Van Hedent S, Hokamp NG, Laukamp KR, et al. Differentiation of Hemorrhage from Iodine Using Spectral Detector CT: A Phantom Study. AJNR Am J Neuroradiol. 2018;39(12):2205-2210. https://doi.org/10.3174/ajnr.A5872

Article  PubMed  PubMed Central  Google Scholar 

Mangesius S, Janjic T, Steiger R, et al. Dual-energy computed tomography in acute ischemic stroke: state-of-the-art. Eur Radiol. 2021;31(6):4138-4147. https://doi.org/10.1007/s00330-020-07543-9

Article  PubMed  Google Scholar 

Gaddam DS, Dattwyler M, Fleiter TR, Bodanapally UK. Principles and Applications of Dual Energy Computed Tomography in Neuroradiology. Semin Ultrasound CT MR. 2021;42(5):418-433. https://doi.org/10.1053/j.sult.2021.07.001

Article  PubMed  Google Scholar 

Hixson HR, Leiva-Salinas C, Sumer S, Patrie J, Xin W, Wintermark M. Utilizing dual energy CT to improve CT diagnosis of posterior fossa ischemia. J Neuroradiol. 2016;43(5):346-352. https://doi.org/10.1016/j.neurad.2016.04.001

Article  CAS  PubMed  Google Scholar 

Mohammed MF, Marais O, Min A, et al. Unenhanced Dual-Energy Computed Tomography: Visualization of Brain Edema. Invest Radiol. 2018;53(2):63-69. https://doi.org/10.1097/RLI.0000000000000413

Article  PubMed  Google Scholar 

van Ommen F, Dankbaar JW, Zhu G, et al. Virtual monochromatic dual-energy CT reconstructions improve detection of cerebral infarct in patients with suspicion of stroke. Neuroradiology. 2021;63(1):41-49. https://doi.org/10.1007/s00234-020-02492-y

Article  PubMed  Google Scholar 

Taguchi K, Itoh T, Fuld MK, Fournie E, Lee O, Noguchi K. “X-Map 2.0” for Edema Signal Enhancement for Acute Ischemic Stroke Using Non–Contrast-Enhanced Dual-Energy Computed Tomography. Invest Radiol. 2018;53(7):432–439. https://doi.org/10.1097/RLI.0000000000000461

Nogueira RG, Jadhav AP, Haussen DC, et al. Thrombectomy 6 to 24 Hours after Stroke with a Mismatch between Deficit and Infarct. New England Journal of Medicine. 2018;378(1):11-21. https://doi.org/10.1056/NEJMoa1706442

Article  PubMed  Google Scholar 

Albers GW, Marks MP, Kemp S, et al. Thrombectomy for Stroke at 6 to 16 Hours with Selection by Perfusion Imaging. N Engl J Med. 2018;378(8):708-718. https://doi.org/10.1056/NEJMoa1713973

Article  PubMed  PubMed Central  Google Scholar 

Ted. W. Post, ed. Mechanical thrombectomy for acute ischemic stroke. In: UpToDate. ; 2023.

Vagal A, Wintermark M, Nael K, et al. Automated CT perfusion imaging for acute ischemic stroke: Pearls and pitfalls for real-world use. Neurology. 2019;93(20):888-898. https://doi.org/10.1212/WNL.0000000000008481

Article  PubMed  Google Scholar 

Kamel PI, Yi PH, Sair HI, Lin CT. Prediction of coronary artery calcium and cardiovascular risk on chest radiographs using deep learning. Radiol Cardiothorac Imaging. 2021;3(3). https://doi.org/10.1148/ryct.2021200486

Olivier A, Moal O, Moal B, et al. Active learning strategy and hybrid training for infarct segmentation on diffusion MRI with a U-shaped network. Journal of Medical Imaging. 2019;6(04):1. https://doi.org/10.1117/1.JMI.6.4.044001

Article  Google Scholar 

Wong KK, Cummock JS, Li G, et al. Automatic Segmentation in Acute Ischemic Stroke: Prognostic Significance of Topological Stroke Volumes on Stroke Outcome. Stroke. 2022;53(9):2896-2905. https://doi.org/10.1161/STROKEAHA.121.037982

