Detection of Urinary Stones on ULDCT With Deep-learning Image Reconstruction Algorithm

Not Applicable

Active, not recruiting

• Conditions: Renal Colic; Urinary Tract Stones; Urolithiasis; Deep Learning Reconstruction

• Registration Number: NCT04490343
• Lead Sponsor: Centre Hospitalier Universitaire, Amiens

Brief Summary

Urolithiasis has an increasing incidence and prevalence worldwide, and some patients may have multiple recurrences. Because these stone-related episodes may lead to multiple diagnostic examinations requiring ionizing radiation, urolithiasis is a natural target for dose reduction efforts. Abdominopelvic low dose CT, which has the highest sensitivity and specificity among available imaging modalities, is the most appropriate diagnostic exam for this pathology. The main objective of this study is to evaluate the diagnostic performance of ultra-low dose CT using deep learning-based reconstruction in urolithiasis patients.

Detailed Description

Not available

Study Timeline

• Study Start: 2020-07-21
• Study First Submitted: 2020-07-24
• Study First Submitted QC: 2020-07-24
• Study First Posted: 2020-07-29
• Primary Completion: 2022-07-01
• Status Verified: 2023-03
• Last Update Submitted: 2023-03-07
• Last Update Posted: 2023-03-08
• Study Completion: 2023-07-01

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 62

Inclusion Criteria

• Age ≥ 18 years old,
• Patient referred for abdominopelvic CT to confirm urolithiasis or for follow-up,
• Affiliation to a social security program,
• Ability of the subject to understand and express opposition

Exclusion Criteria

• Age <18 years old,
• Person under guardianship or curators,
• Pregnant woman,
• Any contraindications to CT

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Primary Outcome Measures

Name	Time	Method
Accuracy between low dose CT using DLIR reconstruction and low dose CT without DLIR reconstruction for the detection of urinary tract stones	day 1	Accuracy between low dose CT using DLIR reconstruction and low dose CT without DLIR reconstruction for the detection of urinary tract stones.; Patients who were referred to the department for abdominopelvic CT exam for urolithiasis diagnostic or follow-up, and had consented to participate in the study, will undergo an additional ultra-low dose acquisition (ULD, \<1 mSv) with deep learning-based reconstruction (DLIR).

Trial Locations

Locations (1)

CHU Amiens; 🇫🇷 Amiens, France