Fluorescence Intensity Calculation Using ImageJ in Laparoscopic Cholecystectomy
To calculate fluorescence intensity during laparoscopic cholecystectomy using ImageJ, import your fluorescence images, select regions of interest (ROIs) on the bile duct and liver parenchyma, measure mean fluorescence intensity (MFI) for each ROI, and calculate the bile duct-to-liver ratio (BLR) to objectively assess biliary visualization quality. 1
Step-by-Step ImageJ Protocol
Image Acquisition and Import
- Capture fluorescence images at standardized timepoints during surgery: before dissection of Calot's triangle, before clipping the cystic duct, and before closure 2
- Import both fluorescence images and corresponding bright field images into ImageJ software for reference 1
- Maintain consistent imaging parameters between compared images, including camera distance from tissue and exposure time 1
Region of Interest (ROI) Selection
- Use the ROI selection tool in ImageJ to outline specific anatomical structures: common bile duct, cystic duct, and liver parenchyma 1
- Apply consistent ROI sizes when comparing multiple images to ensure reproducibility 1
- Use anatomical landmarks to ensure consistent ROI placement across different images and timepoints 1
Quantitative Measurement
- Measure mean fluorescence intensity (MFI) within each selected ROI using ImageJ's "Measure" function 1
- Record raw numeric values for each structure (bile duct, liver background) 1
- Calculate the bile duct-to-liver ratio (BLR) by dividing the MFI of the bile duct by the MFI of the liver parenchyma 2
Advanced Quantification Methods
Surface Area Correction
- For more accurate quantification, adjust measurements using the formula: MFI_corrected = fluorescence intensity of tissue of interest / (injected dose/surface area of the tissue) 1
- This approach parallels SUV calculations in PET imaging but is adapted for fluorescence applications 1
Visual Analysis Enhancement
- Generate pseudo-colored heat maps in ImageJ to visualize intensity differences on a color spectrum 1
- Create black-and-white fluorescence images, pseudo-colored fluorescence overlay images, and heat-maps to display signal intensity differences 3
- Use consistent color scales when comparing multiple images to maintain objectivity 1
Interpretation of Results
Optimal Visualization Criteria
- Ideal fluorescent cholangiography is achieved when maximum fluorescence is present in biliary ducts with minimal signal in liver parenchyma, defined as high signal-to-background ratio (SBR) 4
- A BLR ≥ 3 to ≥ 5 indicates optimal cholangiography quality for clear biliary structure identification 2
- Higher BLR values correlate with better visualization of the cystic duct and common bile duct 2
Timing Considerations
- Fluorescence intensity measurements should be performed at multiple surgical timepoints, as BLR values change during the procedure 2
- The highest BLR typically occurs before surgical dissection of the cystohepatic triangle 2
Critical Pitfalls to Avoid
Technical Factors
- Inconsistent ROI selection is the most common source of measurement error—always use anatomical landmarks to standardize ROI placement 1
- Proximity to vessels, air spaces, or bone can interfere with fluorescence measurements 5
- Variations in camera angle and distance significantly affect fluorescence intensity readings 6
Patient-Related Factors
- Patients with higher BMI demonstrate lower fluorescence intensity, requiring adjustment of interpretation thresholds 6
- Cholecystitis reduces fluorescence intensity but paradoxically makes NIRF imaging more clinically helpful 6
Standardization Requirements
- Strict standardization of imaging protocols, data collection, and analysis is necessary to obtain quantitative, accurate, and reproducible results 5
- Include both qualitative analyses (bright field, black-and-white fluorescence, pseudo-colored overlay) and quantitative data (raw numeric values and ratios) in your reporting 3