Article  CAS  PubMed  Google Scholar 

Cui L, Fan Z, Yang Y, et al. Deep Learning in Ischemic Stroke Imaging Analysis: A Comprehensive Review. Biomed Res Int. 2022;2022:1-15. https://doi.org/10.1155/2022/2456550

Article  Google Scholar 

Liu CF, Hsu J, Xu X, et al. Deep learning-based detection and segmentation of diffusion abnormalities in acute ischemic stroke. Communications Medicine. 2021;1(1):61. https://doi.org/10.1038/s43856-021-00062-8

Article  PubMed  PubMed Central  Google Scholar 

Chen L, Bentley P, Rueckert D. Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks. Neuroimage Clin. 2017;15:633-643. https://doi.org/10.1016/j.nicl.2017.06.016

Article  PubMed  PubMed Central  Google Scholar 

Woo I, Lee A, Jung SC, et al. Fully Automatic Segmentation of Acute Ischemic Lesions on Diffusion-Weighted Imaging Using Convolutional Neural Networks: Comparison with Conventional Algorithms. Korean J Radiol. 2019;20(8):1275-1284. https://doi.org/10.3348/kjr.2018.0615

Article  PubMed  PubMed Central  Google Scholar 

Kamel P, Kanhere A, Kulkarni P, et al. Optimizing Acute Stroke Segmentation on MRI Using Deep Learning: Self-Configuring Neural Networks Provide High Performance Using Only DWI Sequences. Journal of Imaging Informatics in Medicine. Published online August 13, 2024. https://doi.org/10.1007/s10278-024-00994-2

Ostmeier S, Axelrod B, Verhaaren BFJ, et al. Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists. Sci Rep. 2023;13(1):16153. https://doi.org/10.1038/s41598-023-42961-x

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hernandez Petzsche MR, de la Rosa E, Hanning U, et al. ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset. Sci Data. 2022;9(1):762. https://doi.org/10.1038/s41597-022-01875-5

Article  PubMed  PubMed Central  Google Scholar 

Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2021;18(2):203-211. https://doi.org/10.1038/s41592-020-01008-z

Article  CAS  PubMed  Google Scholar 

pynetdicom. 2022. Accessed December 21, 2022. https://pydicom.github.io/pynetdicom/stable/#

RSNA MIRC Clinical Trials Processor. 2022. Accessed December 21, 2022. https://mircwiki.rsna.org/index.php?title=MIRC_CTP

dicom2nifti. Accessed July 2, 2023. https://github.com/icometrix/dicom2nifti

Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17(3):143-155. https://doi.org/10.1002/hbm.10062

Article  PubMed  PubMed Central  Google Scholar 

Rohlfing T, Zahr NM, Sullivan E V, Pfefferbaum A. The SRI24 multichannel atlas of normal adult human brain structure. Hum Brain Mapp. 2010;31(5):798-819. https://doi.org/10.1002/hbm.20906

Article  PubMed  Google Scholar 

ANTsPy. Accessed December 26, 2022. https://antspyx.readthedocs.io/en/latest/index.html

Bodanapally UK, Archer-Arroyo KL, Dreizin D, et al. Dual-Energy Computed Tomography Imaging of Head: Virtual High-Energy Monochromatic (190 keV) Images Are More Reliable Than Standard 120 kV Images for Detecting Traumatic Intracranial Hemorrhages. J Neurotrauma. 2019;36(8):1375-1381. https://doi.org/10.1089/neu.2018.5985

Article  PubMed  Google Scholar 

Zimmerman WD, Pergakis M, Ahmad G, et al. Iodine-based dual-energy CT predicts early neurological decline from cerebral edema after large hemispheric infarction. Res Sq. Published online November 10, 2023. https://doi.org/10.21203/rs.3.rs-3508427/v1

Nikolov S, Blackwell S, Zverovitch A, et al. Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study. J Med Internet Res. 2021;23(7):e26151. https://doi.org/10.2196/26151

Article  PubMed  PubMed Central  Google Scholar 

Surface Distance Metrics. Accessed August 29, 2024. https://github.com/google-deepmind/surface-distance