TMOD-15. RELIABILITY OF IMAGING-BASED MEASURES OF TUMOR ‘MASS-EFFECT’– EVIDENCE FROM A COMPUTATIONAL STUDY

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)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB

UniBE Contributor:

Abler, Daniel and 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:

27 Sep 2019 14:45

Publisher DOI:

10.1093/neuonc/noy148.1127

Related URLs:

URI:

https://boris.unibe.ch/id/eprint/126757

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