e-ASPECTS software improves interobserver agreement and accuracy of interpretation of aspects score Article Swipe
Waleed Brinjikji
,
Mehdi Abbasi
,
Catherine Arnold
,
John C. Benson
,
Sherry A Braksick
,
Norbert G. Campeau
,
Carrie M. Carr
,
Petrice M. Cogswell
,
James P. Klaas
,
Greta B. Liebo
,
Jason T. Little
,
Patrick H. Luetmer
,
Steven A. Messina
,
Alex A. Nagelschneider
,
Kara M. Schwartz
,
Christopher P. Wood
,
Deena M. Nasr
,
David F. Kallmes
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1177/15910199211011861
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1177/15910199211011861
Introduction There is increased interest in the use of artificial intelligence-based (AI) software packages in the evaluation of neuroimaging studies for acute ischemic stroke. We studied whether, compared to standard image interpretation without AI, Brainomix e-ASPECTS software improved interobserver agreement and accuracy in detecting ASPECTS regions affected in anterior circulation LVO. Methods We included 60 consecutive patients with anterior circulation LVO who had TICI 3 revascularization within 60 minutes of their baseline CT. A total of 16 readers, including senior neuroradiologists, junior neuroradiologists and vascular neurologists participated. Readers interpreted CT scans on independent workstations and assessed final ASPECTS and evaluated whether each individual ASPECTS region was affected. Two months later, readers again evaluated the CT scans, but with assistance of e-ASPECTS software. We assessed interclass correlation coefficient for total ASPECTS and interobserver agreement with Fleiss’ Kappa for each ASPECTS region with and without assistance of the e-ASPECTS. We also assessed accuracy for the readers with and without e-ASPECTS assistance. In our assessment of accuracy, ground truth was the 24 hour CT in this cohort of patients who had prompt and complete revascularization. Results Interclass correlation coefficient for total ASPECTS without e-ASPECTS assistance was 0.395, indicating fair agreement compared, to 0.574 with e-ASPECTS assistance, indicating good agreement (P < 0.01). There was significant improvement in inter-rater agreement with e-ASPECTS assistance for each individual region with the exception of M6 and caudate. The e-ASPECTS software had higher accuracy than the overall cohort of readers (with and without e-ASPECTS assistance) for every region except the caudate. Conclusions Use of Brainomix e-ASPECTS software resulted in significant improvements in inter-rater agreement and accuracy of ASPECTS score evaluation in a large group of neuroradiologists and neurologists. e-ASPECTS software was more predictive of final infarct/ASPECTS than the overall group interpreting the CT scans with and without e-ASPECTS assistance.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/15910199211011861
- OA Status
- green
- Cited By
- 40
- References
- 19
- Related Works
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- OpenAlex ID
- https://openalex.org/W3153843819
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W3153843819Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1177/15910199211011861Digital Object Identifier
- Title
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e-ASPECTS software improves interobserver agreement and accuracy of interpretation of aspects scoreWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-04-14Full publication date if available
- Authors
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Waleed Brinjikji, Mehdi Abbasi, Catherine Arnold, John C. Benson, Sherry A Braksick, Norbert G. Campeau, Carrie M. Carr, Petrice M. Cogswell, James P. Klaas, Greta B. Liebo, Jason T. Little, Patrick H. Luetmer, Steven A. Messina, Alex A. Nagelschneider, Kara M. Schwartz, Christopher P. Wood, Deena M. Nasr, David F. KallmesList of authors in order
- Landing page
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https://doi.org/10.1177/15910199211011861Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.ncbi.nlm.nih.gov/pmc/articles/8673896Direct OA link when available
- Concepts
