Evaluating CT Image Quality with Different Reconstruction Methods
The Impact of Different Scanning Methods and Reconstruction Algorithms on CT Image Quality
This study is testing if a new way of creating CT images using deep learning can produce better quality images for patients getting low-dose scans compared to those getting standard-dose scans.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 50 (estimated) |
| Ages | 18 Years to 100 Years |
| Sex | All |
| Sponsor | Qianfoshan Hospital Academic / other |
| Locations | 1 site (Shandong, Jinan Shandong) |
| Trial ID | NCT06142539 on ClinicalTrials.gov |
What this trial studies
This study aims to assess the image quality of deep learning-based image reconstruction (DLIR) in unenhanced abdominal low-dose CT (LDCT) compared to standard-dose CT (SDCT). It involves reconstructing CT images from a phantom using both hybrid iterative reconstruction and DLIR, followed by a detailed evaluation of various image quality metrics. Two patient groups will be analyzed: those undergoing standard-dose CT and those receiving low-dose CT, with a focus on quantitative and qualitative assessments of image quality by radiologists.
Who should consider this trial
Good fit: Ideal candidates for this study are patients scheduled for an unenhanced abdominal CT examination.
Not a fit: Patients who are pregnant or lactating, or those unable to hold their breath during the procedure, may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to improved image quality in low-dose CT scans, enhancing diagnostic accuracy while minimizing radiation exposure.
How similar studies have performed: Other studies have shown promise in improving image quality with advanced reconstruction techniques, suggesting potential for success in this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: Abdominal CT examination Exclusion Criteria: pregnancy and lactation for women unstable breath holding
Where this trial is running
Shandong, Jinan Shandong
- uCT960+ — Shandong, Jinan Shandong, China (Recruiting)
Study contacts
- Study coordinator: ((Wei Li[Author])
- Email: lwqfsh@126.com
- Phone: 13869190655
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.