With algorithms utilized in aerospace technology, the CT LVAS software reportedly provides enhanced assessment of regional airflow and lung ventilation.
The Food and Drug Administration (FDA) has granted 510(k) clearance for CT LVAS, an adjunctive software that provides detailed analysis of lung ventilation based on computed tomography (CT) scans.
Offering color-coded images of regional airflow and lung ventilation that are overlayed on CT scans, the CT LVAS provides quantifiable assessments of lung volume change and regional lung ventilation heterogeneity, according to 4DMedical, the developer of CT LVAS.
The company said the CT LVAS facilitates regional lung ventilation measurement in thousands of locations in the lungs.
“Having assisted with image interpretation of CT LVAS exams in Australia, I've seen the diagnostic power of adding functional assessment to the structural information provided in standard non-contrast chest CTs,” noted Greg Mogel, M.D., a consultant radiologist at 4DMedical. “CT LVAS allows radiologists to provide a whole new dimension of lung health information to referring clinicians needing answers.”
4DMedical added that the combination of CT LVAS with a forthcoming CT:VQ software, which provides quantitative perfusion assessment based on CT scans, may enhance the diagnosis of pulmonary embolism and assessment of conditions such as chronic obstructive pulmonary disease (COPD).
Can a CT-Based Radiomics Model Bolster Detection of Malignant Thyroid Nodules?
May 3rd 2024A computed tomography (CT)-based radiomics model that includes 28 radiomic features showed significantly higher accuracy, sensitivity, and specificity than conventional CT in differentiating benign and malignant thyroid nodules, according to newly published 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.
AI Adjudication Bolsters Chest CT Assessment of Lung Adenocarcinoma
April 11th 2024The inclusion of simulated adjudication for resolving discordant nodule classifications in a deep learning model for assessing lung adenocarcinoma on chest CT resulted in a 12 percent increase in sensitivity rate.