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Deep Learning Reconstruction Algorithms in Dual Low-dose CTA

Recruiting
Conditions
Deep Learning
Registration Number
NCT06372756
Lead Sponsor
Hao Tang
Brief Summary

The goal of this observational study is to evaluate the impact of deep learning image reconstruction on the image quality and diagnostic performance of double low-dose CTA. The main question it aims to answer is to explore the feasibility of deep learning image reconstruction in double low-dose CTA.

Detailed Description

1. The raw data from patients who underwent head and neck CTA, coronary CTA, and abdominal CTA in both standard dose and double low-dose groups were included.

2. Techniques such as filtered back projection, iterative reconstruction, and deep learning reconstruction were performed.

3. The feasibility of deep learning reconstruction in double low-dose CTA was evaluated based on image quality and diagnostic performance.

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
1200
Inclusion Criteria
  • Patients with head and neck CTA, coronary artery CTA, and abdominal CTA due to stroke, coronary heart disease and abdominal inflammatory disease, and abdominal tumors.
Exclusion Criteria
  • Age <18 years, pregnancy, allergic reaction to iodine contrast agent, renal insufficiency, and severe hyperthyroidism.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
The specificity and sensitivity calculated through the optimal cutoff value of the receiver operating characteristic curve.2026.1

The specificity and sensitivity were calculated separately for the standard dose group and the double low-dose group using the optimal cutoff value from the receiver operating characteristic curve, for the purpose of comparing diagnostic accuracy between the two groups.

Secondary Outcome Measures
NameTimeMethod
The signal-to-noise ratio calculated from image CT values and noise2026.1

The signal-to-noise ratio was calculated separately for the standard dose group and the double low-dose group using image CT values and noise, to assess the image quality between the two groups.

Trial Locations

Locations (1)

Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology

🇨🇳

Wuhan, Hubei, China

Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology
🇨🇳Wuhan, Hubei, China
Youfa M Tang
Contact
+8613554101223
1525573397@qq.com

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