Imaging stroke patients with unclear onset times.
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ABSTRACT:
SUBMITTER: Wu O
PROVIDER: S-EPMC3109317 | biostudies-other | 2011 May
REPOSITORIES: biostudies-other
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Imaging stroke patients with unclear onset times.
Wu Ona O Schwamm Lee H LH Sorensen A Gregory AG
Neuroimaging clinics of North America 20110501 2
Stroke is a leading cause of death and adult morbidity worldwide. By defining stroke symptom onset by the time the patient was last known to be well, many patients whose onsets are unwitnessed are automatically ineligible for thrombolytic therapy. Advanced brain imaging may serve as a substitute witness to estimate stroke onset and duration in those patients who do not have a human witness. This article reviews and compares some of these imaging-based approaches to thrombolysis eligibility, whic ...[more]
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Project description:Patients with unwitnessed stroke represent >25% of all strokes. Clinical trials enrolling patients with unwitnessed stroke onset have conservatively used last known normal (LKN) as the time of stroke onset. We explored the impact of alternative methods of selecting onset time in unwitnessed strokes on eligibility into an acute stroke therapeutic trial using a representative sample of acute stroke subjects.We analyzed data on 641 consecutive patients with suspected stroke presenting to our hospital between January 2007 and July 2008. Time of onset was calculated by 3 methods: (1) LKN, (2) first known abnormal (FKA), and (3) midpoint between LKN and FKA. Subjects with incomplete data or a final diagnosis of nonischemic stroke were excluded. Rates of trial eligibility based on different onset times were compared for several inclusion time windows.Onset time was known in 440 subjects (69%). Of the remaining 201 patients with unwitnessed onset, 114 (57%) were "wake-up" strokes. Among unwitnessed stroke subjects, eligibility increased from 18% using LKN to 57% using FKA at 4.5 hours and 42% to 81% at 9 hours (P < .001), respectively. Overall enrollment eligibility for the full cohort increased from 36% to 48% at 4.5 hours and 61% to 73% at 9 hours (P < .001), respectively.Given potential advantages in safety evaluation and the historical inadequate enrollment rates in acute stroke trials, alternative onset time definitions, perhaps in combination with advanced neuroimaging methods (e.g., fluid-attenuated inversion recovery-diffusion-weighted imaging mismatch), should be considered for early-phase trials.
| S-EPMC3718254 | biostudies-other
Project description:BACKGROUND:Objective timing of stroke in emergency departments is expected to improve patient stratification. Magnetic resonance imaging (MRI) relaxations times, T2 and T1? , in abnormal diffusion delineated ischaemic tissue were used as proxies of stroke time in a rat model. METHODS:Both 'non-ischaemic reference'-dependent and -independent estimators were generated. Apparent diffusion coefficient (ADC), T2 and T1? , were sequentially quantified for up to 6 hours of stroke in rats (n = 8) at 4.7T. The ischaemic lesion was identified as a contiguous collection of voxels with low ADC. T2 and T1? in the ischaemic lesion and in the contralateral non-ischaemic brain tissue were determined. Differences in mean MRI relaxation times between ischaemic and non-ischaemic volumes were used to create reference-dependent estimator. For the reference-independent procedure, only the parameters associated with log-logistic fits to the T2 and T1? distributions within the ADC-delineated lesions were used for the onset time estimation. RESULT:The reference-independent estimators from T2 and T1? data provided stroke onset time with precisions of ±32 and ±27 minutes, respectively. The reference-dependent estimators yielded respective precisions of ±47 and ±54 minutes. CONCLUSIONS:A 'non-ischaemic anatomical reference'-independent estimator for stroke onset time from relaxometric MRI data is shown to yield greater timing precision than previously obtained through reference-dependent procedures.
