autoTICI: Automatic Brain Tissue Reperfusion Scoring on 2D DSA Images of Acute Ischemic Stroke Patients

The Thrombolysis in Cerebral Infarction (TICI) score is an important metric for reperfusion therapy assessment in acute ischemic stroke. It is commonly used as a technical outcome measure after endovascular treatment (EVT). Existing TICI scores are defined in coarse ordinal grades based on visual inspection, leading to inter- and intra-observer variation. In this work, we present autoTICI, an automatic and quantitative TICI scoring method. First, each digital subtraction angiography (DSA) sequence is separated into four phases (non-contrast, arterial, parenchymal and venous phase) using a multi-path convolutional neural network (CNN), which exploits spatio-temporal features. The network also incorporates sequence level label dependencies in the form of a state-transition matrix. Next, a minimum intensity map (MINIP) is computed using the motion corrected arterial and parenchymal frames. On the MINIP image, vessel, perfusion and background pixels are segmented. Finally, we quantify the autoTICI score as the ratio of reperfused pixels after EVT. On a routinely acquired multi-center dataset, the proposed autoTICI shows good correlation with the extended TICI (eTICI) reference with an average area under the curve (AUC) score of 0.81. The AUC score is 0.90 with respect to the dichotomized eTICI. In terms of clinical outcome prediction, we demonstrate that autoTICI is overall comparable to eTICI.Comment: 10 pages; submitted to IEEE TM

Hospital Variation in Time to Endovascular Treatment for Ischemic Stroke:What Is the Optimal Target for Improvement?

Background Time to reperfusion in patients with ischemic stroke is strongly associated with functional outcome and may differ between hospitals and between patients within hospitals. Improvement in time to reperfusion can be guided by between-hospital and within-hospital comparisons and requires insight in specific targets for improvement. We aimed to quantify the variation in door-to-reperfusion time between and within Dutch intervention hospitals and to assess the contribution of different time intervals to this variation. Methods and Results We used data from the MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) Registry. The door-to-reperfusion time was subdivided into time intervals, separately for direct patients (door-to-computed tomography, computed tomography-to-computed tomography angiography [CTA], CTA-to-groin, and groin-to-reperfusion times) and for transferred patients (door-to-groin and groin-to-reperfusion times). We used linear mixed models to distinguish the variation in door-to-reperfusion time between hospitals and between patients. The proportional change in variance was used to estimate the amount of variance explained by each time interval. We included 2855 patients of 17 hospitals providing endovascular treatment. Of these patients, 44% arrived directly at an endovascular treatment hospital. The between-hospital variation in door-to-reperfusion time was 9%, and the within-hospital variation was 91%. The contribution of case-mix variables on the variation in door-to-reperfusion time was marginal (2%-7%). Of the between-hospital variation, CTA-to-groin time explained 83%, whereas groin-to-reperfusion time explained 15%. Within-hospital variation was mostly explained by CTA-to-groin time (33%) and groin-to-reperfusion time (42%). Similar results were found for transferred patients. Conclusions Door-to-reperfusion time varies between, but even more within, hospitals providing endovascular treatment for ischemic stroke. Quality of stroke care improvements should not only be guided by between-hospital comparisons, but also aim to reduce variation between patients within a hospital, and should specifically focus on CTA-to-groin time and groin-to-reperfusion time

Radiation dose reduction in pediatric great vessel stent computed tomography using iterative reconstruction: A phantom study

Background To study dose reduction using iterative reconstruction (IR) for pediatric great vessel stent computed tomography (CT). Methods Five different great vessel stents were separately placed in a gel-containing plastic holder within an anthropomorphic chest phantom. The stent lumen was filled with diluted contrast gel. CT acquisitions were performed at routine dose, 52% and 81% reduced dose and reconstructed with filtered back projection (FBP) and IR. Objective image quality in terms of noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as subjective image quality were evaluated. Results Noise, SNR and CNR were improved with IR at routine and 52% reduced dose, compared to FBP at routine dose. The lowest dose level resulted in decreased objective image quality with both FBP and IR. Subjective image quality was excellent at all dose levels. Conclusion IR resulted in improved objective image quality at routine dose and 52% reduced dose, while objective image quality deteriorated at 81% reduced dose. Subjective image quality was not affected by dose reduction

