Patient stratification for dose scaling in cervical cancer: a model-based analysis using image-guided adaptive...

Area of Science:

• Oncology
• Medical Physics
• Radiotherapy

Background:

• Image-guided adaptive brachytherapy (IGABT) is a key treatment for cervical cancer.
• Dose scaling (DS) is a technique to optimize radiation dose delivery.
• Identifying patient subgroups who benefit most from DS is crucial for personalized treatment.

Purpose of the Study:

• To identify characteristics of cervical cancer patients who gain the most therapeutic benefit from model-based dose scaling (DS) in IGABT.
• To evaluate the impact of DS on tumor control probability (TCP) and normal tissue complication probability (NTCP).

Main Methods:

• Retrospective analysis of 57 cervical cancer patients treated with IGABT and external beam radiotherapy.
• Simulation of model-based DS to escalate brachytherapy dose up to NTCP thresholds.
• Comparison of patient characteristics between groups with and without significant TCP gain (>3%).

Main Results:

• 16 out of 53 evaluable patients (30.2%) achieved a significant TCP gain.
• Adeno/adenosquamous carcinoma (AdSq) histology (100% gain) and uterine corpus invasion (UCI) on MRI (significant predictor) were strongly associated with benefit.
• Larger high-risk clinical target volumes limited the potential for dose escalation.

Conclusions:

• Patients with AdSq histology and UCI on MRI are likely to benefit most from DS in IGABT for cervical cancer.
• Model-based DS shows promise for personalized treatment planning in cervical cancer.
• This approach supports tailoring radiation strategies to individual patient and tumor characteristics.