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Lev, Michael

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Lev

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Michael

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Lev, Michael
Author's Publications: search.filters.isAuthorOfPublication.f6dc4cc9-c487-415c-982c-be9bcaa1a35b

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Now showing 1 - 8 of 8
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    Hospital Acquired Pneumonia Is Linked to Right Hemispheric Peri-Insular Stroke
    (Public Library of Science, 2013) Kemmling, André; Lev, Michael; Payabvash, Seyedmehdi; Betensky, Rebecca; Qian, Jing; Masrur, Shihab; Schwamm, Lee
    Purpose Hospital acquired pneumonia (HAP) is a major complication of stroke. We sought to determine associations between infarction of specific brain regions and HAP. Methods: 215 consecutive acute stroke patients with HAP (2003–2009) were carefully matched with 215 non-pneumonia controls by gender, then NIHSS, then age. Admission imaging and binary masks of infarction were registered to MNI-152 space. Regional atlas and voxel-based log-odds were calculated to assess the relationship between infarct location and the likelihood of HAP. An independently validated penalized conditional logistic regression model was used to identify HAP associated imaging regions. Results: The HAP and control patients were well matched by gender (100%), age (95% within 5-years), NIHSS (98% within 1-point), infarct size, dysphagia, and six other clinical variables. Right hemispheric infarcts were more frequent in patients with HAP versus controls (43.3% vs. 34.0%, p = 0.054), whereas left hemispheric infarcts were more frequent in controls (56.7% vs. 44.7%, p = 0.012); there was no significant difference between groups in the rate of brainstem strokes (p = 1.0). Of the 10 most infarcted regions, only right insular cortex volume was different in HAP versus controls (20 vs. 12 ml, p = 0.02). In univariate analyses, the highest log-odds regions for pneumonia were right hemisphere, cerebellum, and brainstem. The best performing multivariate model selected 7 brain regions of infarction and 2 infarct volume-based variables independently associated with HAP. Conclusions: HAP is associated with right hemispheric peri-insular stroke. These associations may be related to autonomic modulation of immune mechanisms, supporting recent hypotheses of stroke mediated immune suppression.
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    Time and Diffusion Lesion Size in Major Anterior Circulation Ischemic Strokes
    (Ovid Technologies (Wolters Kluwer Health), 2014) Hakimelahi, R.; Vachha, Behroze Adi; Copen, William; Papini, G. D. E.; He, J.; Higazi, Mahmoud Mohamad Mounir Ali; Lev, Michael; Schaefer, Pamela; Yoo, Albert J.; Schwamm, Lee; Gonzalez, Ramon
    Background: Major anterior circulation ischemic strokes caused by occlusion of the distal internal carotid artery (ICA) or proximal middle cerebral artery (MCA) or both account for about one-third of ischemic strokes with mostly poor outcomes. These strokes are treatable by IV-tPA and endovascular methods. However, dynamics of infarct growth in these strokes are poorly documented. The purpose was to help understand infarct growth dynamics by measuring acute infarct size with DWI at known times after stroke onset in patients with documented ICA/MCA occlusions. Methods: Retrospectively, we included 47 consecutive patients with documented ICA/MCA occlusions who underwent DWI within 30h of stroke onset. Prospectively, 139 patients were identified using the same inclusion criteria. DWI lesion volumes were measured and correlated to time since stroke onset. Perfusion data was reviewed in those who underwent perfusion imaging. Results: Acute infarct volumes ranged from 0.41-318.3ml. Infarct size and time did not correlate (R2=0.001). The majority of patients had DWI lesions that were less than 25% the territory at risk (<70ml) whether they were imaged < or >8h after stroke onset. DWI lesions corresponded to areas of greatly reduced perfusion. Conclusions: Poor correlation between infarct volume and time after stroke onset suggests that there are factors more powerful than time in determining infarct size within the first 30h. The observations suggest that highly variable cerebral perfusion via the collateral circulation may primarily determine infarct growth dynamics. If verified, clinical implications include the possibility of treating many patients outside traditional time windows.