Effect of first pass reperfusion on outcome in patients with posterior circulation ischemic stroke

BACKGROUND: First pass reperfusion (FPR), that is, excellent reperfusion (expanded treatment in cerebral ischemia (eTICI) 2C-3) in one pass, after endovascular treatment (EVT) of an occluded artery in the anterior circulation, is associated with favorable clinical outcome, even when compared with multiple pass excellent reperfusion (MPR). In patients with posterior circulation ischemic stroke (PCS), the same association is expected, but currently unknown. We aimed to assess characteristics associated with FPR and the influence of FPR versus MPR on outcomes in patients with PCS. METHODS: We used data from the MR CLEAN Registry, a prospective observational study. The effect of FPR on 24-hour National Institutes of Health Stroke Scale (NIHSS) score, as percentage reduction, and on modified Rankin Scale (mRS) scores at 3 months, was tested with linear and ordinal logistic regression models. RESULTS: Of 224 patients with PCS, 45 patients had FPR, 47 had MPR, and 90 had no excellent reperfusion (eTICI <2C). We did not find an association between any of the patient, imaging, or treatment characteristics and FPR. FPR was associated with better NIHSS (-45% (95% CI: -65% to -12%)) and better mRS scores (adjusted common odds ratio (acOR): 2.16 (95% CI: 1.23 to 3.79)) compared with no FPR. Outcomes after FPR were also more favorable compared with MPR, but the effect was smaller and not statistically significant (NIHSS: -14% (95% CI: -51% to 49%), mRS acOR: 1.50 (95% CI: 0.75 to 3.00)). CONCLUSIONS: FPR in patients with PCS is associated with favorable clinical outcome in comparison with no FPR. In comparison with MPR, the effect of FPR was no longer statistically significant. Nevertheless, our data support the notion that FPR should be the treatment target to pursue in every patient treated with EVT

Improving quality of stroke care through benchmarking center performance:why focusing on outcomes is not enough.

Background: Between-center variation in outcome may offer opportunities to identify variation in quality of care. By intervening on these quality differences, patient outcomes may be improved. However, whether observed differences in outcome reflect the true quality improvement potential is not known for many diseases. Therefore, we aimed to analyze the effect of differences in performance on structure and processes of care, and case-mix on between-center differences in outcome after endovascular treatment (EVT) for ischemic stroke. Methods: In this observational cohort study, ischemic stroke patients who received EVT between 2014 and 2017 in all 17 Dutch EVT-centers were included. Primary outcome was the modified Rankin Scale, ranging from 0 (no symptoms) to 6 (death), at 90 days. We used random effect proportional odds regression modelling, to analyze the effect of differences in structure indicators (center volume and year of admission), process indicators (time to treatment and use of general anesthesia) and case-mix, by tracking changes in tau2, which represents the amount of between-center variation in outcome. Results: Three thousand two hundred seventy-nine patients were included. Performance on structure and process indicators varied significantly between EVT-centers (P < 0.001). Predicted probability of good functional outcome (modified Rankin Scale 0–2 at 90 days), which can be interpreted as an overall measure of a center’s case-mix, varied significantly between 17 and 50% across centers. The amount of between-center variation (tau2) was estimated at 0.040 in a model only accounting for random variation. This estimate more than doubled after adding case-mix variables (tau2: 0.086) to the model, while a small amount of between-center variation was explained by variation in performance on structure and process indicators (tau2: 0.081 and 0.089, respectively). This indicates that variation in case-mix affects the differences in outcome to a much larger extent. Conclusions: Between-center variation in outcome of ischemic stroke patients mostly reflects differences in case-mix, rather than differences in structure or process of care. Since the latter two capture the real quality improvement potential, these should be used as indicators for comparing center performance. Especially when a strong association exists between those indicators and outcome, as is the case for time to treatment in ischemic stroke

