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Index by author

June 01, 2019; Volume 40,Issue 6
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Y
  • Z

  1. Chutinet, A.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI
      S. Winzeck, S.J.T. Mocking, R. Bezerra, M.J.R.J. Bouts, E.C. McIntosh, I. Diwan, P. Garg, A. Chutinet, W.T. Kimberly, W.A. Copen, P.W. Schaefer, H. Ay, A.B. Singhal, K. Kamnitsas, B. Glocker, A.G. Sorensen and O. Wu
      American Journal of Neuroradiology June 2019, 40 (6) 938-945; DOI: https://doi.org/10.3174/ajnr.A6077

      Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks. Automated volumes correlated with manually measured volumes for the independent cohort.

  2. Cloughesy, T.F.

    1. Adult Brain
      Open Access
      Association between Tumor Acidity and Hypervascularity in Human Gliomas Using pH-Weighted Amine Chemical Exchange Saturation Transfer Echo-Planar Imaging and Dynamic Susceptibility Contrast Perfusion MRI at 3T
      Y.-L. Wang, J. Yao, A. Chakhoyan, C. Raymond, N. Salamon, L.M. Liau, P.L. Nghiemphu, A. Lai, W.B. Pope, N. Nguyen, M. Ji, T.F. Cloughesy and B.M. Ellingson
      American Journal of Neuroradiology June 2019, 40 (6) 979-986; DOI: https://doi.org/10.3174/ajnr.A6063
  3. Consoli, A.

    1. FELLOWS' JOURNAL CLUBInterventional
      You have access
      First-Line Sofia Aspiration Thrombectomy Approach within the Endovascular Treatment of Ischemic Stroke Multicentric Registry: Efficacy, Safety, and Predictive Factors of Success
      G. Marnat, X. Barreau, L. Detraz, R. Bourcier, B. Gory, A. Sgreccia, F. Gariel, J. Berge, P. Menegon, M. Kyheng, J. Labreuche, A. Consoli, R. Blanc and B. Lapergue on behalf of the ETIS Investigators
      American Journal of Neuroradiology June 2019, 40 (6) 1006-1012; DOI: https://doi.org/10.3174/ajnr.A6074

      The authors performed a retrospective analysis of the prospectively maintained Endovascular Treatment of Ischemic Stroke multicentric registry. Data from consecutive patients who benefited from thrombectomy with a first-line Sofia approach between January 2013 and April 2018 were studied. We excluded other first-line approaches (stent retriever or combined aspiration and stent retriever) and extracranial occlusions. During the study period, 296 patients were treated. Mean age and initial NIHSS score were, respectively, 69.5 years and 16. Successful reperfusion, defined by the modified TICI 2b/3, was obtained in 86.1%. Complete reperfusion (modified TICI 3) was obtained in 41.2%. A first-pass effect was achieved in 24.2%. A rescue stent retriever approach was required in 29.7%. The first-line contact aspiration approach appeared safe and efficient with Sofia catheters. These devices achieved very high reperfusion rates with a low requirement for stent retriever rescue therapy, especially for M1 occlusions.

  4. Copen, W.A.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI
      S. Winzeck, S.J.T. Mocking, R. Bezerra, M.J.R.J. Bouts, E.C. McIntosh, I. Diwan, P. Garg, A. Chutinet, W.T. Kimberly, W.A. Copen, P.W. Schaefer, H. Ay, A.B. Singhal, K. Kamnitsas, B. Glocker, A.G. Sorensen and O. Wu
      American Journal of Neuroradiology June 2019, 40 (6) 938-945; DOI: https://doi.org/10.3174/ajnr.A6077

      Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks. Automated volumes correlated with manually measured volumes for the independent cohort.

  5. D'anna, G.

    1. You have access
      The Continued Rise in Professional Use of Social Media at Scientific Meetings: An Analysis of Twitter Use during the ASNR 2018 Annual Meeting
      G. D'Anna, M.M. Chen, J.L. McCarty, A. Radmanesh and A.L. Kotsenas
      American Journal of Neuroradiology June 2019, 40 (6) 935-937; DOI: https://doi.org/10.3174/ajnr.A6064
  6. Degnan, A.J.

    1. FELLOWS' JOURNAL CLUBAdult Brain
      Open Access
      Surveillance of Unruptured Intracranial Saccular Aneurysms Using Noncontrast 3D-Black-Blood MRI: Comparison of 3D-TOF and Contrast-Enhanced MRA with 3D-DSA
      C. Zhu, X. Wang, L. Eisenmenger, B. Tian, Q. Liu, A.J. Degnan, C. Hess, D. Saloner and J. Lu
      American Journal of Neuroradiology June 2019, 40 (6) 960-966; DOI: https://doi.org/10.3174/ajnr.A6080

      Sixty-four patients with 68 saccular unruptured intracranial aneurysms were recruited. Patients underwent 3T MR imaging with 3D-TOF-MRA, 3D black-blood MR imaging, and contrast-enhanced MRA, and they underwent 3D rotational angiography within 2 weeks. The neck, width, and height of the unruptured intracranial aneurysms were measured by 2 radiologists independently on 3D rotational angiography and 3 MR imaging sequences. 3D black-blood MR imaging demonstrates the best agreement with DSA, with the smallest limits of agreement and measurement error. 3D-TOF-MRA had the largest limits of agreement and measurement error. The authors conclude that 3D black-blood MR imaging achieves better accuracy for aneurysm size measurements compared with 3D-TOF, using 3D rotational angiography as a criterion standard.

