RT Journal Article SR Electronic T1 Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning JF American Journal of Neuroradiology JO Am. J. Neuroradiol. FD American Society of Neuroradiology SP 33 OP 38 DO 10.3174/ajnr.A5889 VO 40 IS 1 A1 H. Kuang A1 M. Najm A1 D. Chakraborty A1 N. Maraj A1 S.I. Sohn A1 M. Goyal A1 M.D. Hill A1 A.M. Demchuk A1 B.K. Menon A1 W. Qiu YR 2019 UL http://www.ajnr.org/content/40/1/33.abstract AB BACKGROUND AND PURPOSE: Alberta Stroke Program Early CT Score (ASPECTS) was devised as a systematic method to assess the extent of early ischemic change on noncontrast CT (NCCT) in patients with acute ischemic stroke (AIS). Our aim was to automate ASPECTS to objectively score NCCT of AIS patients.MATERIALS AND METHODS: We collected NCCT images with a 5-mm thickness of 257 patients with acute ischemic stroke (<8 hours from onset to scans) followed by a diffusion-weighted imaging acquisition within 1 hour. Expert ASPECTS readings on DWI were used as ground truth. Texture features were extracted from each ASPECTS region of the 157 training patient images to train a random forest classifier. The unseen 100 testing patient images were used to evaluate the performance of the trained classifier. Statistical analyses on the total ASPECTS and region-level ASPECTS were conducted.RESULTS: For the total ASPECTS of the unseen 100 patients, the intraclass correlation coefficient between the automated ASPECTS method and DWI ASPECTS scores of expert readings was 0.76 (95% confidence interval, 0.67–0.83) and the mean ASPECTS difference in the Bland-Altman plot was 0.3 (limits of agreement, −3.3, 2.6). Individual ASPECTS region-level analysis showed that our method yielded κ = 0.60, sensitivity of 66.2%, specificity of 91.8%, and area under curve of 0.79 for 100 × 10 ASPECTS regions. Additionally, when ASPECTS was dichotomized (>4 and ≤4), κ = 0.78, sensitivity of 97.8%, specificity of 80%, and area under the curve of 0.89 were generated between the proposed method and expert readings on DWI.CONCLUSIONS: The proposed automated ASPECTS scoring approach shows reasonable ability to determine ASPECTS on NCCT images in patients presenting with acute ischemic stroke.AISacute ischemic strokeAUCarea under curveICCintraclass correlation coefficientIQRinterquartile range