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CompletedNCT05735171SupraGlio-AIUpdated Dec 24, 2025

Supramarginal Resection in Glioblastoma Guided by Artificial Intelligence

An interventional study of AI-guided surgery in Glioblastoma, sponsored by Hospital del Rio Hortega. Completed at 1 site in Spain. Open to participants aged 18 Years to 80 Years. Per ClinicalTrials.gov, last updated 2025-12-24.

Sponsored by Hospital del Rio Hortega · Not applicable, Interventional, and Treatment

From the registry’s dates

  • Registered 3 months after the study started (first participant enrolled Nov 2022, registered Feb 2023).
Phase
Not applicable
Study type
Interventional
Enrollment
20
Allocation
Non-randomized
Ages
18 Years to 80 Years
Sex
All
01

Study summary

Glioblastomas are the most common and poorly prognostic primary brain neoplasms. Despite advances in surgical techniques and chemotherapy, the median survival time for these patients remains less than 15 months. This highlights the need for more effective treatments and improved prognostic tools. The globally accepted surgical strategy currently consists of achieving the maximum safe resection of the enhancing tumor volume. However, the non-enhancing peritumoral region contains viable cells that cause the inevitable recurrence that these patients face. Clinicians currently lack an imaging tool or modality to differentiate neoplastic infiltration in the peritumoral region from vasogenic edema. In addition, it is not always feasible to include all the T2-FLAIR signal alterations surrounding the enhancing tumor in the surgical planning due to the proximity of eloquent areas and the higher risk of postoperative deficits.

However, the investigators have developed a model to predict regions of recurrence based on machine learning and MRI radiomic features that have been trained and evaluated in a multi-institutional cohort.

The investigators aim to analyze whether an adjusted supramarginal resection guided by these new recurrence probability maps improves survival in selected patients with glioblastoma.

Read the detailed description

The SupraGlio-AI study aims to test the feasibility of the proposed AI-guided tailored supratotal resection for glioblastomas. The study will provide preliminary data on the accuracy of the AI model in predicting recurrence and the impact of using this information in surgical planning. This information will be crucial in determining the potential for a larger, randomized controlled trial in the future. The pilot study will also allow for refinement of the study design, intervention, and data collection processes before a larger-scale study is conducted. In addition to testing the feasibility and efficacy of the AI-guided tailored supratotal resection, this pilot study also has two secondary objectives: 1) Survival Analysis: The survival analysis will provide insights into the impact of using the AI model on patient outcomes and help determine the potential benefits of this approach. 2) Histopathological and Transcriptomic Analysis: The study will also include a histopathological and transcriptomic analysis of the tissue samples obtained from the high-risk regions defined by the AI model. This analysis will provide information on the molecular and cellular changes occurring in these regions and may offer insights into the underlying biology of glioblastoma recurrence. These data will inform the development of future studies aimed at improving patient outcomes.

By incorporating these secondary objectives, this pilot study will contribute to a more comprehensive understanding of the potential benefits of using AI in guiding tailored supratotal resection for glioblastomas. The results will inform future research and potentially lead to the development of improved treatment approaches for patients with this type of brain tumor.

02

Conditions studied

  • Glioblastoma

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03

In context

Glioblastoma

1,920 studies on the registry are indexed under Glioblastoma; 450 are open to participants now.

This study's enrollment of 20 is below the median of 36 across 1,618 interventional studies indexed under Glioblastoma.

Browse Glioblastoma studies →

Lead sponsor

Hospital del Rio Hortega is the lead sponsor of 26 studies on the registry; 7 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 80 Years
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  • A suspected diagnosis of supratentorial glioblastoma by MRI.
  • Tumor in non eloquent brain region according to the UCSF (University of California, San Francisco) classification, including the sensor motor areas (precentral and postcentral gyri), perisylvian language areas in the dominant hemisphere (superior temporal, inferior frontal, and inferior parietal gyri), basal ganglia, internal capsule, thalamus, and visual cortex around the calcarine sulcus
  • Indication for surgical treatment and where supramarginal resection is considered possible according to the preoperative imaging. This consideration needs to be verified by two specialists in neurosurgery. This criterion needs to be verified by two senior neurosurgeons.
  • Karnofsky Performance Score ≥ 70;
  • Written informed consent

Exclusion criteria

Exclusion Criteria:

  • Tumors in eloquent areas.
  • Recurrent gliomas (except biopsy)
  • MR image data not usable due to artifacts during acquisition. Inability to give written informed consent
  • KPS \< 70
  • Severe comorbidity.
05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Non-randomized
Intervention model
Single group
Masking
None (open label)
Enrollment
20 participants (actual)

Study arms

  • Experimental
    AI-guided resection

    Tailored supramarginal surgery guided by AI-based recurrence probability maps. Aim of supramarginal resection, where the high-risk of recurrence areas identified by the AI-based model are subsidiary to be removed as safe locations for the patient.

