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Index by author

December 01, 2017; Volume 38,Issue 12

  1. Kruzich, M.S.

    1. Neurointervention
      Wide Variability in Prethrombectomy Workflow Practices in the United States: A Multicenter Survey
      A.P. Kansagra, G.C. Meyers, M.S. Kruzich, D.T. Cross and C.J. Moran
      American Journal of Neuroradiology December 2017, 38 (12) 2238-2242; DOI: https://doi.org/10.3174/ajnr.A5384

  2. Kudo, K.

    1. EDITOR'S CHOICEExtracranial Vascular
      Open Access
      Preoperative Cerebral Oxygen Extraction Fraction Imaging Generated from 7T MR Quantitative Susceptibility Mapping Predicts Development of Cerebral Hyperperfusion following Carotid Endarterectomy
      J.-i. Nomura, I. Uwano, M. Sasaki, K. Kudo, F. Yamashita, K. Ito, S. Fujiwara, M. Kobayashi and K. Ogasawara
      American Journal of Neuroradiology December 2017, 38 (12) 2327-2333; DOI: https://doi.org/10.3174/ajnr.A5390

      Seventy-seven patients with unilateral internal carotid artery stenosis underwent preoperative 3DT2*-weighted imaging using a multiple dipole-inversion algorithm with a 7T MR scanner. Quantitative susceptibility mapping images wereobtained, and oxygen extraction fraction maps were generated. Quantitative brain perfusion single-photon emission CT was alsoperformed before and immediately after carotid endarterectomy. Ten patients (13%) showed post–carotid endarterectomy hyperperfusion. Multivariate analysis showed that a high quantitative susceptibility mapping–oxygen extraction fraction ratio was significantly associated with the development of post–carotid endarterectomy hyperperfusion.

  3. Kuno, H.

    1. FELLOWS' JOURNAL CLUBHead and Neck Imaging
      CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy
      H. Kuno, M.M. Qureshi, M.N. Chapman, B. Li, V.C. Andreu-Arasa, K. Onoue, M.T. Truong and O. Sakai
      American 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.

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