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

Index by author

September 01, 2020; Volume 41,Issue 9
  • A
  • B
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  • G
  • H
  • I
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  • K
  • L
  • M
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  • Z

  1. Bala, W.

    1. EDITOR'S CHOICEPediatrics
      You have access
      Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study
      J.L. Quon, W. Bala, L.C. Chen, J. Wright, L.H. Kim, M. Han, K. Shpanskaya, E.H. Lee, E. Tong, M. Iv, J. Seekins, M.P. Lungren, K.R.M. Braun, T.Y. Poussaint, S. Laughlin, M.D. Taylor, R.M. Lober, H. Vogel, P.G. Fisher, G.A. Grant, V. Ramaswamy, N.A. Vitanza, C.Y. Ho, M.S.B. Edwards, S.H. Cheshier and K.W. Yeom
      American Journal of Neuroradiology September 2020, 41 (9) 1718-1725; DOI: https://doi.org/10.3174/ajnr.A6704

      This study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons, medulloblastoma, pilocytic astrocytoma, and ependymoma. There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRI as input to detect the presence of tumor and predict tumor class. Model tumor detection accuracy exceeded an AUC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F1 score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate.

  2. Bandeira, L.

    1. Head and Neck Imaging
      You have access
      A Simple Formula to Estimate Parathyroid Weight on 4D-CT, Predict Pathologic Weight, and Diagnose Parathyroid Adenoma in Patients with Primary Hyperparathyroidism
      R. Yeh, Y.-K.D. Tay, L. Dercle, L. Bandeira, M.R. Parekh and J.P. Bilezikian
      American Journal of Neuroradiology September 2020, 41 (9) 1690-1697; DOI: https://doi.org/10.3174/ajnr.A6687
  3. Bathla, G.

    1. Adult Brain
      Open Access
      Diagnostic Performance of PET and Perfusion-Weighted Imaging in Differentiating Tumor Recurrence or Progression from Radiation Necrosis in Posttreatment Gliomas: A Review of Literature
      N. Soni, M. Ora, N. Mohindra, Y. Menda and G. Bathla
      American Journal of Neuroradiology September 2020, 41 (9) 1550-1557; DOI: https://doi.org/10.3174/ajnr.A6685
  4. Bautista, A.

    1. Letter
      Open Access
      Possible Acute Disseminated Encephalomyelitis Related to Severe Acute Respiratory Syndrome Coronavirus 2 Infection
      P.S. Utukuri, A. Bautista, A. Lignelli and G. Moonis
      American Journal of Neuroradiology September 2020, 41 (9) E82-E83; DOI: https://doi.org/10.3174/ajnr.A6714
  5. Beccaria, K.

    1. FELLOWS' JOURNAL CLUBPediatric Neuroimaging
      You have access
      Focal Areas of High Signal Intensity in Children with Neurofibromatosis Type 1: Expected Evolution on MRI
      S. Calvez, R. Levy, R. Calvez, C.-J. Roux, D. Grévent, Y. Purcell, K. Beccaria, T. Blauwblomme, J. Grill, C. Dufour, F. Bourdeaut, F. Doz, M.P. Robert, N. Boddaert and V. Dangouloff-Ros
      American Journal of Neuroradiology September 2020, 41 (9) 1733-1739; DOI: https://doi.org/10.3174/ajnr.A6740

      The authors retrospectively examined the MRI of children diagnosed with neurofibromatosis type 1 using the National Institutes of Health Consensus Criteria (1987), with imaging follow-up of at least 4 years. They recorded the number, size, and surface area of focal areas of high signal intensity according to their anatomic distribution on T2WI/T2-FLAIR sequences. A generalized mixed model was used to analyze the evolution of focal areas of high signal intensity according to age, and separate analyses were performed for girls and boys. Thirty-nine patients with a median follow-up of 7 years were analyzed. Focal areas of high signal intensity were found in 100% of patients, preferentially in the infratentorial white matter (35% cerebellum, 30% brain stem) and in the capsular lenticular region (22%). They measured 15mm in 95% of cases. The areas appeared from the age of 1 year; increased in number, size, and surface area to a peak at the age of 7; and then spontaneously regressed by 17 years of age. The authors conclude that the study suggests that the evolution of focal areas of high signal intensity is not related to puberty and has a peak at the age of 7 years.

