Persistent ground-glass nodules in the lungs are worth a closer look, as they are highly associated with malignancy. Dr. Anne Leung offered an overview of how these lesions present on CT imaging at the 2008 Stanford International Symposium on Multidetector-Row CT in Las Vegas.
Persistent ground-glass nodules in the lungs are worth a closer look, as they are highly associated with malignancy. Dr. Anne Leung offered an overview of how these lesions present on CT imaging at the 2008 Stanford International Symposium on Multidetector-Row CT in Las Vegas. "Ground glass is defined as hazy or decreased attenuation on CT that does not obscure underlying bronchovascular bundles," said Leung, chief of thoracic imaging at Stanford University School of Medicine. "The pathologic correlates that have been described with ground-glass nodules are partial airspace filling, interstitial filling, edema, fibrosis, and neoplastic infiltration." Leung pointed out that ground-glass nodules have two subtypes: pure ground glass and ground glass with solid components. Ground-glass nodules with solid elements are more likely to be malignant, particularly if they persist over three months, she said.
Leung highlighted some of the differential diagnoses that can be made on CT when ground-glass nodules are present:
Among the primary neoplastic diseases, she described atypical edematous hyperplasia. The CT features of these peripheral lesions are a size of less than 5 mm, round or oval shape, smooth margins, and pure ground-glass appearance.
Focal ground-glass nodules with solid components are also found with bronchoalveolar cell carcinoma. Other CT features to look for are air lucencies, smooth or irregular contours, and slow growth, Leung said. Finally, there is adenocarcinoma, the most common lung cancer in the U.S. CT features of this disease state are focal ground-glass nodules with solid elements, air lucencies, and smooth or irregular contours. Leung concluded that persistent ground-glass nodules are best seen with thin-section imaging. Readers should keep an eye out for solid components and interval growth. Finally, she recommended against evaluating ground-glass nodules with PET studies, as negative results are generally not a reliable indicator of benign disease.
What is the Best Use of AI in CT Lung Cancer Screening?
April 18th 2025In comparison to radiologist assessment, the use of AI to pre-screen patients with low-dose CT lung cancer screening provided a 12 percent reduction in mean interpretation time with a slight increase in specificity and a slight decrease in the recall rate, according to new research.
The Reading Room: Racial and Ethnic Minorities, Cancer Screenings, and COVID-19
November 3rd 2020In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).
Could Lymph Node Distribution Patterns on CT Improve Staging for Colon Cancer?
April 11th 2025For patients with microsatellite instability-high colon cancer, distribution-based clinical lymph node staging (dCN) with computed tomography (CT) offered nearly double the accuracy rate of clinical lymph node staging in a recent study.