  7. Dejaco, D.

    1. FELLOWS' JOURNAL CLUBHead & Neck
      You have access
      Readout-Segmented Echo-Planar DWI for the Detection of Cholesteatomas: Correlation with Surgical Validation
      N. Fischer, V.H. Schartinger, D. Dejaco, J. Schmutzhard, H. Riechelmann, M. Plaikner and B. Henninger
      American Journal of Neuroradiology June 2019, 40 (6) 1055-1059; DOI: https://doi.org/10.3174/ajnr.A6079

      Readout-segmented echo-planar (RESOLVE)-DWI is a new alternative technique for obtaining DWI with high quality, delivering sharp images at high spatial resolution and reduced slice thickness. Fifty patients with chronic otitis media who underwent MR imaging before an operation of the middle ear were included. The MR imaging protocol consisted of axial and coronal readout-segmented echo-planar DWI with b-values of 0 and 1000 s/mm2 and 3-mm slice thickness. The readout segmented echo-planar diffusion-weighted images were fused with standard T2-weighted sequences for better anatomic assignment. Readout-segmented echo-planar DWI detected 22 of the 25 cases of surgically proved cholesteatoma. It has an accuracy of 92%, a sensitivity of 88%, a specificity of 96%, a positive predictive value of 96%, and a negativepredictive value of 89%. Readout-segmented echo-planar DWI is a promising and reliable MR imaging sequence for the detection and exclusion of cholesteatoma.

  8. Detraz, L.

    1. FELLOWS' JOURNAL CLUBInterventional
      You have access
      First-Line Sofia Aspiration Thrombectomy Approach within the Endovascular Treatment of Ischemic Stroke Multicentric Registry: Efficacy, Safety, and Predictive Factors of Success
      G. Marnat, X. Barreau, L. Detraz, R. Bourcier, B. Gory, A. Sgreccia, F. Gariel, J. Berge, P. Menegon, M. Kyheng, J. Labreuche, A. Consoli, R. Blanc and B. Lapergue on behalf of the ETIS Investigators
      American Journal of Neuroradiology June 2019, 40 (6) 1006-1012; DOI: https://doi.org/10.3174/ajnr.A6074

      The authors performed a retrospective analysis of the prospectively maintained Endovascular Treatment of Ischemic Stroke multicentric registry. Data from consecutive patients who benefited from thrombectomy with a first-line Sofia approach between January 2013 and April 2018 were studied. We excluded other first-line approaches (stent retriever or combined aspiration and stent retriever) and extracranial occlusions. During the study period, 296 patients were treated. Mean age and initial NIHSS score were, respectively, 69.5 years and 16. Successful reperfusion, defined by the modified TICI 2b/3, was obtained in 86.1%. Complete reperfusion (modified TICI 3) was obtained in 41.2%. A first-pass effect was achieved in 24.2%. A rescue stent retriever approach was required in 29.7%. The first-line contact aspiration approach appeared safe and efficient with Sofia catheters. These devices achieved very high reperfusion rates with a low requirement for stent retriever rescue therapy, especially for M1 occlusions.

  9. Ding, Y.-H.

    1. Interventional
      Open Access
      Histologic and Biomolecular Similarities in Healing between Aneurysms and Cutaneous Skin Wounds
      J.R. Ayers-Ringler, Z. Khashim, Y.-H. Ding, D.F. Kallmes and R. Kadirvel
      American Journal of Neuroradiology June 2019, 40 (6) 1018-1021; DOI: https://doi.org/10.3174/ajnr.A6046
  10. Diwan, I.

    1. EDITOR'S CHOICEAdult Brain
      Open Access
      Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI
      S. Winzeck, S.J.T. Mocking, R. Bezerra, M.J.R.J. Bouts, E.C. McIntosh, I. Diwan, P. Garg, A. Chutinet, W.T. Kimberly, W.A. Copen, P.W. Schaefer, H. Ay, A.B. Singhal, K. Kamnitsas, B. Glocker, A.G. Sorensen and O. Wu
      American Journal of Neuroradiology June 2019, 40 (6) 938-945; DOI: https://doi.org/10.3174/ajnr.A6077

      Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks. Automated volumes correlated with manually measured volumes for the independent cohort.

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American Journal of Neuroradiology: 40 (6)
American Journal of Neuroradiology
Vol. 40, Issue 6
1 Jun 2019
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