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Joint Methodology Based on Optical Densitometry and Dynamic Light Scattering for Liver Function Assessment
Elina Karseeva1, Ilya Kolokolnikov1, Ekaterina Medvedeva1
1Higher School of Applied Physics and Space Technologies, Institute of Electronics and Telecommunications, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg 195251, Russia.
Diagnostics (Basel, Switzerland)
|April 13, 2023
Summary
This study introduces a novel method combining optical densitometry and dynamic light scattering for improved liver function assessment. The new approach aids in diagnosing liver disease and predicting treatment outcomes more effectively.
Area of Science:
- Biomedical Engineering
- Medical Diagnostics
- Optical Physics
Background:
- Increasing prevalence of liver damage from various causes (viral hepatitis, cancer, toxins, metabolic disorders) presents a significant health challenge.
- Current liver function assessment methods have limitations hindering prompt and accurate diagnosis, leading to high morbidity and mortality.
- Urgent need for advanced diagnostic tools to improve patient outcomes for liver diseases.
Purpose of the Study:
- To develop and present a novel, combined methodology for assessing liver function.
- To enhance the efficiency of diagnosing liver conditions and predicting treatment response.
- To integrate individual cardiovascular system and tissue metabolism data into liver function analysis.
Main Methods:
- Development of a laboratory model for a combined sensor utilizing optical densitometry and dynamic light scattering.
- Creation of specialized software for sensor control and data processing.
- Calibration and validation through modeling experiments and physical medical studies.
Main Results:
- Successful development and calibration of a combined optical densitometry and dynamic light scattering sensor system.
- Validated software for sensor operation and data analysis.
- Assessment of sensor resolution for dye concentration and minimum flow rate detection.
Conclusions:
- The new joint methodology offers a more efficient approach to diagnosing liver function and predicting treatment dynamics.
- Integration of patient-specific physiological data (cardiovascular, metabolic) enhances diagnostic accuracy.
- The developed sensor and software system show promise for improved liver disease management.