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    Optimal Brain MRI Protocol for New Neurological Complaint
    (Public Library of Science, 2014) Mehan, William; González, R. Gilberto; Buchbinder, Bradley; Chen, John; Copen, William; Gupta, Rajiv; Hirsch, Joshua; Hunter, George; Hunter, Scott; Johnson, Jason M.; Kelly, Hillary R.; Larvie, Mykol; Lev, Michael; Pomerantz, Stuart; Rapalino, Otto; Rincon, Sandra; Romero, Javier; Schaefer, Pamela; Shah, Vinil
    Background/Purpose Patients with neurologic complaints are imaged with MRI protocols that may include many pulse sequences. It has not been documented which sequences are essential. We assessed the diagnostic accuracy of a limited number of sequences in patients with new neurologic complaints. Methods: 996 consecutive brain MRI studies from patients with new neurological complaints were divided into 2 groups. In group 1, reviewers used a 3-sequence set that included sagittal T1-weighted, axial T2-weighted fluid-attenuated inversion recovery, and axial diffusion-weighted images. Subsequently, another group of studies were reviewed using axial susceptibility-weighted images in addition to the 3 sequences. The reference standard was the study's official report. Discrepancies between the limited sequence review and the reference standard including Level I findings (that may require immediate change in patient management) were identified. Results: There were 84 major findings in 497 studies in group 1 with 21 not identified in the limited sequence evaluations: 12 enhancing lesions and 3 vascular abnormalities identified on MR angiography. The 3-sequence set did not reveal microhemorrhagic foci in 15 of 19 studies. There were 117 major findings in 499 studies in group 2 with 19 not identified on the 4-sequence set: 17 enhancing lesions and 2 vascular lesions identified on angiography. All 87 Level I findings were identified using limited sequence (56 acute infarcts, 16 hemorrhages, and 15 mass lesions). Conclusion: A 4-pulse sequence brain MRI study is sufficient to evaluate patients with a new neurological complaint except when contrast or angiography is indicated.
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    Rapid identification of a major diffusion/perfusion mismatch in distal internal carotid artery or middle cerebral artery ischemic stroke
    (BioMed Central, 2012) Hakimelahi, Reza; Yoo, Albert J.; He, Julian; Schwamm, Lee; Lev, Michael; Schaefer, Pamela; González, Ramon Gilberto
    Background: We tested the hypothesis that in patients with occlusion of the terminal internal carotid artery and/or the proximal middle cerebral artery, a diffusion abnormality of 70 ml or less is accompanied by a diffusion/perfusion mismatch of at least 100%. Methods: Sixty-eight consecutive patients with terminal ICA and/or proximal MCA occlusions and who underwent diffusion/perfusion MRI within 24 hours of stroke onset were retrospectively identified. DWI and mean transit time (MTT) volumes were measured. Prospectively, 48 consecutive patients were identified with the same inclusion criteria. DWI and time to peak (TTP) lesion volumes were measured. A large mismatch volume was defined as an MTT or TTP abnormality at least twice the DWI lesion volume. Results: In the retrospective study, 49 of 68 patients had a DWI lesion volume ≤ 70 ml (mean 20.2 ml; SEM 2.9 ml). A DWI/MTT mismatch of > 100% was observed in all 49 patients (P < .0001). In the prospective study, there were 35/48 patients with DWI volumes ≤ 70 ml (mean 18.7 ml; SEM 3.0 ml). A mismatch > 100% was present in all 35 (P < .0001). Conclusions: Acute stroke patients with major anterior circulation artery occlusion are exceedingly likely to have a major diffusion/perfusion mismatch if the diffusion lesion volume is 70 ml or less. This suggests that physiology-based patient assessments may be made using only vessel imaging and diffusion MRI as a simple alternative to perfusion imaging.
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    The Massachusetts General Hospital Acute Stroke Imaging Algorithm: An Experience and Evidence Based Approach
    (BMJ Publishing Group, 2013) Gonzalez, Ramon; Copen, William; Schaefer, Pamela; Lev, Michael; Pomerantz, Stuart; Rapalino, Otto; Chen, John; Hunter, George; Romero, Javier; Buchbinder, Bradley; Larvie, Mykol; Hirsch, Joshua; Gupta, Rajiv
    The Massachusetts General Hospital Neuroradiology Division employed an experience and evidence based approach to develop a neuroimaging algorithm to best select patients with severe ischemic strokes caused by anterior circulation occlusions (ACOs) for intravenous tissue plasminogen activator and endovascular treatment. Methods found to be of value included the National Institutes of Health Stroke Scale (NIHSS), non-contrast CT, CT angiography (CTA) and diffusion MRI. Perfusion imaging by CT and MRI were found to be unnecessary for safe and effective triage of patients with severe ACOs. An algorithm was adopted that includes: non-contrast CT to identify hemorrhage and large hypodensity followed by CTA to identify the ACO; diffusion MRI to estimate the core infarct; and NIHSS in conjunction with diffusion data to estimate the clinical penumbra.
