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Lookup NU author(s): Georgios Pexas,
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© 2020. Background: Posterior fossa hemangioblastomas usually consist of a small solid nodule with a large cyst, while more rarely they present as a large solid mass with a small or absent cyst, which can be surgically challenging. We sought to investigate the potential existence of multiple distinct hemangioblastoma populations using tumor volumetric data as an indicator. Methods: We conducted a retrospective review of surgically treated hemangioblastomas between 2005 and 2019 in our unit, including clinical notes, preoperative magnetic resonance imaging volumetric analysis of the solid component of the tumor, and pathology. Finite Gaussian mixture modeling was applied on the solid component volume dataset to identify potential underlying Gaussian distributions with their associated characteristics. Nonparametric Mann–Whitney U tests were used to investigate significance of differences (P < 0.05) in solid component volume and different variables (Von Hippel–Lindau disease, extent of resection, outcome). Results: A total of 68 consecutive patients were included. Solid component volumes followed a multimodal distribution (median = 1287 mm3, interquartile range of 3428 mm3). The best-fit finite Gaussian mixture modeling model identified 3 statistically significant different (P = 0.001) potential mixture components: X1 (219 ± 187 mm3), X2 (2686 ± 1299 mm3), and X3 (10,800 ± 5514 mm3). The second-best model detected 2 significantly different (P = 9.99e−08) mixture components Y1 (222 ± 189 mm3) and Y2 (5391 ± 5094 mm3). A significant difference in solid component volume was found between patients with favorable and unfavorable outcome (P = 0.002). Conclusions: This study has shown preliminary evidence that large solid hemangioblastomas may constitute a completely distinct population, rather than a variant of one large group of hemangioblastomas.
Author(s): Pitsika M, Pexas G, Joshi A, Mitchell P
Publication type: Article
Publication status: Published
Journal: World Neurosurgery
Print publication date: 01/02/2021
Online publication date: 03/11/2020
Acceptance date: 28/10/2020
ISSN (print): 1878-8750
ISSN (electronic): 1878-8769
Publisher: Elsevier Inc.
PubMed id: 33152496
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