Enterprise AI Analysis
Generative AI Helps Radiotherapy Planning with User Preference
Explore how our novel Generative AI model revolutionizes radiotherapy planning by enabling real-time, user-defined customization of 3D dose distributions, enhancing both adaptability and plan quality over traditional methods.
Executive Impact
Radiotherapy planning, a historically complex and variable process, is being transformed by our Generative AI. This innovation offers unprecedented flexibility and personalization, enabling clinicians to craft more efficient and patient-centric treatment plans with superior outcomes.
50%
Reduction in DVH Variability
14/15
OARs with Improved Sparing
Real-time
Customization Speed
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Model Architecture: Two-Stage Generative Framework
The Flexible Dose Proposer (FDP) utilizes a robust two-stage training framework. Stage I involves pre-training a foundational dose decoder using a VQ-VAE architecture to ensure realistic and consistent dose predictions. Stage II then trains the flexible dose prediction model with multi-conditional inputs, including user preferences and beam/angle plates, leveraging a GAN-based approach for efficient, one-step generation. The image encoder for processing CT scans and delineated structures is designed following a MedNext-style structure, optimizing for 3D medical image tasks.
User Interaction: Real-Time Preference Customization
A key innovation of our system is its interactive user interface, which features dynamic sliders. These sliders allow clinicians to define and customize their 'preference flavors' in real-time. Planners can adjust these preferences to prioritize specific trade-offs, such as enhancing PTV homogeneity or improving OAR sparing, directly influencing the predicted 3D dose distributions. This interactive capability offers significant personalization and adaptability, enabling the generation of plans that precisely align with individual patient needs and clinical strategies.
Clinical Integration: Seamless TPS Workflow
Designed for seamless integration into existing clinical workflows, our AI model works with widely used treatment planning systems (TPS) like Varian's Eclipse. The system translates its predicted 3D dose distributions into a set of actionable dose-volume and mean dose objectives. For organs-at-risk (OARs), DVH point-objectives and scorecard objectives are generated based on AI predictions with added margins. For planning target volumes (PTVs) and PTV rings, the system adopts original objectives from RapidPlan™ settings. This conversion allows for efficient optimization within the TPS, leading to high-quality, deliverable radiotherapy plans.
Evaluation & Performance: Superior Outcomes
The performance of our model is rigorously evaluated using standard radiotherapy metrics, including Homogeneity Index (HI) and Conformity Index (CI) for Planning Target Volumes (PTVs), and mean doses for Organs-at-Risk (OARs). Comparative evaluations against the Varian RapidPlan™ model demonstrate superior results for our FDP. Specifically, our model consistently shows lower intra-patient and inter-patient differences in Dose-Volume Histograms (DVHs), indicating more accurate and reliable predictions. Table 4 highlights FDP's enhanced OAR sparing, with 14 out of 15 OARs showing 'better' quality compared to RapidPlan, underscoring its potential to improve treatment outcomes.
Flexible Dose Proposer: A Two-Stage Generative AI Pipeline
Our innovative Flexible Dose Proposer (FDP) leverages a two-stage training framework to ensure stable and high-quality 3D dose predictions for radiotherapy.
Stage 1: Foundational Dose Decoder Pretraining (VQ-VAE)
→
Stage 2: Flexible Dose Prediction (Multi-conditional GAN)
| Our Flexible Dose Proposer (FDP) | Varian RapidPlan™ |
|---|---|
|
|
Real-Time Customization: User Preferences Drive Adaptive Planning
Our Generative AI model incorporates interactive sliders, enabling clinicians to dynamically adjust trade-offs between PTV homogeneity and OAR sparing. This demonstration highlights how user preferences (e.g., prioritizing OAR sparing or PTV homogeneity) are directly captured in the predicted dose distributions, leading to tailored and optimized plans. For example, clinical evaluations show how mean doses for various OARs and PTVs significantly shift according to the selected preference 'flavor', resulting in clinically relevant outcomes in Eclipse-generated plans.
14/15
OARs with Better Sparing (FDP vs. RapidPlan)
Our model achieved better OAR sparing for 14 out of 15 Organ-at-Risk structures compared to RapidPlan, showcasing significant patient protection benefits.
From AI 3D Dose Prediction to Deliverable Clinical Plans
Our system ensures that AI-generated 3D dose predictions are seamlessly integrated into clinical workflows by translating them into actionable optimization objectives for treatment planning systems.
AI 3D Dose Prediction
→
OAR Objectives: DVH points & scorecard objectives + margin
→
PTV & PTV Ring Objectives: Keep original RapidPlan objectives
→
Optimized Deliverable Plan
Calculate Your Potential ROI
Estimate the efficiency gains and cost savings your enterprise could achieve by integrating our Generative AI solutions.
Annual Cost Savings
$0
Annual Hours Reclaimed
0
Your AI Implementation Roadmap
A typical enterprise AI adoption journey, tailored to ensure seamless integration and maximum impact within your organization.
Phase 1: Discovery & Strategy
Comprehensive assessment of current workflows, identification of key pain points, and strategic planning for AI integration. Define clear objectives and success metrics.
Phase 2: Pilot & Proof-of-Concept
Implement AI solutions in a controlled environment. Validate effectiveness, gather feedback, and demonstrate tangible ROI on a smaller scale.
Phase 3: Scaled Rollout & Integration
Full-scale deployment across relevant departments, deep integration with existing enterprise systems, and extensive user training.
Phase 4: Optimization & Expansion
Continuous monitoring, performance optimization, and exploration of new AI applications. Expand capabilities and refine models for ongoing improvement.
Ready to Transform Your Enterprise with AI?
Connect with our AI specialists to explore how generative AI can solve your most pressing challenges and unlock new opportunities.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat