Index by author
Pivik, R.T.
- PediatricsOpen AccessGestational Age at Birth and Brain White Matter Development in Term-Born Infants and ChildrenX. Ou, C.M. Glasier, R.H. Ramakrishnaiah, A. Kanfi, A.C. Rowell, R.T. Pivik, A. Andres, M.A. Cleves and T.M. BadgerAmerican Journal of Neuroradiology December 2017, 38 (12) 2373-2379; DOI: https://doi.org/10.3174/ajnr.A5408
Pontillo, G.
- Adult BrainYou have accessRedefining the Pulvinar Sign in Fabry DiseaseS. Cocozza, C. Russo, A. Pisani, G. Olivo, E. Riccio, A. Cervo, G. Pontillo, S. Feriozzi, M. Veroux, Y. Battaglia, D. Concolino, F. Pieruzzi, R. Mignani, P. Borrelli, M. Imbriaco, A. Brunetti, E. Tedeschi and G. PalmaAmerican Journal of Neuroradiology December 2017, 38 (12) 2264-2269; DOI: https://doi.org/10.3174/ajnr.A5420
Pourmorteza, A.
- EDITOR'S CHOICEAdult BrainOpen AccessPhoton-Counting CT of the Brain: In Vivo Human Results and Image-Quality AssessmentA. Pourmorteza, R. Symons, D.S. Reich, M. Bagheri, T.E. Cork, S. Kappler, S. Ulzheimer and D.A. BluemkeAmerican Journal of Neuroradiology December 2017, 38 (12) 2257-2263; DOI: https://doi.org/10.3174/ajnr.A5402
Radiation dose–matched energy-integrating detector and photon-counting detector head CT scans were acquired with standardized protocols (tube voltage/current, 120 kV(peak)/370 mAs) in both an anthropomorphic head phantom and 21 asymptomatic volunteers. Image noise, gray matter, and white matter signal-to-noise ratios and GM–WM contrast and contrast-to-noise ratios were measured. Image quality was scored by 2 neuroradiologists blinded to the CT detector type. Photon-counting detector brain CT scans demonstrated greater gray–white matter contrast compared with conventional CT. This was due to both higher soft-tissue contrast and lower image noise for photon-counting CT.
Purcell, D.D.
- InterventionalYou have accessCorrelation between Clinical Outcomes and Baseline CT and CT Angiographic Findings in the SWIFT PRIME TrialA.P. Jadhav, H.-C. Diener, A. Bonafe, V.M. Pereira, E.I. Levy, B.W. Baxter, T.G. Jovin, R.G. Nogueira, D.R. Yavagal, C. Cognard, D.D. Purcell, B.K. Menon, R. Jahan, J.L. Saver and M. Goyal on behalf of the SWIFT PRIME investigatorsAmerican Journal of Neuroradiology December 2017, 38 (12) 2270-2276; DOI: https://doi.org/10.3174/ajnr.A5406
Putman, C.M.
- InterventionalOpen AccessHemodynamic Characteristics of Ruptured and Unruptured Multiple Aneurysms at Mirror and Ipsilateral LocationsR. Doddasomayajula, B.J. Chung, F. Mut, C.M. Jimenez, F. Hamzei-Sichani, C.M. Putman and J.R. CebralAmerican Journal of Neuroradiology December 2017, 38 (12) 2301-2307; DOI: https://doi.org/10.3174/ajnr.A5397
Qureshi, M.M.
- FELLOWS' JOURNAL CLUBHead & NeckYou have accessCT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with ChemoradiotherapyH. Kuno, M.M. Qureshi, M.N. Chapman, B. Li, V.C. Andreu-Arasa, K. Onoue, M.T. Truong and O. SakaiAmerican Journal of Neuroradiology December 2017, 38 (12) 2334-2340; DOI: https://doi.org/10.3174/ajnr.A5407
This was a retrospective study including 62 patients diagnosed with primary head and neck squamous cellcarcinoma who underwent contrast-enhanced CT examinations for staging, followed by chemoradiotherapy. CT texture features of thewhole primary tumor were measured using an in-house developed Matlab-based texture analysis program. Histogram, gray-level co-occurrence matrix, gray-level run-length, gray-level gradient matrix, and Laws features were used for texture feature extraction. Three histogram features (geometric mean, harmonic, and fourth moment) and 4 gray-level run-length features (short-run emphasis, gray-level nonuniformity, run-length nonuniformity, and short-run low gray-level emphasis) were significant predictors of outcome.
Ramakrishnaiah, R.H.
- PediatricsOpen AccessGestational Age at Birth and Brain White Matter Development in Term-Born Infants and ChildrenX. Ou, C.M. Glasier, R.H. Ramakrishnaiah, A. Kanfi, A.C. Rowell, R.T. Pivik, A. Andres, M.A. Cleves and T.M. BadgerAmerican Journal of Neuroradiology December 2017, 38 (12) 2373-2379; DOI: https://doi.org/10.3174/ajnr.A5408
Rathore, R.
- SpineYou have accessPredictive Models in Differentiating Vertebral Lesions Using Multiparametric MRIR. Rathore, A. Parihar, D.K. Dwivedi, A.K. Dwivedi, N. Kohli, R.K. Garg and A. ChandraAmerican Journal of Neuroradiology December 2017, 38 (12) 2391-2398; DOI: https://doi.org/10.3174/ajnr.A5411
Reich, D.S.
- EDITOR'S CHOICEAdult BrainOpen AccessPhoton-Counting CT of the Brain: In Vivo Human Results and Image-Quality AssessmentA. Pourmorteza, R. Symons, D.S. Reich, M. Bagheri, T.E. Cork, S. Kappler, S. Ulzheimer and D.A. BluemkeAmerican Journal of Neuroradiology December 2017, 38 (12) 2257-2263; DOI: https://doi.org/10.3174/ajnr.A5402
Radiation dose–matched energy-integrating detector and photon-counting detector head CT scans were acquired with standardized protocols (tube voltage/current, 120 kV(peak)/370 mAs) in both an anthropomorphic head phantom and 21 asymptomatic volunteers. Image noise, gray matter, and white matter signal-to-noise ratios and GM–WM contrast and contrast-to-noise ratios were measured. Image quality was scored by 2 neuroradiologists blinded to the CT detector type. Photon-counting detector brain CT scans demonstrated greater gray–white matter contrast compared with conventional CT. This was due to both higher soft-tissue contrast and lower image noise for photon-counting CT.
Reinacher, P.C.
- LETTERYou have accessReply:P.C. Reinacher, M.T. Krüger, V.A. Coenen, M. Shah, R. Roelz, C. Jenkner and K. EggerAmerican Journal of Neuroradiology December 2017, 38 (12) E106-E108; DOI: https://doi.org/10.3174/ajnr.A5386