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Title:

Predicting Glioblastoma Recurrence from Preoperative MR Scans Using Fractional-Anisotropy Maps with Free-Water Suppression.

Document type:
Journal Article
Author(s):
Metz, Marie-Christin; Molina-Romero, Miguel; Lipkova, Jana; Gempt, Jens; Liesche-Starnecker, Friederike; Eichinger, Paul; Grundl, Lioba; Menze, Bjoern; Combs, Stephanie E; Zimmer, Claus; Wiestler, Benedikt
Abstract:
Diffusion tensor imaging (DTI), and fractional-anisotropy (FA) maps in particular, have shown promise in predicting areas of tumor recurrence in glioblastoma. However, analysis of peritumoral edema, where most recurrences occur, is impeded by free-water contamination. In this study, we evaluated the benefits of a novel, deep-learning-based approach for the free-water correction (FWC) of DTI data for prediction of later recurrence. We investigated 35 glioblastoma cases from our prospective glioma cohort. A preoperative MR image and the first MR scan showing tumor recurrence were semiautomatically segmented into areas of contrast-enhancing tumor, edema, or recurrence of the tumor. The 10th, 50th and 90th percentiles and mean of FA and mean-diffusivity (MD) values (both for the original and FWC-DTI data) were collected for areas with and without recurrence in the peritumoral edema. We found significant differences in the FWC-FA maps between areas of recurrence-free edema and areas with later tumor recurrence, where differences in noncorrected FA maps were less pronounced. Consequently, a generalized mixed-effect model had a significantly higher area under the curve when using FWC-FA maps (AUC = 0.9) compared to noncorrected maps (AUC = 0.77, p < 0.001). This may reflect tumor infiltration that is not visible in conventional imaging, and may therefore reveal important information for personalized treatment decisions.
Journal title abbreviation:
Cancers
Year:
2020
Journal volume:
12
Journal issue:
3
Fulltext / DOI:
doi:10.3390/cancers12030728
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/32204544
Print-ISSN:
2072-6694
TUM Institution:
Fachgebiet Neuroradiologie (Prof. Zimmer); Institut für Allgemeine Pathologie und Pathologische Anatomie; Klinik und Poliklinik für RadioOnkologie und Strahlentherapie; Neurochirurgische Klinik und Poliklinik
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