Abler, Daniel; Büchler, Philippe; Rockne, Russell (November 2018). TMOD-15. RELIABILITY OF IMAGING-BASED MEASURES OF TUMOR ‘MASS-EFFECT’– EVIDENCE FROM A COMPUTATIONAL STUDY. Neuro-Oncology, 20(suppl_6), vi271-vi271. Oxford University Press 10.1093/neuonc/noy148.1127
Elevated tumor mass-effect is associated to poor prognosis in GBM [1,2]. However, tumor mass-effect is poorly quantified in clinical practice. Recently, Steed et al. [2] proposed ‘Lateral ventricle displacement’ (LVd), defined as the change in center-of-mass position of the lateral ventricles between an undeformed reference and the tumor-bearing anatomy, as quantitative imaging measure of mass-effect. They found that the magnitude of LVd in GBM patients can be associated with overall survival. These results show the clinical importance of tumor mass-effect in GBM, warranting robust clinical measures.
This study characterizes image-derived estimates of tumor mass-effect by their ability to measure mass-effect accurately and reliably. We use a mathematical model to simulate tumor growth, which allows us to control and objectively quantify ‘mass-effect’ [3]. For given simulation parameters and growth location, we compute estimates of mass-effect from anatomical deformation during the growth process. We use multiple regression analysis to evaluate the ability of different estimates to explain the tumor’s objective mass-effect, measured by the tumor-induced pressure on the skull.
References:
[1] Gamburg et al. IJROBP, 2000, 48, 5: 1359–62
[2] Steed et al. Scientific Reports, 2018, 8: 2827
[3] Abler et al. Neuro-Oncology, 2017, 19, suppl 6: vi245.
Item Type: |
Conference or Workshop Item (Poster) |
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Division/Institute: |
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Computational Bioengineering 04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued] |
UniBE Contributor: |
Abler, Daniel, Büchler, Philippe |
Subjects: |
500 Science > 570 Life sciences; biology 600 Technology > 610 Medicine & health 600 Technology > 620 Engineering |
ISSN: |
1522-8517 |
Publisher: |
Oxford University Press |
Funders: |
[124] H2020-MSCA-IF-2016 Project ID 753878 |
Language: |
English |
Submitter: |
Daniel Jakob Silvester Abler |
Date Deposited: |
27 Sep 2019 14:45 |
Last Modified: |
28 Jun 2024 14:32 |
Publisher DOI: |
10.1093/neuonc/noy148.1127 |
Related URLs: |
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URI: |
https://boris.unibe.ch/id/eprint/126757 |