Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning

References

1. 1.↵
   2. Barber PA,
   3. Demchuk AM,
   4. Zhang J, et al

   . 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. Lancet 2000;355:1670–74 doi:10.1016/S0140-6736(00)02237-6 pmid:10905241

   CrossRefPubMedWeb of Science
2. 2.↵
   2. Pexman JW,
   3. Barber PA,
   4. Hill MD, et al

   . Use of the Alberta Stroke Program Early CT Score (ASPECTS) for assessing CT scans in patients with acute stroke. AJNR Am J Neuroradiol 2001;22:1534–42 pmid:11559501

   Abstract/FREE Full Text
3. 3.↵
   2. Aoki J,
   3. Kimura K,
   4. Shibazaki K, et al

   . DWI-ASPECTS as a predictor of dramatic recovery after intravenous recombinant tissue plasminogen activator administration in patients with middle cerebral artery occlusion. Stroke 2013;44:534–37 doi:10.1161/STROKEAHA.112.675470 pmid:23212169

   Abstract/FREE Full Text
4. 4.↵
   2. Nezu T,
   3. Koga M,
   4. Kimura K, et al

   . Pretreatment ASPECTS on DWI predicts 3-month outcome following rt-PA: SAMURAI rt-PA Registry. Neurology 2010;75:555–61 doi:10.1212/WNL.0b013e3181eccf78 pmid:20697108

   CrossRefPubMed
5. 5.↵
   2. Goyal M,
   3. Demchuk AM,
   4. Menon BK, et al

   ; ESCAPE Trial Investigators. Randomized assessment of rapid endovascular treatment of ischemic stroke. N Engl J Med 2015;372:1019–30 doi:10.1056/NEJMoa1414905 pmid:25671798

   CrossRefPubMed
6. 6.↵
   2. Hill MD,
   3. Rowley HA,
   4. Adler F, et al

   ; PROACT-II Investigators. Selection of acute ischemic stroke patients for intra-arterial thrombolysis with pro-urokinase by using ASPECTS. Stroke 2003;34:1925–31 doi:10.1161/01.STR.0000082483.37127.D0 pmid:12843342

   Abstract/FREE Full Text
7. 7.↵
   2. Okazaki S,
   3. Moriwaki H,
   4. Minematsu K, et al

   . Extremely early computed tomography signs in hyperacute ischemic stroke as a predictor of parenchymal hematoma. Cerebrovasc Dis 2008;25:241–46 doi:10.1159/000113862 pmid:18216466

   CrossRefPubMed
8. 8.↵
   2. Yoo AJ,
   3. Berkhemer OA,
   4. Fransen PS, et al

   ; MR CLEAN investigators. Effect of baseline Alberta Stroke Program Early CT Score on safety and efficacy of intra-arterial treatment: a subgroup analysis of a randomised phase 3 trial (MR CLEAN). Lancet Neurol 2016;15:685–94 doi:10.1016/S1474-4422(16)00124-1 pmid:27302238

   CrossRefPubMed
9. 9.↵
   2. Goyal M,
   3. Menon BK,
   4. van Zwam WH, et al

   ; HERMES collaborators. Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials. Lancet 2016;387:1723–31 doi:10.1016/S0140-6736(16)00163-X pmid:26898852

   CrossRefPubMed
10. 10.↵
    2. Grotta JC,
    3. Chiu D,
    4. Lu M, et al

    . Agreement and variability in the interpretation of early CT changes in stroke patients qualifying for intravenous rtPA therapy. Stroke 1999;30:1528–33 doi:10.1161/01.STR.30.8.1528 pmid:10436095

    Abstract/FREE Full Text
11. 11.↵
    2. Menon B,
    3. Smith E,
    4. Modi J, et al

    . Regional leptomeningeal score on CT angiography predicts clinical and imaging outcomes in patients with acute anterior circulation occlusions. AJNR Am J Neuroradiol 2011;32:1640–45 doi:10.3174/ajnr.A2564 pmid:21799045

    Abstract/FREE Full Text
12. 12.↵
    2. Menon BK,
    3. Puetz V,
    4. Kochar P, et al

    . ASPECTS and other neuroimaging scores in the triage and prediction of outcome in acute stroke patients. Neuroimaging Clin N Am 2011;21:407–23 doi:10.1016/j.nic.2011.01.007 pmid:21640307

    CrossRefPubMed
13. 13.↵
    2. Bentley P,
    3. Ganesalingam J,
    4. Carlton Jones AL, et al

    . Prediction of stroke thrombolysis outcome using CT brain machine learning. Neuroimaging Clin 2014;4:635–40 doi:10.1016/j.nicl.2014.02.003 pmid:24936414

    CrossRefPubMed
14. 14.↵
    2. Przelaskowski A,
    3. Sklinda K,
    4. Bargieł P, et al

