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A novel fully automated method for measuring ASPECTS to improve stroke diagnosis: Comparison to traditional ASPECTS.

Authors :
Gohla, Georg
Schwarz, Ricarda
Bier, Georg
Estler, Arne
Bongers, Malte N.
Ditt, Hendrik
Fritz, Jan
Kemmling, André
Ernemann, Ulrike
Horger, Marius
Source :
Journal of Neuroimaging; Jan/Feb2024, Vol. 34 Issue 1, p145-151, 7p
Publication Year :
2024

Abstract

Background and Purpose: To compare the accuracy of subjective Alberta Stroke Program Early CT Score (sASPECTS) evaluation and that of an automated prototype software (aASPECTS) on nonenhanced CT (NECT) in patients with early anterior territory stroke and controls using side‐to‐side quantification of hypoattenuated brain areas. Methods: We retrospectively analyzed the NECT scans of 42 consecutive patients with ischemic stroke before reperfusion and 42 controls using first sASPECTS and subsequently aASPECTS. We assessed the differences in Alberta Stroke Program Early CT Score (ASPECTS) and calculated the sensitivity and specificity of NECT with CT perfusion, whereas cerebral blood volume (CBV) served as the reference standard for brain infarction. Results: The clot was located in the middle cerebral artery (MCA) in 47.6% of cases and the internal carotid artery (ICA) in 28.6% of cases. Ten cases presented combined ICA and MCA occlusions. The stroke was right sided in 52.4% of cases and left sided in 47.6%. Reader‐based NECT analysis yielded a median sASPECTS of 10. The median CBV‐based ASPECTS was 7. Compared to the area of decreased CBV, sASPECTS yielded a sensitivity of 12.5% and specificity of 86.8%. The software prototype (aASPECTS) yielded an overall sensitivity of 65.5% and a specificity of 92.2%. The interreader agreement for ASPECTS evaluation of admission NECT and follow‐up CT was almost perfect (κ =.93). The interreader agreement of the CBV color map evaluation was substantial (κ =.77). Conclusions: aASPECTS of NECT can outperform sASPECTS for stroke detection. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10512284
Volume :
34
Issue :
1
Database :
Complementary Index
Journal :
Journal of Neuroimaging
Publication Type :
Academic Journal
Accession number :
174713173
Full Text :
https://doi.org/10.1111/jon.13159