, there was a trend for a shift towards better outcomes (adj cOR=5.84, 95%CI= 0.90-38.00, P=0.065), figure 1B while there was no difference in patients with core volume < 50 cc (adj cOR=1.01 (95%CI 0.53-1.94, P=0.96), figure 1C. There was an interaction between core volume size and anesthesia type on functional outcome (p=0.042). For every 10cc increase in the core volume, the odds of attaining better functional outcome decreased by 29% (adjusted cOR: 0.71, 95% CI=0.61-0.83, p<0.001) with GA as compared to only 16% (adjusted cOR: 0.84, 95% CI=0.73-0.96, p=0.01) with CS.
Conclusion:
Conscious sedation was associated with a shift towards better EVT outcomes. This effect was driven by patients with larger ischemic core volumes and has implications for randomized trials of conscious sedation vs general anesthesia.
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Affiliation(s)
- Amrou Sarraj
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Peng R Chen
- Neurosurgery, McGovern Med Sch at UTHealth, Houston, TX
| | - Ameer Hassan
- Neurology, Univ of Texas Rio Grande Valley, Harlingen, TX
| | | | - Clark Sitton
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Nirav Vora
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | | | - Chunyan Cai
- Biostatistics, McGovern Med Sch at UTHealth, Houston, TX
| | - Deep Pujara
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Sujan Reddy
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Bita Imam
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Faris Shaker
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Haris Kamal
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
| | - Rishi Gupta
- Neurology, WellStar Health System, Marrietta, GA
| | | | - William J Hicks
- Neurology, OhioHealth - Riverside Methodist Hosp, Columbus, OH
| | | | | | | | - Roy F Riascos
- Neuroradiology, McGovern Med Sch at UTHealth, Houston, TX
| | | | - Sean I Savitz
- Neurology, McGovern Med Sch at UTHealth, Houston, TX
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Cereda CW, Mlynash M, Heit J, Kemp S, Cippà P, Marks MP, Lansberg M, Albers GW. Abstract WP87: Renal Safety of Multimodal Brain Imaging Followed by Endovascular Therapy. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp87] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
Contrast-enhanced non-invasive angiography and perfusion imaging are recommended to identify eligible patients for endovascular therapy (EVT) in extended time windows (>6h or wake-up). If eligible, additional IA contrast exposure will occur during EVT. In this emergency setting, where the use of IV contrast often occurs prior to laboratory confirmation of renal function, renal safety concerns have been raised.
Hypothesis:
We hypothesized that in the DEFUSE 3 study population, patients who received additional IA contrast during EVT would not have evidence of acute contrast-associated kidney injury compared with the medical control group and that there would also be no differences in renal function between the CT perfusion and MR perfusion selected patients.
Methods:
In the randomized DEFUSE 3 trial population
,
we compared changes in serum creatinine between baseline (prior to randomization to EVT vs medial therapy) and 24 hours later. The primary outcome was the relative change in creatinine level between baseline and 24 hours in the EVT vs. medical arm. The secondary outcome was a comparison between CT vs. MRI selection in the EVT arm.
Results:
In the DEFUSE 3 population (n=182, age 69±13, 51% female), mean creatinine decreased from a baseline of 0.98±0.33 mg/dL to 0.88±0.28 mg/dL at 24 hours (p<0.001). There was no difference in change between treatment groups: absolute decrease -0.08±0.18 in EVT vs. -0.12±0.18 in medical, p=0.135; relative to baseline there was a 6.3% reduction in the EVT group vs. 9.2% in medical, p=0.294. Among patients treated with EVT, there was no difference in 24-hour creatinine level changes between patients who were selected with CTA/CTP (-0.08±0.18) vs. MRI (-0.07 ±0.19), p=0.808; or 6.8% reduction vs. 4.8%, p=0.700. The maximum increase in Cr in an EVT treated patient was 0.42 mg/dL in the CT group and 0.58 mg/dL in the MRI group.
Conclusions:
Perfusion imaging prior to EVT was not associated with evidence any decline in renal function.
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Affiliation(s)
| | | | | | | | - Pietro Cippà
- Servizio di Nefrologia, Ospedale Civico, Lugano, Switzerland
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35
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McCullough-Hicks ME, Christensen S, Srivatsan A, Albers GW, Lansberg M. Abstract WP83: Validation of a Relative Non-Contrast CT Map to Detect Early Ischemic Changes in Acute Stroke. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp83] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Discerning signs of early infarct on the non-contrast CT (NCCT) can be difficult. To facilitate interpretation of the NCCT we previously developed a technique to generate symmetry ratio maps of the NCCT (rNCCT maps) on which subtle (≥5%) differences in density between symmetric brain regions are enhanced. We sought to validate the rNCCT map against other measures of early infarction in a large cohort.
Methods:
rNCCT maps were generated for 146 ischemic stroke patients. We assessed how often a neurologist’s interpretation of the NCCT was changed when provided with the rNCCT map. The neurologist was blinded to CTP and DWI but was given the infarct hemisphere. In addition, using the 24-hour DWI as the gold standard, we assessed the sensitivity, specificity and volumetric accuracy of the rNCCT-defined infarct core and compared this to the test characteristics of CTP-defined infarct core (CBF<38% threshold).
Results:
Addition of rNCCT overlay map changed clinician’s initial read 64.4% of the time (95% CI 56-72%); the rNCCT identified new areas of ischemia not appreciated on blinded review 86.2% of the time (95% CI 78-92%) and in 35.1% helped rule out early ischemia where the reader was unsure of its presence (95% CI 26-45%). In the 53 patients with reperfusion and follow-up MRI, specificity of rNCCT for final lesion volume was 99.5% for rNCCT [98.5-99.8%] vs. 99.8% [IQR 98.8-99.9%] for CTP (P=0.08). Sensitivity for rNCCT was 19.9% [7.1-28.1%] vs. 17.5% [4.7-32.2%] for CTP (P=0.56).
