Index by author
Hernesniemi, J.
- InterventionalOpen AccessLocal Hemodynamic Conditions Associated with Focal Changes in the Intracranial Aneurysm WallJ.R. Cebral, F. Detmer, B.J. Chung, J. Choque-Velasquez, B. Rezai, H. Lehto, R. Tulamo, J. Hernesniemi, M. Niemela, A. Yu, R. Williamson, K. Aziz, S. Sakur, S. Amin-Hanjani, F. Charbel, Y. Tobe, A. Robertson and J. FrösenAmerican Journal of Neuroradiology March 2019, 40 (3) 510-516; DOI: https://doi.org/10.3174/ajnr.A5970
Hill, M.D.
- EDITOR'S CHOICEYou have accessImaging of Patients with Suspected Large-Vessel Occlusion at Primary Stroke Centers: Available Modalities and a Suggested ApproachM.A. Almekhlafi, W.G. Kunz, B.K. Menon, R.A. McTaggart, M.V. Jayaraman, B.W. Baxter, D. Heck, D. Frei, C.P. Derdeyn, T. Takagi, A.H. Aamodt, I.M.R. Fragata, M.D. Hill, A.M. Demchuk and M. GoyalAmerican Journal of Neuroradiology March 2019, 40 (3) 396-400; DOI: https://doi.org/10.3174/ajnr.A5971
Endovascular thrombectomy has proven efficacy for a wide range of patients with large-vessel occlusion stroke and in selected cases up to 24 hours from onset. While primary stroke centers have increased the proportion of patients withstroke receiving thrombolytic therapy, delays can be encountereduntil patients with LVO are identified and transferred from the primary stroke center to acomprehensive stroke center. Therefore, any extra steps need to be carefullyweighed. The use of CTA (especially multiphase) at the primary stroke center levelhas many advantages in expediting the transfer of appropriate patients to a comprehensive center.
Hoang, A.
- Adult BrainOpen AccessDynamic Contrast-Enhanced MRI Reveals Unique Blood-Brain Barrier Permeability Characteristics in the Hippocampus in the Normal BrainJ. Ivanidze, M. Mackay, A. Hoang, J.M. Chi, K. Cheng, C. Aranow, B. Volpe, B. Diamond and P.C. SanelliAmerican Journal of Neuroradiology March 2019, 40 (3) 408-411; DOI: https://doi.org/10.3174/ajnr.A5962
- Adult BrainOpen AccessAlterations in Blood-Brain Barrier Permeability in Patients with Systemic Lupus ErythematosusJ.M. Chi, M. Mackay, A. Hoang, K. Cheng, C. Aranow, J. Ivanidze, B. Volpe, B. Diamond and P.C. SanelliAmerican Journal of Neuroradiology March 2019, 40 (3) 470-477; DOI: https://doi.org/10.3174/ajnr.A5990
Hoch, M.J.
- EDITOR'S CHOICEAdult BrainOpen Access3T MRI Whole-Brain Microscopy Discrimination of Subcortical Anatomy, Part 1: Brain StemM.J. Hoch, M.T. Bruno, A. Faustin, N. Cruz, L. Crandall, T. Wisniewski, O. Devinsky and T.M. ShepherdAmerican Journal of Neuroradiology March 2019, 40 (3) 401-407; DOI: https://doi.org/10.3174/ajnr.A5956
The authors applied an optimized TSE T2 sequence to washed postmortem brain samples to reveal exquisite and reproducible brain stem anatomic MR imaging contrast comparable with histologic atlases. Direct TSE MR imaging sequence discrimination of brain stem anatomy can help validate other MR imaging contrasts, such as diffusion tractography, or serve as a structural template for extracting quantitative MR imaging data in future postmortem investigations.
Hong, J.-S.
