In the exciting world of molecular imaging and fluorescence-guided surgery (FGS), the ability to see tumors and tissue boundaries in real-time is revolutionary. But for this technology to move from simple visual guidance to a reliable, reimbursable clinical tool, we must move beyond the qualitative “glow” and achieve quantitative data certainty for accurate diagnosis.
This shift requires System Characterization, a rigorous process that is fundamentally non-negotiable for any medical imaging device to really understand its optical properties and tissue detection limits.
The Problem: Systems Are Not Standard
Every single component in a fluorescence imaging system influences the final image intensity: the excitation light source, the optics, the camera sensor’s sensitivity, and the processing algorithms. If the raw image data changes when you switch cameras or even adjust the distance, that data is unreliable.
The Necessity for Characterization (Quantitative Certainty)
System characterization is the process of precisely measuring and documenting how the entire imaging chain responds to light. It provides the correction factors that allow us to turn a raw, arbitrary image signal into a true, meaningful measurement—a standard that must be maintained to ensure patient safety and data integrity.
| Why Characterization is Essential | Impact on Clinical Practice |
| Calibration and Uniformity | Ensures Consistency: Eliminates the effects of non-uniform illumination (e.g., “hotspots” in the image) and sensor defects. The system must report the same value regardless of where the target is placed in the field of view. |
| Quantitative Repeatability | Enables Data Comparison: Allows researchers and clinicians to compare image intensity measurements taken by different cameras, in different operating rooms, or even years apart. This is crucial for multi-center clinical trials. |
| Regulatory Compliance | Provides Audit Evidence: Documents the device’s technical specifications and verifies that the output remains within safe and accurate operating limits, fulfilling core requirements for the Design History File (DHF) and regulatory submissions. |
| Accurate Diagnostics | Drives Clinical Decision-Making: Moving from “Is there a tumor?” to “What is the concentration of the molecular marker?” This data precision is necessary for future diagnostic applications and dose response monitoring. |
The Solution: Using Reference Standards
To achieve this necessary uniformity, imaging systems must be calibrated using uniformity targets and dot arrays—phantom devices that have precisely known optical properties. These standards serve as the “ruler” against which the system measures its own performance, generating the correction matrices needed for reliable, quantitative imaging.
System characterization is not just a technical exercise; it is the bedrock of quantitative medical imaging, ensuring that the critical data used to make life-saving decisions is reliable, repeatable, and traceable.
Our fluorescence reference targets provide the ability to quantify performance criteria and align with recently published recommendations by international experts. Read more in the full AAPM TG-311 report, or reach out to see how we can help address your needs.
Disclaimer: This post summarizes the general principles of quantitative medical imaging quality assurance and is not a direct excerpt from the cited article.