Conclusions:
This study validates the rNCCT map for detection of early ischemic changes. It is more quantitative and objective than a clinician’s read of the NCCT alone. The sensitivity and specificity for detecting early ischemic changes on rNCCT were comparable to those achieved with CTP. This indicates that the rNCCT could be a valuable tool in the evaluation of acute stroke patients.
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Eakin M, Gian A, Kim F, Muccini J, Lansberg M, Flavin K. Abstract WP185: How to Design Woke Stroke Tech: The STORIES Project. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
There is little foundational evidence describing needs, wants, and concerns of stroke survivors and their carers regarding stroke rehabilitation technology. The aim of the STORIES Project (Stroke Tech- Overviews in Rehabilitation, Insights, and Experiences of Survivors & carers) was to identify, characterize, and prioritize these needs and concerns, as well as differences in characterizations across subgroups, to inform socially inclusive design.
Methods:
Mixed-method, semi-structured interviews were conducted with 29 stroke survivors and 16 carers, including 12 matched patient-carer dyads. Participants used a 1-5 scale to rate confidence and interest in using technologies for stroke rehabilitation and to rate the importance of 41 aspects of rehabilitation technology use. Differences between subgroups were compared via student t-tests. Qualitative data was coded to add depth of understanding to quantitative results.
Results:
Across all participants, aspects rated most important were clear instructions, ability to return a product from home, ease of use, ability to see progress over time, and that technology use did not replace time with a therapist. Human interaction in rehabilitation was deeply important for motivation, effectiveness, and mental health. Compared to carers, patients found the following less important: training carers in rehabilitation technology use (
p
=.006), ability to share progress (
p
=.001), and ability to do exercises with therapists rather than carers (
p
=.001). Non-whites more strongly valued including music in the rehabilitation technology experience (
p
=.001). Medicaid beneficiaries cared more about time & financial risk-minimization strategies (
p
<.000), but not direct cost (
p
=.72). People without a Bachelor’s degree had less technology familiarity and interest (
p
=.003). Finally, patients and carers of patients less than 12 months post-stroke were less interested in stroke rehabilitation technologies (
p
<.000).
Conclusion:
To increase adoption of stroke rehabilitation technologies, development should focus on improving multiple parts of the product experience, including clear instructions, ease of use, progress tracking, music inclusion, free trials, and free returns from home.
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MacLellan A, Mlynash M, Kemp S, Christensen S, Marks M, Lansberg M, Albers G. Abstract TP91: Unfavorable Baseline Hypoperfusion Intensity Ratio is Associated With Infarct Growth and Poor Outcome in Patients With Distal MCA Occlusions. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.tp91] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
A low hypoperfusion intensity ratio (HIR) predicts good collateral vessel status and correlates with infarct growth and functional outcome in early window patients with proximal large vessel anterior circulation occlusions. Its performance in predicting clinical and radiologic outcome has not been assessed in patients with more distal occlusions. In this retrospective analysis of the CT Perfusion to Predict Response to Recanalization in Ischemic Stroke (CRISP) study, we hypothesized that a favorable baseline HIR would predict less infarct growth in patients with distal middle cerebral artery (MCA) occlusions.
Methodology:
Patients with occlusions of an M2 or M3 branch of the MCA on catheter angiography were included; all patients underwent mechanical thrombectomy with TICI2B/3 reperfusion. Baseline ischemic core volume and HIR (Tmax >10s / Tmax >6s) were assessed with RAPID software; late follow-up infarct volumes (>36 hours from initial CT perfusion) were manually determined from DWI MRI. Excellent functional outcome was defined as a modified Rankin score of 0-1.
Results:
Fourteen patients with baseline perfusion and late follow-up imaging were included; nine patients presented with M2 occlusions, and 5 with M3 occlusions. The mean baseline HIR of 0.48 was used to dichotomize patients into favorable or unfavorable baseline profiles. Patients with a favorable baseline HIR had significantly smaller baseline ischemic core volumes (0 mL [IQR 0-3.3] vs. 14.0 mL [IQR 8.7-22.1], p=0.01), smaller final infarct volumes (16.1 mL [IQR 12.7-41.2] vs. 71.4 mL [IQR 43.8-113.5], p=0.01) and less infarct growth (16.1 mL [IQR 9.4-31.9] vs. 49.0 mL [IQR 31.1-100.8], p=0.03). Excellent functional outcome was achieved in 6/6 (100%) of those with favorable baseline HIR, versus 3/8 (37.5%) with unfavorable baseline profile (p=0.03).
Conclusion:
In patients with distal MCA occlusions, poor collateral status at baseline as demonstrated by a high HIR score is associated with more infarct growth and worse clinical outcomes. HIR may be helpful for guiding thrombectomy decisions in patients with distal occlusions and warrants further prospective study in this population.
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Federau C, Christensen S, Scherrer N, Schulze V, Ospel J, Maclaren J, Lansberg M, Sebastian K. Abstract WMP22: Synthetic Image Based Deep Learning of Stroke DWI Lesion Segmentation. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wmp22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
The application of deep learning to stroke image analysis (and medical images in general) faces two major challenges: first, it requires a large number of images to train, which is difficult to obtain. Second, the accurate outlining of infarcts is tedious, requires a high level of expertise, is subjective and error prone. The purpose of this work was to produce a large set of diffusion-weighted images (DWI) with perfectly defined realistic-appearing synthetic acute stroke lesions and to compare the segmentation performance of a deep neural network trained on these DWI scans with synthetic stroke lesions to a network trained on DWI scans of real stroke patients with stroke lesions manually outlined by neuroradiologists.
Methods:
449 DWI scans with stroke lesions (72 ± 14y) and 2027 normal DWI scans (38 ± 24y) were coregistered, resampled, cropped to 96 x 80 x 40 voxels, normalized and divided into training/testing sets (80/20%). Stroke lesions were manually segmented by 3 neuroradiologists. 2000 synthetic 3D stroke DWI were produced by fusing thresholded (min 8%) signal increase of random DWI lesions to random coregistered normal DWI (
A
). A 3D U-Net (Tensorflow, depth 3, initial 64 feature maps doubled with each downsampling, bottleneck 3; hyperparameters optimized with cross-validation) was trained separately on 3 datasets: human-labeled real stroke cases (HL); 2000 synthetic cases (S); human-labeled real stroke cases + 2000 synthetic cases (HL+S).
