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  • Ovid Technologies (Wolters Kluwer Health)  (3)
  • Kunz, Wolfgang G.  (3)
  • Sabel, Bastian O.  (3)
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  • Ovid Technologies (Wolters Kluwer Health)  (3)
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  • 1
    Online Resource
    Online Resource
    Effect of stroke thrombolysis predicted by distal vessel occlusion detection
    Ovid Technologies (Wolters Kluwer Health) ; 2018
    In:  Neurology Vol. 90, No. 20 ( 2018-05-15), p. e1742-e1750
    Details
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 90, No. 20 ( 2018-05-15), p. e1742-e1750
    Abstract: Among ischemic stroke patients with negative CT angiography (CTA), we aimed to determine the predictive value of enhanced distal vessel occlusion detection using CT perfusion postprocessing (waveletCTA) for the treatment effect of IV thrombolysis (IVT). Methods Patients were selected from 1,851 consecutive patients who had undergone CT perfusion. Inclusion criteria were (1) significant cerebral blood flow (CBF) deficit, (2) no occlusion on CTA, and (3) infarction confirmed on follow-up. Favorable morphologic response was defined as smaller values of final infarction volume divided by initial CBF deficit volume (FIV/CBF). Favorable functional outcome was defined as modified Rankin Scale score of ≤2 after 90 days and decrease in NIH Stroke Scale score of ≥3 from admission to 24 hours (∆NIHSS). Results Among patients with negative CTA (n = 107), 58 (54%) showed a distal occlusion on waveletCTA. There was no difference between patients receiving IVT (n = 57) vs supportive care (n = 50) regarding symptom onset, early ischemic changes, perfusion mismatch, or admission NIHSS score (all p 〉 0.05). In IVT-treated patients, the presence of an occlusion was an independent predictor of a favorable morphologic response (FIV/CBF: β −1.43; 95% confidence interval [CI] −1.96, −0.83; p = 0.001) and functional outcome (90-day modified Rankin Scale: odds ratio 7.68; 95% CI 4.33–11.51; p = 0.039; ∆NIHSS: odds ratio 5.76; 95% CI 3.98–8.27; p = 0.013), while it did not predict outcome in patients receiving supportive care (all p 〉 0.05). Conclusion In stroke patients with negative CTA, distal vessel occlusions as detected by waveletCTA are an independent predictor of a favorable response to IVT.
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    URL: Article
    DOI: 10.1212/WNL.0000000000005519
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2018
    Location Call Number Limitation Availability
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Artificial Intelligence Algorithm Detecting Lung Infection in Supine Chest Radiographs of Critically Ill Patients With a Diagnostic Accuracy Similar to Board-Certified Radiologists
    Ovid Technologies (Wolters Kluwer Health) ; 2020
    In:  Critical Care Medicine Vol. 48, No. 7 ( 2020-07), p. e574-e583
    Details
    In: Critical Care Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 48, No. 7 ( 2020-07), p. e574-e583
    Abstract: Interpretation of lung opacities in ICU supine chest radiographs remains challenging. We evaluated a prototype artificial intelligence algorithm to classify basal lung opacities according to underlying pathologies. Design: Retrospective study. The deep neural network was trained on two publicly available datasets including 297,541 images of 86,876 patients. Patients: One hundred sixty-six patients received both supine chest radiograph and CT scans (reference standard) within 90 minutes without any intervention in between. Measurements and Main Results: Algorithm accuracy was referenced to board-certified radiologists who evaluated supine chest radiographs according to side-separate reading scores for pneumonia and effusion (0 = absent, 1 = possible, and 2 = highly suspected). Radiologists were blinded to the supine chest radiograph findings during CT interpretation. Performances of radiologists and the artificial intelligence algorithm were quantified by receiver-operating characteristic curve analysis. Diagnostic metrics (sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) were calculated based on different receiver-operating characteristic operating points. Regarding pneumonia detection, radiologists achieved a maximum diagnostic accuracy of up to 0.87 (95% CI, 0.78–0.93) when considering only the supine chest radiograph reading score 2 as positive for pneumonia. Radiologist’s maximum sensitivity up to 0.87 (95% CI, 0.76–0.94) was achieved by additionally rating the supine chest radiograph reading score 1 as positive for pneumonia and taking previous examinations into account. Radiologic assessment essentially achieved nonsignificantly higher results compared with the artificial intelligence algorithm: artificial intelligence-area under the receiver-operating characteristic curve of 0.737 (0.659–0.815) versus radiologist’s area under the receiver-operating characteristic curve of 0.779 (0.723–0.836), diagnostic metrics of receiver-operating characteristic operating points did not significantly differ. Regarding the detection of pleural effusions, there was no significant performance difference between radiologist’s and artificial intelligence algorithm: artificial intelligence-area under the receiver-operating characteristic curve of 0.740 (0.662–0.817) versus radiologist’s area under the receiver-operating characteristic curve of 0.698 (0.646–0.749) with similar diagnostic metrics for receiver-operating characteristic operating points. Conclusions: Considering the minor level of performance differences between the algorithm and radiologists, we regard artificial intelligence as a promising clinical decision support tool for supine chest radiograph examinations in the clinical routine with high potential to reduce the number of missed findings in an artificial intelligence–assisted reading setting.
