ArticleScientific reports2021
Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 28 citations in OpenAlex.
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- Brain metastases converge on shared geometric architecture and transcriptomic landscape yet remain distinct from gliomas.iScience · 2026Article
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- Drawing the Line: From U-Net-Based Glioblastoma Segmentation to Machine Learning-Driven Survival Prediction.Medical sciences (Basel, Switzerland) · 2026Article
- Fractal-geometry analysis of pediatric posterior fossa tumors - a preoperative tool for prediction of histopathology.Neurosurgical review · 2026Article
- IDH mutation prediction in non-enhancing gliomas with relaxed T2-FLAIR mismatch and fractal dimension: a two-center study.BMC medical imaging · 2026Article
- Fractal and Machine Learning Analyses of MALDI-TOF Mass Spectrometry Data in Glioblastoma.Computational and structural biotechnology journal · 2026Article
- Article
- Astrocyte Reprogramming Drives Tumor Progression and Chemotherapy Resistance in Agent-Based Models of Breast Cancer Brain Metastases.Bulletin of mathematical biology · 2025Article
- Magnetic resonance imaging fractal analysis of O(6)-methylguanine-DNA methyltransferase promoter methylation status in isocitrate dehydrogenase wild-type glioblastoma.Quantitative imaging in medicine and surgery · 2025Article
- [Predicting Invasive Non-mucinous Lung Adenocarcinoma IASLC Grading: A Nomogram Based on Dual-energy CT Imaging and Conventional Features].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Article
- The invasion phenotypes of glioblastoma depend on plastic and reprogrammable cell states.Nature communications · 2025Article
- Nomogram prediction of molecular characteristics in WHO grade 3-4 diffuse gliomas based on fractal analysis and VASARI features.Scientific reports · 2025Article
- Automated Lesion and Feature Extraction Pipeline for Brain MRIs with Interpretability.Neuroinformatics · 2025Article
- EGFR amplification and EGFRvIII predict and participate in TAT-Cx43266-283 antitumor response in preclinical glioblastoma models.Neuro-oncology · 2024Article
- Generative modeling of biological shapes and images using a probabilisticbioRxiv : the preprint server for biology · 2024Article
- Network efficiency of spatial systems with fractal morphology: a geometric graphs approach.Scientific reports · 2023Article
- Precision Nomothetic Medicine in Depression Research: A New Depression Model, and New Endophenotype Classes and Pathway Phenotypes, and A Digital Self.Journal of personalized medicine · 2022Article
- Article
- Magnetic Resonance Imaging Correlates of Immune Microenvironment in Glioblastoma.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.