    Procedure: AI-guided surgery

Interventions

  • ProcedureAI-guided surgery

    Neuronavigated targeted biopsy sampling. Supramarginal resection including high-risk areas of recurrence defined by a radiomics-based model.

06

What researchers measure

Primary outcomes

  1. Feasibility using eligibility

    Among all screened patients, the proportion of patients who meet the eligibility criteria

    Time frame: Screening/Enrollment

  2. Feasibility using the proportion of consent

    Among all screened patients, the proportion of patients consenting to participate

    Time frame: Screening/Enrollment

Secondary outcomes

  1. Efficacy using overall survival

    Measured in days from surgery to the time of death

    Time frame: From date of surgery until the date of death from any cause, assessed up to 36 months

  2. Efficacy using progression-free survival

    Assessment of progression-free survival based on the Modified Criteria for Radiographic Response Assessment in Glioblastoma (mRANO) criteria.

    Time frame: From date of surgery until the date of first documented progression, assessed up to 36 months

  3. Safety using the neurological function

    The National Institutes of Healt Stroke Scale (NIHSS) will be used to assess neurological function. The NIHSS is composed of 11 items, each of which scores a specific ability between a 0 and 4. For each item, a score of 0 typically indicates normal function in that specific ability, while a higher score is indicative of some level of impairment.

    Time frame: 30 days

  4. Safety using global disability

    The modified Rankin scale (mRS ) is a measure of global disability that has been widely used to assess outcome after stroke. The scale runs from 0-6, running from perfect health without symptoms to death

    Time frame: 30 days

  5. Extent of resection

    Volumetric measurement of contrast enhancement and T2-FLAIR signal alteration on MRI

    Time frame: < 72 hours after surgery

  6. Postoperative complication

    Relevant post surgical complication that requires a second surgery or prolong the length of hospitalization (i.e. hematoma, infection)

    Time frame: 30 days

07

Study locations

1 site
  • University Hospital Rio Hortega
    Valladolid, Valladolid 47012, Spain
08

References and documents

Publications

  • Cepeda S, Luppino LT, Perez-Nunez A, Solheim O, Garcia-Garcia S, Velasco-Casares M, Karlberg A, Eikenes L, Sarabia R, Arrese I, Zamora T, Gonzalez P, Jimenez-Roldan L, Kuttner S. Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI. Cancers (Basel). 2023 Mar 22;15(6):1894. doi: 10.3390/cancers15061894. PubMed 36980783 ↗
  • Cepeda S, Hernando-Perez E, Perez-Riesgo E, Rodriguez-Valle I, Esteban-Sinovas O, Arrese I, Lucero-Salaverry MM, Zamora T, Torres-Nieto MA, Luppino LT, Kuttner S, Wodzinski M, Escudero T, Garzon J, Romero-Oraa R, Hornero R, Nunez L, Villalobos C, Sarabia R. Prospective biopsy-controlled validation of an AI model for predicting glioblastoma infiltration: Results from the SupraGlio trial. Neuro Oncol. 2026 Apr 20:noag088. doi: 10.1093/neuonc/noag088. Online ahead of print. PubMed 42010946 ↗

Individual participant data

Plan to share: Undecided

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Dec 24, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT05735171
Lead sponsor
Hospital del Rio Hortega
Collaborators
UiT The Arctic University of Norway, University Hospital of North Norway, University of Valladolid
Responsible party
Santiago Cepeda (Principal Investigator, Hospital del Rio Hortega) — Principal investigator
First posted
Feb 21, 2023
Start date
Nov 1, 2022
Primary completion
May 30, 2025
Completion
Dec 1, 2025
Last update
Dec 24, 2025

Study contacts

Santiago Cepeda, PhD
principal investigator · Hospital Río Hortega

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Dec 2025. You cannot join it, but the record below documents what was studied.

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