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Comparison of image quality between idose4 and precise image for low-dose CT of the abdomen and pelvis among low B.M.I individuals

Comparison of image quality between hybrid iterative reconstruction and deep learning image reconstruction for low-dose CT of the abdomen and pelvis among low B.M.I individuals - nil

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2024/03/064056
Enrollment
50
Registered
2024-03-13
Start date
Unknown
Completion date
Unknown
Last updated
2025-05-26

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: R935- Abnormal findings on diagnostic imaging of other abdominal regions, including retroperitoneum Health Condition 2: R933- Abnormal findings on diagnostic imaging of other parts of digestive tract Health Condition 3: R932- Abnormal findings on diagnostic imaging of liver and biliary tract

Interventions

Intervention1: NIL: NIL

Sponsors

Kasturba Hospital
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Patients who are of age above 18 years, referred for CECT abdomen. Low Body Mass Index population (less than 18.5 kg/m²)

Exclusion criteria

Exclusion criteria: Patients who come above 18.5 kg/m2 Body mass index Population. Uncooperative patients. Fatty, liver cirrhosis patients will be excluded

Design outcomes

Primary

MeasureTime frame
Signal-to-Noise Ratio (SNR), Contrast-to-Noise Ratio (CNR), and image noiseTimepoint: 16 months—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactMs Nitika C Panakkal

Manipal college of health professions MAHE Manipal

abraham.mchpmpl2023@learner.manipal.edu9843530612

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026