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AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Index by author

January 01, 2020; Volume 41,Issue 1
  • A
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  • G
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  • K
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  1. Baek, J.H.

    1. Head and Neck Imaging
      You have access
      CT and MRI Findings of Glomangiopericytoma in the Head and Neck: Case Series Study and Systematic Review
      C.H. Suh, J.H. Lee, M.K. Lee, S.J. Cho, S.R. Chung, Y.J. Choi and J.H. Baek
      American Journal of Neuroradiology January 2020, 41 (1) 155-159; DOI: https://doi.org/10.3174/ajnr.A6336
  2. Balchandani, P.

    1. Adult Brain
      Open Access
      Emerging Use of Ultra-High-Field 7T MRI in the Study of Intracranial Vascularity: State of the Field and Future Directions
      J.W. Rutland, B.N. Delman, C.M. Gill, C. Zhu, R.K. Shrivastava and P. Balchandani
      American Journal of Neuroradiology January 2020, 41 (1) 2-9; DOI: https://doi.org/10.3174/ajnr.A6344
  3. Banerjee, M.

    1. FELLOWS' JOURNAL CLUBAdult Brain
      Open Access
      Vessel Wall Thickening and Enhancement in High-Resolution Intracranial Vessel Wall Imaging: A Predictor of Future Ischemic Events in Moyamoya Disease
      A. Kathuveetil, P.N. Sylaja, S. Senthilvelan, K. Chandrasekharan, M. Banerjee and B. Jayanand Sudhir
      American Journal of Neuroradiology January 2020, 41 (1) 100-105; DOI: https://doi.org/10.3174/ajnr.A6360

      Twenty-nine patients with Moyamoya disease were enrolled in this study. The median age at symptom onset was 12 years. A total of 166 steno-occlusive lesions were detected by high-resolution intracranial vessel wall imaging. Eleven lesions with concentric wall thickening (6.6%) were noted in 9 patients. Ten concentric contrast-enhancing lesions were observed in 8 patients, of which 4 lesions in 3 patients showed grade II enhancement. The presence of contrast enhancement and wall thickening showed a statistically significant association with ischemic events within 3 months before and after the vessel wall imaging. The presence of wall thickening and enhancement may predict future ischemic events in patients with MMD.

  4. Bartha-doering, L.

    1. Functional
      You have access
      Lesion-Specific Language Network Alterations in Temporal Lobe Epilepsy
      O. Foesleitner, K.-H. Nenning, L. Bartha-Doering, C. Baumgartner, E. Pataraia, D. Moser, M. Schwarz, V. Schmidbauer, J.A. Hainfellner, T. Czech, C. Dorfer, G. Langs, D. Prayer, S. Bonelli and G. Kasprian
      American Journal of Neuroradiology January 2020, 41 (1) 147-154; DOI: https://doi.org/10.3174/ajnr.A6350
  5. Baumgartner, C.

    1. Functional
      You have access
      Lesion-Specific Language Network Alterations in Temporal Lobe Epilepsy
      O. Foesleitner, K.-H. Nenning, L. Bartha-Doering, C. Baumgartner, E. Pataraia, D. Moser, M. Schwarz, V. Schmidbauer, J.A. Hainfellner, T. Czech, C. Dorfer, G. Langs, D. Prayer, S. Bonelli and G. Kasprian
      American Journal of Neuroradiology January 2020, 41 (1) 147-154; DOI: https://doi.org/10.3174/ajnr.A6350
  6. Bay, C.

