Index by author
Slawski, M.
- NeurointerventionOpen AccessIdentification of Small, Regularly Shaped Cerebral Aneurysms Prone to RuptureS.F. Salimi Ashkezari, F. Mut, M. Slawski, C.M. Jimenez, A.M. Robertson and J.R. CebralAmerican Journal of Neuroradiology April 2022, 43 (4) 547-553; DOI: https://doi.org/10.3174/ajnr.A7470
Smith, M.
- FELLOWS' JOURNAL CLUBHead & NeckYou have accessRevisiting CT Signs of Unilateral Vocal Fold Paralysis: A Single, Blinded StudyM.H. Bashir, C. Joyce, A. Bolduan, V. Sehgal, M. Smith and S.J. CharousAmerican Journal of Neuroradiology April 2022, 43 (4) 592-596; DOI: https://doi.org/10.3174/ajnr.A7451
Predicting vocal cord paralysis on the basis of CT findings is not as accurate or straightforward in prospective prediction as previously implied in prior studies.
Speck, O.
- Adult BrainYou have accessPulsatility Index in the Basal Ganglia Arteries Increases with Age in Elderly with and without Cerebral Small Vessel DiseaseV. Perosa, T. Arts, A. Assmann, H. Mattern, O. Speck, J. Oltmer, H.-J. Heinze, E. Düzel, S. Schreiber and J.J.M. ZwanenburgAmerican Journal of Neuroradiology April 2022, 43 (4) 540-546; DOI: https://doi.org/10.3174/ajnr.A7450
Spector, M.E.
- EDITOR'S CHOICEHead and Neck ImagingOpen AccessPrediction of Wound Failure in Patients with Head and Neck Cancer Treated with Free Flap Reconstruction: Utility of CT Perfusion and MR Perfusion in the Early Postoperative PeriodY. Ota, A.G. Moore, M.E. Spector, K. Casper, C. Stucken, K. Malloy, R. Lobo, A. Baba and A. SrinivasanAmerican Journal of Neuroradiology April 2022, 43 (4) 585-591; DOI: https://doi.org/10.3174/ajnr.A7458
CT perfusion and dynamic contrast-enhanced MR imaging are both promising imaging techniques to predict wound complications after head and neck free flap reconstruction.
Srinivasan, A.
- EDITOR'S CHOICEHead and Neck ImagingOpen AccessPrediction of Wound Failure in Patients with Head and Neck Cancer Treated with Free Flap Reconstruction: Utility of CT Perfusion and MR Perfusion in the Early Postoperative PeriodY. Ota, A.G. Moore, M.E. Spector, K. Casper, C. Stucken, K. Malloy, R. Lobo, A. Baba and A. SrinivasanAmerican Journal of Neuroradiology April 2022, 43 (4) 585-591; DOI: https://doi.org/10.3174/ajnr.A7458
CT perfusion and dynamic contrast-enhanced MR imaging are both promising imaging techniques to predict wound complications after head and neck free flap reconstruction.
Staib, L.H.
- EDITOR'S CHOICEAdult BrainOpen AccessMachine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias AssessmentG.I. Cassinelli Petersen, J. Shatalov, T. Verma, W.R. Brim, H. Subramanian, A. Brackett, R.C. Bahar, S. Merkaj, T. Zeevi, L.H. Staib, J. Cui, A. Omuro, R.A. Bronen, A. Malhotra and M.S. AboianAmerican Journal of Neuroradiology April 2022, 43 (4) 526-533; DOI: https://doi.org/10.3174/ajnr.A7473
Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.
Stucken, C.
- EDITOR'S CHOICEHead and Neck ImagingOpen AccessPrediction of Wound Failure in Patients with Head and Neck Cancer Treated with Free Flap Reconstruction: Utility of CT Perfusion and MR Perfusion in the Early Postoperative PeriodY. Ota, A.G. Moore, M.E. Spector, K. Casper, C. Stucken, K. Malloy, R. Lobo, A. Baba and A. SrinivasanAmerican Journal of Neuroradiology April 2022, 43 (4) 585-591; DOI: https://doi.org/10.3174/ajnr.A7458
CT perfusion and dynamic contrast-enhanced MR imaging are both promising imaging techniques to predict wound complications after head and neck free flap reconstruction.
Stuempflen, M.
- Pediatric NeuroimagingYou have accessDifferent from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates—A Quantitative MRI StudyV.U. Schmidbauer, M.S. Yildirim, G.O. Dovjak, K. Goeral, J. Buchmayer, M. Weber, M.C. Diogo, V. Giordano, G. Mayr-Geisl, F. Prayer, M. Stuempflen, F. Lindenlaub, V. List, S. Glatter, A. Rauscher, F. Stuhr, C. Lindner, K. Klebermass-Schrehof, A. Berger, D. Prayer and G. KasprianAmerican Journal of Neuroradiology April 2022, 43 (4) 611-619; DOI: https://doi.org/10.3174/ajnr.A7472
Stuhr, F.
- Pediatric NeuroimagingYou have accessDifferent from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates—A Quantitative MRI StudyV.U. Schmidbauer, M.S. Yildirim, G.O. Dovjak, K. Goeral, J. Buchmayer, M. Weber, M.C. Diogo, V. Giordano, G. Mayr-Geisl, F. Prayer, M. Stuempflen, F. Lindenlaub, V. List, S. Glatter, A. Rauscher, F. Stuhr, C. Lindner, K. Klebermass-Schrehof, A. Berger, D. Prayer and G. KasprianAmerican Journal of Neuroradiology April 2022, 43 (4) 611-619; DOI: https://doi.org/10.3174/ajnr.A7472
Subramanian, H.
- EDITOR'S CHOICEAdult BrainOpen AccessMachine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias AssessmentG.I. Cassinelli Petersen, J. Shatalov, T. Verma, W.R. Brim, H. Subramanian, A. Brackett, R.C. Bahar, S. Merkaj, T. Zeevi, L.H. Staib, J. Cui, A. Omuro, R.A. Bronen, A. Malhotra and M.S. AboianAmerican Journal of Neuroradiology April 2022, 43 (4) 526-533; DOI: https://doi.org/10.3174/ajnr.A7473
Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.
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