Advertisement

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

Index by author

September 01, 2020; Volume 41,Issue 9

  1. Tanaka, Y.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Myelin and Axonal Damage in Normal-Appearing White Matter in Patients with Moyamoya Disease
      S. Hara, M. Hori, A. Hagiwara, Y. Tsurushima, Y. Tanaka, T. Maehara, S. Aoki and T. Nariai
      American Journal of Neuroradiology September 2020, 41 (9) 1618-1624; DOI: https://doi.org/10.3174/ajnr.A6708

      Eighteen patients with Moyamoya disease (16–55 years of age) and 18 age- and sex-matched healthy controls were evaluated with myelin-sensitive MR imaging based on magnetization transfer saturation imaging and 2-shell diffusion MR imaging. The myelin volume fraction, which reflects the amount of myelin sheath; the g-ratio, which represents the ratio of the inner (axon) to the outer (axon plus myelin) diameter of the fiber; and the axon volume fraction, which reflects axonal components, were calculated and compared between the patients and controls. Compared with the healthy controls, the patients with Moyamoya disease showed a significant decrease in the myelin and axon volume fractions in many WM regions, while the increases in the g-ratio values were not statistically significant. Correlations with cognitive performance were most frequently observed with the axon volume fraction. The authors conclude that the relationship with cognitive performance might be stronger with axonal damage than with myelin damage.

  2. Tay, Y.-K.D.

    1. Head and Neck Imaging
      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. Taylor, M.D.

    1. EDITOR'S CHOICEPediatrics
      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.

  4. Tian, W.

    1. Spine
      Open Access
      The Evaluation and Prediction of Laminoplasty Surgery Outcome in Patients with Degenerative Cervical Myelopathy Using Diffusion Tensor MRI
      X. Han, X. Ma, D. Li, J. Wang, W. Jiang, X. Cheng, G. Li, H. Guo and W. Tian
      American Journal of Neuroradiology September 2020, 41 (9) 1745-1753; DOI: https://doi.org/10.3174/ajnr.A6705

  5. Toh, C.H.

    1. Adult Brain
      Open Access
      MRS as an Aid to Diagnose Malignant Transformation in Low-Grade Gliomas with Increasing Contrast Enhancement
      C.H. Toh, M. Castillo, K.-C. Wei and P.-Y. Chen
      American Journal of Neuroradiology September 2020, 41 (9) 1592-1598; DOI: https://doi.org/10.3174/ajnr.A6688

  6. Tonetti, D.A.

    1. Neurointervention
      Emergent Premedication for Contrast Allergy Prior to Endovascular Treatment of Acute Ischemic Stroke
      D.A. Tonetti, S.M. Desai, A. Morrison, B.A. Gross, T.G. Jovin, B.T. Jankowitz and A.P. Jadhav
      American Journal of Neuroradiology September 2020, 41 (9) 1647-1651; DOI: https://doi.org/10.3174/ajnr.A6720

  7. Tong, E.

    1. EDITOR'S CHOICEPediatrics
      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.

  8. Tran, H.D.B.

    1. Pediatric Neuroimaging
      Neuroimaging Appearance of Cerebral Malignant Epithelioid Glioneuronal Tumors in Children
      G. Orman, S. Mohammed, H.D.B. Tran, F.Y. Lin, A. Meoded, N. Desai, T.A.G.M. Huisman and S.F. Kralik
      American Journal of Neuroradiology September 2020, 41 (9) 1740-1744; DOI: https://doi.org/10.3174/ajnr.A6668

  9. Tsuboi, T.

    1. Adult Brain
      Open Access
      Neuroimaging Advances in Deep Brain Stimulation: Review of Indications, Anatomy, and Brain Connectomics
      E.H. Middlebrooks, R.A. Domingo, T. Vivas-Buitrago, L. Okromelidze, T. Tsuboi, J.K. Wong, R.S. Eisinger, L. Almeida, M.R. Burns, A. Horn, R.J. Uitti, R.E. Wharen, V.M. Holanda and S.S. Grewal
      American Journal of Neuroradiology September 2020, 41 (9) 1558-1568; DOI: https://doi.org/10.3174/ajnr.A6693

  10. Tsurushima, Y.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Myelin and Axonal Damage in Normal-Appearing White Matter in Patients with Moyamoya Disease
      S. Hara, M. Hori, A. Hagiwara, Y. Tsurushima, Y. Tanaka, T. Maehara, S. Aoki and T. Nariai
      American Journal of Neuroradiology September 2020, 41 (9) 1618-1624; DOI: https://doi.org/10.3174/ajnr.A6708

      Eighteen patients with Moyamoya disease (16–55 years of age) and 18 age- and sex-matched healthy controls were evaluated with myelin-sensitive MR imaging based on magnetization transfer saturation imaging and 2-shell diffusion MR imaging. The myelin volume fraction, which reflects the amount of myelin sheath; the g-ratio, which represents the ratio of the inner (axon) to the outer (axon plus myelin) diameter of the fiber; and the axon volume fraction, which reflects axonal components, were calculated and compared between the patients and controls. Compared with the healthy controls, the patients with Moyamoya disease showed a significant decrease in the myelin and axon volume fractions in many WM regions, while the increases in the g-ratio values were not statistically significant. Correlations with cognitive performance were most frequently observed with the axon volume fraction. The authors conclude that the relationship with cognitive performance might be stronger with axonal damage than with myelin damage.

Back to top

In this issue

Advertisement
Advertisement