- InterventionalOpen AccessValidating the Automatic Independent Component Analysis of DSAJ.-S. Hong, Y.-H. Kao, F.-C. Chang and C.-J. LinAmerican Journal of Neuroradiology March 2019, 40 (3) 540-542; DOI: https://doi.org/10.3174/ajnr.A5963
Horakova, D.
- Adult BrainYou have accessA Serial 10-Year Follow-Up Study of Atrophied Brain Lesion Volume and Disability Progression in Patients with Relapsing-Remitting MSR. Zivadinov, D. Horakova, N. Bergsland, J. Hagemeier, D.P. Ramasamy, T. Uher, M. Vaneckova, E. Havrdova and M.G. DwyerAmerican Journal of Neuroradiology March 2019, 40 (3) 446-452; DOI: https://doi.org/10.3174/ajnr.A5987
Hoxworth, J.M.
- FELLOWS' JOURNAL CLUBAdult BrainOpen AccessAccurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer LearningL.S. Hu, H. Yoon, J.M. Eschbacher, L.C. Baxter, A.C. Dueck, A. Nespodzany, K.A. Smith, P. Nakaji, Y. Xu, L. Wang, J.P. Karis, A.J. Hawkins-Daarud, K.W. Singleton, P.R. Jackson, B.J. Anderies, B.R. Bendok, R.S. Zimmerman, C. Quarles, A.B. Porter-Umphrey, M.M. Mrugala, A. Sharma, J.M. Hoxworth, M.G. Sattur, N. Sanai, P.E. Koulemberis, C. Krishna, J.R. Mitchell, T. Wu, N.L. Tran, K.R. Swanson and J. LiAmerican Journal of Neuroradiology March 2019, 40 (3) 418-425; DOI: https://doi.org/10.3174/ajnr.A5981
The authors evaluated tumor cell density using a transfer learning method that generates individualized patient models, grounded in the wealth of population data, while also detecting and adjusting for interpatient variabilities based on each patient's own histologic data. They collected 82 image-recorded biopsy samples, from 18 patients with primary GBM. With multivariate modeling, transfer learning improved performance (r = 0.88) compared with one-model-fits-all (r = 0.39). They conclude that transfer learning significantly improves predictive modeling performance for quantifying tumor cell density in glioblastoma.
Hu, L.S.
- FELLOWS' JOURNAL CLUBAdult BrainOpen AccessAccurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer LearningL.S. Hu, H. Yoon, J.M. Eschbacher, L.C. Baxter, A.C. Dueck, A. Nespodzany, K.A. Smith, P. Nakaji, Y. Xu, L. Wang, J.P. Karis, A.J. Hawkins-Daarud, K.W. Singleton, P.R. Jackson, B.J. Anderies, B.R. Bendok, R.S. Zimmerman, C. Quarles, A.B. Porter-Umphrey, M.M. Mrugala, A. Sharma, J.M. Hoxworth, M.G. Sattur, N. Sanai, P.E. Koulemberis, C. Krishna, J.R. Mitchell, T. Wu, N.L. Tran, K.R. Swanson and J. LiAmerican Journal of Neuroradiology March 2019, 40 (3) 418-425; DOI: https://doi.org/10.3174/ajnr.A5981
The authors evaluated tumor cell density using a transfer learning method that generates individualized patient models, grounded in the wealth of population data, while also detecting and adjusting for interpatient variabilities based on each patient's own histologic data. They collected 82 image-recorded biopsy samples, from 18 patients with primary GBM. With multivariate modeling, transfer learning improved performance (r = 0.88) compared with one-model-fits-all (r = 0.39). They conclude that transfer learning significantly improves predictive modeling performance for quantifying tumor cell density in glioblastoma.
Hygino Da Cruz, L.C.
- LETTERYou have accessHigh-Resolution Vessel Wall MR Imaging as an Alternative to Brain BiopsyD.G. Corrêa and L.C. Hygino da CruzAmerican Journal of Neuroradiology March 2019, 40 (3) E17-E18; DOI: https://doi.org/10.3174/ajnr.A5950