Cancer Risk Scoring Algorithm for Lung Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cancer detection methods face challenges in accurately identifying lung cancer in asymptomatic individuals due to high rates of false positives and negatives, leading to unnecessary testing and delayed diagnosis, while existing methods lack a non-invasive and precise way to quantify individual cancer risk.
Innovation Solution
A blood test that analyzes a panel of biomarkers to generate a composite score, compared to a database of cancer and control samples, categorizing an individual's risk as low, intermediate, or high, allowing for targeted follow-up testing and reducing unnecessary procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cancer detection tests are made more sensitive to detect early-stage cancer, then the ability to detect cancer improves, but the rate of false positives increases
Solution Approach 1:
The invention segments the cancer detection process into multiple independent components: a blood-based biomarker screening test that identifies high-risk individuals, followed by targeted CT imaging only for those who test positive. This segmentation allows the highly sensitive CT scans to be applied selectively, reducing overall false positives while maintaining high detection sensitivity for the screened population.
Solution Approach 2:
The invention introduces an intermediary blood-based biomarker test between the general population and CT scanning. This intermediary screen filters individuals based on their risk profile before subjecting them to CT imaging, thereby reducing the number of false positives that would otherwise occur from universal screening while still capturing early-stage cancers in the high-risk subset.
2Measurement precision
If universal cancer screening is performed on all asymptomatic individuals, then early detection rate improves, but the number of unnecessary follow-up tests and radiation exposure increases
Solution Approach 1:
The invention applies local quality by tailoring the screening intensity to individual risk profiles. Instead of uniform screening, high-risk individuals (based on biomarkers, smoking history, and other factors) receive intensive CT-based screening, while low-risk individuals receive minimal or no screening, thereby reducing unnecessary radiation exposure and testing while maintaining high early detection rates in the vulnerable population.
Solution Approach 2:
The invention changes the screening parameters dynamically based on individual characteristics. The blood biomarker levels, smoking history, age, and other risk factors serve as parameters that determine the screening intensity. This parameter-based approach allows the system to optimize the balance between early detection and minimizing harmful effects for each individual patient.
3Ease of operation
If binary yes/no cancer test results are provided, then patient understanding improves, but the nuance of risk levels is lost leading to misleading conclusions
Solution Approach 1:
The invention segments the risk assessment into distinct categories (e.g., low risk, intermediate risk, high risk, very high risk) rather than providing a single binary result. This segmented approach maintains patient comprehensibility while preserving the nuanced information about different risk levels, allowing clinicians to appropriately tailor follow-up recommendations to each risk category.
Data Source
AI summary
A method of data interpretation from a multiplex cancer assay is described. The aggregate normalized score from the assay is transformed to a quantitative risk score quantifying a human subject's increased risk for the presence of cancer as compared to the known prevalence of the cancer in the population before testing the subject.