Progressive disease in glioblastoma: Benefits and limitations of semi-automated volumetry.

Thomas HuberGeorgina AlberStefanie BetteJohannes KaesmacherTobias Boeckh-BehrensJens GemptFlorian RingelHanno M SpechtBernhard MeyerClaus ZimmerBenedikt WiestlerJan S Kirschke

Published in: PloS one (2017)

Absolute volume changes of the contrast enhancing tumor part were the most accurate volumetric determinant to detect progressive disease in assessment of GB and outweighed FLAIR changes as well as regional, segmentation-based image subtractions. This parameter might be useful in upcoming objective response criteria for glioblastoma.

Keyphrases

deep learning
multiple sclerosis
machine learning
convolutional neural network
high throughput
high resolution
magnetic resonance imaging
computed tomography
single cell