Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis

Lee Curtin, Paula Whitmire, Haylye White, Kamila M. Bond, Maciej M. Mrugala, Leland S. Hu, Kristin R. Swanson

Research output: Contribution to journalArticlepeer-review


Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, a morphological measure of the complexity of pixel arrangement, have shown relationships with outcome across a variety of cancers. However, the application of these metrics to glioblastoma (GBM), a very aggressive primary brain tumor, has not been fully explored. In this project, we computed lacunarity and fractal dimension values for GBM-induced abnormalities on clinically standard magnetic resonance imaging (MRI). In our patient cohort (n = 402), we connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension on necrotic regions (n = 390), all abnormalities present on T1Gd MRI (n = 402), and abnormalities present on T2/FLAIR MRI (n = 257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome for all three imaging regions that we tested, with the shape of T2/FLAIR abnormalities that are typically associated with edema showing the strongest relationship with overall survival. This link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.

Original languageEnglish (US)
Article number23202
JournalScientific reports
Issue number1
StatePublished - Dec 2021

ASJC Scopus subject areas

  • General


Dive into the research topics of 'Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis'. Together they form a unique fingerprint.

Cite this