| S-EPMC5495158 | biostudies-literature
Project description:Meaningful delays occurred in the Interventional Management of Stroke (IMS) III trial. Analysis of the work flow will identify factors contributing to the in-hospital delays.In the endovascular arm of the IMS III trial, the following time intervals were calculated: stroke onset to emergency department arrival; emergency department to computed tomography (CT); CT to intravenous tissue plasminogen activator start; intravenous tissue plasminogen activator start to randomization; randomization to groin puncture; groin puncture to thrombus identification; thrombus identification to start of endovascular therapy; and start of endovascular therapy to reperfusion. The effects of enrollment time, CT angiography use, interhospital transfers, and intubation on work flow were evaluated. Delays occurred notably in the time intervals from intravenous tissue plasminogen activator initiation to groin puncture (median 84 minutes) and start of endovascular therapy to reperfusion (median 85 minutes). The CT to groin puncture time was significantly shorter during working hours than after. Times from emergency department to reperfusion and groin puncture to reperfusion decreased over the trial period. Patients with CT angiography had shorter emergency department to reperfusion and onset to reperfusion times. Transfer of patients resulted in a longer onset to reperfusion time compared with those treated in the same center. Age, sex, National Institutes of Health Stroke Scale score, and intubation did not affect delays.Important delays were identified before reperfusion in the IMS III trial. Delays decreased as the trial progressed. Use of CT angiography and endovascular treatment in the same center were associated with time savings. These data may help in optimizing work flow in current and future endovascular trials.http://www.clinicaltrials.gov. Unique identifier: NCT00359424.
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Project description:ObjectiveTo determine the IV tissue plasminogen activator (tPA) treatment rate of patients with minor acute ischemic stroke (mAIS) at our centers and compare the frequency of MRI targets by treatment stratification and clinical severity, we evaluated clinical characteristics and baseline MRIs for tPA-treated and untreated patients.MethodsPatients with ischemic stroke from 2015 to 2017 with admit NIH Stroke Scale (NIHSS) <6 were considered. The treated cohort received standard IV tPA and was screened with baseline MRI. The untreated cohort received no acute intervention and baseline MRI was <4 hours from onset. Patients were stratified into "clearly" and "not clearly" disabling deficits by NIHSS elements. Baseline MRI was evaluated by independent raters for AIS targets, with frequencies compared between groups.ResultsOf 255 patients with mAIS ≤4.5 hours from onset, 140 (55%) received IV tPA, accounting for 46% of all IV tPA patients (n = 305). Eighty-five percent (n = 119) were screened with baseline MRI and had significantly more frequent imaging targets compared to those untreated (n = 90). Of this treated cohort, 75% (n = 89) were not clearly disabling. Except for perfusion-diffusion mismatch (81% clearly disabling vs 56% not clearly disabling [p = 0.036]), there were no significant differences in the frequency of imaging targets across the treated cohort stratified by clinical severity.ConclusionsIn MRI-screened mAIS, imaging targets were more frequently seen in patients treated with IV tPA, with similar frequencies even in those without clearly disabling deficits. MRI targets could be used to guide thrombolytic therapy in patients with mAIS; however, a randomized trial is needed to demonstrate efficacy.
| S-EPMC8055325 | biostudies-literature
Project description:IntroductionMechanical 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 methodsA 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.ResultsWe 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).DiscussionAfter validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown.ConclusionIn 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.
| S-EPMC6460412 | biostudies-literature
Project description:IMPORTANCE:Physicians often must decide whether to treat patients with acute stroke locally or refer them to a more distant Primary Stroke Center (PSC). There is little evidence on how much the increased risk of prolonged travel time offsets benefits of a specialized PSC care. OBJECTIVES:To examine the association of case fatality with receiving care in PSCs vs other hospitals for patients with stroke and to identify whether prolonged travel time offsets the effect of PSCs. DESIGN, SETTING, AND PARTICIPANTS:Retrospective cohort study of Medicare beneficiaries with stroke admitted to a hospital between January 1, 2010, and December 31, 2013. Drive times were calculated based on zip code centroids and street-level road network data. We used an instrumental variable analysis based on the differential travel time to PSCs to control for unmeasured confounding. The setting was a 100% sample of Medicare fee-for-service claims. EXPOSURES:Admission to a PSC. MAIN OUTCOMES AND MEASURES:Seven-day and 30-day postadmission case-fatality rates. RESULTS:Among 865?184 elderly patients with stroke (mean age, 78.9 years; 55.5% female), 53.9% were treated in PSCs. We found that admission to PSCs was associated with 1.8% (95% CI, -2.1% to -1.4%) lower 7-day and 1.8% (95% CI, -2.3% to -1.4%) lower 30-day case fatality. Fifty-six patients with stroke needed to be treated in PSCs to save one life at 30 days. Receiving treatment in PSCs was associated with a 30-day survival benefit for patients traveling less than 90 minutes, but traveling at least 90 minutes offset any benefit of PSC care. CONCLUSIONS AND RELEVANCE:Hospitalization of patients with stroke in PSCs was associated with decreased 7-day and 30-day case fatality compared with noncertified hospitals. Traveling at least 90 minutes to receive care offset the 30-day survival benefit of PSC admission.
