Understanding Fluorescence Image Contrast

Understanding your system's performance characteristics is crucial for ensuring reliable results. Three key parameters - (1) system linearity, (2) limit of detection, and (3) saturation point - form the foundation of your system's imaging contrast. Let's break down what these mean and how to measure them.

Why These Parameters Matter

Imagine trying to take pictures of stars with a camera. Too dim, and the stars disappear into the background. Too bright, and the stars “wash out,” making it challenging to pick them apart. 

The same stars are photographed in all three pictures, but with different camera contrast settings. 

Fluorescence imaging faces similar challenges - knowing exactly how bright the scene and its components are will ensure accurate detection of fluorophores or contrast agents. Without evaluating the contrast of the imaging system, subtle variations in fluorescence or misinterpretation of the contrast between a highly fluorescent structure and its moderately fluorescent surroundings can occur. The imaging contrast tells us how much variation a particular imaging system can capture.

The same QUEL coin is imaged on the same fluorescence imaging system with different contrast settings. The system’s excitation laser setting is the same in all three images so the coin is emitting the same amount of fluorescence.

Understanding System Linearity

System linearity is the relationship between the input (fluorophore concentration) and output (measured fluorescence intensity). Under ideal conditions, these quantities should be proportional to one another. This proportional relationship is crucial for two key reasons:

1. Accurate estimation of fluorophore concentrations in tissue
2. Proper visualization of tissue structures or spatial variations in fluorophore density, particularly of fluorescently-labeled regions against background

Characterizing Your System’s Linearity, Limit of Detection, and Saturation

1. Using your imaging system, take images of the Concentration Target at your working distance under typical conditions with standard imaging parameters. QUEL’s Concentration Target features a black, non-fluorescent background. Each of the gray circles is like a thick fluorescent coin called a “well,” each containing different concentrations of contrast agent.  The imaging system may capture images is shown at the right, where the well with highest concentration will appear brightest and the well with lowest concentration will appear dimmest.
2. For each of the wells, measure the pixel intensity.
3. Plot measured pixel intensity vs. concentration. A representative example of the expected data outcome is shown to the right on a log-log plot
4. Identify the range where the relationship is proportional. This is “system linearity.”
5. The “limit of detection” can be estimated as the concentration at which contrast-to-noise ratio equals 3. Below this, a change in concentration no longer produces a proportional change in fluorescence intensity. And the “noise floor” is where the change in concentration leads to no (or small random) change in fluorescence intensity.
6. At the other end of the spectrum, the “saturation point” is where an increase in fluorescence concentration does not appear to be brighter on the imaging system. 

Here are some example images of what you may see with your fluorescence imaging system:

For detailed step-by-step instructions, follow Use Guide: Concentration Targets.

Best Practices for Characterization

Reference targets, such as concentration-specific phantoms, provide a standardized way to characterize these parameters. When selecting tools:

• Ensure they cover fluorophore levels that represent expected concentrations
• Account for photobleaching effects
• Consider shelf-stability, if conducting longitudinal studies

Test your system using the same settings (camera exposure time, camera gain, working distance, ambient lighting conditions, etc.) that will be used in clinical practice. If your system has different operating modes, characterize each one separately.

Looking Ahead

As medical imaging systems become more sophisticated, understanding and characterizing these fundamental parameters becomes increasingly important. Proper characterization of your system ensures your imaging system can reliably detect and measure the biological phenomena you're investigating.

For more detailed guidance on system characterization and standardization, refer to the AAPM TG311 guidelines. Implementation tools and reference targets are available to help you meet these standards effectively.

Interested in characterizing your imaging system or developing a customized fluorescence reference target? Contact QUEL Imaging!