Finite Element Modeling of Abdominal Near-Infrared Spectroscopy for Infant Splanchnic Oximetry

Area of Science:

• Biomedical optics
• Medical imaging
• Computational modeling

Background:

• Near-infrared spectroscopy (NIRS) shows potential for early infant disease detection.
• Optimal NIRS sensor design for infant splanchnic oximetry remains undefined.
• Necrotizing enterocolitis requires early detection to prevent irreversible injury.

Purpose of the Study:

• To develop and demonstrate a computational method for evaluating NIRS sensor designs for infant splanchnic oximetry.
• To determine the optimal source-detector distance (SDD) for NIRS sensors in infants.

Main Methods:

• Utilized a finite element (FE) approach to simulate near-infrared light transport.
• Created a 3D infant abdomen model from computed tomography (CT) images.
• Calculated contrast-to-noise ratio (CNR) as a function of SDD for different sensor positions.

Main Results:

• Maximal contrast-to-noise ratio (CNR) for splanchnic oximetry was observed at source-detector distances (SDD) between 4 and 5 cm.
• Sensor positions near the umbilicus yielded comparable results.
• NIRS sensors at 4-5 cm SDD showed greater sensitivity to intestinal tissue than superficial adipose tissue.

Conclusions:

• Finite element (FE) modeling provides an effective method for evaluating NIRS sensor designs for infant splanchnic oximetry.
• Optimized NIRS sensor design can enhance the reliability and application of infant splanchnic oximetry.
• This approach can aid in the early detection of infant pathologies, improving patient outcomes.