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Index by author

April 01, 2022; Volume 43,Issue 4

  1. Bhatia, K.D.

    1. Interventional
      Open Access
      Endovascular Management of Intracranial Dural AVFs: Transvenous Approach
      K.D. Bhatia, H. Lee, H. Kortman, J. Klostranec, W. Guest, T. Wälchli, I. Radovanovic, T. Krings and V.M. Pereira
      American Journal of Neuroradiology April 2022, 43 (4) 510-516; DOI: https://doi.org/10.3174/ajnr.A7300

  2. Bolduan, A.

    1. FELLOWS' JOURNAL CLUBHead & Neck
      Revisiting CT Signs of Unilateral Vocal Fold Paralysis: A Single, Blinded Study
      M.H. Bashir, C. Joyce, A. Bolduan, V. Sehgal, M. Smith and S.J. Charous
      American Journal of Neuroradiology April 2022, 43 (4) 592-596; DOI: https://doi.org/10.3174/ajnr.A7451

      Predicting vocal cord paralysis on the basis of CT findings is not as accurate or straightforward in prospective prediction as previously implied in prior studies.

  3. Borg, N.

    1. Neurointervention
      Open Access
      Anatomy of Spinal Venous Drainage for the Neurointerventionalist: From Puncture Site to Intervertebral Foramen
      N. Borg, J. Cutsforth-Gregory, S. Oushy, T. Huynh, L.E. Savastano, H.J. Cloft, G. Lanzino and W. Brinjikji
      American Journal of Neuroradiology April 2022, 43 (4) 517-525; DOI: https://doi.org/10.3174/ajnr.A7409

  4. Brackett, A.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
      G.I. Cassinelli Petersen, J. Shatalov, T. Verma, W.R. Brim, H. Subramanian, A. Brackett, R.C. Bahar, S. Merkaj, T. Zeevi, L.H. Staib, J. Cui, A. Omuro, R.A. Bronen, A. Malhotra and M.S. Aboian
      American Journal of Neuroradiology April 2022, 43 (4) 526-533; DOI: https://doi.org/10.3174/ajnr.A7473

      Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.

  5. Brim, W.R.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
      G.I. Cassinelli Petersen, J. Shatalov, T. Verma, W.R. Brim, H. Subramanian, A. Brackett, R.C. Bahar, S. Merkaj, T. Zeevi, L.H. Staib, J. Cui, A. Omuro, R.A. Bronen, A. Malhotra and M.S. Aboian
      American Journal of Neuroradiology April 2022, 43 (4) 526-533; DOI: https://doi.org/10.3174/ajnr.A7473

      Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.

  6. Brinjikji, W.

    1. Neurointervention
      Open Access
      Anatomy of Spinal Venous Drainage for the Neurointerventionalist: From Puncture Site to Intervertebral Foramen
      N. Borg, J. Cutsforth-Gregory, S. Oushy, T. Huynh, L.E. Savastano, H.J. Cloft, G. Lanzino and W. Brinjikji
      American Journal of Neuroradiology April 2022, 43 (4) 517-525; DOI: https://doi.org/10.3174/ajnr.A7409

  7. Bronen, R.A.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
      G.I. Cassinelli Petersen, J. Shatalov, T. Verma, W.R. Brim, H. Subramanian, A. Brackett, R.C. Bahar, S. Merkaj, T. Zeevi, L.H. Staib, J. Cui, A. Omuro, R.A. Bronen, A. Malhotra and M.S. Aboian
      American Journal of Neuroradiology April 2022, 43 (4) 526-533; DOI: https://doi.org/10.3174/ajnr.A7473

      Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.

  8. Buchmayer, J.

    1. Pediatric Neuroimaging
      Different from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates—A Quantitative MRI Study
      V.U. Schmidbauer, M.S. Yildirim, G.O. Dovjak, K. Goeral, J. Buchmayer, M. Weber, M.C. Diogo, V. Giordano, G. Mayr-Geisl, F. Prayer, M. Stuempflen, F. Lindenlaub, V. List, S. Glatter, A. Rauscher, F. Stuhr, C. Lindner, K. Klebermass-Schrehof, A. Berger, D. Prayer and G. Kasprian
      American Journal of Neuroradiology April 2022, 43 (4) 611-619; DOI: https://doi.org/10.3174/ajnr.A7472

  9. Burel, J.

    1. Interventional
      Follow-up of Intracranial Aneurysms Treated by Flow Diverters: Evaluation of Parent Artery Patency Using 3D-T1 Gradient Recalled-Echo Imaging with 2-Point Dixon in Combination with 3D-TOF-MRA with Compressed Sensing
      J. Burel, E. Gerardin, M. Vannier, A. Curado, M Verdalle-Cazes, N. Magne, M. Lefebvre and C. Papagiannaki
      American Journal of Neuroradiology April 2022, 43 (4) 554-559; DOI: https://doi.org/10.3174/ajnr.A7448
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