Ultrasound for Body Composition Measurements and Nutritional Status Assessment

Abstract

Human body composition measurements such as fat and fat-free mass play a critical role in qualifying health and nutritional status, the impact of disease, and change due to nutritional, therapeutic, or behavioral intervention. However, these measures are difficult to obtain, and require expensive equipment as well as specialized facilities and staff. Given the rise of low-cost mobile ultrasound systems, and ultrasound’s proven ability to assess measures of adipose tissue and skeletal muscle, our team will develop a novel ultrasound tool that can guide a user to collect high quality data and automatically determine body composition measures for nutritional evaluation. Through support from the Schiller Institute, we are launching a pilot study with clinical collaborators at the Brigham and Women’s Hospital (Boston, MA) and Jimma University (Jimma, Ethiopia). The pilot study will consist of: (1) clinical data collection, (2) developing machine learning models for image analysis and prediction, and (3) human-centered design for frontline healthcare workers. This project involves research collaboration across engineering, nursing, and computer science.

Presentations

• Accepted poster presentation at the Biomedical Engineering Society (BMES) Annual Meeting (will be held in Baltimore in October 2024)
• 2023 Sigma Region 15 Nursing Research Symposium. Allison Lombardi, Susie Kwon, Mary Loeb, Bryan Ranger, Jinhee Park. “Ultrasound for Assessing Growth and Nutritional Status in the Pediatric Population: A Scoping Review”

Publications 

• Ranger, B., Lombardi, A., Kwon, S., Loeb, M., Cho, H., He., K., Wei, D., and Park, J. "Ultrasound for assessing growth and development in the pediatric population: scoping review and future directions." Acta Paediatrica.
• Li, Y., He, K., Cho, H., & Ranger, B. J. “Ultrasound segmentation using deep learning: training on musculoskeletal phantom data and testing on clinical data.” 2023 IEEE MIT Undergraduate Research Technology Conference (URTC).
• Gaudette, C., Cho, H., Saikia, M. J., & Ranger, B. J. (2022, September). “Mimicry of skeletal muscle tissue with layered phantom for ultrasound imaging.” In 2022 IEEE MIT Undergraduate Research Technology Conference (URTC) (pp. 1-6). IEEE.
  

Students Trained 

• 5 Undergraduate Students
  • Hayoung Cho, Department of Engineering
  • Yi Li, Department of Engineering
  • Mary Loeb, Department of Engineering
  • Allison Lombardi, Department of Engineering
  • Susie Kwon, Department of Engineering
    
• 3 Graduate Students
  • Marisa Albert, Department of Engineering
  • Jini Kim, Department of Engineering
  • Esther Apraku Bondzie, Department of Engineering

Additional Accomplishments 

• Established key partnerships between Boston College departments of Engineering, Computer Science, and Nursing were created, as well as formal clinical partnerships with Brigham and Women's Hospital (Boston) and Jimma University Medical Center (Ethiopia).
• Developed new protocols for clinical data collection, set up research databases, and acquired necessary equipment for pilot studies at Brigham and Women’s Hospital and Jimma Medical Center
• Visited (with 2 graduate students and 1 undergraduate student) our partners in Jimma, Ethiopia (August 2023).
• Prof. Ranger received a Google Research Scholar Program grant on related research topics.