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    Index by author — October 01, 2024, 45 (10) | American Journal of Neuroradiology  
    
















    





















    
  
  




    
    

  

      


    

      

  
  
  

    

  

    

  

                
    

      

  

    

  
      
  
  

    


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Index by author
  	
      
October 01, 2024; Volume 45,Issue 10 

  
  
   

  
  



  


  
  



			

		

	
	
 	
	  
  

		
		

			

			  

  
      
  
  

    
  1. Cho, Nicholas S.
    1. 
  
  
      
      Brain Tumor Imaging 
      
  
      
      
  
      Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma  
    	
      Nicholas S. Cho, Chencai Wang, Kathleen Van Dyk, Francesco Sanvito, Sonoko Oshima, Jingwen Yao, Albert Lai, Noriko Salamon, Timothy F. Cloughesy, Phioanh L. Nghiemphu and Benjamin M. Ellingson
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1552-1561; DOI: https://doi.org/10.3174/ajnr.A8327 
      
  
  
  

      

  2. Choi, Kyu Sung
    1. 
  
  
      
      Neurovascular/Stroke Imaging 
      
  
      
      
  
      Quantification of Infarct Core Volume in Patients with Acute Ischemic Stroke Using Cerebral Metabolic Rate of Oxygen in CT Perfusion  
    	
      Chuluunbaatar Otgonbaatar, Huijin Song, Keun-Hwa Jung, Inpyeong Hwang, Young Hun Jeon, Kyu Sung Choi, Dong Hyun Yoo and Chul-Ho Sohn
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1432-1440; DOI: https://doi.org/10.3174/ajnr.A8360 
      
  
  
  

      

  3. Cloughesy, Timothy F.
    1. 
  
  
      
      Brain Tumor Imaging 
      
  
      
      
  
      Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma  
    	
      Nicholas S. Cho, Chencai Wang, Kathleen Van Dyk, Francesco Sanvito, Sonoko Oshima, Jingwen Yao, Albert Lai, Noriko Salamon, Timothy F. Cloughesy, Phioanh L. Nghiemphu and Benjamin M. Ellingson
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1552-1561; DOI: https://doi.org/10.3174/ajnr.A8327 
      
  
  
  

      

  4. Collins, Scott
    1. 
  
  
      
      Neurodegenerative Disorder Imaging 
      
  
      
      
  
      MRI-Based Prediction of Clinical Improvement after Ventricular Shunt Placement for Normal Pressure Hydrocephalus: Development and Evaluation of an Integrated Multisequence Machine Learning Algorithm  
    	
      Owen P. Leary, Zhusi Zhong, Lulu Bi, Zhicheng Jiao, Yu-Wei Dai, Kevin Ma, Shanzeh Sayied, Daniel Kargilis, Maliha Imami, Lin-Mei Zhao, Xue Feng, Gerald Riccardello, Scott Collins, Konstantina Svokos, Abhay Moghekar, Li Yang, Harrison Bai, Petra M. Klinge and Jerrold L. Boxerman
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1536-1544; DOI: https://doi.org/10.3174/ajnr.A8372 
      
  
  
  

      

  5. Conklin, John
    1. 
  
  
      
      EDITOR'S CHOICEEmergency Neuroradiology 
      
  
      
      
  
      Evaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the Head  
    	
      Isabella Newbury-Chaet, Sarah F. Mercaldo, John K. Chin, Ankita Ghatak, Madeleine A. Halle, Ashley L. MacDonald, Karen Buch, John Conklin, William A. Mehan, Stuart Pomerantz, Sandra Rincon, Keith J. Dreyer, Bernardo C. Bizzo and James M. Hillis
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1528-1535; DOI: https://doi.org/10.3174/ajnr.A8358 
      
  
    	
      This study compared the accuracy of a stand-alone AI model with consensus neuroradiologists’ interpretations in detecting mass effect and vasogenic edema on CT of the head. The ability to identify these findings could assist the clinical workflow through prioritizing the interpretation of abnormal cases.
      
  
  

      

  6. Cross, Nathan M.
    1. 
  
  
      
      Artificial Intelligence 
      
  
      
      
  
      Using an Ensemble of Segmentation Methods to Detect Vertebral Bodies on Radiographs  
    	
      Brian C. Chang, Jonathan Renslo, Qifei Dong, Sandra K. Johnston, Jessica Perry, David R. Haynor, Gang Luo, Nancy E. Lane, Jeffrey G. Jarvik and Nathan M. Cross
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1512-1520; DOI: https://doi.org/10.3174/ajnr.A8343 
      
  
  
  

      

  7. Cutsforth-gregory, Jeremy
    1. 
  
  
      
      FELLOWS' JOURNAL CLUBHead and Neck Imaging 
      
  
      
      Open Access
      
  
      Skull Base CSF Leaks: Potential Underlying Pathophysiology and Evaluation of Brain MR Imaging Findings Associated with Spontaneous Intracranial Hypotension  
    	
      Ian T. Mark, Jeremy Cutsforth-Gregory, Patrick Luetmer, Ajay A. Madhavan, Michael Oien, Paul Farnsworth, Girish Bathla, Steve Messina, Michael Link and Jamie Van Gompel
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1593-1596; DOI: https://doi.org/10.3174/ajnr.A8333 
      
  
    	
      The purpose of this study was to use a validated brain MRI scoring system (Bern score) to evaluate patients with confirmed skull base CSF leaks for findings associated with SIH.  The authors found that patients with skull base CSF leaks did not have brain MRI findings that are associated with SIH and likely have distinct pathophysiology from spinal CSF leaks.
      
  
  

      

  8. Cutsforth-gregory, Jeremy K.
    1. 
  
  
      
      EDITOR'S CHOICESpine Imaging and Spine Image-Guided Interventions 
      
  
      
      
  
      Myelographic Techniques for the Localization of CSF-Venous Fistulas: Updates in 2024  
    	
      Ajay A. Madhavan, Waleed Brinjikji, Jeremy K. Cutsforth-Gregory, Timothy J. Amrhein, Peter G. Kranz, John C. Benson, Felix E. Diehn, Ben A. Johnson-Tesch, Greta B. Liebo, Vance T. Lehman, Ian T. Mark, Pearse P. Morris, Michael P. Oien, Darya P. Shlapak and Jared T. Verdoorn
      
  
    	
      American Journal of Neuroradiology October 2024, 45 (10) 1403-1412; DOI: https://doi.org/10.3174/ajnr.A8299 
      
  
    	
      This is an updated comprehensive review of the various myelographic techniques that can be used to identify CSF-venous fistulas. The authors discuss the advantages and disadvantages of each and describe provocative maneuvers that may improve the conspicuity of CVFs.
      
  
  

      

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