Ultra-low dose CT aids pneumonia diagnosis in immunocompromised patients: Study

From September 2020 to December 2022, 54 immunocompromised patients with fevers were referred to Dr. Klug’s division to undergo two chest CT scans: a normal dose scan and an ultra-low dose scan. A deep learning algorithm was applied to denoise all 54 of the ultra-low dose CT scans.

Radiologists individually assessed and documented their findings from the normal dose CT, ultra-low dose CT and denoised ultra-low dose CT scans. They were blinded to all patient clinical information.

The deep learning algorithm significantly improved the image quality and clarity of the ultra-low dose CT scans and reduced false positives. Nodules were also more easily identified on the denoised scans.

The average effective radiation dose for ultra-low dose scans was 2% of the average effective radiation dose of the standard CT scans.

“This study paves the way for safer, AI-driven imaging that reduces radiation exposure while preserving diagnostic accuracy,” Dr. Klug said.

The researchers note that deep learning-based denoising on ultra-low dose CT scans can be beneficial in other patient groups, such as young patients.

“This pilot study identified infection with a fraction of the radiation dose,” Dr. Klug said. “This approach could drive larger studies and ultimately reshape clinical guidelines, making denoised ultra-low dose CT the new standard for young immunocompromised patients.”

Reference:

Maximiliano Klug, Tamer Sobeh, Michael Green, Denoised Ultra-Low-Dose Chest CT to Assess Pneumonia in Individuals Who Are Immunocompromised, Radiology Cardiothoracic Imaging, https://doi.org/10.1148/ryct.240189