For many people, gastrointestinal (GI) disorders are chronic and life-changing circumstances. Despite their prevalence, doctors are often challenged by patients who experience persistent symptoms without being accurately identified and diagnosed.
Lei Shi from Kennesaw State University – A Association of Mechanical Engineering at Southern Polytechnic College of Engineering and Engineering Technology (SPCEET), together with Dr. ir. Anand Jain from Emory University – works to change that. Supported by a recent National Science Foundation (NSF) fair, Shi leads a research project that could change how GI disorders are diagnosed and treated using virtual replicas of a human stomach.
“This research is personally for me,” said Shi. “I have experienced stomach problems myself and I know how disturbing they can be. Many people feel discomfort, nausea or digestive problems, but after an endoscopy or imaging she is told that everything looks normally. We want to understand what is happening at a deeper level.”
SHI’s approach is based on two important assumptions. Firstly, microscopic changes in the mechanical properties of the stomach can exist, even when the organ seems normal. Secondly, these disturbances in the natural electrical signaling patterns of the stomach can change how the contract and moves food. By combining advanced medical imaging, biomechanics tests and computational modeling, his team develops patient-specific ‘digital twins’. These twins are virtual models of the stomach of a person who simulate both his physical structure and his electrical activity.
The research includes collaboration with two doctors at Emory University, which provide Shi data, including CT scans, endoscopy images and a specialized measurement called manometry, which records pressure changes and distortion in the stomach and esophagus. In its intelligent biomechanics laboratory on the Marietta campus from KSU, Shi and his team integrate this data in 3D models and then perform biomechanical tests such as pull and biasxial tests to determine the stiffness and elasticity of the tissue.
“Two stomachs can look the same, but one can be stiff while the other is soft. That difference influences how it moves,” said Shi. “By combining mechanical properties with electrical activity patterns, we can make a model that behaves just like the real organ.”
These digital twins can have far -reaching implications. They could not only help to detect subtle changes in the stomach that miss current tools, but they can also serve as a test bed for treatment planning.
“The innovative research by Dr. Shi shows the power of collaboration to create a better life for everyone,” said Spceet Dean Lawrence Whitman. “By combining engineering, computer science and medicine, his work has the potential to transform both scientific understanding and patient care.”
Shi’s vision does not stop at the stomach. His goals include expanding the modeling to the entire Gi channel from the esophagus to the intestines and studying the interaction with other systems, such as the brain gutter axis. He also plans to record machine learning to speed up analysis and prediction. By applying lessons from his earlier work modeling of the heart, the womb and the cervix, Shi hopes to speed up progress and develop a virtual platform for studying the digestive function.
Here is an exclusive Tech slips Interview, edited for length and clarity, with Shi.
Tech slips: What was the biggest technical challenge you were confronted with during the development of this patient -specific digital twins?
Shi: First of all, I want to briefly explain what digital twins are. In our case, digital twins are only a virtual copy of the organ. We start with the patient’s medical images and clinical data to build a computer model that mimics how the organs move and function. But we do not simply simulate the form in this work; We build physical models that connect what connect to the entire organ and ultimately with patient populations at the molecular level and the cellular level.
We can use this type of model to serve as a virtual test bed for virtual surgery and virtual treatment planning for the organ. For example, if we cut this a little and we make this part a bit stiffer, what will happen and can we restore the normal function of the heart?
It is actually very similar to how engineers test aircraft in simulations before they fly. Digital twins are already the gold standard in some industries. We want to bring the same idea into medicine.
So with regard to the biggest technical challenges there were several here. Unlike the aircraft example I have just mentioned, no two patients are the same. Everyone’s organs are different, making the patient model much more challenging than other industries. So the biggest obstacle was to balance the biological complexity with computational efficiency.
Tech slips: Do you have fixed plans or further research, work, etc.?
Shi: Yes. We spread from the stomach to the entire upper Gi channel.
Of the physical esophagus, for example, via the intestine. We will investigate how things interact with the brain gut axis. We know that the brain is influenced by the intestine and intestines.
Another step is to integrate the advanced AI methodology, such as generative models and neural networks to make the predictions faster and more personalized.
I also want to express my appreciation to the National Science Foundation, which supports this kind of fundamental research.
And we work together with the clinicians to validate these models against real patient data. This is the important next step, which is very necessary to translate this into health care practice.
My long -term goal is actually simple but important. I think it works for everyone. I want to help people feel healthier and happier when they eat and drink.
Tech slips: Those are all the questions I have. Is there anything else you would like to add that I didn’t touch?
Shi: An exciting aspect is that these digital twins are not just a tool for doctors; They can empower patients automatically. Imagine having your own personalized model that helps predict how your body could react to a treatment or even to a change in diet. That’s powerful.
#digital #twins #lead #function