Neuroimaging of astroblastomas: A case series and systematic review. Issue 2 (23rd November 2021)

• Record Type: Journal Article
• Authors: Kurokawa, Ryo; Baba, Akira; Kurokawa, Mariko; Ota, Yoshiaki; Hassan, Omar; Capizzano, Aristides; Kim, John; Johnson, Timothy; Srinivasan, Ashok; Moritani, Toshio
• Is Part Of: Journal of neuroimaging. Volume 32:Issue 2(2022)
• Page Start: 201
• Page End: 212
• Publication Date: 2021-11-23
• Subjects: astroblastoma -- CT -- MRI -- neuroimaging features -- systematic review; Diagnostic imaging -- Periodicals; Nervous system -- Diseases -- Diagnosis -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Système nerveux -- Maladies -- Diagnostic -- Périodiques; Imagerie médicale; Neuroimagerie; Neurologie; Système nerveux; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.804754
• DOI: 10.1111/jon.12948
• Languages: English
• ISSNs: 1051-2284

Abstract

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.