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Supramarginal Resection in Glioblastoma Guided by Artificial Intelligence

NCT05735171 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 20

Last updated 2025-12-24

No results posted yet for this 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.

Conditions

Interventions

PROCEDURE

AI-guided surgery

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

Sponsors & Collaborators

  • UiT The Arctic University of Norway

    collaborator OTHER

  • University Hospital of North Norway

    collaborator OTHER

  • University of Valladolid

    collaborator OTHER

  • Hospital del Rio Hortega

    lead OTHER

Principal Investigators

  • Santiago Cepeda, PhD · Hospital Río Hortega

Study Design

Allocation
NON_RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-11-01
Primary Completion
2025-05-30
Completion
2025-12-01

Countries

  • Spain

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05735171 on ClinicalTrials.gov