Index by author
April 01, 2024; Volume 45,Issue 4
Marnat, G.
- Neurovascular/Stroke ImagingYou have accessThe Management of Persistent Distal Occlusions after Mechanical Thrombectomy and Thrombolysis: An Inter- and Intrarater Agreement StudyW. Boisseau, A. Benomar, C. Ducroux, R. Fahed, S. Smajda, J. D. B. Diestro, G. Charbonnier, J. Ognard, J. Burel, A. Ter Schiphorst, M. Boulanger, A. Nehme, J. Boucherit, G. Marnat, D. Volders, Q. Holay, G. Forestier, M. Bretzner, D. Roy, S. Vingadassalom, M. Elhorany, L. Nico, G. Jacquin, M. Abdalkader, A. Guedon, P. Seners, K. Janot, V. Dumas, R. Olatunji, S. Gazzola, G. Milot, J. Zehr, T.E. Darsaut, D. Iancu and J. RaymondAmerican Journal of Neuroradiology April 2024, 45 (4) 400-405; DOI: https://doi.org/10.3174/ajnr.A8149
Mccullagh, Kassie L.
- EDITOR'S CHOICEHead and Neck ImagingYou have accessDoes CISS MRI Reliably Depict the Endolymphatic Duct in Children with and without Vestibular Aqueduct Enlargement?Olutayo I. Olubiyi, Nicholas Thompson, Thad Benefield, Kassie L. McCullagh and Benjamin Y. HuangAmerican Journal of Neuroradiology April 2024, 45 (4) 511-517; DOI: https://doi.org/10.3174/ajnr.A8158
In this retrospective review of temporal bone high-resolution CT and CISS MR imaging of 98 hearing-impaired children, the authors found that the CISS MR imaging technique commonly used for inner ear evaluation performs poorly overall at resolving the endolymphatic duct and underdiagnoses enlarged vestibular aqueduct. If the endolymphatic duct is easily seen on CISS imaging, there is a .99% probability that the vestibular aqueduct is enlarged.
Mccullough-hicks, Margy E.
- EDITOR'S CHOICENeurovascular/Stroke ImagingYou have accessA Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke OutcomesYongkai Liu, Preya Shah, Yannan Yu, Jai Horsey, Jiahong Ouyang, Bin Jiang, Guang Yang, Jeremy J. Heit, Margy E. McCullough-Hicks, Stephen M. Hugdal, Max Wintermark, Patrik Michel, David S. Liebeskind, Maarten G. Lansberg, Gregory W. Albers and Greg ZaharchukAmerican Journal of Neuroradiology April 2024, 45 (4) 406-411; DOI: https://doi.org/10.3174/ajnr.A8140
The authors in this study used a deep learning-based predictive model (DLPD) that incorporated DWI and clinical data from the acute period to predict 90-day mRS outcomes and compared its predictions with those made by physicians. The results showed that the clinical and imaging fused deep learning model is noninferior to expert physicians in predicting specific mRS outcomes and unfavorable prognoses.
