Research

Implant one day may replace dialysis

Vanderbilt researchers used pharmacological manipulations to increase salt and water transport by kidney cells grown in culture, a step necessary for realizing an implantable artificial kidney device.

Antibodies eye Pacific Island “fever”

Vanderbilt Vaccine Center team isolates monoclonal antibodies against Ross River virus, which causes rash, fever and debilitating muscle and joint pain lasting three to six months.

The adaptable anthrax bacterium

Vanderbilt researchers discover how anthrax bacterium defends itself against structural damage and resists the toxicity of the antimicrobial drug targocil.

Yin receives early investigator MERIT Award from NCI

Zhijun Yin, PhD, assistant professor of Biomedical Informatics at Vanderbilt University Medical Center, has received the National Cancer Institute’s Method to Extend Research in Time Award (or MERIT Award) for Early Stage Investigators.

Pioneering nephrologist William Stone mourned

William J. Stone, MD, nephrologist and professor of Medicine, emeritus, who retired in December after 50 years as a member of the faculty of the Vanderbilt University School of Medicine, died Monday, May 11, at his home in Nashville. He was 83.

New method captures early viral-host protein interactions

Researchers have developed a method to identify the primary interactions between incoming viral RNA genomes and host proteins.

May 7, 2020

Study finds AI can categorize cancer risk of lung nodules

by Tom Wilemon Computed tomography scans for people at risk for lung cancer lead to earlier diagnoses and improve survival rates, but they can also lead to overtreatment when suspicious nodules turn out to be benign. A study published in American Journal of Respiratory and Critical Care Medicine indicates that an artificial intelligence strategy can correctly assess and categorize these indeterminate pulmonary nodules (IPNs). When compared to the conventional risk models clinicians currently use, the algorithm developed by the team of researchers in a very large dataset (15,693 nodules) reclassified IPNs into low-risk or high-risk categories in over a third of cancers and benign nodules. “These results suggest the potential clinical utility of this deep learning algorithm to revise the probability of cancer among IPNs aiming to decrease invasive procedures and shorten time to diagnosis,” said Pierre Massion, MD, Cornelius Vanderbilt Chair in Medicine at Vanderbilt University, the study’s lead author. Currently, clinicians refer to guidelines issued by the American College of Radiology and the American College of Chest Physicians. Adherence to these guidelines can be variable, and how patient cases are classified can be subjective. With the goal of providing clinicians with an unbiased assessment tool, the researchers developed an algorithm based on datasets from the National Lung Screening Trial, Vanderbilt University Medical Center and Oxford University Hospital. Their study is the first to validate a risk stratification tool on multiple independent cohorts and to show reclassification performance that is significantly superior to existing risk models. With IPNs, clinicians are often faced with the dilemma of weighing whether to advise a patient to undergo an invasive surgical procedure, which may be unnecessary, against a watch-and-wait strategy, which may result in delaying needed cancer treatment. A definitive diagnosis of an IPN can take up to two years. Better assessment tools are needed by clinicians as screenings for patients at risk for lung cancer increase. Lung cancer is the leading cause of cancer-related death in the United States and globally. The overall five-year survival rate is 21.7%, but it is much greater (92%) for those patients who receive an early diagnosis of stage IA1 non-small cell cancer. n
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