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CT Reconstruction Levels Affect Automated and Reader‐Based ASPECTS Ratings in Acute Ischemic Stroke
Author(s) -
Seker Fatih,
Pfaff Johannes,
Nagel Simon,
Vollherbst Dominik,
Gerry Stephen,
Möhlenbruch Markus A.,
Bendszus Martin,
Herweh Christian
Publication year - 2018
Publication title -
journal of neuroimaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.822
H-Index - 64
eISSN - 1552-6569
pISSN - 1051-2284
DOI - 10.1111/jon.12562
Subject(s) - medicine , ground truth , stroke (engine) , affect (linguistics) , consistency (knowledge bases) , acute stroke , internal consistency , software , projection (relational algebra) , radiology , artificial intelligence , surgery , algorithm , mechanical engineering , linguistics , philosophy , tissue plasminogen activator , computer science , engineering , patient satisfaction , programming language
BACKGROUND AND PURPOSE We investigated whether automated and reader‐based ASPECTS in acute stroke patients are affected by different CT image reconstruction algorithms. METHODS ASPECTS were assessed by commercial software and four independent blinded readers (two residents and two consultants) from different CT reconstructions (filtered back projection and two different iterative reconstruction [IR] levels) in 43 acute stroke patients with proximal middle cerebral artery occlusion. Ground truth was provided by an expert with unrestricted data access. RESULTS The residents showed significant variations between IR levels and had a significantly lower internal consistency across different reconstructions compared to the software, which performed similarly to the consultants. The consultant as well as the software also showed different deviations from ground truth with different IR levels, which were least at IR strength level 2. CONCLUSIONS CT image postprocessing affects either automated or human ASPECTS in acute stroke patients. This effect was most pronounced in the less experienced readers, while the software had the most robust performance.