Diagnostic performance of an algorithm for automated large vessel occlusion detection on CT angiography

BACKGROUND: Machine learning algorithms hold the potential to contribute to fast and accurate detection of large vessel occlusion (LVO) in patients with suspected acute ischemic stroke. We assessed the diagnostic performance of an automated LVO detection algorithm on CT angiography (CTA). METHODS: Data from the MR CLEAN Registry and PRESTO were used including patients with and without LVO. CTA data were analyzed by the algorithm for detection and localization of LVO (intracranial internal carotid artery (ICA)/ICA terminus (ICA-T), M1, or M2). Assessments done by expert neuroradiologists were used as reference. Diagnostic performance was assessed for detection of LVO and per occlusion location by means of sensitivity, specificity, and area under the curve (AUC). RESULTS: We analyzed CTAs of 1110 patients from the MR CLEAN Registry (median age (IQR) 71 years (60-80); 584 men; 1110 with LVO) and of 646 patients from PRESTO (median age (IQR) 73 years (62-82); 358 men; 141 with and 505 without LVO). For detection of LVO, the algorithm yielded a sensitivity of 89% in the MR CLEAN Registry and a sensitivity of 72%, specificity of 78%, and AUC of 0.75 in PRESTO. Sensitivity per occlusion location was 88% for ICA/ICA-T, 94% for M1, and 72% for M2 occlusion in the MR CLEAN Registry, and 80% for ICA/ICA-T, 95% for M1, and 49% for M2 occlusion in PRESTO. CONCLUSION: The algorithm provided a high detection rate for proximal LVO, but performance varied significantly by occlusion location. Detection of M2 occlusion needs further improvement

Determinants of Symptomatic Intracranial Hemorrhage After Endovascular Stroke Treatment:A Retrospective Cohort Study

Background: Symptomatic intracranial hemorrhage (sICH) is a serious complication after endovascular treatment for ischemic stroke. We aimed to identify determinants of its occurrence and location. Methods: We retrospectively analyzed data from the Dutch MR CLEAN trial (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) and MR CLEAN registry. We included adult patients with a large vessel occlusion in the anterior circulation who underwent endovascular treatment within 6.5 hours of stroke onset. We used univariable and multivariable logistic regression analyses to identify determinants of overall sICH occurrence, sICH within infarcted brain tissue, and sICH outside infarcted brain tissue. Results: SICH occurred in 203 (6%) of 3313 included patients and was located within infarcted brain tissue in 50 (25%), outside infarcted brain tissue in 23 (11%), and both within and outside infarcted brain tissue in 116 (57%) patients. In 14 patients (7%), data on location were missing. Prior antiplatelet use, baseline systolic blood pressure, baseline plasma glucose levels, post-endovascular treatment modified treatment in cerebral ischemia score, and duration of procedure were associated with all outcome parameters. In addition, determinants of sICH within infarcted brain tissue included history of myocardial infarction (adjusted odds ratio, 1.65 [95% CI, 1.06-2.56]) and poor collateral score (adjusted odds ratio, 1.42 [95% CI, 1.02-1.95]), whereas determinants of sICH outside infarcted brain tissue included level of occlusion on computed tomography angiography (internal carotid artery or internal carotid artery terminus compared with M1: adjusted odds ratio, 1.79 [95% CI, 1.16-2.78]). Conclusions: Several factors, some potentially modifiable, are associated with sICH occurrence. Further studies should investigate whether modification of baseline systolic blood pressure or plasma glucose level could reduce the risk of sICH. In addition, determinants differ per location of sICH, supporting the hypothesis of varying underlying mechanisms. Registration: URL: https://www.isrctn.com/; Unique identifier: ISRCTN10888758