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Detection of Urinary Stones on ULDCT With Deep-learning Image Reconstruction Algorithm (URO DLIR)

Primary Purpose

Urolithiasis, Urinary Tract Stones, Renal Colic

Status
Active
Phase
Not Applicable
Locations
France
Study Type
Interventional
Intervention
Abdominopelvic low dose CT
Sponsored by
Centre Hospitalier Universitaire, Amiens
About
Eligibility
Locations
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Urolithiasis focused on measuring Urolithiasis, Urinary Tract Stones, Renal Colic, deep learning reconstruction, radiation dose, dose reduction, low dose CT

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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

Sites / Locations

  • CHU Amiens

Outcomes

Primary Outcome Measures

Accuracy between low dose CT using DLIR reconstruction and low dose CT without DLIR reconstruction for the detection of urinary tract stones
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).

Secondary Outcome Measures

Full Information

First Posted
July 24, 2020
Last Updated
March 7, 2023
Sponsor
Centre Hospitalier Universitaire, Amiens
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1. Study Identification

Unique Protocol Identification Number
NCT04490343
Brief Title
Detection of Urinary Stones on ULDCT With Deep-learning Image Reconstruction Algorithm
Acronym
URO DLIR
Official Title
Detection of Urinary Tract Stones on Ultra-low Dose Abdominopelvic CT Imaging With Deep-learning Image Reconstruction Algorithm
Study Type
Interventional

2. Study Status

Record Verification Date
March 2023
Overall Recruitment Status
Active, not recruiting
Study Start Date
July 21, 2020 (Actual)
Primary Completion Date
July 1, 2022 (Actual)
Study Completion Date
July 1, 2023 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Centre Hospitalier Universitaire, Amiens

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Urolithiasis, Urinary Tract Stones, Renal Colic, Deep Learning Reconstruction
Keywords
Urolithiasis, Urinary Tract Stones, Renal Colic, deep learning reconstruction, radiation dose, dose reduction, low dose CT

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
62 (Actual)

8. Arms, Groups, and Interventions

Intervention Type
Diagnostic Test
Intervention Name(s)
Abdominopelvic low dose CT
Intervention Description
Patients with urinary stones will undergo multiple computed tomography (CT) examinations
Primary Outcome Measure Information:
Title
Accuracy between low dose CT using DLIR reconstruction and low dose CT without DLIR reconstruction for the detection of urinary tract stones
Description
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).
Time Frame
day 1

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
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
Facility Information:
Facility Name
CHU Amiens
City
Amiens
ZIP/Postal Code
80480
Country
France

12. IPD Sharing Statement

Plan to Share IPD
No

Learn more about this trial

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

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