Evaluation of the Efficacy and Safety of Personalized Radiotherapy Guided by Predictive Models of Tumor Infiltration, Combining Artificial Intelligence and Multiparametric MRI in Glioblastomas
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 40
- 主要终点
- Feasibility of AI-Guided Radiotherapy for Glioblastoma
研究概览
简要总结
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 15 Years 至 —（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients with a recent diagnosis of IDH wild-type glioblastoma, grade 4 according to the Central Nervous System Tumors classification of the World Health Organization of
- •Ability to undergo MRI studies.
- •Performance status with Karnofsky Performance Status (KPS) ≥
- •Life expectancy ≥ 12 weeks.
- •Laboratory results within the following ranges, obtained in the 14 days prior to enrollment:
- •Leucocitos ≥ 3,000/µL.
- •Absolute neutrophils ≥ 1,500/µL.
- •Plaquetas ≥ 75,000/µL.
- •Hemoglobin ≥ 9.0 g/dL (transfusion is allowed to reach the minimum level).
- •Glutamic-oxaloacetic transaminase (SGOT) ≤ 2 times the upper limit of normal.
- •Bilirubin ≤ 2 times the upper limit of normal.
- •Creatinina ≤ 1.5 mg/dL.
- •Women of childbearing age must present a negative pregnancy test ≤ 14 days prior to enrollment.
- •Ability to understand and sign the informed consent.
- •Willingness to refrain from other cytotoxic or noncytotoxic therapies against the tumor during the protocol.
排除标准
- •Presence of pacemakers, neurostimulators, cochlear implants, metal in ocular structures, or work history that compromise safety in MRI.
- •Significant medical illnesses that may compromise tolerance to treatment, at the discretion of the investigator.
- •History of invasive cancer in the last 3 years, with few exceptions.
- •Active infections or serious intercurrent illnesses.
- •Previous treatments with cytotoxic, noncytotoxic, experimental agents, or cranial radiation therapy.
- •Maximum radiation target volume (GTV3) greater than 65 cc.
结局指标
主要结局
Feasibility of AI-Guided Radiotherapy for Glioblastoma
时间窗: 12 months after the start of radiotherapy for the last enrolled patient.
The primary outcome of the study is to assess the feasibility of integrating an AI-based predictive model into radiotherapy planning for patients with glioblastoma. The model uses radiomic features derived from multiparametric MRI to generate tumor infiltration probability maps, which guide the personalized adjustment of treatment volumes and doses. Feasibility will be determined by evaluating the successful integration of the AI model into clinical practice, the precision of the model in identifying areas of tumor infiltration, and the ability to implement personalized treatment plans in a routine clinical setting.
次要结局
- Progression-Free Survival (PFS) at 1 Year(12 months after the start of radiotherapy for each patient.)
- Overall Survival (OS)(24 months after the start of radiotherapy for each patient.)
- Quality of Life(12 months after the start of radiotherapy for each patient.)
研究者
Santiago Cepeda
Attending Neurosurgeon
Hospital del Rio Hortega