Quantified Surgery

Using Big Data, sophisticated computer modeling, and 3D imaging to personalize surgery before ever entering the operating room

Modern medicine generates huge amounts of data for each patient, from vital signs and lab tests to imaging technologies like x-rays, MRIs and cat scans. Larry Smarr is the exception who proves the rule.

For years, the physicist, computer scientist and founder of Calit2 has meticulously monitored and documented almost every aspect of his physiological being, down to the microbial diversity of his colon and its output—all part of an effort to better understand and treat a chronic
intestinal condition. He called it his “quantified self.”

When Smarr eventually needed part of his colon removed, he pushed the concept of quantified self further: “quantified surgery.” With colleagues and his medical team, led by Sonia Ramamoorthy, MD, he created a 3D model of his affected abdomen that Ramamoorthy could study and explore long before her first actual incision. The work was largely based upon Smarr’s abundant, existing medical data.

Smarr’s procedure was an experiment, but also perhaps a glimpse of the future. His quantified surgery was a success, minimizing potential complications in the operating room and speeding his recovery. He, Ramamoorthy and colleagues at UC San Diego are now trying to develop simpler, faster, cheaper ways to make quantified surgery a viable option for all patients.

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