In vivo 3D tissue imaging, able to visualize “live biology” beneath the skin, is the aim of a new project funded at the highest possible level ($10 million) by the National Science Foundation’s (NSF’s) Directorate for Computer and Information Science and Engineering (CISE).
Rice University (Houston, TX) is leading the project, which aims to obviate the need for the biopsies and blood tests currently required for assessment of nearly 100 different health conditions. A multidisciplinary team plans to achieve this by creating “miniaturized, light-based microscopes for use in wearables, point-of-care, bedside diagnostics, ambulances, operating rooms, and more,” says Rice Professor Ashutosh Sabharwal, principal investigator on the grant, which involves 11 coinvestigators from Rice, Carnegie Mellon, Harvard, MIT, and Cornell.
A major objective for the team will be to address light scattering in soft tissue—an issue that has kept optical techniques on the periphery of medical imaging. They plan to use a combination of mathematical algorithms, camera design, and imaging sensors to “reverse-engineer” the path of scattered light.
Associate professor Ashok Veeraraghavan, one of the Rice coinvestigators, will lend his expertise in computational imaging to the task. Veeraraghavan, who has helped pioneer development of FlatScope (a flat, lensless, widefield, fingertip-sized fluorescence microscope that produces micrometer resolution over a several-cubic-millimeter volume), described a plan to use the type of inverse-engineering techniques that geoscientists apply to seismic waves to resolve deep interior images of the Earth. But, he says, “Our task, in some ways, is even more complicated because the amount of light scattering that takes place in even a few millimeters of tissue far exceeds other problems.” FlatScope uses a specialized algorithm to reconstruct high-resolution 3D images from a single frame of sensor data.1
The researchers’ technology platform will use on-chip illumination and sensing for noninvasive diagnosis and monitoring (see figure). “If we succeed, this isn’t just one product,” Sabharwal says. “It’s a platform technology that will be able to spin off into many products.”
A $10 million NSF grant aims, in part, to better understand light scattering in tissue, which currently hampers applications of optical bioimaging; with “computational scatterography,” the project aims to leverage low-power light (which is nonionizing; cheap to produce, control and sense; and can travel through more than a centimeter of soft tissue), such as that from a smartphone LED flash—and apply it for in vivo 3D tissue imaging. (Courtesy of A. Sabharwal/Rice University)
To highlight its potential, Sabharwal notes that oncologists in the U.S. monitor chemotherapy patients by using millions of white blood cell count (WBC) tests every week—tests that must be done at medical facilities because they require a blood draw or finger prick and laboratory analysis. He imagines such patients having access to a wristwatch-sized wearable device able to continuously measure WBC and send the readings to their oncologist’s office. Under this scenario, a patient would need to visit the hospital only if the sensor data indicated a problem.
The work is funded by CISE’s Expeditions in Computing, a program it established to pursue ambitious, fundamental research that promises disruptive innovations. Funded at up to $2 million annually for five years, Expeditions projects represent some of the largest single investments currently made by the CISE directorate to concurrently support multiple fields or sub-fields with a goal of “deep and enduring outcomes.” Sabharwal’s team is one of three groups to win five-year Expeditions grants in 2018.
Rice co-investigators include Richard Baraniuk, Rebecca Richards-Kortum, and Lin Zhong. Carnegie Mellon’s Srinivasa Narasimhan is associate director of the project; Carnegie Mellon coinvestigators include Artur Dubrawski, Ioannis Gkioulekas, and Aswin Sankaranarayanan. Additional coinvestigators include Cornell’s Al Molnar, Harvard’s Latanya Sweeney, and MIT’s Ramesh Raskar.
1. J. K. Adams et al., Sci. Adv., 3, 12, e1701548 (2017); doi:10.1126/sciadv.1701548.