Automatic exposure control and estimation of effective system noise in diffuse fluorescence tomography

Area of Science:

• Biomedical Optics
• Medical Imaging
• Fluorescence Tomography

Background:

• Diffuse fluorescence tomography (DFT) is a powerful imaging modality for biological tissues.
• Accurate quantification of endogenous or exogenous fluorophores is crucial for disease diagnosis.
• Previous DFT systems faced limitations in dynamic range, restricting detection sensitivity.

Purpose of the Study:

• To develop an automated DFT system with extended dynamic range for improved fluorophore detection.
• To enhance the quantification accuracy of biologically relevant fluorophores like protoporphyrin IX.
• To characterize system performance using an effective noise metric.

Main Methods:

• Implementation of a diffuse fluorescence tomography system utilizing time-correlated single photon counting.
• Development of an automated algorithm for dynamic range variation via exposure control.
• Characterization of system performance using an effective noise metric integrating model-mismatch and calibration bias.

Main Results:

• Achieved an order of magnitude extension in upper and lower detection levels for fluorophores.
• Demonstrated a slight decrease in system effective noise.
• Attained an effective error of approximately 7% of the reconstructed fluorescent yield.
• Enabled quantification of protoporphyrin IX concentrations down to 50 ng/ml in tumor-sized regions.

Conclusions:

• The automated DFT system significantly enhances detection capabilities for low-yield, biologically relevant fluorophores.
• The system offers precise quantification of protoporphyrin IX, crucial for tumor imaging.
• The developed technology shows promise for improved cancer diagnostics and research.