Results:
The model trained on the human-labeled real stroke cases + 2000 synthetic cases (average dice coefficient between 300 and 600 epochs= 0.66±0.14) significantly outperformed the model trained on the 2000 synthetic cases only (0.60±0.14) and the model trained on human-labeled real stroke cases only (0.55±0.18; p<10
-29
for all comparisons) (
B-C
).
Conclusions:
Deep learning segmentation of acute stroke lesions was significantly improved and was more stable by using synthetically generated images.
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39
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Sarraj A, Hassan AE, Grotta J, Sitton C, Cutter G, Cai C, Chen PR, Imam B, Pujara D, Arora A, Reddy S, Parsha K, Riascos RF, Vora N, Abraham M, Edgell R, Hellinger F, Haussen DC, Blackburn S, Kamal H, Barreto AD, Martin-Schild S, Lansberg M, Gupta R, Savitz S, Albers GW. Optimizing Patient Selection for Endovascular Treatment in Acute Ischemic Stroke (SELECT): A Prospective, Multicenter Cohort Study of Imaging Selection. Ann Neurol 2020; 87:419-433. [PMID: 31916270 DOI: 10.1002/ana.25669] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 01/03/2020] [Accepted: 01/06/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The primary imaging modalities used to select patients for endovascular thrombectomy (EVT) are noncontrast computed tomography (CT) and CT perfusion (CTP). However, their relative utility is uncertain. We prospectively assessed CT and CTP concordance/discordance and correlated the imaging profiles on both with EVT treatment decisions and clinical outcomes. METHODS A phase 2, multicenter, prospective cohort study of large-vessel occlusions presented up to 24 hours from last known well was conducted. Patients received a unified prespecified imaging evaluation (CT, CT angiography, and CTP with Rapid Processing of Perfusion and Diffusion software mismatch determination). The treatment decision, EVT versus medical management, was nonrandomized and at the treating physicians' discretion. An independent, blinded, neuroimaging core laboratory adjudicated favorable profiles based on predefined criteria (CT:Alberta Stroke Program Early CT Score ≥ 6, CTP:regional cerebral blood flow (<30%) < 70ml with mismatch ratio ≥ 1.2 and mismatch volume ≥ 10ml). RESULTS Of 4,722 patients screened from January 2016 to February 2018, 361 patients were included. Two hundred eighty-five (79%) received EVT, of whom 87.0% had favorable CTs, 91% favorable CTPs, 81% both favorable profiles, 16% discordant, and 3% both unfavorable. Favorable profiles on the 2 modalities correlated similarly with 90-day functional independence rates (favorable CT = 56% vs favorable CTP = 57%, adjusted odds ratio [aOR] = 1.91, 95% confidence interval [CI] = 0.40-9.01, p = 0.41). Having a favorable profile on both modalities significantly increased the odds of receiving thrombectomy as compared to discordant profiles (aOR = 3.97, 95% CI = 1.97-8.01, p < 0.001). Fifty-eight percent of the patients with favorable profiles on both modalities achieved functional independence as compared to 38% in discordant profiles and 0% when both were unfavorable (p < 0.001 for trend). In favorable CT/unfavorable CTP profiles, EVT was associated with high symptomatic intracranial hemorrhage (sICH) (24%) and mortality (53%) rates. INTERPRETATION Patients with favorable imaging profiles on both modalities had higher odds of receiving EVT and high functional independence rates. Patients with discordant profiles achieved reasonable functional independence rates, but those with an unfavorable CTP had higher adverse outcomes. Ann Neurol 2020;87:419-433.
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Affiliation(s)
- Amrou Sarraj
- Department of Neurology, University of Texas at Houston, Houston, TX
| | - Ameer E Hassan
- Department of Neurology, University of Texas Rio Grande Valley, Harlingen, TX
| | - James Grotta
- Department of Neurology, University of Texas at Houston, Houston, TX
| | - Clark Sitton
- Department of Radiology, University of Texas at Houston, Houston, TX
| | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - Chunyan Cai
- Department of Clinical and Translational Science, University of Texas at Houston, Houston, TX
| | - Peng R Chen
- Department of Neurosurgery, University of Texas at Houston, Houston, TX
| | - Bita Imam
- Department of Neurology, University of Texas at Houston, Houston, TX
| | - Deep Pujara
- Department of Neurology, University of Texas at Houston, Houston, TX
| | | | - Sujan Reddy
- Department of Neurology, University of Texas at Houston, Houston, TX
| | - Kaushik Parsha
- Department of Neurology, University of Texas at Houston, Houston, TX
| | - Roy F Riascos
- Department of Radiology, University of Texas at Houston, Houston, TX
| | - Nirav Vora
- Department of Neurology, OhioHealth-Riverside Methodist Hospital, Columbus, OH
| | - Michael Abraham
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS
| | - Randall Edgell
- Department of Neurology, Saint Louis University, St. Louis, MO
| | | | | | - Spiros Blackburn
- Department of Neurosurgery, University of Texas at Houston, Houston, TX
| | - Haris Kamal
- Department of Neurology, University of Texas at Houston, Houston, TX
| | - Andrew D Barreto
- Department of Neurology, University of Texas at Houston, Houston, TX
| | - Sheryl Martin-Schild
- Department of Neurology, Touro Infirmary and New Orleans East Hospital, New Orleans, LA
| | | | - Rishi Gupta
- Department of Neurology, WellStar Health System, Atlanta, GA
| | - Sean Savitz
- Department of Neurology, University of Texas at Houston, Houston, TX
| | | |
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40
