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Index by author

April 01, 2024; Volume 45,Issue 4

  1. Yamin, Ghiam

    1. Brain Tumor Imaging
      Open Access
      Arterial Spin-Labeling and DSC Perfusion Metrics Improve Agreement in Neuroradiologists’ Clinical Interpretations of Posttreatment High-Grade Glioma Surveillance MR Imaging—An Institutional Experience
      Ghiam Yamin, Eric Tranvinh, Bryan A. Lanzman, Elizabeth Tong, Syed S. Hashmi, Chirag B. Patel and Michael Iv
      American Journal of Neuroradiology April 2024, 45 (4) 453-460; DOI: https://doi.org/10.3174/ajnr.A8190

  2. Yang, Guang

    1. EDITOR'S CHOICENeurovascular/Stroke Imaging
      A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes
      Yongkai Liu, Preya Shah, Yannan Yu, Jai Horsey, Jiahong Ouyang, Bin Jiang, Guang Yang, Jeremy J. Heit, Margy E. McCullough-Hicks, Stephen M. Hugdal, Max Wintermark, Patrik Michel, David S. Liebeskind, Maarten G. Lansberg, Gregory W. Albers and Greg Zaharchuk
      American Journal of Neuroradiology April 2024, 45 (4) 406-411; DOI: https://doi.org/10.3174/ajnr.A8140

      The authors in this study used a deep learning-based predictive model (DLPD) that incorporated DWI and clinical data from the acute period to predict 90-day mRS outcomes and compared its predictions with those made by physicians. The results showed that the clinical and imaging fused deep learning model is noninferior to expert physicians in predicting specific mRS outcomes and unfavorable prognoses.

  3. Yang, YanXing

    1. Brain Tumor Imaging
      Improved Detection of Target Metabolites in Brain Tumors with Intermediate TE, High SNR, and High Bandwidth Spin-Echo Sequence at 5T
      Wenbo Sun, Dan Xu, YanXing Yang, Linfei Wen, Hanjiang Yu, Yaowen Xing, Xiaopeng Song, Huan Li and Haibo Xu
      American Journal of Neuroradiology April 2024, 45 (4) 461-467; DOI: https://doi.org/10.3174/ajnr.A8150

  4. Yokka, Akira

    1. Neurointervention
      Evaluation of Conditions for the Development of Cryogenic Spinal Cord Injury Using a Canine Model: An Experimental Study on the Safety of Cryoablation for Metastatic Spinal Tumors
      Motoya Kobayashi, Satoshi Kato, Satoru Demura, Noriaki Yokogawa, Akira Yokka, Yusuke Nakade, Ryohei Annen, Toshifumi Gabata and Hiroyuki Tsuchiya
      American Journal of Neuroradiology April 2024, 45 (4) 424-431; DOI: https://doi.org/10.3174/ajnr.A8151

  5. Yokogawa, Noriaki

    1. Neurointervention
      Evaluation of Conditions for the Development of Cryogenic Spinal Cord Injury Using a Canine Model: An Experimental Study on the Safety of Cryoablation for Metastatic Spinal Tumors
      Motoya Kobayashi, Satoshi Kato, Satoru Demura, Noriaki Yokogawa, Akira Yokka, Yusuke Nakade, Ryohei Annen, Toshifumi Gabata and Hiroyuki Tsuchiya
      American Journal of Neuroradiology April 2024, 45 (4) 424-431; DOI: https://doi.org/10.3174/ajnr.A8151

  6. Yu, Hanjiang

    1. Brain Tumor Imaging
      Improved Detection of Target Metabolites in Brain Tumors with Intermediate TE, High SNR, and High Bandwidth Spin-Echo Sequence at 5T
      Wenbo Sun, Dan Xu, YanXing Yang, Linfei Wen, Hanjiang Yu, Yaowen Xing, Xiaopeng Song, Huan Li and Haibo Xu
      American Journal of Neuroradiology April 2024, 45 (4) 461-467; DOI: https://doi.org/10.3174/ajnr.A8150

  7. Yu, Yannan

    1. EDITOR'S CHOICENeurovascular/Stroke Imaging
      A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes
      Yongkai Liu, Preya Shah, Yannan Yu, Jai Horsey, Jiahong Ouyang, Bin Jiang, Guang Yang, Jeremy J. Heit, Margy E. McCullough-Hicks, Stephen M. Hugdal, Max Wintermark, Patrik Michel, David S. Liebeskind, Maarten G. Lansberg, Gregory W. Albers and Greg Zaharchuk
      American Journal of Neuroradiology April 2024, 45 (4) 406-411; DOI: https://doi.org/10.3174/ajnr.A8140

      The authors in this study used a deep learning-based predictive model (DLPD) that incorporated DWI and clinical data from the acute period to predict 90-day mRS outcomes and compared its predictions with those made by physicians. The results showed that the clinical and imaging fused deep learning model is noninferior to expert physicians in predicting specific mRS outcomes and unfavorable prognoses.

  8. Yu, ZeChen

    1. Neuroimaging Physics/Functional Neuroimaging/CT and MRI Technology
      Visualizing the Habenula Using 3T High-Resolution MP2RAGE and QSM: A Preliminary Study
      BingYang Bian, Lin Hou, YaTing Chai, YueLuan Jiang, XingChen Pan, Yang Sun, HongChao Wang, DongDong Qiu, ZeChen Yu, Hua Zhao, HuiMao Zhang, FanYang Meng and Lei Zhang
      American Journal of Neuroradiology April 2024, 45 (4) 504-510; DOI: https://doi.org/10.3174/ajnr.A8156
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