Mehta, Parv
- Brain Tumor ImagingYou have accessHigh-Grade Astrocytoma with Piloid Features: A Dual Institutional Review of Imaging Findings of a Novel EntityNeetu Soni, Amit Agarwal, Pranav Ajmera, Parv Mehta, Vivek Gupta, Mukta Vibhute, Maria Gubbiotti, Ian T. Mark, Steven A. Messina, Suyash Mohan and Girish BathlaAmerican Journal of Neuroradiology April 2024, 45 (4) 468-474; DOI: https://doi.org/10.3174/ajnr.A8166
Memon, Fatima
- Pediatric NeuroimagingYou have accessComparison of Volumetric and 2D Measurements and Longitudinal Trajectories in the Response Assessment of BRAF V600E-Mutant Pediatric Gliomas in the Pacific Pediatric Neuro-Oncology Consortium Clinical TrialDivya Ramakrishnan, Sarah C. Brüningk, Marc von Reppert, Fatima Memon, Nazanin Maleki, Sanjay Aneja, Anahita Fathi Kazerooni, Ali Nabavizadeh, MingDe Lin, Khaled Bousabarah, Annette Molinaro, Theodore Nicolaides, Michael Prados, Sabine Mueller and Mariam S. AboianAmerican Journal of Neuroradiology April 2024, 45 (4) 475-482; DOI: https://doi.org/10.3174/ajnr.A8189
Mendili, Mohamed Mounir El
- Neurodegenerative Disorder ImagingYou have accessNeurofilament Light Chain Levels Interact with Neurodegenerative Patterns and Motor Neuron Dysfunction in Amyotrophic Lateral SclerosisPenelope Tilsley, Antoine Moutiez, Alexandre Brodovitch, Mohamed Mounir El Mendili, Benoit Testud, Wafaa Zaaraoui, Annie Verschueren, Shahram Attarian, Maxime Guye, José Boucraut, Aude-Marie Grapperon and Jan-Patrick StellmannAmerican Journal of Neuroradiology April 2024, 45 (4) 494-503; DOI: https://doi.org/10.3174/ajnr.A8154
Meng, FanYang
- Neuroimaging Physics/Functional Neuroimaging/CT and MRI TechnologyYou have accessVisualizing the Habenula Using 3T High-Resolution MP2RAGE and QSM: A Preliminary StudyBingYang Bian, Lin Hou, YaTing Chai, YueLuan Jiang, XingChen Pan, Yang Sun, HongChao Wang, DongDong Qiu, ZeChen Yu, Hua Zhao, HuiMao Zhang, FanYang Meng and Lei ZhangAmerican Journal of Neuroradiology April 2024, 45 (4) 504-510; DOI: https://doi.org/10.3174/ajnr.A8156
Messina, Steven A.
- Brain Tumor ImagingYou have accessHigh-Grade Astrocytoma with Piloid Features: A Dual Institutional Review of Imaging Findings of a Novel EntityNeetu Soni, Amit Agarwal, Pranav Ajmera, Parv Mehta, Vivek Gupta, Mukta Vibhute, Maria Gubbiotti, Ian T. Mark, Steven A. Messina, Suyash Mohan and Girish BathlaAmerican Journal of Neuroradiology April 2024, 45 (4) 468-474; DOI: https://doi.org/10.3174/ajnr.A8166
Michel, Patrik
- EDITOR'S CHOICENeurovascular/Stroke ImagingYou have accessA Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke OutcomesYongkai Liu, Preya Shah, Yannan Yu, Jai Horsey, Jiahong Ouyang, Bin Jiang, Guang Yang, Jeremy J. Heit, Margy E. McCullough-Hicks, Stephen M. Hugdal, Max Wintermark, Patrik Michel, David S. Liebeskind, Maarten G. Lansberg, Gregory W. Albers and Greg ZaharchukAmerican Journal of Neuroradiology April 2024, 45 (4) 406-411; DOI: https://doi.org/10.3174/ajnr.A8140
The authors in this study used a deep learning-based predictive model (DLPD) that incorporated DWI and clinical data from the acute period to predict 90-day mRS outcomes and compared its predictions with those made by physicians. The results showed that the clinical and imaging fused deep learning model is noninferior to expert physicians in predicting specific mRS outcomes and unfavorable prognoses.
Milot, G.
- Neurovascular/Stroke ImagingYou have accessThe Management of Persistent Distal Occlusions after Mechanical Thrombectomy and Thrombolysis: An Inter- and Intrarater Agreement StudyW. Boisseau, A. Benomar, C. Ducroux, R. Fahed, S. Smajda, J. D. B. Diestro, G. Charbonnier, J. Ognard, J. Burel, A. Ter Schiphorst, M. Boulanger, A. Nehme, J. Boucherit, G. Marnat, D. Volders, Q. Holay, G. Forestier, M. Bretzner, D. Roy, S. Vingadassalom, M. Elhorany, L. Nico, G. Jacquin, M. Abdalkader, A. Guedon, P. Seners, K. Janot, V. Dumas, R. Olatunji, S. Gazzola, G. Milot, J. Zehr, T.E. Darsaut, D. Iancu and J. RaymondAmerican Journal of Neuroradiology April 2024, 45 (4) 400-405; DOI: https://doi.org/10.3174/ajnr.A8149
In this issue
American Journal of Neuroradiology
Vol. 45, Issue 4
1 Apr 2024
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