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    Index by author — September 01, 2020, 41 (9) | American Journal of Neuroradiology  
    
















    





















    
  
  




    
    

  

      


    

      

  
  
  

    

  

    

  

                
    

      

  

    

  
      
  
  

    


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Index by author
  	
      
September 01, 2020; Volume 41,Issue 9 

  
  
   

  
  



  


  
  



			

		

	
	
 	
	  
  

		
		

			

			  

  
      
  
  

    
  1. Goyal, M.
    1. 
  
  
      
      LETTER 
      
  
      
      
  
      Missed Medium-Vessel Occlusions on CT Angiography: Make It Easier … Easily!  
    	
      J.M. Ospel, W. Qiu and M. Goyal
      
  
    	
      American Journal of Neuroradiology September 2020, 41 (9) E73-E74; DOI: https://doi.org/10.3174/ajnr.A6670 
      
  
  
  

      

  2. Grant, G.A.
    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.
      
  
  

      

  3. Gray, L.
    1. 
  
  
      
      Spine 
      
  
      
      
  
      Respiratory Phase Affects the Conspicuity of CSF–Venous Fistulas in Spontaneous Intracranial Hypotension  
    	
      T.J. Amrhein, L. Gray, M.D. Malinzak and P.G. Kranz
      
  
    	
      American Journal of Neuroradiology September 2020, 41 (9) 1754-1756; DOI: https://doi.org/10.3174/ajnr.A6663 
      
  
  
  

      

  4. Grevent, D.
    1. 
  
  
      
      FELLOWS' JOURNAL CLUBPediatrics 
      
  
      
      
  
      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.
      
  
  

      

  5. Grewal, S.S.
    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 
      
  
  
  

      

  6. Griffith, B.
    1. 
  
  
      
      Extracranial Vascular 
      
  
      
      Open Access
      
  
      Intraluminal Carotid Artery Thrombus in COVID-19: Another Danger of Cytokine Storm?  
    	
      A.Y. Mohamud, B. Griffith, M. Rehman, D. Miller, A. Chebl, S.C. Patel, B. Howell, M. Kole and H. Marin
      
  
    	
      American Journal of Neuroradiology September 2020, 41 (9) 1677-1682; DOI: https://doi.org/10.3174/ajnr.A6674 
      
  
  
  

      

  7. Grill, J.
    1. 
  
  
      
      FELLOWS' JOURNAL CLUBPediatrics 
      
  
      
      
  
      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.
      
  
  

      

  8. Gross, B.A.
    1. 
  
  
      
      Interventional 
      
  
      
      
  
      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 
      
  
  
  

      

  9. Guo, H.
    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 
      
  
  
  

      

  10. Hagemeier, J.
    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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