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Sarraj A, Hassan AE, Savitz S, Sitton C, Grotta J, Chen P, Cai C, Cutter G, Imam B, Reddy S, Parsha K, Pujara D, Riascos R, Vora N, Abraham M, Kamal H, Haussen DC, Barreto AD, Lansberg M, Gupta R, Albers GW. Outcomes of Endovascular Thrombectomy vs Medical Management Alone in Patients With Large Ischemic Cores: A Secondary Analysis of the Optimizing Patient's Selection for Endovascular Treatment in Acute Ischemic Stroke (SELECT) Study. JAMA Neurol 2019; 76:1147-1156. [PMID: 31355873 DOI: 10.1001/jamaneurol.2019.2109] [Citation(s) in RCA: 109] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Importance The efficacy and safety of endovascular thrombectomy (EVT) in patients with large ischemic cores remains unknown, to our knowledge. Objective To compare outcomes in patients with large ischemic cores treated with EVT and medical management vs medical management alone. Design, Setting, and Participants This prespecified analysis of the Optimizing Patient's Selection for Endovascular Treatment in Acute Ischemic Stroke (SELECT) trial, a prospective cohort study of imaging selection that was conducted in 9 US comprehensive stroke centers, enrolled patients between January 2016 and February 2018, and followed them up for 90 days. Patients with moderate to severe stroke and anterior circulation large-vessel occlusion presenting up to 24 hours from the time they were last known to be well were eligible for the cohort. Of these, patients with large ischemic cores on computed tomography (CT) (Alberta Stroke Program Early CT Score <6) or CT perfusion scanning (a volume with a relative cerebral blood flow <30% of ≥50 cm3) were included in analyses. Exposures Endovascular thrombectomy with medical management (MM) or MM only. Main Outcomes and Measures Functional outcomes at 90 days per modified Rankin scale; safety outcomes (mortality, symptomatic intracerebral hemorrhage, and neurological worsening). Results A total of 105 patients with large ischemic cores on either CT or CT perfusion images were included: 71 with Alberta Stroke Program Early CT Scores of 5 or less (EVT, 37; MM, 34), 74 with cores of 50 cm3 or greater on CT perfusion images (EVT, 39; MM, 35), and 40 who had large cores on both CT and CT perfusion images (EVT, 14; MM, 26). The median (interquartile range) age was 66 (60-75) years; 45 patients (43%) were female. Nineteen of 62 patients (31%) who were treated with EVT achieved functional independence (modified Rankin Scale scores, 0-2) vs 6 of 43 patients (14%) treated with MM only (odds ratio [OR], 3.27 [95% CI, 1.11-9.62]; P = .03). Also, EVT was associated with better functional outcomes (common OR, 2.12 [95% CI, 1.05-4.31]; P = .04), less infarct growth (44 vs 98 mL; P = .006), and smaller final infarct volume (97 vs 190 mL; P = .001) than MM. In the odds of functional independence, there was a 42% reduction per 10-cm3 increase in core volume (adjusted OR, 0.58 [95% CI, 0.39-0.87]; P = .007) and a 40% reduction per hour of treatment delay (adjusted OR, 0.60 [95% CI, 0.36-0.99]; P = .045). Of 10 patients who had EVT with core volumes greater than 100 cm3, none had a favorable outcome. Conclusions and Relevance Although the odds of good outcomes for patients with large cores who receive EVT markedly decline with increasing core size and time to treatment, these data suggest potential benefits. Randomized clinical trials are needed.
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Affiliation(s)
- Amrou Sarraj
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Ameer E Hassan
- Department of Neurology, University of Texas Rio Grande Valley, Harlingen.,Department of Neurology, University of Texas Health Science Center, Neurology, San Antonio.,Department of Radiology, University of Texas Health Science Center, San Antonio
| | - Sean Savitz
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Clark Sitton
- Department of Radiology, University of Texas McGovern Medical School, Houston
| | - James Grotta
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Peng Chen
- Department of Neurosurgery, University of Texas McGovern Medical School, Houston
| | - Chunyan Cai
- Clinical and Translational Science, University of Texas McGovern Medical School, Houston
| | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham
| | - Bita Imam
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Sujan Reddy
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Kaushik Parsha
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Deep Pujara
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Roy Riascos
- Department of Radiology, University of Texas McGovern Medical School, Houston
| | - Nirav Vora
- Department of Neurology, OhioHealth-Riverside Methodist Hospital, Columbus
| | - Michael Abraham
- Department of Neurology, University of Kansas Medical Center, Kansas City
| | - Haris Kamal
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | | | - Andrew D Barreto
- Department of Neurology, University of Texas McGovern Medical School, Houston
| | - Maarten Lansberg
- Department of Neurology, Stanford University, Stanford, California
| | - Rishi Gupta
- Department of Neurology, Wellstar Health System, Atlanta, Georgia
| | - Gregory W Albers
- Department of Neurology, Stanford University, Stanford, California
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41
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Demeestere J, Scheldeman L, Cornelissen SA, Heye S, Wouters A, Dupont P, Christensen S, Mlynash M, Albers GW, Lansberg M, Lemmens R. Alberta Stroke Program Early CT Score Versus Computed Tomographic Perfusion to Predict Functional Outcome After Successful Reperfusion in Acute Ischemic Stroke. Stroke 2019; 49:2361-2367. [PMID: 30355098 DOI: 10.1161/strokeaha.118.021961] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose- We aimed to compare the ability of conventional Alberta Stroke Program Early CT Score (ASPECTS), automated ASPECTS, and ischemic core volume on computed tomographic perfusion to predict clinical outcome in ischemic stroke because of large vessel occlusion ≤18 hours after symptom onset. Methods- We selected patients with acute ischemic stroke from the CRISP study (Computed Tomographic Perfusion to Predict Response to Recanalization in Ischemic Stroke Project) with successful reperfusion (modified treatment in cerebral ischemia score 2b or 3). We used e-ASPECTS software to calculate automated ASPECTS and RAPID software to estimate ischemic core volumes. We studied associations between these imaging characteristics and good outcome (modified Rankin Scale score, 0-2) or poor outcome (modified Rankin Scale score, 4-6) in univariable and multivariable analysis, after adjustment for relevant clinical confounders. Results- We included 156 patients. Conventional and automated ASPECTS was not associated with good or poor outcome in univariable analysis ( P=nonsignificant for all). Automated ASPECTS was associated with good outcome in multivariable analysis ( P=0.02) but not with poor outcome. Ischemic core volume was associated with good ( P<0.01) and poor outcome ( P=0.04) in univariable and multivariable analysis ( P=0.03 and P=0.02, respectively). Computed tomographic perfusion predicted good outcome with an area under the curve of 0.62 (95% CI, 0.53-0.71) and optimal cutoff core volume of 15 mL. Conclusions- Ischemic core volume assessed on computed tomographic perfusion is a predictor of clinical outcome among patients in whom endovascular reperfusion is achieved ≤18 hours after symptom onset. In this population, conventional or automated ASPECTS did not predict outcome.