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    Good Outcome Rate of 35% in IV-tPA-Treated Patients With Computed Tomography Angiography Confirmed Severe Anterior Circulation Occlusive Stroke
    (Ovid Technologies (Wolters Kluwer Health), 2013) Gonzalez, Ramon; Furie, K. L.; Goldmacher, G. V.; Smith, W. S.; Kamalian, S.; Payabvash, S.; Harris, Gordon; Halpern, Elkan F.; Koroshetz, W. J.; Camargo, Erica; Dillon, W. P.; Lev, Michael
    BACKGROUND AND PURPOSE: To determine the effect of intravenous tissue plasminogen activator (IV-tPA) on outcomes in patients with severe major anterior circulation ischemic stroke. METHODS: Prospectively, 649 patients with acute stroke had admission National Institutes of Health stroke scale (NIHSS) scores, noncontrast computed tomography (CT), CT angiography (CTA), and 6-month outcome assessed using modified Rankin scale. IV-tPA treatment decisions were made before CTA, at the time of noncontrast CT scanning, as per routine clinical protocol. Severe symptoms were defined as NIHSS>10. Poor outcome was defined as modified Rankin scale >2. Major occlusions were identified on CTA. Univariate and multivariate stepwise-forward logistic regression analyses of the full cohort were performed. RESULTS: Of 649 patients, 188 (29%) patients presented with NIHSS>10, and 64 out of 188 (34%) patients received IV-tPA. Admission NIHSS, large artery occlusion, and IV-tPA all independently predicted good outcomes; however, a significant interaction existed between IV-tPA and occlusion (P<0.001). Of the patients who presented with NIHSS>10 with anterior circulation occlusion, twice the percentage had good outcomes if they received IV-tPA (17 out of 49 patients, 35%) than if they did not (13 out of 77 patients, 17%; P=0.031). The number needed to treat was 7 (95% confidence interval, 3-60). CONCLUSIONS: IV-tPA treatment resulted in significantly better outcomes in patients with severely symptomatic stroke with major anterior circulation occlusions. The 35% good outcome rate was similar to rates found in endovascular therapy trials. Vascular imaging may help in patient selection and stratification for trials of IV-thrombolytic and endovascular therapies.
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    Improved Outcome Prediction Using CT Angiography in Addition to Standard Ischemic Stroke Assessment: Results from the STOPStroke Study
    (Public Library of Science, 2012) Lev, Michael; Smith, Wade S.; Payabvash, Seyedmehdi; Harris, Gordon; Halpern, Elkan F.; Koroshetz, Walter J.; Dillon, William P.; Furie, Karen L.; Goldmacher, Gregory V.; Camargo, Erica; Gonzalez, Ramon
    Purpose: To improve ischemic stroke outcome prediction using imaging information from a prospective cohort who received admission CT angiography (CTA). Methods: In a prospectively designed study, 649 stroke patients diagnosed with acute ischemic stroke had admission NIH stroke scale scores, noncontrast CT (NCCT), CTA, and 6-month outcome assessed using the modified Rankin scale (mRS) scores. Poor outcome was defined as mRS>2. Strokes were classified as “major” by the (1) Alberta Stroke Program Early CT Score (ASPECTS+) if NCCT ASPECTS was\(\leq7\); (2) Boston Acute Stroke Imaging Scale (BASIS+) if they were ASPECTS+ or CTA showed occlusion of the distal internal carotid, proximal middle cerebral, or basilar arteries; and (3) NIHSS for scores>10. Results: Of 649 patients, 253 (39.0%) had poor outcomes. NIHSS, BASIS, and age, but not ASPECTS, were independent predictors of outcome. BASIS and NIHSS had similar sensitivities, both superior to ASPECTS (p<0.0001). Combining NIHSS with BASIS was highly predictive: 77.6% (114/147) classified as NIHSS>10/BASIS+ had poor outcomes, versus 21.5% (77/358) with NIHSS\(\leq10\)/BASIS− (p<0.0001), regardless of treatment. The odds ratios for poor outcome is 12.6 (95% CI: 7.9 to 20.0) in patients who are NIHSS>10/BASIS+ compared to patients who are NIHSS\(\leq10\)/BASIS−; the odds ratio is 5.4 (95% CI: 3.5 to 8.5) when compared to patients who are only NIHSS>10 or BASIS+. Conclusions: BASIS and NIHSS are independent outcome predictors. Their combination is stronger than either instrument alone in predicting outcomes. The findings suggest that CTA is a significant clinical tool in routine acute stroke assessment.
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    An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets
    (Springer Science and Business Media LLC, 2018-12-17) Lee, Hyunkwang; Yune, Sehyo; Mansouri, Mohammad; Kim, Myeongchan; Tajmir, Shahein H.; Guerrier, Claude E.; Ebert, Sarah A.; Pomerantz, Stuart; Romero, Javier; Kamalian, Mohammad; Gonzalez, Ramon; Lev, Michael; Do, Synho
    Owing to improvements in image recognition via deep learning, machine-learning algorithms could eventually be applied to automated medical diagnoses that can guide clinical decision-making. However, these algorithms remain a 'black box' in terms of how they generate the predictions from the input data. Also, high-performance deep learning requires large, high-quality training datasets. Here, we report the development of an understandable deep-learning system that detects acute intracranial haemorrhage (ICH) and classifies five ICH subtypes from unenhanced head computed-tomography scans. By using a dataset of only 904 cases for algorithm training, the system achieved a performance similar to that of expert radiologists in two independent test datasets containing 200 cases (sensitivity of 98% and specificity of 95%) and 196 cases (sensitivity of 92% and specificity of 95%). The system includes an attention map and a prediction basis retrieved from training data to enhance explainability, and an iterative process that mimics the workflow of radiologists. Our approach to algorithm development can facilitate the development of deep-learning systems for a variety of clinical applications and accelerate their adoption into clinical practice.