    Type of Medium: Online Resource
    ISSN: 0090-3493
    URL: Article
    DOI: 10.1097/CCM.0000000000004397
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2020
    detail.hit.zdb_id: 2034247-0
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Early Imaging Prediction of Malignant Cerebellar Edema Development in Acute Ischemic Stroke
    Ovid Technologies (Wolters Kluwer Health) ; 2017
    In:  Stroke Vol. 48, No. 9 ( 2017-09), p. 2597-2600
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 48, No. 9 ( 2017-09), p. 2597-2600
    Abstract: Malignant cerebellar edema (MCE) is a life-threatening complication of acute ischemic stroke that requires timely diagnosis and management. Aim of this study was to identify imaging predictors in initial multiparametric computed tomography (CT), including whole-brain CT perfusion (WB-CTP). Methods— We consecutively selected all subjects with cerebellar ischemic WB-CTP deficits and follow-up–confirmed cerebellar infarction from an initial cohort of 2635 patients who had undergone multiparametric CT because of suspected stroke. Follow-up imaging was assessed for the presence of MCE, measured using an established 10-point scale, of which scores ≥4 are considered malignant. Posterior circulation–Acute Stroke Prognosis Early CT Score (pc-ASPECTS) was determined to assess ischemic changes on noncontrast CT, CT angiography (CTA), and parametric WB-CTP maps (cerebellar blood flow [CBF]; cerebellar blood volume; mean transit time; time to drain). Fisher’s exact tests, Mann–Whitney U tests, and receiver operating characteristics analyses were performed for statistical analyses. Results— Out of a total of 51 patients who matched the inclusion criteria, 42 patients (82.4%) were categorized as MCE− and 9 (17.6%) as MCE+. MCE+ patients had larger CBF, cerebellar blood volume, mean transit time, and time to drain deficit volumes (all with P 〈 0.001) and showed significantly lower median pc-ASPECTS assessed using WB-CTP (CBF, cerebellar blood volume, mean transit time, time to drain; all with P 〈 0.001) compared with MCE− patients, while median pc-ASPECTS on noncontrast CT and CTA was not significantly different (both P 〉 0.05). Receiver operating characteristics analyses yielded the largest area under the curve values for the prediction of MCE development for CBF (0.979) and cerebellar blood volume deficit volumes (0.956) and pc-ASPECTS on CBF (0.935), whereas pc-ASPECTS on noncontrast CT (0.648) and CTA (0.684) had less diagnostic value. The optimal cutoff value for CBF deficit volume was 22 mL, yielding 100% sensitivity and 90% specificity for MCE classification. Conclusions— WB-CTP provides added diagnostic value for the early identification of patients at risk for MCE development in acute cerebellar stroke.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/STROKEAHA.117.018237
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2017
    detail.hit.zdb_id: 1467823-8
    Location Call Number Limitation Availability
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