End-user validation of BRIGHT with custom-developed graphical user interface applied to cervical cancer brachytherapy

2026-02-19 · Source: cs.NE updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Medical AI Applications · Depth: Expert, extended

Summary

BRIGHT (BRachytherapy via artificially Intelligent GOMEA-Heuristic based Treatment planning), a semi-automated multi-objective optimization method, has been extended to cervical cancer brachytherapy. This study introduces and validates a novel graphical user interface (GUI) for BRIGHT, designed to facilitate plan navigation, pairwise comparisons, dose distribution visualization, and adjustments. End-user validation involved a multidisciplinary brachytherapy team emulating clinical practice for ten previously treated cervical cancer patients. The GUI achieved an "excellent" System Usability Scale (SUS) score of 83.3. BRIGHT-generated plans outperformed clinical practice in 50% of cases and performed equally well in the remainder, with BRIGHT plans preferred in 8 out of 10 patients, four of which showed clinically relevant differences. The GUI's features, including the "Golden Corner" for aim achievability and re-optimization capabilities, were highly valued.

Key takeaway

For AI Scientists developing clinical decision support tools, this study demonstrates that a well-designed GUI is paramount for user adoption and efficient integration of multi-objective optimization into clinical workflows. Focus on intuitive plan navigation and comparison features, like BRIGHT's Golden Corner and difference view, to empower clinicians to quickly assess trade-offs and tailor treatment plans, even if it means allowing for manual adjustments outside the core optimization to build trust.

Key insights

BRIGHT with its new GUI offers an excellent, user-friendly semi-automated planning tool for cervical cancer brachytherapy.

Principles

• Multi-objective optimization improves plan quality.
• GUIs are essential for clinical adoption of AI tools.
• End-user validation in emulated settings is critical.

Method

BRIGHT uses MO-RV-GOMEA for multi-objective optimization, generating a Pareto approximation front of plans. The GUI enables navigation, comparison, and re-optimization based on user-defined constraints, with dose calculation points used for precise DV metric optimization.

In practice

• Use BRIGHT's "Golden Corner" to quickly assess planning aim achievability.
• Utilize the difference view for one-on-one plan comparisons.
• Adjust dwell time contributions via re-optimization for tailored plans.

Topics

• Cervical Cancer Brachytherapy
• Multi-objective Optimization
• BRIGHT Treatment Planning
• Graphical User Interface
• End-user Validation

Best for: AI Scientist, Research Scientist, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.NE updates on arXiv.org.