FindTrial
Sign In

Use of Artificial Intelligence with dual energy CT Scan to Accurately Measure renal Stone composition

Dual energy CT Characterization of renal calculi composition using AI

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/06/112786
Enrollment
300
Registered
2026-06-16
Start date
Unknown
Completion date
Unknown
Last updated
2026-06-22

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

Conditions

None listed

Interventions

Intervention1: Nil: Nil

Sponsors

Saveetha Medical college
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: People above the age of 19 years, Undergoing CT KUB evaluation

Exclusion criteria

Exclusion criteria: Individuals under the age of 18 years, incomplete imaging data. Poor quality CT images.

Design outcomes

Primary

MeasureTime frame
Sensitivity, Specificity and overall accuracy of AI for Renal calculi compositionTimepoint: At baseline (single assessment)—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactDrSKeerthi Charitha

Saveetha medical college and hospital

kkdrkr@gmail.com9903005065

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Jun 29, 2026