A New Deep-learning Based Artificial Intelligence Iterative Reconstruction (AIIR) Algorithm in Low-dose Liver CT
Evaluation of a New Deep-learning Based Artificial Intelligence Iterative Reconstruction (AIIR) Algorithm in Different Enhancement Phases of Low-dose Liver CT
1 other identifier
interventional
100
1 country
1
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for not_applicable
Started Sep 2022
Shorter than P25 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
September 14, 2022
CompletedFirst Posted
Study publicly available on registry
September 22, 2022
CompletedStudy Start
First participant enrolled
September 30, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 30, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
April 30, 2023
CompletedSeptember 22, 2022
September 1, 2022
6 months
September 14, 2022
September 18, 2022
Conditions
Outcome Measures
Primary Outcomes (3)
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
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
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
Study Arms (2)
standard-dose CT
NO INTERVENTIONthose patients undergo standard-dose liver CT in portal vein and delayed phase
low-dose CT
EXPERIMENTALthose patients undergo low-dose liver CT in portal vein and delayed phase
Interventions
those patients undergo low-dose liver CT in portal vein and delayed phase.
Eligibility Criteria
You may qualify if:
- those scheduled for contrast-enhanced liver CT
You may not qualify if:
- images affected by artifacts (motion or implants)
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Qianfoshan Hospital (The First Affiliated Hospital of Shandong First Medical University)
Jinan, Shandong, China
Study Officials
- STUDY DIRECTOR
Qingshi Zeng
Qianfoshan Hospital
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- OTHER
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Clinical Professor
Study Record Dates
First Submitted
September 14, 2022
First Posted
September 22, 2022
Study Start
September 30, 2022
Primary Completion
March 30, 2023
Study Completion
April 30, 2023
Last Updated
September 22, 2022
Record last verified: 2022-09