The use of a new imaging technique--quantitative computed tomography texture analysis (QTA)--could help provide lung cancer patients with improved treatments and better track their progress, according to a study in the journal PLOS ONE.
The study was based on a review of 48 patients with non-small cell lung cancer (NSCLC), which represents more than 85 percent of all lung cancers. Researchers found that by scanning their tumors with QTA, they could determined with 90 percent accuracy those tumors that had a cancer-causing K-ras gene mutation.
Consequently, the researchers believe, this method can be an accurate, non-invasive alternative to performing surgical biopsies or any other invasive method of collecting biological samples.
"The ability to rapidly and non-invasively characterize NSCLC tumors would be a great asset to clinical oncologists," lead study author Glen Weiss, director of clinical research at Cancer Treatment Centers of America's Western Regional Medical Center in Phoenix, said in an announcement. "QTA applied to molecularly defined NSCLC cases may have a broader application to precision medicine by offering a non-invasive way of identifying the best therapies for each patient."
Senior study author Ronald Korn, medical director of Scottsdale Healthcare's Virginia G. Piper Cancer Center, called the use of QTA a step forward in imaging, adding that the non-invasive characterization of a tumor's molecular features could help clinicians better manage a patient's treatment.
"Non-invasive QTA can differentiate the presence of K-ras mutation from pan-wildtype NSCLC," Korn said.
At the end of April, the Medicare Evidence Development & Coverage Advisory Committee (MEDCAC) declined to support Medicare coverage for low-dose CT (LDCT) lung cancer screening, with many of the panelists arguing that there are too many doubts that the benefits of LDCT screening would outweigh the harms in the Medicare population.
Meanwhile, real-time MRI combined with new non-invasive cellular mapping techniques are being used to develop a new biopsy technique that can more accurately diagnose patients with brain cancer.
To learn more:
- read the study in PLOS ONE
- see the announcement