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Allison CM, Scoones D, Batra A, Sinclair G. Thirteen-year long-term follow-up in a rare case of anaplastic astroblastoma: What makes the difference? Surg Neurol Int 2022; 13:221. [PMID: 35673675 PMCID: PMC9168415 DOI: 10.25259/sni_1065_2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 05/02/2022] [Indexed: 11/24/2022] Open
Abstract
Background: Astroblastomas are uncommon neuroepithelial tumors of the central nervous system with a distinct, yet, controversial radiological, histological, and molecular profile. Debatable differences between low- and high-grade astroblastoma have been reported in the medical literature; indeed, despite the increasing relevance of molecular genetic profiling in the realm of astroblastoma, its application is still in its early stages. As a result, the diagnostic criteria for astroblastoma remain undecided with yet no real consensus on the most ideal management. Case Description: This report describes a case of astroblastoma diagnosed 13 years ago in a young woman who despite six episodes of recurrence, transformation, and progression was able to retain a perfomace status of 0 by World Health Organization standard, throughout. Conclusion: This report discusses the clinical, radiological, histological features, and management of this rare tumor with an extraordinarily long survival, with an aim to strengthen the literature on management options. To the best of our knowledge, this is the longest surviving case of anaplastic astroblastoma reported in the available medical literature.
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Affiliation(s)
| | - David Scoones
- Department of Neuropathology, James Cook University Hospital, Middlesbrough, UK
| | - Arun Batra
- Department of Radiology James Cook University Hospital, Middlesbrough, UK
| | - Georges Sinclair
- Department of Oncology, James Cook University Hospital, Middlesbrough, UK.,Department of Oncology, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom.,Department of Neurosurgery, Bezmialem Vakif University Hospital, Istanbul, Turkey
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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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