Index by author
Tong, E.
- EDITOR'S CHOICEPediatricsYou have accessDeep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional StudyJ.L. Quon, W. Bala, L.C. Chen, J. Wright, L.H. Kim, M. Han, K. Shpanskaya, E.H. Lee, E. Tong, M. Iv, J. Seekins, M.P. Lungren, K.R.M. Braun, T.Y. Poussaint, S. Laughlin, M.D. Taylor, R.M. Lober, H. Vogel, P.G. Fisher, G.A. Grant, V. Ramaswamy, N.A. Vitanza, C.Y. Ho, M.S.B. Edwards, S.H. Cheshier and K.W. YeomAmerican Journal of Neuroradiology September 2020, 41 (9) 1718-1725; DOI: https://doi.org/10.3174/ajnr.A6704
This study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons, medulloblastoma, pilocytic astrocytoma, and ependymoma. There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRI as input to detect the presence of tumor and predict tumor class. Model tumor detection accuracy exceeded an AUC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F1 score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate.
Tran, H.D.B.
- Pediatric NeuroimagingYou have accessNeuroimaging Appearance of Cerebral Malignant Epithelioid Glioneuronal Tumors in ChildrenG. Orman, S. Mohammed, H.D.B. Tran, F.Y. Lin, A. Meoded, N. Desai, T.A.G.M. Huisman and S.F. KralikAmerican Journal of Neuroradiology September 2020, 41 (9) 1740-1744; DOI: https://doi.org/10.3174/ajnr.A6668
Tsuboi, T.
- Adult BrainOpen AccessNeuroimaging Advances in Deep Brain Stimulation: Review of Indications, Anatomy, and Brain ConnectomicsE.H. Middlebrooks, R.A. Domingo, T. Vivas-Buitrago, L. Okromelidze, T. Tsuboi, J.K. Wong, R.S. Eisinger, L. Almeida, M.R. Burns, A. Horn, R.J. Uitti, R.E. Wharen, V.M. Holanda and S.S. GrewalAmerican Journal of Neuroradiology September 2020, 41 (9) 1558-1568; DOI: https://doi.org/10.3174/ajnr.A6693
Tsurushima, Y.
- EDITOR'S CHOICEAdult BrainOpen AccessMyelin and Axonal Damage in Normal-Appearing White Matter in Patients with Moyamoya DiseaseS. Hara, M. Hori, A. Hagiwara, Y. Tsurushima, Y. Tanaka, T. Maehara, S. Aoki and T. NariaiAmerican Journal of Neuroradiology September 2020, 41 (9) 1618-1624; DOI: https://doi.org/10.3174/ajnr.A6708
Eighteen patients with Moyamoya disease (16–55 years of age) and 18 age- and sex-matched healthy controls were evaluated with myelin-sensitive MR imaging based on magnetization transfer saturation imaging and 2-shell diffusion MR imaging. The myelin volume fraction, which reflects the amount of myelin sheath; the g-ratio, which represents the ratio of the inner (axon) to the outer (axon plus myelin) diameter of the fiber; and the axon volume fraction, which reflects axonal components, were calculated and compared between the patients and controls. Compared with the healthy controls, the patients with Moyamoya disease showed a significant decrease in the myelin and axon volume fractions in many WM regions, while the increases in the g-ratio values were not statistically significant. Correlations with cognitive performance were most frequently observed with the axon volume fraction. The authors conclude that the relationship with cognitive performance might be stronger with axonal damage than with myelin damage.
Uitti, R.J.
- Adult BrainOpen AccessNeuroimaging Advances in Deep Brain Stimulation: Review of Indications, Anatomy, and Brain ConnectomicsE.H. Middlebrooks, R.A. Domingo, T. Vivas-Buitrago, L. Okromelidze, T. Tsuboi, J.K. Wong, R.S. Eisinger, L. Almeida, M.R. Burns, A. Horn, R.J. Uitti, R.E. Wharen, V.M. Holanda and S.S. GrewalAmerican Journal of Neuroradiology September 2020, 41 (9) 1558-1568; DOI: https://doi.org/10.3174/ajnr.A6693
Usui, Y.
