American Journal of Neuroradiology: 39 (7)

Index by author

July 01, 2018; Volume 39,Issue 7

Padgett, K.
1. You have access
  REPLY:
  B. Hill, K. Padgett, V. Karla and R. Quencer
  
  American Journal of Neuroradiology July 2018, 39 (7) E83; DOI: https://doi.org/10.3174/ajnr.A5661
Patel, A.M.
1. Spine
  
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  Efficacy and Safety of Percutaneous Microwave Ablation and Cementoplasty in the Treatment of Painful Spinal Metastases and Myeloma
  M.A. Khan, G. Deib, B. Deldar, A.M. Patel and J.S. Barr
  
  American Journal of Neuroradiology July 2018, 39 (7) 1376-1383; DOI: https://doi.org/10.3174/ajnr.A5680
Patz, S.
1. EDITOR'S CHOICEAdult Brain
  
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  Relationship between Cough-Associated Changes in CSF Flow and Disease Severity in Chiari I Malformation: An Exploratory Study Using Real-Time MRI
  A.F. Bezuidenhout, D. Khatami, C.B. Heilman, E.M. Kasper, S. Patz, N. Madan, Y. Zhao and R.A. Bhadelia
  
  American Journal of Neuroradiology July 2018, 39 (7) 1267-1272; DOI: https://doi.org/10.3174/ajnr.A5670
  
  The authors correlated disease severity in symptomatic patients with Chiari I malformation with cough-associated changes in CSF flow as measured with real-time MR imaging. Patients were classified into 2 groups by neurosurgeons blinded to MR imaging measurements: 1) nonspecific Chiari I malformation (5/13)—Chiari I malformation with nonspecific symptoms like non-cough-related or mild occasional cough-related headache, neck pain, dizziness, paresthesias, and/or trouble swallowing; 2) specific Chiari I malformation (8/13)—patients with Chiari I malformation with specific symptoms and/or objective findings like severe cough-related headache, myelopathy, syringomyelia, and muscle atrophy. There was a significant negative correlation between the percentage change in CSF stroke volume (resting to post coughing) and Chiari I malformation disease severity. They conclude that assessment of CSF flow response to a coughing challenge has the potential to become a valuable objective noninvasive test for clinical assessment of disease severity in patients with Chiari I malformation.
Paul, F.
1. Spine
  
  Open Access
  MRI-Based Methods for Spinal Cord Atrophy Evaluation: A Comparison of Cervical Cord Cross-Sectional Area, Cervical Cord Volume, and Full Spinal Cord Volume in Patients with Aquaporin-4 Antibody Seropositive Neuromyelitis Optica Spectrum Disorders
  C. Chien, A.U. Brandt, F. Schmidt, J. Bellmann-Strobl, K. Ruprecht, F. Paul and M. Scheel
  
  American Journal of Neuroradiology July 2018, 39 (7) 1362-1368; DOI: https://doi.org/10.3174/ajnr.A5665
Pereira, V.M.
1. Interventional
  
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  Risk of Branch Occlusion and Ischemic Complications with the Pipeline Embolization Device in the Treatment of Posterior Circulation Aneurysms
  N. Adeeb, C.J. Griessenauer, A.A. Dmytriw, H. Shallwani, R. Gupta, P.M. Foreman, H. Shakir, J. Moore, N. Limbucci, S. Mangiafico, A. Kumar, C. Michelozzi, Y. Zhang, V.M. Pereira, C.C. Matouk, M.R. Harrigan, A.H. Siddiqui, E.I. Levy, L. Renieri, T.R. Marotta, C. Cognard, C.S. Ogilvy and A.J. Thomas
  
  American Journal of Neuroradiology July 2018, 39 (7) 1303-1309; DOI: https://doi.org/10.3174/ajnr.A5696
Pfeilschifter, W.
1. Adult Brain
  
  Open Access
  Extent of Microstructural Tissue Damage Correlates with Hemodynamic Failure in High-Grade Carotid Occlusive Disease: An MRI Study Using Quantitative T2 and DSC Perfusion
  A. Seiler, R. Deichmann, U. Nöth, A. Lauer, W. Pfeilschifter, O.C. Singer and M. Wagner
  
  American Journal of Neuroradiology July 2018, 39 (7) 1273-1279; DOI: https://doi.org/10.3174/ajnr.A5666
Poisson, L.M.
1. EDITOR'S CHOICEAdult Brain
  
  Open Access
  Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas
  P. Chang, J. Grinband, B.D. Weinberg, M. Bardis, M. Khy, G. Cadena, M.-Y. Su, S. Cha, C.G. Filippi, D. Bota, P. Baldi, L.M. Poisson, R. Jain and D. Chow
  
  American Journal of Neuroradiology July 2018, 39 (7) 1201-1207; DOI: https://doi.org/10.3174/ajnr.A5667
  
  MR imaging data and molecular information were retrospectively obtained from The Cancer Imaging Archives for 259 patients with either low- or high-grade gliomas. A convolutional neural network was trained to classify IDH1 mutation status, 1p/19q codeletion, and MGMT promotor methylation status. Classification had high accuracy: IDH1 mutation status, 94%; 1p/19q codeletion, 92%; and MGMT promotor methylation status, 83%. The authors conclude that this shows the feasibility of a deep-learning CNN approach for the accurate classification of individual genetic mutations of both low- and high-grade gliomas and that the relevant MR imaging features acquired from an added dimensionality-reduction technique are concordant with existing literature, showing that neural networks are capable of learning key imaging components without prior feature selection or human directed training.
Prager, M.
1. Head & Neck
  
  You have access
  MSVAT-SPACE-STIR and SEMAC-STIR for Reduction of Metallic Artifacts in 3T Head and Neck MRI
  T. Hilgenfeld, M. Prager, F.S. Schwindling, M. Nittka, P. Rammelsberg, M. Bendszus, S. Heiland and A. Juerchott
  
  American Journal of Neuroradiology July 2018, 39 (7) 1322-1329; DOI: https://doi.org/10.3174/ajnr.A5678
Prihod'ko, I.Y.
1. Pediatrics
  
  Open Access
  Quantitative Assessment of Normal Fetal Brain Myelination Using Fast Macromolecular Proton Fraction Mapping
  V.L. Yarnykh, I.Y. Prihod'ko, A.A. Savelov and A.M. Korostyshevskaya
  
  American Journal of Neuroradiology July 2018, 39 (7) 1341-1348; DOI: https://doi.org/10.3174/ajnr.A5668

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American Journal of Neuroradiology

Index by author

Padgett, K.

Patel, A.M.

Patz, S.

Paul, F.

Pereira, V.M.

Pfeilschifter, W.

Poisson, L.M.

Prager, M.

Prihod'ko, I.Y.

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