Enterprise AI Analysis
coPERCIST: AI-assisted PET-CT response assessment
This study demonstrates the feasibility of AI-assisted PERCIST evaluation for [18F]FDG PET-CT, showing promising accuracy. coPERCIST offers potential for reproducible response assessment and supports future multicentre validation. It is freely available to researchers via the RECOMIA platform.
Executive Impact
Leveraging AI to revolutionize PET-CT response assessment, coPERCIST delivers enhanced accuracy and efficiency, critical for precision oncology.
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SULpeak Quantification Accuracy
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Review Time (Minutes)
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Patients Evaluated
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
AI-Assisted Diagnostics
Predictive Analytics
Operational Efficiency
Enhanced Diagnostic Precision
AI-assisted diagnostics, exemplified by coPERCIST, dramatically improve the accuracy and consistency of medical image analysis. By automating complex, labor-intensive tasks like lesion segmentation and longitudinal comparison, AI reduces human variability and ensures standardized, quantitative assessments. This leads to more reliable treatment response evaluations, enabling clinicians to make data-driven decisions faster and with greater confidence. The integration into platforms like RECOMIA democratizes access to advanced tools, fostering multicentre validation and accelerating research into new treatment protocols.
Forecasting Patient Outcomes
While coPERCIST primarily focuses on current response assessment, its robust quantitative output lays a strong foundation for future predictive analytics. By standardizing SULpeak calculations and lesion tracking over time, AI creates consistent datasets essential for training models that could forecast patient outcomes, identify non-responders earlier, or predict the efficacy of different therapeutic regimens. This shift towards predictive capabilities transforms reactive treatment adjustments into proactive, personalized care strategies, optimizing resource allocation and improving patient quality of life.
Streamlining Clinical Workflows
Operational efficiency is significantly boosted through AI automation in PET-CT response assessment. Manual PERCIST analysis is time-consuming and requires specialized expertise, creating bottlenecks in busy clinical settings. coPERCIST's semi-automated workflow reduces review time to less than a minute for most cases, freeing up clinicians for more complex tasks and increasing patient throughput. This efficiency gain not only lowers operational costs but also improves the timely delivery of critical diagnostic information, enhancing overall healthcare system performance.
coPERCIST Baseline Study Workflow
The AI-assisted workflow for baseline PET-CT studies automates key steps, streamlining PERCIST analysis.
Organ Segmentation
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Background Activity Quantification
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Lesion Segmentation
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PERCIST Response Assessment
93%
Patients meeting PERCIST quality criteria for background SUL
Our AI-suggested liver and aorta VOIs were correctly positioned in all cases, leading to a high percentage of patients meeting PERCIST quality criteria for background SUL. No manual adjustments were needed for VOI placement, showcasing the AI's precision.
| Feature | Manual PERCIST | coPERCIST (AI-Assisted) |
|---|---|---|
| Workflow Automation | Extensive manual steps |
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| Time Efficiency | Time-consuming and laborious |
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| Reproducibility | Prone to variability |
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| Image Alignment | Manual or basic tools |
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| Lesion Tracking | Manual identification and matching |
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AI-Assisted Lesion Matching Success
Problem: Accurately tracking and comparing lesions across multiple PET-CT scans is a major challenge in traditional PERCIST, often leading to variability and increased review time.
Solution: coPERCIST implemented a novel image alignment method using organ-specific transformations and uncertainty estimation. This enabled accurate lesion tracking over time.
Outcome: The anatomical alignment method demonstrated accurate lesion matching in all cases (100%). Quantitative assessment of changes in PET tracer activity was accurate in 95% (123/130 lesions), significantly improving efficiency and reliability of response assessment.
100%
Accurate Anatomical Lesion Alignment
Calculate Your AI ROI
Estimate the potential time savings and financial return for your enterprise by integrating AI-driven medical imaging analysis.
Estimated Annual Savings
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Annual Hours Reclaimed
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Your AI Implementation Roadmap
A strategic overview of how coPERCIST can be integrated into your enterprise, ensuring a smooth transition and maximal impact.
Phase 1: Platform Integration & Core Automation
Seamless integration of coPERCIST into the RECOMIA platform and automation of fundamental PERCIST steps like background activity quantification and lesion detection.
Phase 2: Advanced Longitudinal Analysis
Development and validation of novel image alignment methods, including organ-specific transformations for accurate lesion tracking and comparison over time.
Phase 3: Multi-Centre Validation & Expansion
Broader validation across diverse patient populations and clinical settings, including multicentre trials, to establish generalizability and utility in precision oncology.
Phase 4: Research Accessibility & Future Enhancements
Making coPERCIST freely available to researchers via the RECOMIA platform and continuously improving AI models for enhanced accuracy and expanded capabilities.
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