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Affiliation(s)
- Jelle Demeestere
- From the Division of Experimental Neurology, Department of Neurosciences (J.D., A.W., R.L.), Catholic University (KU) Leuven-University of Leuven, Belgium.,Flemish Institute for Biotechnology (VIB), Center for Brain and Disease Research, Laboratory of Neurobiology, Leuven, Belgium (J.D., A.W., R.L.).,Department of Neurology (J.D., L.S., A.W., R.L.), University Hospitals Leuven, Belgium
| | - Lauranne Scheldeman
- Department of Neurology (J.D., L.S., A.W., R.L.), University Hospitals Leuven, Belgium
| | | | - Sam Heye
- Department of Radiology, Jessa Hospital, Hasselt, Belgium (S.H.)
| | - Anke Wouters
- From the Division of Experimental Neurology, Department of Neurosciences (J.D., A.W., R.L.), Catholic University (KU) Leuven-University of Leuven, Belgium.,Flemish Institute for Biotechnology (VIB), Center for Brain and Disease Research, Laboratory of Neurobiology, Leuven, Belgium (J.D., A.W., R.L.).,Department of Neurology (J.D., L.S., A.W., R.L.), University Hospitals Leuven, Belgium
| | - Patrick Dupont
- Department of Neurosciences, Laboratory for Cognitive Neurology (P.D.), Catholic University (KU) Leuven-University of Leuven, Belgium
| | - Sören Christensen
- Stanford University and Stanford Stroke Center, Palo Alto, CA (S.C., M.M., G.W.A., M.L.)
| | - Michael Mlynash
- Stanford University and Stanford Stroke Center, Palo Alto, CA (S.C., M.M., G.W.A., M.L.)
| | - Gregory W Albers
- Stanford University and Stanford Stroke Center, Palo Alto, CA (S.C., M.M., G.W.A., M.L.)
| | - Maarten Lansberg
- Stanford University and Stanford Stroke Center, Palo Alto, CA (S.C., M.M., G.W.A., M.L.)
| | - Robin Lemmens
- From the Division of Experimental Neurology, Department of Neurosciences (J.D., A.W., R.L.), Catholic University (KU) Leuven-University of Leuven, Belgium.,Flemish Institute for Biotechnology (VIB), Center for Brain and Disease Research, Laboratory of Neurobiology, Leuven, Belgium (J.D., A.W., R.L.).,Department of Neurology (J.D., L.S., A.W., R.L.), University Hospitals Leuven, Belgium
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Sussman ES, Martin B, Mlynash M, Marks MP, Marcellus D, Albers G, Lansberg M, Dodd R, Do HM, Heit JJ. Thrombectomy for acute ischemic stroke in nonagenarians compared with octogenarians. J Neurointerv Surg 2019; 12:266-270. [DOI: 10.1136/neurintsurg-2019-015147] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 07/05/2019] [Accepted: 07/10/2019] [Indexed: 01/19/2023]
Abstract
IntroductionMultiple randomized trials have shown that endovascular thrombectomy (EVT) leads to improved outcomes in acute ischemic stroke (AIS) due to large vessel occlusion (LVO). Elderly patients were poorly represented in these trials, and the efficacy of EVT in nonagenarian patients remains uncertain.MethodsWe performed a retrospective cohort study at a single center. Inclusion criteria were: age 80–99, LVO, core infarct <70 mL, and salvageable penumbra. Patients were stratified into octogenarian (80–89) and nonagenarian (90–99) cohorts. The primary outcome was the ordinal score on the modified Rankin Scale (mRS) at 90 days. Secondary outcomes included dichotomized functional outcome (mRS ≤2 vs mRS ≥3), successful revascularization, symptomatic intracranial hemorrhage (ICH), and mortality.Results108 patients met the inclusion criteria, including 79 octogenarians (73%) and 29 nonagenarians (27%). Nonagenarians were more likely to be female (86% vs 58%; p<0.01); there were no other differences between groups in terms of demographics, medical comorbidities, or treatment characteristics. Successful revascularization (TICI 2b–3) was achieved in 79% in both cohorts. Median mRS at 90 days was 5 in octogenarians and 6 in nonagenarians (p=0.09). Functional independence (mRS ≤2) at 90 days was achieved in 12.5% and 19.7% of nonagenarians and octogenarians, respectively (p=0.54). Symptomatic ICH occurred in 21.4% and 6.4% (p=0.03), and 90-day mortality rate was 63% and 40.9% (p=0.07) in nonagenarians and octogenarians, respectively.ConclusionsNonagenarians may be at higher risk of symptomatic ICH than octogenarians, despite similar stroke- and treatment-related factors. While there was a trend towards higher mortality and worse functional outcomes in nonagenarians, the difference was not statistically significant in this relatively small retrospective study.
