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

Not Applicable

Not yet recruiting

• Conditions: Deep Learning
• Interventions: Other: low-dose CT

• Registration Number: NCT05550012
• Lead Sponsor: Qianfoshan Hospital

Brief 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.

Detailed 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.

Study Timeline

• Status Verified: 2022-09
• Study First Submitted: 2022-09-14
• Study First Submitted QC: 2022-09-18
• Last Update Submitted: 2022-09-18
• Study First Posted: 2022-09-22
• Last Update Posted: 2022-09-22
• Study Start: 2022-09-30
• Primary Completion: 2023-03-30
• Study Completion: 2023-04-30

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 100

Inclusion Criteria

• those scheduled for contrast-enhanced liver CT

Exclusion Criteria

• images affected by artifacts (motion or implants)

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
low-dose CT	low-dose CT	those patients undergo low-dose liver CT in portal vein and delayed phase

Primary Outcome Measures

Name	Time	Method
contrast to noise ratio (CNR)	6 months	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
diagnostic confidence	6 months	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
signal-to-noise ratio (SNR)	6 months	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

Trial Locations

Locations (1)

Qianfoshan Hospital (The First Affiliated Hospital of Shandong First Medical University); 🇨🇳 Jinan, Shandong, China