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COMPLETED
NCT04490343
NA

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

Sponsor: Centre Hospitalier Universitaire, Amiens

View on ClinicalTrials.gov

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.

Official title: Detection of Urinary Tract Stones on Ultra-low Dose Abdominopelvic CT Imaging With Deep-learning Image Reconstruction Algorithm

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

INTERVENTIONAL

Enrollment

62

Start Date

2020-06-15

Completion Date

2022-03-04

Last Updated

2026-06-15

Healthy Volunteers

No

Interventions

DIAGNOSTIC_TEST

Abdominopelvic low dose CT

Patients with urinary stones will undergo multiple computed tomography (CT) examinations

Locations (1)

CHU Amiens

Amiens, France