pierre massion

Members of the newly named MASLAB gathered for a portrait on the Medical Center Plaza. The early lung cancer detection research initiative was named in honor of the late Pierre Massion, MD.
September 15, 2022

Lung cancer detection program lands grant renewal

The National Cancer Institute has renewed funding for the Early Detection Research Network Lung Cancer Clinical Validation Center at Vanderbilt- Ingram Cancer Center.

By Tom Wilemon
Shown at Monday’s VICC Annual Scientific Retreat are (front row, from left) Timothy Blackwell, MD, Fabien Maldonado, MD, Denise Aberle, MD, Melinda Aldrich, PhD, MPH, Kim Sandler, MD, (back row, from left) Eric Grogan, MD, MPH, Sudhir Srivastava, PhD, MPH, M. Patricia Rivera, MD, Julien Sage, PhD, David Carbone, MD, PhD, and Scott Hiebert, PhD.
May 5, 2022

VICC Scientific Retreat focuses on lung cancer

By Tom Wilemon
April 6, 2021

Vanderbilt mourns the passing of Pierre Massion

Pierre Massion, MD, Cornelius Vanderbilt Chair and Professor of Medicine, an internationally known expert on early detection and prevention strategies for lung cancer, died April 4 of an apparent heart attack. He was 58.

By Tom Wilemon
March 9, 2021

Study incorporates genetics with smoking history to identify high-risk smokers for lung cancer screening

A study by Vanderbilt researchers that analyzed both smoking history and genetic risk variants for lung cancer supports modifying current guidelines to include additional smokers for lung cancer screening.

By Tom Wilemon
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

By Tom Wilemon
April 9, 2020

Study tracks genomics of lung tumor behavior

A study by Vanderbilt researchers has identified genomic alterations in early stage adenocarcinomas of the lung that may indicate whether the lesions develop into aggressive tumors.

By Tom Wilemon
November 29, 2018

Lung cancer survival signal

A receptor thought to be a cell growth inhibitor actually sends pro-survival signals in small cell lung cancer and is a candidate biomarker for poor prognosis.
By VUMC News and Communications
August 16, 2018

A new target for lung cancer

Vanderbilt researchers have identified a new vulnerability in lung cancer — the transporter protein xCT — that may a therapeutic target for the disease.
By Leigh MacMillan
June 1, 2017

Veterans Affairs Research Conference

The 3rd National Veterans Health Affairs Research Conference held at Vanderbilt University Medical Center May 17-18.
By VUMC News and Communications
January 12, 2017

Team’s discovery offers new insight on lung cancer risk

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.
By Bill Snyder
September 15, 2016

Grant spurs study of novel imaging technique for COPD

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.
By Kathy Whitney
July 28, 2016

Massion named to lead new cancer prevention initiative

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.
By VUMC News and Communications
November 23, 2015

Ten Vanderbilt faculty members elected AAAS fellows

Ten members of Vanderbilt University’s faculty have been elected fellows of the American Association for the Advancement of Science.
By Bill Snyder
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