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Wouters A, Dupont P, Christensen S, Norrving B, Laage R, Thomalla G, Kemp S, Lansberg M, Thijs V, Albers GW, Lemmens R. Multimodal magnetic resonance imaging to identify stroke onset within 6 h in patients with large vessel occlusions. Eur Stroke J 2019; 3:185-192. [PMID: 31008349 DOI: 10.1177/2396987317753486] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 12/05/2017] [Indexed: 11/17/2022] Open
Abstract
Introduction Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. Patients and methods A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. Results We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with <6 h time-window and included in the model: interquartile range and median relative diffusion weighted imaging, hypoperfusion intensity ratio, core volume and the interaction between median relative diffusion weighted imaging and hypoperfusion intensity ratio as predictors of the 6 h time-window. The area under the curve was 0.80 with a positive predictive value of 0.90 (95%CI 0.79-0.96). In the validation cohort (N = 90), the area under the curve was 0.73 (P for difference = 0.4) with a positive predictive value of 0.85 (95%CI 0.69-0.95). Discussion After validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown. Conclusion In patients with large vessel occlusion and unknown time of stroke onset an automated multivariate imaging model is able to select patients who are likely within the 6 h time-window.
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Affiliation(s)
- Anke Wouters
- Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND), KU Leuven - University of Leuven, Leuven, Belgium.,Center for Brain & Disease Research, Laboratory of Neurobiology, VIB, Leuven, Belgium.,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Patrick Dupont
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Soren Christensen
- Stanford Stroke Center, Stanford University Medical Center, Palo Alto, USA
| | - Bo Norrving
- Department of Clinical Sciences, Section of Neurology, Lund University, Lund, Sweden
| | - Rico Laage
- Guided Development GmbH, Heidelberg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stephanie Kemp
- Stanford Stroke Center, Stanford University Medical Center, Palo Alto, USA
| | - Maarten Lansberg
- Stanford Stroke Center, Stanford University Medical Center, Palo Alto, USA
| | - Vincent Thijs
- 9Florey Institute of Neuroscience and Mental Health, Heidelberg, Australia
| | - Gregory W Albers
- Stanford Stroke Center, Stanford University Medical Center, Palo Alto, USA
| | - Robin Lemmens
- Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND), KU Leuven - University of Leuven, Leuven, Belgium.,Center for Brain & Disease Research, Laboratory of Neurobiology, VIB, Leuven, Belgium.,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
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Sarraj A, Hassan A, Grotta J, Sitton C, Chen PR, Cai C, Cutter G, Pujara D, Imam B, Reddy S, Kamal H, Abraham M, McCullough L, Lansberg M, Savitz S, Albers G, Gupta R. Abstract WP75: Ischemic Core Volume Modifies the Association Between ASPECT Score and Clinical Outcome. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.wp75] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
While CT ASPECT scores predict clinical outcomes, the association between the scores and ischemic lesion volume is not linear as the subcortical regions involve small volumes while the cortical areas often involve large volumes. We evaluated whether ASPECTS and CTP ischemic core volume, modify each other’s association with clinical outcome in patients undergoing endovascular thrombectomy (EVT).
Methods:
In a prospective multicenter cohort study of imaging selection (SELECT), anterior circulation large vessel occlusion patients up to 24 hours from last known well were enrolled at 9 centers. All patients received a unified imaging profile (NCCT, CTA, and CTP with ischemic core volume [rCBF <30%] by RAPID software). A blinded core lab adjudicated all images.
Results:
Of 445 enrolled, 284 received EVT and are included in this analysis. Median (IQR) ASPECTS was 8 (7-9), median (IQR) ischemic core volume 10 ml (0-33). Both ASPECTS and ischemic core volume independently correlated with good outcome after EVT. For ASPECTS, the probability of good outcome decreased by 14% per point (aOR 1.18, 95% CI 1.01-1.38, p=0.03). For CTP mRS 0-2 probability dropped by 25% for each 10 ml increase in core volume (aOR 0.75, 95% CI 0.67-0.84, P<0.001). The correlation between ASPECTS and good outcome was substantially altered when adjusted for ischemic core size (fig 1). Outcomes were poor irrespective of ASPECTS in patients with large core lesions while outcomes were generally favorable in patients with a small ischemic core, even with lower ASPECTS. In contrast, the relationship between CTP ischemic core and favorable outcome was not altered when adjusted for ASPECTS (pre-ASPECTS aOR: 0.75 (0.67-0.84), p<0.001 vs post-ASPECTS aOR: 0.75 (0.67-0.85), p<0.001) (fig 2).
Conclusion:
ASPECTS association with clinical outcome after EVT was strongly modified by ischemic core volumes. Favorable outcomes were achieved in patients with small ischemic core volume despite low ASPECTS.
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Affiliation(s)
| | - Ameer Hassan
- Univ of Texas - Rio Grande Valley, Harlingen, TX
| | | | | | - Peng R Chen
- UT Health Science Cntr at Houston, Houston, TX
| | - Chunyan Cai
- UT Health Science Cntr at Houston, Houston, TX
| | - Gary Cutter
- Univ of Alabama at Birmingham, Birmingham, AL
| | - Deep Pujara
- UT Health Science Cntr at Houston, Houston, TX
| | - Bita Imam
- UT Health Science Cntr at Houston, Houston, TX
| | - Sujan Reddy
- UT Health Science Cntr at Houston, Houston, TX
| | - Haris Kamal
- UT Health Science Cntr at Houston, Houston, TX
| | | | | | | | - Sean Savitz
- UT Health Science Cntr at Houston, Houston, TX
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Sarraj A, Mlynash M, Heit J, Marks M, Lansberg M, Albers G. Abstract 113: Late Window Transfer Patients had Favorable Outcomes Following Thrombectomy in DEFUSE 3. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Although the treatment benefit of endovascular thrombectomy (EVT) was maintained in transfer patients in the early window trials, overall rates of functional independence were lower in both the EVT and control groups among transfer patients. We hypothesized that the imaging-based selection criteria employed in DEFUSE 3 would lead to comparable outcome rates and treatment efficacy in transfer vs. direct admission patients.
Methods:
DEFUSE 3 patients were stratified based on if they presented directly to the study site or were transferred from a primary center. The primary and secondary efficacy and safety outcomes of DEFUSE 3 were compared.
