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

NCT ID: NCT05550012

Last Updated: 2022-09-22

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

100 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-09-30

Study Completion Date

2023-04-30

Brief Summary

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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

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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.

Conditions

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Deep Learning

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

OTHER

Blinding Strategy

NONE

Study Groups

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standard-dose CT

those patients undergo standard-dose liver CT in portal vein and delayed phase

Group Type NO_INTERVENTION

No interventions assigned to this group

low-dose CT

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

Group Type EXPERIMENTAL

low-dose CT

Intervention Type OTHER

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

Interventions

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low-dose CT

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

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* those scheduled for contrast-enhanced liver CT

Exclusion Criteria

* images affected by artifacts (motion or implants)
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Qianfoshan Hospital

OTHER

Sponsor Role lead

Responsible Party

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Qingshi Zeng

Clinical Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Qingshi Zeng

Role: STUDY_DIRECTOR

Qianfoshan Hospital

Locations

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Qianfoshan Hospital (The First Affiliated Hospital of Shandong First Medical University)

Jinan, Shandong, China

Site Status

Countries

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China

Central Contacts

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Qingshi Zeng

Role: CONTACT

18560081565

Facility Contacts

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Qingshi Zeng

Role: primary

Other Identifiers

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LD-SH-2022

Identifier Type: -

Identifier Source: org_study_id

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