NCT05398887

Effectiveness of Ultra-low-dose Chest CT With AI Based Denoising Solution

Utilization and Effectiveness of Ultra-low-dose Chest Computed Tomography Using Innovative CT Denoising Solution Based on Deep Learning Technology

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 200 (estimated)
• Sponsor: Intermed Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The main objective of the study is to evaluate the detection rate of pulmonary conditions, percentage of ionizing radiation dose reduction, and state of image quality of ULDCT coupling with innovative vendor-neutral CT denoising solution based on deep learning technology.

Detailed description

Considering lung cancer-related public health challenges, a reliable lung cancer screening method for high-risk cohorts in Mongolia is needed. Thus, our study aims to assess the detection rate of pulmonary conditions, percentage of ionizing radiation dose reduction, and state of image quality of ULDCT coupling with artificial intelligence based CT denoising technique among various patient groups.

Conditions

• Lung Diseases

Interventions

Type	Name	Description
RADIATION	Low radiation dose CT	Underwent low dose chest CT with 30% lower radiation dose
RADIATION	Underwent ultra dose chest CT	Underwent ultra dose chest CT with 90% lower radiation dose
OTHER	Artificial Intelligence based model	Deep-learning based contrast boosting algorithms

Timeline

• Start date: 2022-06-15
• Primary completion: 2022-09-01
• Completion: 2022-10-01
• First posted: 2022-06-01
• Last updated: 2022-06-01