SE Valley Times

In the United States alone, more than 900,000 heart surgeries are performed each year. Around the globe, 17.9 million people die from heart-related diseases annually, according to the World Health Organization, making it the leading cause of death.

Comparably, 15 million colonoscopies are performed in the United States annually, and according to the American Cancer Society, colorectal cancer is the United States' second leading cause of cancer-related deaths.

Assistant Professor Sui Yang and Associate Professor Hamid Marvi, both researchers in the School for Engineering of Matter, Transport and Energy at Arizona State University (ASU), are applying their expertise to find innovative solutions for surgical procedure-related issues.

Yang is developing an endoscopic lens that will enable cardiac doctors to view high-resolution images of patients’ tissues, while Marvi aims to help colonoscopy surgeons perform successful endoscopic operations with ease.

Yang and Marvi recently earned the 2024 Arizona Biomedical Research Centre (ABRC) New Investigator Award. The award provides up to $250,000 over three years to accelerate promising research toward clinical testing and breakthroughs designed to improve the health of Arizonans.

Traditionally, doctors use an endoscope—a thin medical instrument with a light and a lens—to examine parts of the heart invisible to them. The endoscope’s flexibility and image resolution directly affect doctors’ ability to make informed decisions about their patients’ treatments.

While regular endoscopes have saved many lives, they have limited resolution and are not flexible enough to reach all parts of the heart. Yang is developing a novel cardiac endoscope lens based on metamaterials with unique custom-designed nanostructures that give the endoscopic imaging instruments entirely new properties.

“In principle, this lens has unbounded imaging capability,” Yang says.

A traditional endoscope has three main parts: the control section used to control the endoscope; the insertion section which goes into the body; and the umbilical cord which connects to the light source and video processor. When using a cardiac endoscope, a light reflects off the heart tissue being investigated and is collected by the lens. The clarity of this image depends heavily on how much light a lens can refract.

“Commercially available lenses are usually made of silica, polymers or other ordinary refractive index materials, which limits their resolutions,” Yang says. His research offers a solution for that limitation using metamaterials capable of refracting rays of light that normal lenses can’t reach.

Marvi’s quest began when he observed surgeons carrying out a colonoscopy operation during one of his visits to Mayo Clinic in Arizona. “I noticed that the endoscopic surgeons are limited to just one hand,” Marvi says. He is developing robotic technology that will act as a supporting hand during surgeries.

Imagine doctors detect an early-stage tumor during a colonoscopy. One method is performing full surgery in a laparoscopic manner; however, this involves removing an entire segment of the colon leading to difficult recovery and higher risk of complications. Alternatively, doctors can perform an innovative procedure called endoscopic submucosal dissection (ESD).

“To safely remove affected tissue using an endoscope you need to be able to manipulate it,” Marvi says. Using his magnetic robotic technology would allow doctors precise control over tissue manipulation during ESD procedures.

Marvi’s technology uses magnets deployed through an endoscope’s instrument channel for tissue manipulation. Magnetic sensors ensure precision while pulling tissue with an external magnet on a robotic arm.

“We have already carried out successful preclinical models at Mayo Clinic in Arizona in collaboration with Dr. Terry Jue,” Marvi says.

Reflecting on his collaboration with Marvi and its impact Jue states: “The Mayo Clinic and ASU Alliance has been an outstanding opportunity... We are honored for this award.”

Marvi aims further improvements using machine learning techniques for semi-autonomous control systems allowing surgeons easier interaction without distraction from patient focus.