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NCT06657027: ARTPLAN-GLIO
Artificial Intelligence-Guided Radiotherapy Planning for Glioblastoma
trial in Glioblastoma in 40 participants. Not yet recruiting.
31 December 2026
Quick facts
| Lead sponsor | Hospital del Rio Hortega |
|---|---|
| Status | Not yet recruiting |
| Study type | OBSERVATIONAL |
| Enrollment | 40 |
| Start date | 1 January 2025 |
| Primary completion | 31 December 2026 |
| Estimated completion | 30 June 2027 |
Conditions studied
- Glioblastoma — all drugs for Glioblastoma →
Sponsor
Hospital del Rio Hortega
Who can join
15 and older, any sex, with Glioblastoma. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
The ARTPLAN-GLIO study aims to evaluate the feasibility and effectiveness of integrating artificial intelligence in personalized radiotherapy planning for glioblastomas. On the basis of previous work by our group, where a predictive model was developed from radiological characteristics extracted from MR images, this project will evaluate the use of tumor infiltration probability maps in radiotherapy planning. Currently, radiotherapy treatment uses margins defined by population studies, without considering the individual characteristics of the patients. Although 80% of recurrences occur in peritumoral areas close to the surgical margins, treatment volumes are not customized owing to the lack of techniques that distinguish between edema and infiltrated tumor tissue. Our recurrence probability maps address this limitation and could improve radiation planning. In this study, the volumes and doses of radiotherapy were adjusted according to the predictions of the model, with a focus on high-risk areas to optimize local control and reduce toxicity in healthy tissues. Survival results will be compared between patients treated with personalized AI-guided radiotherapy and a historical cohort with standard treatment. In addition, the safety of the approach will be evaluated by adverse event analysis. Finally, an accessible online platform with the potential to transform glioblastoma treatment and improve patient survival will be developed to implement this predictive model.
Publications & conference data
2 peer-reviewed publications reference this trial (live from Europe PMC):
-
Decoding the Glioblastoma Microenvironment: AI-Driven Analysis of Cellular MRI Signatures for Targeted Therapy.
Sun Y, Wang K, Ye T. · · 2026 · PMID 41784819 · DOI 10.1007/s10571-026-01705-x -
Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma.
Cepeda S, Esteban-Sinovas O, Luppino LT, Kuttner S, et al · · 2025 · PMID 41402363 · DOI 10.1038/s41598-025-27711-5
Verify or expand the search:
- PubMed search for NCT06657027
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06657027 (US National Library of Medicine, public domain)
- Publications: Europe PMC API search by NCT ID, retrieved 10 June 2026
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Hospital del Rio Hortega
- Last refreshed: 24 October 2024
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06657027.
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