- FELLOWS' JOURNAL CLUBHead & NeckOpen AccessMRI Findings of Immune Checkpoint Inhibitor–Induced Hypophysitis: Possible Association with FibrosisR. Kurokawa, Y. Ota, W. Gonoi, A. Hagiwara, M. Kurokawa, H. Mori, E. Maeda, S. Amemiya, Y. Usui, N. Sato, Y. Nakata, T. Moritani and O. AbeAmerican Journal of Neuroradiology September 2020, 41 (9) 1683-1689; DOI: https://doi.org/10.3174/ajnr.A6692
This retrospective international multicenter study comprised 20 patients with melanoma who were being treated with immune checkpoint inhibitors and clinically diagnosed with immune checkpoint inhibitor–induced hypophysitis. Three radiologists evaluated the following MR imaging findings: enlargement of the pituitary gland and stalk; homogeneity of enhancement of the pituitary gland; presence/absence of a well-defined poorly enhanced area and, if present, its location, shape, and signal intensity in T2WI; and enhancement pattern in contrast-enhanced dynamic MR imaging. Enlargement of the pituitary gland and stalk was observed in 12 and 20 patients, respectively. Nineteen patients showed poorly enhanced lesions (geographic hypoenhancing lesions) in the anterior lobe, and 11 of these lesions showed hypointensity on T2WI. Thyrotropin deficiency and corticotropin deficiency were observed in 19/20 and 12/17 patients, respectively. The authors conclude that pituitary geographic hypoenhancing lesions in the anterior lobe of the pituitary gland are characteristic and frequent MR imaging findings of immune checkpoint inhibitor–induced hypophysitis.
Utukuri, P.S.
- LetterOpen AccessPossible Acute Disseminated Encephalomyelitis Related to Severe Acute Respiratory Syndrome Coronavirus 2 InfectionP.S. Utukuri, A. Bautista, A. Lignelli and G. MoonisAmerican Journal of Neuroradiology September 2020, 41 (9) E82-E83; DOI: https://doi.org/10.3174/ajnr.A6714
Valenca, M.M.
- Head & NeckOpen AccessAnosmia in COVID-19 Associated with Injury to the Olfactory Bulbs Evident on MRIM.F.V.V. Aragão, M.C. Leal, O.Q. Cartaxo Filho, T.M. Fonseca and M.M. ValençaAmerican Journal of Neuroradiology September 2020, 41 (9) 1703-1706; DOI: https://doi.org/10.3174/ajnr.A6675
Vitanza, N.A.
- EDITOR'S CHOICEPediatricsYou have accessDeep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional StudyJ.L. Quon, W. Bala, L.C. Chen, J. Wright, L.H. Kim, M. Han, K. Shpanskaya, E.H. Lee, E. Tong, M. Iv, J. Seekins, M.P. Lungren, K.R.M. Braun, T.Y. Poussaint, S. Laughlin, M.D. Taylor, R.M. Lober, H. Vogel, P.G. Fisher, G.A. Grant, V. Ramaswamy, N.A. Vitanza, C.Y. Ho, M.S.B. Edwards, S.H. Cheshier and K.W. YeomAmerican Journal of Neuroradiology September 2020, 41 (9) 1718-1725; DOI: https://doi.org/10.3174/ajnr.A6704
This study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons, medulloblastoma, pilocytic astrocytoma, and ependymoma. There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRI as input to detect the presence of tumor and predict tumor class. Model tumor detection accuracy exceeded an AUC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F1 score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate.
Vivas-buitrago, T.
- Adult BrainOpen AccessNeuroimaging Advances in Deep Brain Stimulation: Review of Indications, Anatomy, and Brain ConnectomicsE.H. Middlebrooks, R.A. Domingo, T. Vivas-Buitrago, L. Okromelidze, T. Tsuboi, J.K. Wong, R.S. Eisinger, L. Almeida, M.R. Burns, A. Horn, R.J. Uitti, R.E. Wharen, V.M. Holanda and S.S. GrewalAmerican Journal of Neuroradiology September 2020, 41 (9) 1558-1568; DOI: https://doi.org/10.3174/ajnr.A6693