Can AI help chest DDR achieve clinical adoption?

Chest dynamic digital radiography (DDR) may have received a boost toward clinical use in patients with lung disorders, with researchers developing AI to perform time-consuming analysis involved in the technology, according to researchers in New York City. A group at Mount Sinai Hospital developed a “pipeline” of convolutional neural networks (CNNs) to analyze lung areas in DDR image sequences from patients. The model performed well enough to act as a surrogate to standard pulmonary function tests, they found. “Our findings add to growing evidence suggesting DDR as a potential [pulmonary function test] surrogate,” noted lead author and internal medicine fellow Valeria Santibanez, MD, and colleagues. The study was published March 29 in Chest Pulmonary. Common diagnostic tests for pulmonary disorders include chest x-rays and pulmonary function tests (PFTs). Although essential, these tests offer a limited static assessment, the authors wrote. Alternatively, previous research has shown that chest DDR can capture active lung movement during respiration by offering a detailed view of lung and diaphragm motion. DDR is relatively easy to obtain, but barriers to its clinical adoption include time-consuming manual analysis and unclear correlation with standard PFTs, the authors noted. To that end, the group developed two convolutional neural networks (CNN) designed to quantify key measurements in DDR image sequences. For data, they used PFT and DDR studies from 55 patients ...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Digital X-Ray Artificial Intelligence Source Type: news