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

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

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.

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