A New Deep-learning Based Artificial Intelligence Iterative Reconstruction (AIIR) Algorithm in Low-dose Liver CT

Deep Learning Clinical Trial

Official title:

Evaluation of a New Deep-learning Based Artificial Intelligence Iterative Reconstruction (AIIR) Algorithm in Different Enhancement Phases of Low-dose Liver CT

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05550012
• Other study ID #: LD-SH-2022
• Status: Not yet recruiting
• Phase: N/A
• Start date: September 30, 2022
• Est. completion date: April 30, 2023

Study information

• Verified date: September 2022
• Source: Qianfoshan Hospital
• Contact: Qingshi Zeng
• Phone: 18560081565
• Email: zengqs2021[@]163.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

CT-enhanced scans are routine imaging modality for the diagnosis and follow-up of liver disease. However, this means that patients will receive more radiation dose. Therefore, it is necessary to reduce the radiation dose received by patients as much as possible. Deep learning-based reconstruction algorithms have been introduced to improve image quality recently. For many years, researchers attempt to maintain image quality using an advanced method while reducing radiation dose. Recently, a new deep-learning based iterative reconstruction algorithm, namely artificial intelligence iterative reconstruction (AIIR, United Imaging Healthcare, Shanghai, China) has been introduced. In this study, we evaluate the image and diagnostic qualities of AIIR for low-dose portal vein and delayed phase liver CT with those of a KARL method normally used in standard-dose CT.

Description:

In our hospital, patients with abdominal pelvic cancer undergo follow-up low-dose CT for the evaluation of treatment plan after clinical treatment or disease progress. The raw-data of low-dose CT were collected retrospectively and reconstructed using KARL and AIIR algorithm. In this study, we evaluate the image and diagnostic qualities of AIIR for low-dose portal vein and delayed phase liver CT with those of a KARL method normally used in standard-dose CT.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 100
• Est. completion date: April 30, 2023
• Est. primary completion date: March 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• those scheduled for contrast-enhanced liver CT

Exclusion Criteria:

• images affected by artifacts (motion or implants)

Related Conditions & MeSH terms

• Deep Learning

Intervention

Other:
• low-dose CT
those patients undergo low-dose liver CT in portal vein and delayed phase.

Locations

Country	Name	City	State
China	Qianfoshan Hospital (The First Affiliated Hospital of Shandong First Medical University)	Jinan	Shandong

Sponsors (1)

Lead Sponsor	Collaborator
Qianfoshan Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	signal-to-noise ratio (SNR)	Evaluate the image qualities of AIIR for low-dose portal vein and delayed phase liver CT with those of a KARL method normally used in standard-dose CT	6 months
Primary	contrast to noise ratio (CNR)	Evaluate the image qualities of AIIR for low-dose portal vein and delayed phase liver CT with those of a KARL method normally used in standard-dose CT	6 months
Primary	diagnostic confidence	Evaluate the diagnostic qualities of AIIR for low-dose portal vein and delayed phase liver CT with those of a KARL method normally used in standard-dose CT	6 months