Yayu Monica Hew's Internship Highlights: Development of a Reliable Device for Peripheral Edema Quantification via Ultrasound Imaging

Yayu Monica Hew: Development of a Reliable Device for Peripheral Edema Quantification via Ultrasound Imaging

Figure 1. Pictures showing the 2018 Hypoxia Experiment operation. Top: The hypoxia chamber activity area. This chamber will simulate the oxygen level from 2000m to 6000m. Bottom Right: participants filled out mountain sickness surveys. Bottom Left: the monitoring console allows researcher to monitor the chamber conditions and the participant activities in the chamber remotely.

Summary of the Project

As a continuation of my previous assignment at the German Space Center (DLR), Dept of Space Physiology, I completed a series of tasks as shown below during my internship. My project developed the biomechanical device, the operation procedure, and the ultrasound image analysis software to study the tissue swelling in the human body (edema) under various space environment conditions, such as in the hypoxia conditions when the astronauts are subject to the reduced levels of oxygen. Using the hardware and software developed from last year, I was able to deploy this method to study the edema developed in our 20 medical test participants during the 2018 Hypoxia Study. Additionally, I have also completed many important milestones and made a significant contribution to the DLR. Beyond this project, I also helped another Stanford student in setting up a possible future internship at DLR as well as a possible post-doctoral position for myself working on the next generation space sleeping bag for the astronauts.

Tasks Completed

1.   Edema measurement in the 2018 Hypoxia Study
2.   Improved edema measurement experimental protocols
3.   Simplified software interface and architecture
4.   A manuscript for JoVE: Peer-reviewed Journal of Visualized Experiments
5.   Minor hardware refinement and some 3D printed spare parts for the device

Figure 2. Snap shots of the JoVE manuscript draft.

Figure 2. Snap shots of the JoVE manuscript draft.

In the following sections, we will only highlight two key contribution sections: Edema measurement in the 2018 Hypoxia Study and Software Augmentation for Simplified User Interface.

Highlight 1: Edema measurement in the 2018 Hypoxia Study

I led the scientific operation of the peripheral edema measurements (at forehead and limb positions) for a high-altitude chamber experiment that simulated the low-oxygen environment from 2000m to 6000 m. A total of 19 participants (volunteers) have been measured during a 4-day high-altitude chamber study. In addition to the edema measurement, the 2018 Hypoxia Study also gave me an excellent opportunity to collaborate with other researchers from the University of Dusseldorf in studying the microcirculation changes before and after the hypoxia exposure.

Figure 3. The 2018 Hypoxia Experiment Measurement Schedule. The scientific study last for four days, including two setup days (Day 1 and Day 3) and two experiment day (Day 2 and Day 4). On each measurement day, participants stay inside the hypoxia chamber for 6 to 9 hours (as shown in the figure) and will be exposed to reduced oxygen levels to simulate the hypoxia conditions.

Figure 4. The result of the 2018 Hypoxia Study.

Impact: Conducted the first successful edema field measurement in the hypoxia chamber environment. Acquired the first high-precision robust acute edema data.

Highlight 2: Software Augmentation for Simplified User Interface

Figure 5. The software architecture of the Tissue Edema Analysis Software (TEAS).

I have developed a Matlab software, the Tissue Edema Analysis Software (TEAS), to analyze the tissue thickness ultrasound images and compute the tissue thickness automatically. In this summer, I have simplified the TEAS software architecture significantly to allow a more user-friendly interface for the future researchers. The simplified software architecture of TEAS is presented in Figure 6. The TEAS software enables tissue boundary identification automatically and through user manually. The tissue thickness will then be computed automatically using the algorithm I developed. With the successful development of TEAS, we can reduce the tissue thickness image analysis time by more than 200% (compared to when TEAS is not used). We also remove the user bias in the image analysis process and thus improve the quality of the data. The TEAS sample output is shown in Figure 7. The user can acquire these automatic results within minutes after executing the TEAS software, and a summary report will also be generated in both Excel and CSV (comma separated files) that can be used in statistical analysis software directly.

Impact: Improve edema analysis efficiency by more than 200% especially for large population study; Reduce analysis bias introduced by human researchers.

Figure 7. Sample output from the Tissue Edema Analysis Software (TEAS).

Figure 6. Sample output from the Tissue Edema Analysis Software (TEAS). Tissue boundaries are identified automatically, and a tissue thickness array is computed. The results are shown in both tabular and image format.

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