Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping.

Abstract

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice.

• Authors: Lauren Keith, Brian D Ross, Craig J Galbán, Gary D Luker, Stefanie Galbán, Binsheng Zhao, Xiaotao Guo, Thomas L Chenevert, Benjamin A Hoff
• Journal: Tomography (Ann Arbor, Mich.) (Tomography) Vol. 2 Issue 4 Pg. 267-275 (Dec 2016) ISSN: 2379-1381 [Print] Switzerland
• PMID: 28286871 (Publication Type: Journal Article)