  6. Beck, E.S.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Manganese-Enhanced MRI in Patients with Multiple Sclerosis
      D.J. Suto, G. Nair, D.M. Sudarshana, S.U. Steele, J. Dwyer, E.S. Beck, J. Ohayon, H. McFarland, A.P. Koretsky, I.C.M. Cortese and D.S. Reich
      American Journal of Neuroradiology September 2020, 41 (9) 1569-1576; DOI: https://doi.org/10.3174/ajnr.A6665

      Mangafodipir is a manganese chelate that was clinically approved for MR imaging of liver lesions. The authors present a case series of 6 adults with multiple sclerosis who were scanned at baseline with gadolinium, then injected with mangafodipir, and followed at variable time points. Fourteen new lesions formed during or shortly before the study, of which 10 demonstrated manganese enhancement of varying intensity, timing, and spatial pattern. One gadolinium-enhancing extra-axial mass, presumably a meningioma, also demonstrated enhancement with manganese. Manganese enhancement was detected in lesions that formed in the days after mangafodipir injection, and this enhancement persisted for several weeks. They conclude that multiple sclerosis lesions were enhanced with a temporal and spatial profile distinct from that of gadolinium.

  7. Beer, M.

    1. Interventional
      You have access
      Shape Modification is Common in Woven EndoBridge–Treated Intracranial Aneurysms: A Longitudinal Quantitative Analysis Study
      J. Rosskopf, M. Braun, J. Dreyhaupt, M. Beer, B.L. Schmitz and Y. Ozpeynirci
      American Journal of Neuroradiology September 2020, 41 (9) 1652-1656; DOI: https://doi.org/10.3174/ajnr.A6669
  8. Belachew, S.

    1. Adult Brain
      You have access
      Patterning Chronic Active Demyelination in Slowly Expanding/Evolving White Matter MS Lesions
      C. Elliott, D.L. Arnold, H. Chen, C. Ke, L. Zhu, I. Chang, E. Cahir-McFarland, E. Fisher, B. Zhu, S. Gheuens, M. Scaramozza, V. Beynon, N. Franchimont, D.P. Bradley and S. Belachew
      American Journal of Neuroradiology September 2020, 41 (9) 1584-1591; DOI: https://doi.org/10.3174/ajnr.A6742
  9. Ben Maacha, M.

    1. Neurointervention
      You have access
      Fusion Image Guidance for Supra-Aortic Vessel Catheterization in Neurointerventions: A Feasibility Study
      A. Feddal, S. Escalard, F. Delvoye, R. Fahed, J.P. Desilles, K. Zuber, H. Redjem, J.S. Savatovsky, G. Ciccio, S. Smajda, M. Ben Maacha, M. Mazighi, M. Piotin and R. Blanc
      American Journal of Neuroradiology September 2020, 41 (9) 1663-1669; DOI: https://doi.org/10.3174/ajnr.A6707
  10. Bergsland, N.

    1. Adult Brain
      Open Access
      Disability Improvement Is Associated with Less Brain Atrophy Development in Multiple Sclerosis
      E. Ghione, N. Bergsland, M.G. Dwyer, J. Hagemeier, D. Jakimovski, D.P. Ramasamy, D. Hojnacki, A.A. Lizarraga, C. Kolb, S. Eckert, B. Weinstock-Guttman and R. Zivadinov
      American Journal of Neuroradiology September 2020, 41 (9) 1577-1583; DOI: https://doi.org/10.3174/ajnr.A6684
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American Journal of Neuroradiology: 41 (9)
American Journal of Neuroradiology
Vol. 41, Issue 9
1 Sep 2020
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