    . Improved early stroke detection: wavelet-based perception enhancement of computerized tomography exams. Comput Biol Med 2007;37:524–33 doi:10.1016/j.compbiomed.2006.08.004 pmid:16999952

    CrossRefPubMed
15. 15.↵
    2. Rajini NH,
    3. Bhavani R

    . Computer aided detection of ischemic stroke using segmentation and texture features. Measurement 2013;46:1865–74 doi:10.1016/j.measurement.2013.01.010

    CrossRef
16. 16.↵
    2. Tang FH,
    3. Ng DK,
    4. Chow DH

    . An image feature approach for computer-aided detection of ischemic stroke. Comput Biol Med 2011;41:529–36 doi:10.1016/j.compbiomed.2011.05.001 pmid:21605853

    CrossRefPubMed
17. 17.↵
    2. Chawla M,
    3. Sharma S,
    4. Sivaswamy J, et al

    . A method for automatic detection and classification of stroke from brain CT images. Conf Proc IEEE Eng Med Biol Soc 2009;2009:3581–84 pmid:19965232

    PubMed
18. 18.↵
    2. Hampton-Till J,
    3. Harrison M,
    4. Kühn AL, et al

    . Automated quantification of stroke damage on brain computed tomography scans: e-ASPECTS. EMJ 2015;3:69–74 https://www.emjreviews.com/neurology/article/automated-quantification-of-stroke-damage-on-brain-computed-tomography-scans-e-aspects/. Accessed August 6, 2015.
19. 19.↵
    2. Nagel S,
    3. Sinha D,
    4. Day D, et al

    . e-ASPECTS software is non-inferior to neuroradiologists in applying the ASPECT score to computed tomography scans of acute ischemic stroke patients. Int J Stroke 2017;12:615–22 doi:10.1177/1747493016681020 pmid:27899743

    CrossRefPubMed
20. 20.↵
    2. Herweh C,
    3. Ringleb PA,
    4. Rauch G, et al

    . Performance of e-ASPECTS software in comparison to that of stroke physicians on assessing CT scans of acute ischemic stroke patients. Int J Stroke 2016;11:438–45 doi:10.1177/1747493016632244 pmid:26880058

    CrossRefPubMed
21. 21.↵
    2. Stoel BC,
    3. Marquering HA,
    4. Staring M, et al

    . Automated brain computed tomographic densitometry of early ischemic changes in acute stroke. J Med Imaging (Bellingham) 2015;2:014004 doi:10.1117/1.JMI.2.1.014004 pmid:26158082

    CrossRefPubMed
22. 22.↵
    2. Shieh Y,
    3. Chang CH

    . Automated ASPECTS scoring system as a clinical support system for acute stroke care. In: Proceedings of 2012 IEEE-Engineering in Medicine and Biology Society International Conference on Biomedical and Health Informatics, Hong Kong, China. January 5–7, 2012:691–94
23. 23.↵
    2. Shieh Y,
    3. Chang CH,
    4. Shieh M, et al

    . Computer-aided diagnosis of hyperacute stroke with thrombolysis decision support using a contralateral comparative method of CT image analysis. J Digit Imaging 2014;27:392–406 doi:10.1007/s10278-013-9672-x pmid:4464216

    CrossRefPubMed
24. 24.↵
    2. Su JL,
    3. Chan L,
    4. Huang SY

    . Development of computer aids ASPECTS system for acute ischemic stroke patient: a preliminary study. In: Proceedings of the 2017 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences, Pantang, Malaysia. December 7, 2017:203–07
25. 25.↵
    2. Inoue M,
    3. Olivot JM,
    4. Labreuche J, et al

    . Impact of diffusion-weighted imaging Alberta stroke program early computed tomography score on the success of endovascular reperfusion therapy. Stroke 2014;45:1992–98 doi:10.1161/STROKEAHA.114.005084 pmid:24923724

    Abstract/FREE Full Text
26. 26.↵
    2. Obuchowski NA

    . Nonparametric analysis of clustered ROC curve data. Biometrics 1997;53:567–78 pmid:9192452

    CrossRefPubMedWeb of Science
27. 27.↵
    2. Criminisi A,
    3. Shotton J

    . Decision Forests for Computer Vision and Medical Image Analysis. London; Springer-Verlag; 2013
28. 28.↵
    2. Maier O,
    3. Schröder C,
    4. Forkert ND, et al

    . Classifiers for ischemic stroke lesion segmentation: a comparison study. PLoS One 2015;10:e0145118 doi:10.1371/journal.pone.0145118 pmid:26672989

    CrossRefPubMed
29. 29.↵
    2. Aljabar P,
    3. Heckemann RA,
    4. Hammers A, et al

    . Multi-atlas-based segmentation of brain images: atlas selection and its effect on accuracy. Neuroimage 2009;46:726–38 doi:10.1016/j.neuroimage.2009.02.018 pmid:19245840

    CrossRefPubMedWeb of Science