Transformative technology
Mount Sinai establishes institute for research and training
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NEW YORK—To leverage its imaging and nanomedicine program, the Mount Sinai Health System is creating the Biomedical Engineering and Imaging Institute (BMEII). The institute, which is said to be one of a few in the world, will offer broad biomedical engineering research and training programs for its graduate and medical students, in addition to developing inventions in the areas of imaging, nanomedicine, artificial intelligence, robotics, sensors, medical devices and computer vision technologies, such as virtual, augmented and extended reality.
According to Dr. Zahi Fayad, director of the BMEII, the institute plans to be fully operational by early 2020. BMEII will recruit at least nine prestigious principal investigators and their teams in the areas of imaging science, nanomedicine and molecular imaging, artificial intelligence and machine learning as applied to imaging and sensors data, next-generation medical devices and sensors, and computer vision and augmented reality. Fayad said that the new recruits will join current Mount Sinai teams to develop cutting-edge biomedical engineering and imaging technologies to improve the detection, diagnosis, treatment and prevention of a wide range of human diseases, including cancer, cardiovascular and neurological diseases.
Fayad added, “We have recently recruited Dr. Li Feng, an expert in novel imaging methods that speed up the acquisition of MRI using advanced techniques such as machine learning. We are in the process of recruiting many others in the five areas mentioned above, with multiple offers already on the table. We will also allocate dedicate space and resources for each of the programs to enable the research and to the translation to patient research and care.” Funding, he said, will be from a combination of Mount Sinai and external grants and gifts.
As he explained, “Our imaging and nanomedicine programs are leaders in the development and application of these novel technologies to improve patients’ diagnosis and treatment. By integrating artificial intelligence, sensors, robotics and virtual reality into our programs, the BMEII will take a transformative leap forward in the implementation of next-generation medicine and healthcare for our patients and society.”
BMEII will concentrate on three research areas. For artificial intelligence in advanced imaging, the institute will develop new computational tools and algorithms to expedite and improve the way in which radiologists generate, interpret and use clinical imaging technologies to improve the speed and accuracy of diagnosis. Building upon Mount Sinai researchers’ development of radiology augmentation technologies that can rapidly triage the severity of neurologic injuries, accurately characterize cancer types and identify the early presence of coronary disease, they will help to diagnose disease faster while streamlining the workflow of radiologists.
Research into next-generation medical technologies will focus on developing new medical devices to improve patient outcomes. BMEII will be integrated into the Mount Sinai Health System, enabling it to draw from the interdisciplinary fields of engineering and daily clinical practice to ensure a needs-based approach to medical devices. Wearable technologies based on smart sensors may alert patients with heart disease to blood pressure or cholesterol level changes so they can avoid a potential cardiac event, or they may alert patients with post-traumatic stress disorder that their stress levels are extraordinarily high. Robotic surgery will be enhanced by developing more portable, flexible and miniaturized robotic devices that can be used to improve treatments for many conditions in areas such as cardiology, cancer, orthopedics and interventional radiology.
Research into virtual, augmented and extended reality (VR/AR/XR) will explore their use in several areas of medicine, educate and train future generations of researchers and physicians, understand patient-specific disease processes, treat pain and anxiety, and build personalized mechanisms of engagement between doctors and patients. Researchers will build patient-specific disease process models in order to help surgeons better plan for surgery, guide their work during surgery, analyze results and drive robotic interventions, as well as to communicate the course of care with patients.
Fayad concluded, “We are already seeing results in many of the new areas that we have invested in, such as in new ways to read brain MRI and providing a quick diagnosis via artificial intelligence engines—with more to come in 2020.”
