Department of Biomedical Engineering

Biomedical engineering professor Carrie Perlman has been awarded $576,525 from the National Institutes of Health (NIH) to develop improved methods of mechanical ventilation for lungs affected by acute respiratory distress syndrome (ARDS).

ARDS is a lung condition in which fluid builds up in the lung’s air sacs, or alveoli, causing difficulties breathing and low oxygen. Alveoli receive oxygen and expel carbon dioxide during the breathing process.

Mechanical ventilation, in which air is pumped into and out of the lungs, is a lifesaving therapy for ARDS but can also cause additional ventilation-induced lung injury (VILI).

Titled “Improved Ventilation of the Edematous Lung,” Perlman’s bioengineering project will introduce a new method in which she uses the decay of an electrical signal to determine the permeability of the barrier between the alveoli (air sacs) and capillaries (blood vessels).

Perlman and team will use this method to test the interaction between mechanical and inflammatory stresses in an ex vivo model, thereby determining why VILI occurs and how such injury propagates through the lungs. Perlman will also test sulforhodamine B, a dye that she has found to lower surface tension in the lungs, as a novel treatment for reducing ventilation-induced lung injury.

Stevens Institute of Technology and the Hackensack Meridian School of Medicine (HMSOM) have announced an academic partnership whereby HMSOM medical students have an opportunity to pursue a master’s degree in biomedical engineering on Stevens’ Hoboken, New Jersey, campus.

The accelerated program will be part of HMSOM’s highly individualized Phase 3 curriculum, which is available to students seeking to augment previous backgrounds in engineering or related fields.

Medical students with this additional training will be well-equipped to understand advances in medical device design and development in the future to best care for their patients.

“We are so excited to have medical students on campus and participating in this exciting curricular offering,” said Jennifer J. Kang-Mieler, chair and professor of biomedical engineering at Stevens.

HMSOM Vice Dean Stanley R. Terlecky, Ph.D., cited the emergent ties with Stevens on research and academic fronts as “important strategic initiatives through which we will continue to grow.”

Students will be eligible to enroll as early as 2024.

Jinho Kim, an assistant professor in the Department of Biomedical Engineering, recently received a $591,006 grant from the Cystic Fibrosis Foundation for his project, “Technology Platform for Modeling Cystic Fibrosis Ex Vivo.” The project seeks to establish and validate a robust model of cystic fibrosis (CF) using readily available animal model and human lungs with bioartificial mucus, supported outside the body, to optimize CF gene therapy delivery. The project is in collaboration with Columbia University.

Challenges to successful CF gene therapy include delivering the genes to the correct areas of the lung, transporting the microscopic particles used to carry gene therapies through the thick layer of mucus present in the lungs of CF patients, and inserting the necessary genes into the appropriate lung cells. Existing animal models and lung cell cultures of are poor predictors of how well gene therapies will work in humans.

Kim will develop three types of lung models for testing and optimizing gene therapy ex vivo (outside the body): a miniature model using small sections of lung in a chamber that keeps the lung tissue alive and functional; a more complex whole pig lung model; and a whole lung model of CF using human lungs that have been rejected for transplant.

This platform for modeling CF ex vivo will provide valuable insight towards developing a cure for CF.

Yu Gan, an assistant professor in the Department of Biomedical Engineering, recently received a $600,000 National Science Foundation CAREER Award for his project, “Developing Algorithms for Object-Adaptive Super-Resolution in Biomedical Imaging.” The five-year project seeks to develop intelligent, computationally efficient algorithms to improve the clarity and quality of diagnostic biomedical images in a cost-effective and generalizable manner.

Gan’s project seeks to advance national health by developing an optimized artificial intelligence framework that adaptively improves digital imaging resolution while minimizing the cost of computation in the super-resolution process. He will develop a robust neural network to detect regions of biomedical images to be super-resolved and computationally efficient algorithms to super-resolve those images when enlarged to different scales. The framework will be generalized for use across multiple biological imaging categories, including optical coherence tomography (OCT), magnetic resonance imaging (MRI) and ultrasound images for different applications.

Gan’s research will help develop cost-effective biomedical imaging methods, improving access to advanced diagnostic methods and medical care for underrepresented groups.