Results:
Of 182 patients randomized, 121 (66%) were transfers and 61 (34%) direct. The 2 groups had similar baseline characteristics, other than transfers had 30 min longer median times from last known well time to arrival at the study site. The primary efficacy outcome (mRS shift at day 90) did not differ in the direct vs. transfer groups, OR 2.9, 95% CI 1.2-7.2, P=0.014 for direct and OR=2.6, 95% CI 1.3-4.8, P=0.009 for transfer (Fig 1). The overall rate of functional independence (mRS 0-2 at day 90) in the EVT group did not differ (44% direct, 45% transfer) nor did the treatment effect: RR 2.0 (0.9-4.4) direct vs. 3.1 (1.6-6.1) for transfer. EVT reperfusion rates were identical (mTICI≥2b 76%) in both groups. The rates of death and SICH did not differ. Transfer patients had more favorable collateral profiles (based on the hypoperfusion intensity ratio) median (IQR) for transfer 0.35 (0.18-0.47) vs. 0.42 (0.25-0.56) for direct, p=0.050.
Conclusions:
In late window patients selected by penumbral mismatch criteria, both the favorable outcome rates and treatment effects did not decline in transfer patients. These results have healthcare implications indicating transferring potential candidates for late window thrombectomy to EVT centers is associated with substantial clinical benefits and should be strongly encouraged.
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Sarraj A, Hassan A, Grotta J, Sitton C, Chen PR, Vora N, Cai C, Cutter G, Pujara D, Imam B, Reddy S, Kamal H, Abraham M, McCullough L, Lansberg M, Savitz S, Gupta R, Albers G. Abstract 4: Endovascular Thrombectomy May Be Safe and Effective in Patients With Large Core Lesions on Either Simple CT or Perfusion Images. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Endovascular thrombectomy (EVT) efficacy and safety is not established in patients with large core. We evaluated the clinical and radiologic outcomes following EVT in acute strokes with large ischemic core lesions defined by CT ASPECTS and/or CTP.
Methods:
From a multicenter prospective cohort study of imaging selection for thrombectomy (SELECT), patients with large ischemic core on CTP (rCBF< 30%) >50 ml and/or ASPECT≤5 up to 24 hrs from last known well were identified at 9 U.S centers. All patients received a baseline CT and CTP with automated ischemic core determination by RAPID. A blinded core lab adjudicated all images. The primary outcome was 90 day mRS 0-2. Safety outcomes were sICH and mortality. Outcomes of EVT patients were compared to those who received medical management (MM) only.
Results:
Of 445 enrolled, 106 had large core on either CT or CTP: 71 ASPECTS≤5 (EVT 37, MM 34) and 75 CTP core >50 ml (EVT 40, MM 35), 40 on both CT and CTP. Median (IQR) age 66 yr, NIHSS 20 (16-23), time to puncture 224 min (range 69-832), ASPECTS 5 (4-6) and CTP core 72 ml (41-96). Baseline characteristics were similar in EVT vs. MM patients in both CT and CTP definition groups. The EVT group had better mRS 0-2 rates as compared to MM (32 % vs 14%), aOR: 2.9 (95% CI: 1.0-7.9, p=0.041) and a favorable mRS shift on ordinal analysis aOR: 2.0 (95% CI 1.0-4.1, p=0.049), smaller final infarct volume 96 (49-196) vs 175 (127-225) ml, p=0.02, and less infarct growth 44 (0.7-107.6) vs 83 (61-133) ml, p=0.03 with similar mortality 29% EVT, 42% MM, p=0.16 and sICH 13% EVT, 7% MM, p=0.3. EVT patients were more likely to achieve mRS 0-2 if treated early (0-6) vs late (>6-24 hrs) for both CTP defined (27% vs 0%) and CT defined large core (44% vs. 18%). The good outcome declined by 20% for each hr of treatment delay (Fig 1).
Conclusion:
EVT may be effective and safe for patients with a large core, especially if treated early. RCTs are needed.
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Affiliation(s)
| | - Ameer Hassan
- Univ of Texas - Rio Grande Valley, Harlingen, TX
| | | | | | - Peng R Chen
- UT Health Science Cntr at Houston, Houston, TX
| | - Nirav Vora
- OhioHeatlh - Riverside Methodist Hosp, Columbus, OH
| | - Chunyan Cai
- UT Health Science Cntr at Houston, Houston, TX
| | - Gary Cutter
- Univ of Alabama at Birmingham Birmingham, Birmingham, AL
| | - Deep Pujara
- UT Health Science Cntr at Houston, Houston, TX
| | - Bita Imam
- UT Health Science Cntr at Houston, Houston, TX
| | - Sujan Reddy
- UT Health Science Cntr at Houston, Houston, TX
| | - Haris Kamal
- UT Health Science Cntr at Houston, Houston, TX
| | | | | | | | - Sean Savitz
- UT Health Science Cntr at Houston, Houston, TX
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de Havenon A, Mlynash M, Kim-Tenser MA, Lansberg M, Leslie-Mazwi T, Christensen S, McTaggart R, Alexander M, Albers G, Broderick J, Marks MP, Heit JJ. Abstract 6: Results From the DEFUSE 3 Trial: Good Leptomeningeal Collaterals Are Associated With Reduced Core Infarct Size but Not Improved Neurologic Outcome. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
The role of collaterals for acute ischemic stroke patients who qualify for endovascular thrombectomy (EVT) in the late therapeutic window (>6 hours from last known normal) remains unknown. We hypothesize that good collaterals on CT angiography (CTA) will moderate neurologic outcome and the effect of EVT.
Methods:
This is a prespecified analysis of DEFUSE 3. The primary outcome is functional independence (modified Rankin scale ≤2). Additional outcomes include baseline infarct volume, change from baseline in the infarct volume at 24 hours, and death at 90 days.
Results:
Of 130 patients, 33 (25%) had poor and 97 (75%) had good collaterals. There was no difference in the rate of functional independence with good versus poor collaterals (30% vs. 39%, p=0.3), but good collaterals were associated with significantly smaller infarct volume and less infarct growth. The difference in the treatment effect of EVT between good versus poor collaterals was not significant (p=0.8). Collateral status did not affect the rate of death [19% vs. 24%, p=0.5].
