Early Cancer Detection in Blood Vessels Using Mobile Nanosensors

Area of Science:

• Biomedical Engineering
• Nanotechnology
• Medical Diagnostics

Background:

• Early-stage cancer detection is challenging due to low biomarker concentrations in conventional blood tests.
• Cancer cells release specific biomarkers into the cardiovascular system.
• Proximity to cancer cells allows for higher biomarker concentration, enabling detection.

Purpose of the Study:

• To propose and evaluate mobile nanosensors (MNSs) for early-stage anomaly detection, specifically cancer cells in blood vessels.
• To develop analytical models for biomarker concentration and MNS activation levels.
• To design and assess decision rules for anomaly detection at a fusion center (FC).

Main Methods:

• Analytical derivation of biomarker concentration and MNS activation probability mass function.
• Particle-based simulations for validating analytical models.
• Derivation of an optimal decision rule for the FC assuming network knowledge.
• Proposal of a network-topology-independent sum detector for the FC.

Main Results:

• Analytical models for biomarker concentration and MNS activation were derived and validated.
• An optimal decision rule and a practical sum detector were developed for the FC.
• Both proposed detectors significantly outperformed a benchmark scheme using fixed nanosensors.

Conclusions:

• Mobile nanosensors (MNSs) show promise for early-stage anomaly detection in cardiovascular systems.
• The proposed MNS-based approach offers superior performance compared to fixed nanosensor methods.
• The developed detection strategies provide effective means for identifying anomalies based on MNS activation levels.