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Published in: Journal of Neuro-Oncology 1/2018

01-08-2018 | Clinical Study

Tumor growth dynamics in serially-imaged low-grade glioma patients

Authors: Chloe Gui, Suzanne E. Kosteniuk, Jonathan C. Lau, Joseph F. Megyesi

Published in: Journal of Neuro-Oncology | Issue 1/2018

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Abstract

Background

Diffuse low-grade gliomas (LGGs) are infiltrative, slow-growing primary brain tumors that remain relatively asymptomatic for long periods of time before progressing into aggressive and fatal high-grade gliomas.

Methods

We retrospectively identified LGG patients with numerous (≥ 8) serial magnetic resonance imaging (MRI) studies. Tumor volumes were measured by manual segmentation on serial imaging to study the natural history and growth of the lesion. Patient demographic information, tumor characteristics, and histological data were collected from electronic medical records and paper charts.

Results

Out of 74 LGG patients, 10 patients (13.5%) were identified to meet the study criteria with number of MRIs acquired ranging from 8 to 18 (median, 11.5) over a median of 79.7 months (range 39.8–113.8 months). Tumor diameter increased at a median of 2.17 mm/year in a linear trajectory. Cox regression analysis revealed that initial tumor volume was an independent predictor of time to clinical intervention, and Mann–Whitney U test found that patients younger than 50 years old had significantly slower-growing tumors. Clinical intervention was more likely for tumors above a volume threshold of 73.6 mL.

Conclusion

We retrospectively analyzed the natural history of LGGs of patients managed at a single institution with numerous serial MRI scans. Comparisons of our cohort to the literature suggest that this is a subset of particularly slow-growing and low-risk tumors.
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Metadata
Title
Tumor growth dynamics in serially-imaged low-grade glioma patients
Authors
Chloe Gui
Suzanne E. Kosteniuk
Jonathan C. Lau
Joseph F. Megyesi
Publication date
01-08-2018
Publisher
Springer US
Published in
Journal of Neuro-Oncology / Issue 1/2018
Print ISSN: 0167-594X
Electronic ISSN: 1573-7373
DOI
https://doi.org/10.1007/s11060-018-2857-x

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