Literature DB >> 27304197

First Automated Stroke Imaging Evaluation via Electronic Alberta Stroke Program Early CT Score in a Mobile Stroke Unit.

Iris Quasar Grunwald1, Andreas Ragoschke-Schumm, Michael Kettner, Lenka Schwindling, Safwan Roumia, Stefan Helwig, Matthias Manitz, Silke Walter, Umut Yilmaz, Eric Greveson, Martin Lesmeister, Wolfgang Reith, Klaus Fassbender.   

Abstract

BACKGROUND: Recently, a mobile stroke unit (MSU) was shown to facilitate acute stroke treatment directly at the emergency site. The neuroradiological expertise of the MSU is improved by its ability to detect early ischemic damage via automatic electronic (e) evaluation of CT scans using a novel software program that calculates the electronic Alberta Stroke Program Early CT Score (e-ASPECTS).
METHODS: The feasibility of integrating e-ASPECTS into an ambulance was examined, and the clinical integration and utility of the software in 15 consecutive cases evaluated.
RESULTS: Implementation of e-ASPECTS onto the MSU and into the prehospital stroke management was feasible. The values of e-ASPECTS matched with the results of conventional neuroradiologic analysis by the MSU team. The potential benefits of e-ASPECTS were illustrated by three cases. In case 1, excluding early infarct signs supported the decision to directly perform prehospital thrombolysis. In case 2, in which stroke was caused by large-vessel occlusion, the high e-ASPECTS value supported the decision to initiate intra-arterial treatment and triage the patient to a comprehensive stroke center. In case 3, the e-ASPECTS value was 10, indicating the absence of early infarct signs despite pre-existing cerebral microangiopathy and macroangiopathy, a finding indicating the program's robustness against artefacts.
CONCLUSIONS: This study on the integration of e-ASPECTS into the prehospital stroke management via a MSU showed for the first time that such integration is feasible, and aids both decision regarding the treatment option and the triage regarding the most appropriate target hospital.
© 2016 S. Karger AG, Basel.

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Mesh:

Year:  2016        PMID: 27304197     DOI: 10.1159/000446861

Source DB:  PubMed          Journal:  Cerebrovasc Dis        ISSN: 1015-9770            Impact factor:   2.762


  10 in total

1.  Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT score (ASPECTS) in the clinical routine.

Authors:  Nika Guberina; U Dietrich; A Radbruch; J Goebel; C Deuschl; A Ringelstein; M Köhrmann; C Kleinschnitz; M Forsting; C Mönninghoff
Journal:  Neuroradiology       Date:  2018-07-31       Impact factor: 2.804

Review 2.  Mobile Stroke Units: Bringing Treatment to the Patient.

Authors:  Mikel S Ehntholt; Melvin Parasram; Saad A Mir; Mackenzie P Lerario
Journal:  Curr Treat Options Neurol       Date:  2020-02-06       Impact factor: 3.598

Review 3.  Impact of mobile stroke units.

Authors:  Klaus Fassbender; Fatma Merzou; Martin Lesmeister; Silke Walter; Iris Quasar Grunwald; Andreas Ragoschke-Schumm; Thomas Bertsch; James Grotta
Journal:  J Neurol Neurosurg Psychiatry       Date:  2021-05-25       Impact factor: 10.154

4.  Systematic review of novel technology-based interventions for ischemic stroke.

Authors:  Steven Mulackal Thomas; Ellie Delanni; Brandon Christophe; Edward Sander Connolly
Journal:  Neurol Sci       Date:  2021-02-18       Impact factor: 3.830

5.  Brain computerized tomography reading in suspected acute ischemic stroke patients: what are essentials for medical students?

Authors:  Chi-Hung Liu; Cheng-Ting Hsiao; Ting-Yu Chang; Yeu-Jhy Chang; Sheng-Han Kuo; Chun-Wei Chang; Chi-Jen Chen; Chien-Fu Chen; Po-Liang Cheng; Shy-Chyi Chin; Te-Fa Chiu; Jung-Lung Hsu; Peng-Wei Hsu; Tsong-Hai Lee; Chih-Hsiang Liao; Chun-Jen Lin; Li-Han Lin; Chen-June Seak; Pi-Shan Sung; Tao-Chieh Yang; Yi-Ming Wu
Journal:  BMC Med Educ       Date:  2019-09-18       Impact factor: 2.463

6.  Guidelines for Intravenous Thrombolysis (Recombinant Tissue-type Plasminogen Activator), the Third Edition, March 2019: A Guideline from the Japan Stroke Society.

Authors:  Kazunori Toyoda; Masatoshi Koga; Yasuyuki Iguchi; Ryo Itabashi; Manabu Inoue; Yasushi Okada; Kuniaki Ogasawara; Akira Tsujino; Yasuhiro Hasegawa; Taketo Hatano; Hiroshi Yamagami; Toru Iwama; Yoshiaki Shiokawa; Yasuo Terayama; Kazuo Minematsu
Journal:  Neurol Med Chir (Tokyo)       Date:  2019-12-05       Impact factor: 1.742

Review 7.  Computer-aided imaging analysis in acute ischemic stroke - background and clinical applications.

Authors:  Yahia Mokli; Johannes Pfaff; Daniel Pinto Dos Santos; Christian Herweh; Simon Nagel
Journal:  Neurol Res Pract       Date:  2019-08-15

8.  Noninvasive and portable stroke type discrimination and progress monitoring based on a multichannel microwave transmitting-receiving system.

Authors:  Jia Xu; Jingbo Chen; Wei Yu; Haisheng Zhang; Feng Wang; Wei Zhuang; Jun Yang; Zelin Bai; Lin Xu; Jian Sun; Gui Jin; Yongjian Nian; Mingxin Qin; Mingsheng Chen
Journal:  Sci Rep       Date:  2020-12-10       Impact factor: 4.379

9.  Bedside detection of intracranial midline shift using portable magnetic resonance imaging.

Authors:  Kevin N Sheth; Matthew M Yuen; Mercy H Mazurek; Bradley A Cahn; Anjali M Prabhat; Sadegh Salehi; Jill T Shah; Samantha By; E Brian Welch; Michal Sofka; Laura I Sacolick; Jennifer A Kim; Seyedmehdi Payabvash; Guido J Falcone; Emily J Gilmore; David Y Hwang; Charles Matouk; Barbara Gordon-Kundu; Adrienne Ward Rn; Nils Petersen; Joseph Schindler; Kevin T Gobeske; Lauren H Sansing; Gordon Sze; Matthew S Rosen; W Taylor Kimberly; Prantik Kundu
Journal:  Sci Rep       Date:  2022-01-07       Impact factor: 4.996

Review 10.  How does artificial intelligence in radiology improve efficiency and health outcomes?

Authors:  Kicky G van Leeuwen; Maarten de Rooij; Steven Schalekamp; Bram van Ginneken; Matthieu J C M Rutten
Journal:  Pediatr Radiol       Date:  2021-06-12
  10 in total

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