Feasibility of ONCOhabitats for Surgical and Treatment Planning in IDH-Wildtype Glioblastoma (SINUE)
NCT ID: NCT07111195
Last Updated: 2025-08-08
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
RECRUITING
140 participants
OBSERVATIONAL
2024-07-16
2026-09-30
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
The study aims to evaluate whether imaging biomarkers derived from pre-surgical MRI using ONCOhabitats can predict overall survival and support clinical decision-making.
The primary research questions are:
* Can ONCOhabitats identify vascular and molecular characteristics within the peritumoral infiltrated edema (IPE) that are associated with patient prognosis?
* Can these imaging biomarkers aid in stratifying patients according to their response to treatment, including temozolomide and immunotherapy?
Participants will:
* Be adults diagnosed with high-grade glioma who are scheduled for surgical tumor resection
* Undergo preoperative MRI processed with ONCOhabitats to segment the tumor into four biological habitats (HAT, LAT, IPE, and VPE)
* Provide tissue samples from each habitat when feasible, based on surgical and clinical considerations
Researchers will analyze:
* Imaging biomarkers (e.g., relative cerebral blood volume, rCBV)
* Molecular and histopathological features (e.g., MGMT promoter methylation, gene expression profiles associated with immunosuppression)
* Clinical and survival outcomes
This study seeks to enhance glioblastoma characterization and support personalized treatment strategies through the clinical validation of a software platform.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Feasibility of Acquiring Hyperpolarized Imaging in Patients With Meningioma
NCT06014905
BIOhabitats: Biological Validation of Vascular Habitats Within Astrocytoma Grade 4 at Molecular, Cellular, and Histopathological Levels
NCT05375318
Longitudinal Prospective Study of Neurocognition & Neuroimaging in Primary BT Patients
NCT05576103
Multicentre Validation of How Vascular Biomarkers From Tumor Can Predict the Survival of the Patient With Glioblastoma
NCT03439332
Automated Segmentation and Volumetry for Meningioma Using Deep Learning
NCT05093751
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
COHORT
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Patients with IDH-wildtype Glioblastoma
Patients with IDH-wildtype glioblastoma who have undergone a pre-surgical MRI study
The ONCOhabitats software for MRI-based habitat segmentation
ONCOhabitats is an MRI-based software platform designed to segment IDH-wildtype glioblastomas into four biologically distinct habitats (HAT, LAT, IPE, and VPE) based on vascular heterogeneity.
In this study, the software is applied preoperatively to generate imaging biomarkers that guide surgical sampling and are assessed for their ability to predict overall survival and stratify patients accordingly.
The intervention includes advanced perfusion imaging processing using the HTS methodology, non-invasive tumor characterization, and integration with molecular and histopathological data.
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
The ONCOhabitats software for MRI-based habitat segmentation
ONCOhabitats is an MRI-based software platform designed to segment IDH-wildtype glioblastomas into four biologically distinct habitats (HAT, LAT, IPE, and VPE) based on vascular heterogeneity.
In this study, the software is applied preoperatively to generate imaging biomarkers that guide surgical sampling and are assessed for their ability to predict overall survival and stratify patients accordingly.
The intervention includes advanced perfusion imaging processing using the HTS methodology, non-invasive tumor characterization, and integration with molecular and histopathological data.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* Radiological diagnosis of high-grade glioma
* Candidates for surgical resection
* Availability of complete preoperative MRI studies, including:
* T1-weighted MRI (pre- and post-gadolinium)
* T2-weighted MRI
* FLAIR (Fluid-Attenuated Inversion Recovery)
* T2\*-weighted DSC perfusion MRI
* Signed informed consent to participate in the clinical study
Exclusion Criteria
* Patients deemed inoperable
Withdrawal criteria:
* MRI data that cannot be processed using ONCOhabitats
* Patient withdraws informed consent at any time
18 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Hospital Clínico Universitario de Valencia
OTHER
Hospital Universitario de Canarias
OTHER
Hospital General Universitario de Alicante
OTHER
Hospital Universitario Virgen de la Arrixaca
OTHER
Hospital Vall d'Hebron
OTHER
Juan M Garcia-Gomez
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Juan M Garcia-Gomez
Full professor
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Hospital General Universitario Dr. Balmis
Alicante, , Spain
Hopsital Universitari Vall d'Hebron
Barcelona, , Spain
Hospital Clínico Universitario Virgen de la Arrixaca
Murcia, , Spain
Hospital Universitario de Canarias
Santa Cruz de Tenerife, , Spain
Hospital Clínic i Universitari de València
Valencia, , Spain
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
References
Explore related publications, articles, or registry entries linked to this study.
Juan-Albarracin J, Fuster-Garcia E, Perez-Girbes A, Aparici-Robles F, Alberich-Bayarri A, Revert-Ventura A, Marti-Bonmati L, Garcia-Gomez JM. Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival. Radiology. 2018 Jun;287(3):944-954. doi: 10.1148/radiol.2017170845. Epub 2018 Jan 19.
Del Mar Alvarez-Torres M, Juan-Albarracin J, Fuster-Garcia E, Bellvis-Bataller F, Lorente D, Reynes G, Font de Mora J, Aparici-Robles F, Botella C, Munoz-Langa J, Faubel R, Asensio-Cuesta S, Garcia-Ferrando GA, Chelebian E, Auger C, Pineda J, Rovira A, Oleaga L, Molla-Olmos E, Revert AJ, Tshibanda L, Crisi G, Emblem KE, Martin D, Due-Tonnessen P, Meling TR, Filice S, Saez C, Garcia-Gomez JM. Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. J Magn Reson Imaging. 2020 May;51(5):1478-1486. doi: 10.1002/jmri.26958. Epub 2019 Oct 26.
Juan-Albarracin J, Fuster-Garcia E, Garcia-Ferrando GA, Garcia-Gomez JM. ONCOhabitats: A system for glioblastoma heterogeneity assessment through MRI. Int J Med Inform. 2019 Aug;128:53-61. doi: 10.1016/j.ijmedinf.2019.05.002. Epub 2019 May 16.
Related Links
Access external resources that provide additional context or updates about the study.
ONCOhabitats website
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
INNEST/2022/087
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.