Salvato in:
| Autori principali: | , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2505.17715 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866913880514494464 |
|---|---|
| author | López-Mateu, Carles Gómez-Mahiques, Maria Gil-Terrón, F. Javier Montosa-i-Micó, Víctor Sederevičius, Donatas Emblem, Kyrre E. García-Gómez, Juan M. Fuster-García, Elies |
| author_facet | López-Mateu, Carles Gómez-Mahiques, Maria Gil-Terrón, F. Javier Montosa-i-Micó, Víctor Sederevičius, Donatas Emblem, Kyrre E. García-Gómez, Juan M. Fuster-García, Elies |
| contents | Glioblastoma (GBM) exhibits two principal growth phenotypes: infiltrative, characterized by diffuse invasion with minimal mass effect, and proliferative, characterized by pronounced tissue compression. Their quantitative delineation and prognostic implications remain uncertain. We introduce an MRI-derived biomarker, the dynamic infiltration rate (DIR), defined as the ratio of tumor-volume expansion to mass-effect--induced peritumoral compression, and evaluate it in silico and clinically. In a synthetic dataset spanning realistic infiltrative-proliferative spectra, DIR correlates strongly with ground truth ($R^{2}=0.85$). Applied to patient data, a data-driven threshold separates high- and low-infiltration groups with markedly different overall survival (median 16.0 versus 35.2 weeks; log-rank $p<0.001$; hazard ratio 2.49). Multivariate Cox analysis adjusted for age, sex, and MGMT status confirms DIR as an independent prognostic factor (HR = 1.38, 95% CI 1.12-1.70; $p=0.0027$). DIR therefore differentiates proliferative from infiltrative GBM phenotypes and provides prognostic information that could inform personalized therapy and follow-up. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_17715 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Biomechanical Mapping of Tumor Growth: A Novel Method to Quantify Glioma Infiltration and Mass Effect López-Mateu, Carles Gómez-Mahiques, Maria Gil-Terrón, F. Javier Montosa-i-Micó, Víctor Sederevičius, Donatas Emblem, Kyrre E. García-Gómez, Juan M. Fuster-García, Elies Medical Physics Glioblastoma (GBM) exhibits two principal growth phenotypes: infiltrative, characterized by diffuse invasion with minimal mass effect, and proliferative, characterized by pronounced tissue compression. Their quantitative delineation and prognostic implications remain uncertain. We introduce an MRI-derived biomarker, the dynamic infiltration rate (DIR), defined as the ratio of tumor-volume expansion to mass-effect--induced peritumoral compression, and evaluate it in silico and clinically. In a synthetic dataset spanning realistic infiltrative-proliferative spectra, DIR correlates strongly with ground truth ($R^{2}=0.85$). Applied to patient data, a data-driven threshold separates high- and low-infiltration groups with markedly different overall survival (median 16.0 versus 35.2 weeks; log-rank $p<0.001$; hazard ratio 2.49). Multivariate Cox analysis adjusted for age, sex, and MGMT status confirms DIR as an independent prognostic factor (HR = 1.38, 95% CI 1.12-1.70; $p=0.0027$). DIR therefore differentiates proliferative from infiltrative GBM phenotypes and provides prognostic information that could inform personalized therapy and follow-up. |
| title | Biomechanical Mapping of Tumor Growth: A Novel Method to Quantify Glioma Infiltration and Mass Effect |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2505.17715 |