Artificial Intelligence

Artificial intelligence matches radiologists at predicting patients’ emphysema severity

“Performance of the assessed AI prototypes was similar to radiologists’ subjective assessment of emphysema severity and bronchial airways,” Mannudeep Kalra, MD, with Mass General’s Department of Radiology, and colleagues wrote Oct. 14. “Although outputs from the assessed AI prototypes were robust across different scanner types, scan parameters, and reconstruction settings, there is lack of consistent performance across patients with larger body habitus due to inadequate radiation dose,” the authors cautioned.

Patients in the retrospective study underwent chest CT between 2018-2020 at a single healthcare institution, receiving a diagnosis of COPD. CT scanners from three different vendors were used in the study, while the images were processed with the AI-Rad Companion Chest prototype from Siemens Healthineers. Trained radiologists and a fully automated software from Philips assessed bronchial abnormality.

Artificial intelligence and the thoracic radiologists were able to differentiate mild, moderate and severe emphysema based on forced expiratory volume, with area under the curve scores of 0.77 and 0.76, respectively. They noted a strong positive correlation between the two. And the combo of emphysema and bronchial abnormality quantification from radiologist and AI assessments could differentiate between different severities (AUC of 0.80-0.82 and 0.87, respectively).


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