| S-EPMC5434865 | biostudies-literature
Project description:Many ischaemic stroke patients are ineligible for thrombolytic therapy due to unknown onset time. Quantitative MRI (qMRI) is a potential surrogate for stroke timing. Rats were subjected to permanent middle cerebral artery occlusion and qMRI parameters including hemispheric differences in apparent diffusion coefficient, T2-weighted signal intensities, T1 and T2 relaxation times (qT1, qT2) and f1, f2 and Voverlap were measured at hourly intervals at 4.7 or 9.4 T. Accuracy and sensitivity for identifying strokes scanned within and beyond 3 h of onset was determined. Accuracy for Voverlap, f2 and qT2 (>90%) was significantly higher than other parameters. At a specificity of 1, sensitivity was highest for Voverlap (0.90) and f2 (0.80), indicating promise of these qMRI indices in the clinical assessment of stroke onset time.
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Project description:ImportanceTreatments for time-sensitive acute stroke are not available at every hospital, often requiring interhospital transfer. Current guidelines recommend hospitals achieve a door-in-door-out time of no more than 120 minutes at the transferring emergency department (ED).ObjectiveTo evaluate door-in-door-out times for acute stroke transfers in the American Heart Association Get With The Guidelines-Stroke registry and to identify patient and hospital factors associated with door-in-door-out times.Design, setting, and participantsUS registry-based, retrospective study of patients with ischemic or hemorrhagic stroke from January 2019 through December 2021 who were transferred from the ED at registry-affiliated hospitals to other acute care hospitals.ExposurePatient- and hospital-level characteristics.Main outcomes and measuresThe primary outcome was the door-in-door-out time (time of transfer out minus time of arrival to the transferring ED) as a continuous variable and a categorical variable (≤120 minutes, >120 minutes). Generalized estimating equation (GEE) regression models were used to identify patient and hospital-level characteristics associated with door-in-door-out time overall and in subgroups of patients with hemorrhagic stroke, acute ischemic stroke eligible for endovascular therapy, and acute ischemic stroke transferred for reasons other than endovascular therapy.ResultsAmong 108 913 patients (mean [SD] age, 66.7 [15.2] years; 71.7% non-Hispanic White; 50.6% male) transferred from 1925 hospitals, 67 235 had acute ischemic stroke and 41 678 had hemorrhagic stroke. Overall, the median door-in-door-out time was 174 minutes (IQR, 116-276 minutes): 29 741 patients (27.3%) had a door-in-door-out time of 120 minutes or less. The factors significantly associated with longer median times were age 80 years or older (vs 18-59 years; 14.9 minutes, 95% CI, 12.3 to 17.5 minutes), female sex (5.2 minutes; 95% CI, 3.6 to 6.9 minutes), non-Hispanic Black vs non-Hispanic White (8.2 minutes, 95% CI, 5.7 to 10.8 minutes), and Hispanic ethnicity vs non-Hispanic White (5.4 minutes, 95% CI, 1.8 to 9.0 minutes). The following were significantly associated with shorter median door-in-door-out time: emergency medical services prenotification (-20.1 minutes; 95% CI, -22.1 to -18.1 minutes), National Institutes of Health Stroke Scale (NIHSS) score exceeding 12 vs a score of 0 to 1 (-66.7 minutes; 95% CI, -68.7 to -64.7 minutes), and patients with acute ischemic stroke eligible for endovascular therapy vs the hemorrhagic stroke subgroup (-16.8 minutes; 95% CI, -21.0 to -12.7 minutes). Among patients with acute ischemic stroke eligible for endovascular therapy, female sex, Black race, and Hispanic ethnicity were associated with a significantly higher door-in-door-out time, whereas emergency medical services prenotification, intravenous thrombolysis, and a higher NIHSS score were associated with significantly lower door-in-door-out times.Conclusions and relevanceIn this US registry-based study of interhospital transfer for acute stroke, the median door-in-door-out time was 174 minutes, which is longer than current recommendations for acute stroke transfer. Disparities and modifiable health system factors associated with longer door-in-door-out times are suitable targets for quality improvement initiatives.
