AI boosts CTPA ' s ability to predict lung disease survival

The percentage of lung fibrosis quantified on CT pulmonary angiograms (CTPA) by an AI model is associated with increased risk of mortality -- and boosts clinicians' ability to predict the survival of lung disease patients, researchers have found. The information is especially useful when used in combination with radiologic severity scoring -- compared with radiologic scoring alone -- and the study findings could help clinicians better care for their patients, wrote a team led by Krit Dwivedi, PhD, of the University of Sheffield in England. The results were published February 6 in Radiology. "There is clinical need to better quantify lung disease severity in pulmonary hypertension, particularly in idiopathic pulmonary arterial hypertension and pulmonary hypertension associated with lung disease," it noted. The severity of lung disease is an important discriminating factor between two pulmonary hypertension types: pulmonary arterial hypertension and pulmonary hypertension associated with lung disease. But "distinguishing between these two groups is challenging in patients with radiologically scored mild or no fibrosis due to overlapping clinical characteristics, particularly in the most common form of pulmonary arterial hypertension, idiopathic pulmonary arterial hypertension," the researchers explained. "Only patients diagnosed with idiopathic pulmonary arterial hypertension are eligible for novel targeted therapies that improve survival." Dwivedi's group conducted a study...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Subspecialties Chest Radiology Source Type: news