American Journal of Neuroradiology: 40 (3)

Index by author

March 01, 2019; Volume 40,Issue 3

Pai, J.S.
1. Adult Brain
  
  Open Access
  Preoperative MR Imaging to Differentiate Chordoid Meningiomas from Other Meningioma Histologic Subtypes
  J.D. Baal, W.C. Chen, D.A. Solomon, J.S. Pai, C.-H. Lucas, J.H. Hara, N.A. Oberheim Bush, M.W. McDermott, D.R. Raleigh and J.E. Villanueva-Meyer
  
  American Journal of Neuroradiology March 2019, 40 (3) 433-439; DOI: https://doi.org/10.3174/ajnr.A5996
Patel, S.H.
1. FELLOWS' JOURNAL CLUBAdult Brain
  
  You have access
  Neuroimaging-Based Classification Algorithm for Predicting 1p/19q-Codeletion Status in IDH-Mutant Lower Grade Gliomas
  P.P. Batchala, T.J.E. Muttikkal, J.H. Donahue, J.T. Patrie, D. Schiff, C.E. Fadul, E.K. Mrachek, M.-B. Lopes, R. Jain and S.H. Patel
  
  American Journal of Neuroradiology March 2019, 40 (3) 426-432; DOI: https://doi.org/10.3174/ajnr.A5957
  
  One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor or cyst texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lowergrade gliomas; and 2)a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation ofthe classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers.
Patrie, J.T.
1. FELLOWS' JOURNAL CLUBAdult Brain
  
  You have access
  Neuroimaging-Based Classification Algorithm for Predicting 1p/19q-Codeletion Status in IDH-Mutant Lower Grade Gliomas
  P.P. Batchala, T.J.E. Muttikkal, J.H. Donahue, J.T. Patrie, D. Schiff, C.E. Fadul, E.K. Mrachek, M.-B. Lopes, R. Jain and S.H. Patel
  
  American Journal of Neuroradiology March 2019, 40 (3) 426-432; DOI: https://doi.org/10.3174/ajnr.A5957
  
  One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor or cyst texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lowergrade gliomas; and 2)a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation ofthe classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers.
Perrini, P.
1. Interventional
  
  You have access
  Flow-Diversion Treatment of Unruptured Saccular Anterior Communicating Artery Aneurysms: A Systematic Review and Meta-Analysis
  F. Cagnazzo, N. Limbucci, S. Nappini, L. Renieri, A. Rosi, A. Laiso, D. Tiziano di Carlo, P. Perrini and S. Mangiafico
  
  American Journal of Neuroradiology March 2019, 40 (3) 497-502; DOI: https://doi.org/10.3174/ajnr.A5967
Pfeiffer, H.
1. Pediatrics
  
  Open Access
  Understanding Subdural Collections in Pediatric Abusive Head Trauma
  D. Wittschieber, B. Karger, H. Pfeiffer and M.L. Hahnemann
  
  American Journal of Neuroradiology March 2019, 40 (3) 388-395; DOI: https://doi.org/10.3174/ajnr.A5855
Piergallini, L.
1. Interventional
  
  You have access
  Comparison of Pipeline Embolization Device Sizing Based on Conventional 2D Measurements and Virtual Simulation Using the Sim&Size Software: An Agreement Study
  J.M. Ospel, G. Gascou, V. Costalat, L. Piergallini, K.A. Blackham and D.W. Zumofen
  
  American Journal of Neuroradiology March 2019, 40 (3) 524-530; DOI: https://doi.org/10.3174/ajnr.A5973
Pierot, L.
1. Interventional
  
  Open Access
  Aneurysm Characteristics, Study Population, and Endovascular Techniques for the Treatment of Intracranial Aneurysms in a Large, Prospective, Multicenter Cohort: Results of the Analysis of Recanalization after Endovascular Treatment of Intracranial Aneurysm Study
  M. Gawlitza, S. Soize, C. Barbe, A. le Clainche, P. White, L. Spelle and L. Pierot ARETA Study Group
  
  American Journal of Neuroradiology March 2019, 40 (3) 517-523; DOI: https://doi.org/10.3174/ajnr.A5991
Pinho, M.
1. FELLOWS' JOURNAL CLUBAdult Brain
  
  Open Access
  Disorder in Pixel-Level Edge Directions on T1WI Is Associated with the Degree of Radiation Necrosis in Primary and Metastatic Brain Tumors: Preliminary Findings
  P. Prasanna, L. Rogers, T.C. Lam, M. Cohen, A. Siddalingappa, L. Wolansky, M. Pinho, A. Gupta, K.J. Hatanpaa, A. Madabhushi and P. Tiwari
  
  American Journal of Neuroradiology March 2019, 40 (3) 412-417; DOI: https://doi.org/10.3174/ajnr.A5958
  
  The authors sought to investigate whether co-occurrence of local anisotropic gradient orientations (COLLAGE) measurements from posttreatment gadolinium-contrast T1WI could distinguish varying extents of cerebral radiation necrosis and recurrent tumor classes in a lesion across primary and metastatic brain tumors. On 75 gadolinium-contrast T1WI studies obtained from patients with primary and metastatic brain tumors and nasopharyngeal carcinoma, the extent of cerebral radiation necrosis and recurrent tumor in every brain lesion was histopathologically defined by a neuropathologist as the following: 1) “pure” cerebral radiation necrosis; 2) “mixed” pathology with coexistence of cerebral radiation necrosis and recurrent tumors; 3) “predominant” (>80%) cerebral radiation necrosis; 4) predominant (>80%) recurrent tumor; and 5) pure tumor. COLLAGE features were extracted from the expert-annotated ROIs on MR imaging. COLLAGE features exhibited decreased skewness for patients with pure and predominant cerebral radiation necrosis and were statistically significantly different from those in patients with predominant recurrent tumors, which had highly skewed COLLAGE values.
Pollard, S.H.
1. Pediatrics
  
  You have access
  Infant Midnasal Stenosis: Reliability of Nasal Metrics
  M.E. Graham, K.M. Loveridge, S.H. Pollard, K.R. Moore and J.R. Skirko
  
  American Journal of Neuroradiology March 2019, 40 (3) 562-567; DOI: https://doi.org/10.3174/ajnr.A5980
Pop, R.
1. Interventional
  
  You have access
  Predictors and Clinical Impact of Delayed Stent Thrombosis after Thrombectomy for Acute Stroke with Tandem Lesions
  R. Pop, I. Zinchenko, V. Quenardelle, D. Mihoc, M. Manisor, J.S. Richter, F. Severac, M. Simu, S. Chibbaro, O. Rouyer, V. Wolff and R. Beaujeux
  
  American Journal of Neuroradiology March 2019, 40 (3) 533-539; DOI: https://doi.org/10.3174/ajnr.A5976

Main menu

User menu

Search

American Journal of Neuroradiology

Index by author

Pai, J.S.

Patel, S.H.

Patrie, J.T.

Perrini, P.

Pfeiffer, H.

Piergallini, L.

Pierot, L.

Pinho, M.

Pollard, S.H.

Pop, R.

In this issue

News and Updates

Resources

Opportunities

American Society of Neuroradiology