Index by author
Mccollough, Cynthia H.
- Neurovascular/Stroke ImagingYou have accessHigh-Resolution Head CTA: A Prospective Patient Study Comparing Image Quality of Photon-Counting Detector CT and Energy-Integrating Detector CTFelix E. Diehn, Zhongxing Zhou, Jamison E. Thorne, Norbert G. Campeau, Alex A. Nagelschneider, Laurence J. Eckel, John C. Benson, Ajay A. Madhavan, Girish Bathla, Vance T. Lehman, Nathan R. Huber, Francis Baffour, Joel G. Fletcher, Cynthia H. McCollough and Lifeng YuAmerican Journal of Neuroradiology October 2024, 45 (10) 1441-1449; DOI: https://doi.org/10.3174/ajnr.A8342
Meadows, Julie
- Pediatric NeuroimagingYou have accessComparing Vascular Morphology and Hemodynamics in Patients with Vein of Galen Malformations Using Intracranial 4D Flow MRIJeffrey N. Stout, Alfred Pokmeng See, Julie Meadows, Shivani D. Rangwala and Darren B. OrbachAmerican Journal of Neuroradiology October 2024, 45 (10) 1586-1592; DOI: https://doi.org/10.3174/ajnr.A8353
Mehan, William A.
- EDITOR'S CHOICEEmergency NeuroradiologyYou have accessEvaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the HeadIsabella 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. HillisAmerican 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.
Mendoza, Steve
- Neurovascular/Stroke ImagingYou have accessDeep Learning Denoising Improves CT Perfusion Image Quality in the Setting of Lower Contrast Dosing: A Feasibility StudyMahmud Mossa-Basha, Chengcheng Zhu, Tanya Pandhi, Steve Mendoza, Javid Azadbakht, Ahmed Safwat, Dean Homen, Carlos Zamora, Dinesh Kumar Gnanasekaran, Ruiyue Peng, Steven Cen, Vinay Duddalwar, Jeffry R. Alger and Danny J.J. WangAmerican Journal of Neuroradiology October 2024, 45 (10) 1468-1474; DOI: https://doi.org/10.3174/ajnr.A8367
Mercaldo, Sarah F.
- EDITOR'S CHOICEEmergency NeuroradiologyYou have accessEvaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the HeadIsabella 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. HillisAmerican 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.
Messina, Steve
- FELLOWS' JOURNAL CLUBHead and Neck ImagingOpen AccessSkull Base CSF Leaks: Potential Underlying Pathophysiology and Evaluation of Brain MR Imaging Findings Associated with Spontaneous Intracranial HypotensionIan T. Mark, Jeremy Cutsforth-Gregory, Patrick Luetmer, Ajay A. Madhavan, Michael Oien, Paul Farnsworth, Girish Bathla, Steve Messina, Michael Link and Jamie Van GompelAmerican 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.
Michel, Samira
- NeurointerventionYou have accessEndovascular Embolization as a Stand-Alone Treatment of Head and Neck Paragangliomas with Long-Term Tumor ControlSamira Michel, Riccardo Ludovichetti, Gergely Bertalan, Patrick Thurner, Jawid Madjidyar, Tilman Schubert, Martina Broglie Däppen, Svenja Nölting, Alexander Huber and Zsolt KulcsarAmerican Journal of Neuroradiology October 2024, 45 (10) 1499-1505; DOI: https://doi.org/10.3174/ajnr.A8328
Mirsky, David M.
- Pediatric NeuroimagingYou have accessSotos Syndrome: Deep Neuroimaging Phenotyping Reveals a High Prevalence of Malformations of Cortical DevelopmentBar Neeman, Sniya Sudhakar, Asthik Biswas, Jessica Rosenblum, Jai Sidpra, Felice D’Arco, Ulrike Löbel, Marta Gómez-Chiari, Mercedes Serrano, Mercè Bolasell, Kartik Reddy, Liat Ben-Sira, Reem Zakzouk, Amal Al-Hashem, David M. Mirsky, Rajan Patel, Rupa Radhakrishnan, Karuna Shekdar, Matthew T. Whitehead and Kshitij MankadAmerican Journal of Neuroradiology October 2024, 45 (10) 1570-1577; DOI: https://doi.org/10.3174/ajnr.A8364
Moghekar, Abhay
- Neurodegenerative Disorder ImagingYou have accessMRI-Based Prediction of Clinical Improvement after Ventricular Shunt Placement for Normal Pressure Hydrocephalus: Development and Evaluation of an Integrated Multisequence Machine Learning AlgorithmOwen 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. BoxermanAmerican Journal of Neuroradiology October 2024, 45 (10) 1536-1544; DOI: https://doi.org/10.3174/ajnr.A8372
Mohammed, Marwa A.
- Artificial IntelligenceYou have accessDSA Quantitative Analysis and Predictive Modeling of Obliteration in Cerebral AVM following Stereotactic RadiosurgeryMohamed Sobhi Jabal, Marwa A. Mohammed, Cody L. Nesvick, Hassan Kobeissi, Christopher S. Graffeo, Bruce E. Pollock and Waleed BrinjikjiAmerican Journal of Neuroradiology October 2024, 45 (10) 1521-1527; DOI: https://doi.org/10.3174/ajnr.A8351