    1. FELLOWS' JOURNAL CLUBAdult Brain
      Open Access
      Deep Transfer Learning and Radiomics Feature Prediction of Survival of Patients with High-Grade Gliomas
      W. Han, L. Qin, C. Bay, X. Chen, K.-H. Yu, N. Miskin, A. Li, X. Xu and G. Young
      American Journal of Neuroradiology January 2020, 41 (1) 40-48; DOI: https://doi.org/10.3174/ajnr.A6365

      Fifty patients with high-grade gliomas from the authors’ hospital and 128 patients with high-grade gliomas from The Cancer Genome Atlas were included in this study. For each patient, the authors calculated 348 hand-crafted radiomics features and 8192 deep features generated by a pretrained convolutional neural network. They then applied feature selection and Elastic Net-Cox modeling to differentiate patients into long- and short-term survivors. In the 50 patients with high-grade gliomas from their institution, the combined feature analysis framework classified the patients into long- and short-term survivor groups with a log-rank test P value <.001. In the 128 patients from The Cancer Genome Atlas, the framework classified patients into long- and short-term survivors with a log-rank test P value of .014. In conclusion, the authors report successful production and initial validation of a deep transfer learning model combining radiomics and deep features to predict overall survival of patients with glioblastoma from postcontrast T1-weighed brain MR imaging.

  7. Beall, D.

    1. EDITOR'S CHOICESpine Imaging and Spine Image-Guided Interventions
      You have access
      Number Needed to Treat with Vertebral Augmentation to Save a Life
      J.A. Hirsch, R.V. Chandra, N.S. Carter, D. Beall, M. Frohbergh and K. Ong
      American Journal of Neuroradiology January 2020, 41 (1) 178-182; DOI: https://doi.org/10.3174/ajnr.A6367

      The purpose of this study was to calculate the number needed to treat to save 1 life at 1 year and up to 5 years after vertebral augmentation. A 10-year sample of the 100% US Medicare data base was used to identify patients with vertebral compression fractures treated with nonsurgical management, balloon kyphoplasty, and vertebroplasty. The number needed to treat was calculated between augmentation and nonsurgical management groups from years 1–5 following a vertebral compression fracture diagnosis, using survival probabilities for each management approach. The adjusted number needed to treat to save 1 life for nonsurgical management versus kyphoplasty ranged from 14.8 at year 1 to 11.9 at year 5. The adjusted number needed to treat for nonsurgical management versus vertebroplasty ranged from 22.8 at year 1 to 23.8 at year 5. The authors conclude that the NNT analysis of more than 2 million patients with VCF reveals that only 15 patients need to be treated to save 1 life at 1 year. This has an obvious clinically significant impact and given that all augmentation clinical trials are underpowered to detect a mortality benefit, this large dataset analysis reveals that vertebral augmentation provides a significant mortality benefit over nonsurgical management with a low NNT.

  8. Beheshtian, E.

    1. You have access
      Redundant Neurovascular Imaging: Who Is to Blame and What Is the Value?
      E. Beheshtian, S. Emamzadehfard, S. Sahraian, R. Jalilianhasanpour and D.M. Yousem
      American Journal of Neuroradiology January 2020, 41 (1) 35-39; DOI: https://doi.org/10.3174/ajnr.A6329
  9. Benson, J.C

    1. Spine Imaging and Spine Image-Guided Interventions
      Open Access
      Lateral Decubitus Digital Subtraction Myelography: Tips, Tricks, and Pitfalls
      D.K. Kim, W. Brinjikji, P.P. Morris, F.E. Diehn, V.T. Lehman, G.B. Liebo, J.M. Morris, J.T. Verdoorn, J.K. Cutsforth-Gregory, R.I. Farb, J.C Benson and C.M. Carr
      American Journal of Neuroradiology January 2020, 41 (1) 21-28; DOI: https://doi.org/10.3174/ajnr.A6368
  10. Berndt, M.T.

    1. Adult Brain
      You have access
      Microstructural Integrity of Salvaged Penumbra after Mechanical Thrombectomy
      M.T. Berndt, C. Maegerlein, T. Boeckh-Behrens, S. Wunderlich, C. Zimmer, S. Wirth, F.G. Mück, S. Mönch, B. Friedrich and J. Kaesmacher
      American Journal of Neuroradiology January 2020, 41 (1) 79-85; DOI: https://doi.org/10.3174/ajnr.A6364
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American Journal of Neuroradiology: 41 (1)
American Journal of Neuroradiology
Vol. 41, Issue 1
1 Jan 2020
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