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Medicine, Interpretation (philosophy), Software, Medical physics, Nuclear medicine, Radiology, Computer science, Programming languageTop concepts (fields/topics) attached by OpenAlex
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40Total citation count in OpenAlex
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2025: 11, 2024: 6, 2023: 9, 2022: 14Per-year citation counts (last 5 years)
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19Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.caudate. | 229, 252 |
| abstract_inverted_index.compared | 27 |
| abstract_inverted_index.complete | 180 |
| abstract_inverted_index.improved | 37 |
| abstract_inverted_index.included | 53 |
| abstract_inverted_index.interest | 4 |
| abstract_inverted_index.ischemic | 22 |
| abstract_inverted_index.packages | 13 |
| abstract_inverted_index.patients | 56, 175 |
| abstract_inverted_index.readers, | 77 |
| abstract_inverted_index.resulted | 259 |
| abstract_inverted_index.software | 12, 36, 232, 258, 281 |
| abstract_inverted_index.standard | 29 |
| abstract_inverted_index.vascular | 84 |
| abstract_inverted_index.whether, | 26 |
| abstract_inverted_index.Brainomix | 34, 256 |
| abstract_inverted_index.Fleiss’ | 134 |
| abstract_inverted_index.accuracy, | 163 |
| abstract_inverted_index.affected. | 106 |
| abstract_inverted_index.agreement | 39, 132, 196, 205, 215, 265 |
| abstract_inverted_index.compared, | 197 |
| abstract_inverted_index.detecting | 43 |
| abstract_inverted_index.e-ASPECTS | 35, 120, 157, 190, 201, 217, 231, 245, 257, 280, 299 |
| abstract_inverted_index.evaluated | 99, 112 |
| abstract_inverted_index.exception | 225 |
| abstract_inverted_index.including | 78 |
| abstract_inverted_index.increased | 3 |
| abstract_inverted_index.software. | 121 |
| abstract_inverted_index.Interclass | 183 |
| abstract_inverted_index.artificial | 9 |
| abstract_inverted_index.assessment | 161 |
| abstract_inverted_index.assistance | 118, 143, 191, 218 |
| abstract_inverted_index.e-ASPECTS. | 146 |
| abstract_inverted_index.evaluation | 16, 271 |
| abstract_inverted_index.indicating | 194, 203 |
| abstract_inverted_index.individual | 102, 221 |
| abstract_inverted_index.interclass | 124 |
| abstract_inverted_index.predictive | 284 |
| abstract_inverted_index.Conclusions | 253 |
| abstract_inverted_index.assistance) | 246 |
| abstract_inverted_index.assistance, | 202 |
| abstract_inverted_index.assistance. | 158, 300 |
| abstract_inverted_index.circulation | 49, 59 |
| abstract_inverted_index.coefficient | 126, 185 |
| abstract_inverted_index.consecutive | 55 |
| abstract_inverted_index.correlation | 125, 184 |
| abstract_inverted_index.improvement | 212 |
| abstract_inverted_index.independent | 92 |
| abstract_inverted_index.inter-rater | 214, 264 |
| abstract_inverted_index.interpreted | 88 |
| abstract_inverted_index.significant | 211, 261 |
| abstract_inverted_index.Introduction | 0 |
| abstract_inverted_index.improvements | 262 |
| abstract_inverted_index.interpreting | 292 |
| abstract_inverted_index.neuroimaging | 18 |
| abstract_inverted_index.neurologists | 85 |
| abstract_inverted_index.workstations | 93 |
| abstract_inverted_index.interobserver | 38, 131 |
| abstract_inverted_index.neurologists. | 279 |
| abstract_inverted_index.participated. | 86 |
| abstract_inverted_index.interpretation | 31 |
| abstract_inverted_index.infarct/ASPECTS | 287 |
| abstract_inverted_index.neuroradiologists | 82, 277 |
| abstract_inverted_index.revascularization | 65 |
| abstract_inverted_index.intelligence-based | 10 |
| abstract_inverted_index.neuroradiologists, | 80 |
| abstract_inverted_index.revascularization. | 181 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| corresponding_author_ids | https://openalex.org/A5051049858 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 18 |
| corresponding_institution_ids | https://openalex.org/I4210125099 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/17 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile.value | 0.95420735 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |