pierre massion Archives
May. 7, 2020—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
Jan. 12, 2017—Researchers in the Schools of Medicine and Engineering at Vanderbilt University have discovered a proteomic “signature” from the airways of heavy smokers that could lead to better risk assessment and perhaps new ways to stop lung cancer before it starts.
Sep. 15, 2016—Vanderbilt researchers have received an R01 grant from the National Institutes of Health to study a novel non-invasive imaging approach to detect activation of inflammatory cells in the lungs of patients with chronic obstructive pulmonary disease (COPD), a progressive lung condition that makes breathing difficult.
Jul. 28, 2016—Pierre Massion, M.D., Cornelius Vanderbilt Professor of Medicine, has been named to direct the Vanderbilt-Ingram Cancer Center (VICC) Cancer Early Detection and Prevention Initiative.
Nov. 23, 2015—Ten members of Vanderbilt University’s faculty have been elected fellows of the American Association for the Advancement of Science.
Jun. 11, 2015—Pierre Massion, M.D., director of the Thoracic Program and an Ingram Professor of Cancer Research at Vanderbilt-Ingram Cancer Center, has been recognized for his pioneering work in lung cancer by the LUNGevity Foundation.
Apr. 23, 2015—Seven faculty members of the Vanderbilt University School of Medicine named to endowed chairs were honored for their academic achievements during a celebration on Wednesday at the Student Life Center.