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Joshi PR, Pandey SB, Manandhar U, GC S, Sedain G. Cerebral astroblastoma radiologically mimicking pilocytic astrocytoma: A case report. Clin Case Rep 2022; 10:e05781. [PMID: 35498346 PMCID: PMC9036196 DOI: 10.1002/ccr3.5781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 04/03/2022] [Accepted: 04/07/2022] [Indexed: 11/06/2022] Open
Affiliation(s)
| | | | - Usha Manandhar
- Department of Pathology Tribhuvan University Teaching Hospital Kathmandu Nepal
| | - Saroj GC
- Maharajgunj Medical Campus Kathmandu Nepal
| | - Gopal Sedain
- Department of Neurosurgery Tribhuvan University Teaching Hospital Kathmandu Nepal
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Kurokawa R, Baba A, Kurokawa M, Ota Y, Hassan O, Capizzano A, Kim J, Johnson T, Srinivasan A, Moritani T. Neuroimaging of astroblastomas: A case series and systematic review. J Neuroimaging 2021; 32:201-212. [PMID: 34816541 DOI: 10.1111/jon.12948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND AND PURPOSE Astroblastoma is a rare type of glial tumor, histologically classified into two types with different prognoses: high and low grade. We aimed to investigate the CT and MRI findings of astroblastomas by collecting studies with analyzable neuroimaging data and extracting the imaging features useful for tumor grading. METHODS We searched for reports of pathologically proven astroblastomas with analyzable neuroimaging data using PubMed, Scopus, and Embase. Sixty-five studies with 71 patients with astroblastomas met the criteria for a systematic review. We added eight patients from our hospital, resulting in a final study cohort of 79 patients. The proportion of high-grade tumors was compared in groups based on the morphology (typical and atypical) using Fisher's exact test. RESULTS High- and low-grade tumors were 35/71 (49.3%) and 36/71 (50.7%), respectively. There was a significant difference in the proportion of high-grade tumors based on the tumor morphology (typical morphology: high-grade = 33/58 [56.9%] vs. atypical morphology, 2/13 [15.4%], p = .012). The reviews of neuroimaging findings were performed using the images included in each article. The articles had missing data due to the heterogeneity of the collected studies. CONCLUSIONS Detailed neuroimaging features were clarified, including tumor location, margin status, morphology, CT attenuation, MRI signal intensity, and contrast enhancement pattern. The classification of tumor morphology may help predict the tumor's histological grade, contributing to clinical care and future oncologic research.
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Affiliation(s)
- Ryo Kurokawa
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Akira Baba
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Mariko Kurokawa
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Yoshiaki Ota
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Omar Hassan
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Aristides Capizzano
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - John Kim
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Timothy Johnson
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Ashok Srinivasan
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Toshio Moritani
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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