The Impact of Different Scanning Methods and Reconstruction Algorithms on CT Image Quality

Recruiting

• Conditions: CT Examination of the Abdomen
• Interventions: Radiation: CT Radiation Doses

• Registration Number: NCT06142539
• Lead Sponsor: Wei Li

Brief Summary

Purpose: To evaluate the image quality of deep learning-based image reconstruction (DLIR) algorithm in unenhanced abdominal low-dose CT (LDCT).

Methods: CT images of a phantom were reconstructed with Hybrid iterative reconstruction and deep learning image reconstruction (DLIR). The noise power spectrum (NPS) and task transfer function (TTF) were measured. Two patient groups were included in this study: consecutive patients who underwent unenhanced abdominal standard-dose CT reconstructed with hybrid iterative reconstruction (SDCT group) and consecutive patients who underwent unenhanced abdominal LDCT reconstructed of HIR and DLIR (LDCT group). The CT values, standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the hepatic parenchyma and paraspinal muscle and abdominal subcutaneous fat were evaluated. Radiologists assessed the subjective image quality and lesion diagnostic confidence using a 5-point Likert scale. Quantitative and qualitative parameters were compared between SDCT and LDCT groups.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2023-11-07
• Study First Submitted QC: 2023-11-16
• Study First Posted: 2023-11-21
• Status Verified: 2024-03
• Last Update Submitted: 2024-03-12
• Study Start: 2024-03-13
• Last Update Posted: 2024-03-15
• Primary Completion: 2025-02
• Study Completion: 2025-05

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 50

Inclusion Criteria

Abdominal CT examination

Exclusion Criteria

pregnancy and lactation for women unstable breath holding

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
LDCT group	CT Radiation Doses	-

Primary Outcome Measures

Name	Time	Method
Results of phantom research	up to six months	Compare the changes in spatial resolution (TTF curve) and noise (NPS curve) between different algorithms
Results of human clinical study	up to six months	General information of clinical trial personnel Compare the general information of two groups of subjects, such as age, weight（kg）, height（m）, gender, and BMI (kg/m2).; Quantitative image analysis The standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the hepatic parenchyma and paraspinal muscle were evaluated.; Qualitative image analysis Two radiologists qualitatively assessed the overall image noise and overall image quality depiction.

Secondary Outcome Measures

Name	Time	Method
Patient demographics	up to six months	Participant demographics: Age (year)/Gender/Body weight (kg) / Body mass index (kg/m2)

Trial Locations

Locations (1)

uCT960+; 🇨🇳 Shandong, Jinan Shandong, China