Skip to main content
OpenTrials
Completed

NCT Number: NCT05735171

Supramarginal Resection in Glioblastoma Guided by Artificial Intelligence

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.

Completed

Looking for future studies?

Notify Me

Key information

Conditions

Glioblastoma Astrocytoma Glioma Neoplasms Neoplasms by Histologic Type Neoplasms, Germ Cell and Embryonal Neoplasms, Glandular and Epithelial Neoplasms, Nerve Tissue Neoplasms, Neuroepithelial Neuroectodermal Tumors

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

University Hospital Rio Hortega

Valladolid, 47012, Spain

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

  • 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.

Treatment and study plan

AI-guided surgery

Procedure

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

Primary outcomes

  1. Feasibility using eligibility

    Time frame: Screening/Enrollment

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

  2. Feasibility using the proportion of consent

    Time frame: Screening/Enrollment

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

Secondary outcomes

  1. Efficacy using overall survival

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

    Measured in days from surgery to the time of death

  2. Efficacy using progression-free survival

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

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

  3. Safety using the neurological function

    Time frame: 30 days

    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.

  4. Safety using global disability

    Time frame: 30 days

    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

  5. Extent of resection

    Time frame: < 72 hours after surgery

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

  6. Postoperative complication

    Time frame: 30 days

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

Sponsors and collaborators

Lead sponsor

Hospital del Rio Hortega

Other

Collaborators

  • UiT The Arctic University of Norway
  • University Hospital of North Norway
  • University of Valladolid

Registry information

Official study title

Tailored Supramarginal Resection in Glioblastoma Guided by Artificial Intelligence-based Recurrence Probability Maps. A Non-randomized Pilot Study

Acronym: SupraGlio-AI

Important dates

Study start
2022
Primary completion
2025
Study completion
2025
First posted
Feb 21, 2023
Registry last updated
Dec 24, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.