Literature DB >> 30219935

Automated ASPECT rating: comparison between the Frontier ASPECT Score software and the Brainomix software.

Juliane Goebel1, Elena Stenzel2, Nika Guberina2, Isabel Wanke2, Martin Koehrmann3, Christoph Kleinschnitz3, Lale Umutlu2, Michael Forsting2, Christoph Moenninghoff2, Alexander Radbruch2.   

Abstract

PURPOSE: Computer-aided diagnosis (CAD) appears promising in early ischemic change detection computed tomography (CT). This study aimed to compare the performance of two new CAD systems (Frontier ASPECTS Prototype and Brainomix) with two experienced readers in selected patients with suspected acute ischemic stroke.
METHODS: Retrospectively, non-contrast brain CTs of 150 patients suspected for acute middle cerebral artery ischemia were analyzed with respect to ASPECTS first separately, than in consensus by two senior radiologists, and by use of Frontier and Brainomix. Besides the fully automatic Frontier and Brainomix readings (Frontier_1, Brainomix_1), readings adjusted for the affected brain side (known by CT angiography or clinical presentation, Frontier_2, Brainomix_2) were assessed. Statistical analysis was performed by intraclass correlation and Bland-Altman statistics.
RESULTS: The score-based ASPECTS readings of Brainomix_1, Brainomix_2, both radiologists, and the expert consensus reading correlated highly (r = 0.714 to 0.841; always p < 0.001), whereas Frontier_1 and Frontier_2 correlated only lowly or moderately with both radiologists, the expert consensus reading, and Brainomix (r = 0.471 to 0.680; always p < 0.001). Bland-Altman analysis revealed lower mean ASPECT difference and standard deviation of difference for Brainomix_2 (mean difference = -0.2; SD = 1.15) compared to Frontier_2 (mean difference = 1.2; SD = 1.76). Correlation of region-based ASPECTS reading with the expert consensus reading was moderate for Brainomix_2 (r = 0.534), but only low for Frontier_2 (r = 0283; always p < 0.001).
CONCLUSION: We found high agreement in ASPECTS rating between both radiologists, expert consensus reading, and Brainomix, but only low to moderate agreement to Frontier.

Entities:  

Keywords:  ASPECTS; Artificial intelligence; Brain computed tomography; Computer-aided diagnosis; Early ischemic change detection

Mesh:

Year:  2018        PMID: 30219935     DOI: 10.1007/s00234-018-2098-x

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  14 in total

1.  Automated brain computed tomographic densitometry of early ischemic changes in acute stroke.

Authors:  Berend C Stoel; Henk A Marquering; Marius Staring; Ludo F Beenen; Cornelis H Slump; Yvo B Roos; Charles B Majoie
Journal:  J Med Imaging (Bellingham)       Date:  2015-03-24

2.  Machine Learning Will Change Medicine.

Authors:  Michael Forsting
Journal:  J Nucl Med       Date:  2017-02-02       Impact factor: 10.057

3.  e-ASPECTS software is non-inferior to neuroradiologists in applying the ASPECT score to computed tomography scans of acute ischemic stroke patients.

Authors:  Simon Nagel; Devesh Sinha; Diana Day; Wolfgang Reith; René Chapot; Panagiotis Papanagiotou; Elizabeth A Warburton; Paul Guyler; Sharon Tysoe; Klaus Fassbender; Silke Walter; Marco Essig; Jens Heidenrich; Angelos A Konstas; Michael Harrison; Michalis Papadakis; Eric Greveson; Olivier Joly; Stephen Gerry; Holly Maguire; Christine Roffe; James Hampton-Till; Alastair M Buchan; Iris Q Grunwald
Journal:  Int J Stroke       Date:  2016-12-01       Impact factor: 5.266

4.  Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score.

Authors:  P A Barber; A M Demchuk; J Zhang; A M Buchan
Journal:  Lancet       Date:  2000-05-13       Impact factor: 79.321

5.  ASPECTS (Alberta Stroke Program Early CT Score) Measurement Using Hounsfield Unit Values When Selecting Patients for Stroke Thrombectomy.

Authors:  Maxim Mokin; Christopher T Primiani; Adnan H Siddiqui; Aquilla S Turk
Journal:  Stroke       Date:  2017-05-09       Impact factor: 7.914

6.  e-ASPECTS Correlates with and Is Predictive of Outcome after Mechanical Thrombectomy.

Authors:  J Pfaff; C Herweh; S Schieber; S Schönenberger; J Bösel; P A Ringleb; M Möhlenbruch; M Bendszus; S Nagel
Journal:  AJNR Am J Neuroradiol       Date:  2017-06-08       Impact factor: 3.825

7.  Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.

Authors:  Ziad Obermeyer; Ezekiel J Emanuel
Journal:  N Engl J Med       Date:  2016-09-29       Impact factor: 91.245

8.  Sensitivity and prognostic value of early CT in occlusion of the middle cerebral artery trunk.

Authors:  R von Kummer; U Meyding-Lamadé; M Forsting; L Rosin; K Rieke; W Hacke; K Sartor
Journal:  AJNR Am J Neuroradiol       Date:  1994-01       Impact factor: 3.825

9.  STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies.

Authors:  Patrick M Bossuyt; Johannes B Reitsma; David E Bruns; Constantine A Gatsonis; Paul P Glasziou; Les Irwig; Jeroen G Lijmer; David Moher; Drummond Rennie; Henrica C W de Vet; Herbert Y Kressel; Nader Rifai; Robert M Golub; Douglas G Altman; Lotty Hooft; Daniël A Korevaar; Jérémie F Cohen
Journal:  BMJ       Date:  2015-10-28

Review 10.  Deep into the Brain: Artificial Intelligence in Stroke Imaging.

Authors:  Eun-Jae Lee; Yong-Hwan Kim; Namkug Kim; Dong-Wha Kang
Journal:  J Stroke       Date:  2017-09-29       Impact factor: 6.967

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  3 in total

1.  Innovative use of artificial intelligence and digital communication in acute stroke pathway in response to COVID-19.

Authors:  Kiruba Nagaratnam; George Harston; Enrico Flossmann; Clara Canavan; Rui Carmelo Geraldes; Chani Edwards
Journal:  Future Healthc J       Date:  2020-06

Review 2.  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

3.  Automated detection and segmentation of intracranial hemorrhage suspect hyperdensities in non-contrast-enhanced CT scans of acute stroke patients.

Authors:  N Schmitt; Y Mokli; C S Weyland; S Gerry; C Herweh; P A Ringleb; S Nagel
Journal:  Eur Radiol       Date:  2021-11-13       Impact factor: 7.034

  3 in total

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