| S-EPMC10427946 | biostudies-literature
Project description:Current clinical practice relies on clinical history to determine the time since stroke (TSS) onset. Imaging-based determination of acute stroke onset time could provide critical information to clinicians in deciding stroke treatment options, such as thrombolysis. The patients with unknown or unwitnessed TSS are usually excluded from thrombolysis, even if their symptoms began within the therapeutic window. In this paper, we demonstrate a machine learning approach for TSS classification using routinely acquired imaging sequences. We develop imaging features from the magnetic resonance (MR) images and train machine learning models to classify the TSS. We also propose a deep-learning model to extract hidden representations for the MR perfusion-weighted images and demonstrate classification improvement by incorporating these additional deep features. The cross-validation results show that our best classifier achieved an area under the curve of 0.765, with a sensitivity of 0.788 and a negative predictive value of 0.609, outperforming existing methods. We show that the features generated by our deep-learning algorithm correlate with the MR imaging features, and validate the robustness of the model on imaging parameter variations (e.g., year of imaging). This paper advances magnetic resonance imaging analysis one-step-closer to an operational decision support tool for stroke treatment guidance.
| S-EPMC6661120 | biostudies-literature
Project description:CT-based perfusion and collateral imaging is increasingly used in the assessment of patients with acute stroke. Time of stroke onset is a critical factor in determining eligibility for and benefit from thrombolysis. Animal studies predict that the volume of ischemic penumbra decreases with time. Here, we evaluate if CT is able to detect a relationship between perfusion or collateral status, as assessed by CT, and time since stroke onset.We studied 53 consecutive patients with proximal vessel occlusions, mean (SD) age of 71.3 (14.9) years, at a mean (SD) of 125.2 (55.3) minutes from onset, using whole-brain CT perfusion (CTp) imaging. Penumbra was defined using voxel-based thresholds for cerebral blood flow (CBF) and mean transit time (MTT); core was defined by cerebral blood volume (CBV). Normalized penumbra fraction was calculated as Penumbra volume/(Penumbra volume?+?Core volume) for both CBF and MTT (PenCBF and PenMTT, respectively). Collaterals were assessed on CT angiography (CTA). CTp ASPECTS score was applied visually, lower scores indicating larger lesions. ASPECTS ratios were calculated corresponding to penumbra fractions.Both PenCBF and PenMTT showed decremental trends with increasing time since onset (Kendall's tau-b?=?-0.196, p?=?0.055, and -0.187, p?=?0.068, respectively). The CBF/CBV ASPECTS ratio, which showed a relationship to PenCBF (Kendall's tau-b?=?0.190, p?=?0.070), decreased with increasing time since onset (Kendall's tau-b?=?-0.265, p?=?0.006). Collateral response did not relate to time (Kendall's tau-b?=?-0.039, p?=?0.724).Even within 4.5?h since stroke onset, a decremental relationship between penumbra and time, but not between collateral status and time, may be detected using perfusion CT imaging. The trends that we demonstrate merit evaluation in larger datasets to confirm our results, which may have potential wider applications, e.g., in the setting of strokes of unknown onset time.
| S-EPMC4391339 | biostudies-other