Conclusion:
In DEFUSE 3 patients, good leptomeningeal collaterals on CTA were not predictive of functional independence or death. These findings introduce the possibility that CTA collaterals may not have a causal relationship with neurologic outcome for anterior circulation large vessel occlusion patients with Target Mismatch in the late window.
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Kleindorfer DO, Moomaw CJ, Mlynash M, Broderick JP, Khatri P, Saver JL, Alwell K, Kemp S, Janis S, Moy C, Woo D, Flaherty ML, Ferioli S, Adeoye O, Kissela BM, Lansberg M, Albers G. Abstract TP60: Comparison of Predicted vs. Actual Enrollment Into the NIH StrokeNet DEFUSE 3 Trial: Effectiveness of a Population-Based Epidemiology Feasibility Assessment in Improving Enrollment Into Clinical Trials. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.tp60] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
The NIH StrokeNet trial network aims to improve recruitment and retention into stroke clinical trials. In addition to StrokeNet infrastructure, a population-based feasibility assessment is performed prior to submission to NIH. We sought to describe the impact of this assessment on the design and recruitment efficiency of the DEFUSE 3 trial, the first trial to be proposed and completed entirely within NIH StrokeNet.
Methods:
We identified all ischemic stroke (IS) cases in the region in 2005 by screening all local hospital ICD-9 codes 430-436 among residents of the Greater Cincinnati/Northern Kentucky (GCNK) region, a biracial population of 1.3 million through chart abstraction and physician review. Initial proposed, and final revised DEFUSE 3 trial entry criteria were analyzed for population-based eligibility.
Results:
DEFUSE 3 is an acute reperfusion ischemic stroke (IS) trial conducted at 38 US centers between 5/16-5/17. Initial inclusion/exclusion criteria proposed by trial PIs predicted that 2.4% (46 of 1843 in 2005) of IS patients would be eligible for DEFUSE-3. After criteria revision, this increased to 4.0% (74/1843). Four exclusion criteria were changed by study PIs after receiving feedback: upper age limit, baseline disability, time since last seen normal, and NIHSS (Table). Overall, 57% (104/182) of enrolled patients qualified via the broadened study entry criteria. In subsequent implementation, the trial randomized 0.47 patients per site per month which was nearly twice the expected enrollment rate.
Conclusion:
Feedback from formal epidemiologic feasibility assessment to trial investigators during multicenter clinical trial design led to a broadening of entry criteria, and more than half of eventually enrolled patients were eligible only because of the expanded criteria. Iterative trialist-epidemiologist interaction is a promising approach to improve multicenter clinical trial planning and efficient study conduct.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Scott Janis
- National Institutes of Health, Washington DC, DC
| | - Claudia Moy
- National Institutes of Health, Washington DC, DC
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50
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Sarraj A, Savitz S, Sitton C, Hassan A, Cai C, Pujara D, Grotta J, Imam B, Chen PR, Cutter G, Reddy S, Kamal H, Abraham M, McCullough L, Lansberg M, Gupta R, Albers G. Abstract 164: Early Infarct Growth Correlates With Both Collateral Status and Clinical Outcomes After Thrombecomy. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
We assessed the correlation between early infarct growth rate (EIGR), collaterals and clinical outcomes following endovascular thrombectomy (EVT).
Methods:
In a prospective multicenter cohort study of imaging selection for EVT (SELECT), consecutive patients with large vessel occlusion (ICA, M1, M2) presenting up to 24 hr from last known well (LKW) were enrolled at 9 centers. CT perfusion was obtained prior to EVT. EIGR was defined as CTP ischemic core volume (rCBF<30%) divided by the time from LKW to baseline CTP. The optimal EIGR cutoff was identified by maximizing the sum of the sensitivity and specificity to predict favorable outcome (90 day mRS 0-2). Slow progressors were defined as having an EIGR below the cutoff. Good collaterals were defined on CTP as a hypoperfusion intensity ratio (HIR) <0.4 and on CTA as collateral score
>
2.
Results:
Of 445 enrolled, 284 received EVT. The optimal EIGR was <10 ml/hr; 199 were slow and 85 fast progressors. Fast progressors had higher median NIHSS (19 vs. 15, P< 0.001), earlier median LKW to puncture 180 vs. 266 min, P< 0.001,. Slow progressors had better collaterals on both CTP and CTAs: HIR aOR 4.97 (2.3-10.7), p<0.001; CTA collaterals 3.02 (1.6-5.7), p=0.001. EIGR was an independent predictor of good outcome after adjusting for age NIHSS, LKW to puncture, mTICI and tPA aOR 0.73 (95% CI 0.61-0.89, p=0.001). Slow progressors were 3.5 times more likely to achieve mRS 0-2 after EVT aOR 3.51 (95% CI 1.8-6.7, p<0.001). Fast progressors had substantially worse clinical outcomes both in early and late time window (Table 1). The odds of good outcome decreased by 14% for each 5 ml/hour increase in EIGR, OR:0.87(0.80-0.94), p<0.001 and the probability of good outcome declined more rapidly in fast progressors (Figure 1).
Conclusion:
The early infarct growth strongly correlates with both collateral status and clinical outcomes after EVT. Fast progressors have a much more rapid decline in favorable outcomes at late treatment times.
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Affiliation(s)
| | - Sean Savitz
- UT Health Science Cntr at Houston, Houston, TX
| | | | - Ameer Hassan
- Univ of Texas - Rio Grande Valley, Harlingen, TX
| | - Chunyan Cai
- UT Health Science Cntr at Houston, Houston, TX
| | - Deep Pujara
- UT Health Science Cntr at Houston, Houston, TX
| | | | - Bita Imam
- UT Health Science Cntr at Houston, Houston, TX
| | - Peng R Chen
- UT Health Science Cntr at Houston, Houston, TX
| | - Gary Cutter
- Univ of Alabama at Birmingham, Birmingham, AL
| | - Sujan Reddy
- UT Health Science Cntr at Houston, Houston, TX
| | - Haris Kamal
- UT Health Science Cntr at Houston, Houston, TX
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