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A new method using artificial intelligence for grading kidney stones with dual energy CT scan

Neoteric Approach to Artificial Intelligence Based Grading of Renal Calculus in Coronal Plane Images of 128 Dual Energy CT - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/04/108327
Enrollment
500
Registered
2026-04-13
Start date
Unknown
Completion date
Unknown
Last updated
2026-04-27

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

Conditions

Health Condition 1: N200- Calculus of kidney

Interventions

Intervention1: Nil: Nil Intervention2: Nil: Nil

Sponsors

Sri Indira Kumar U
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: patients aged 18 to 80 years undergoing dual energy CT scan for evaluation of renal calculi. Patients with radiologically confirmed renal stones on 128 slice dual energy CT. Patients who provide informed consent to participate in the study

Exclusion criteria

Exclusion criteria: Patients with prior surgical intervention for renal calculi. Patients with poor image quality or motion artefacts affecting evaluation. Patients with non renal urinary calculi. Pregnant patients. Patients not willing to participate in the study

Design outcomes

Primary

MeasureTime frame
Diagnostic accuracy of artificial intelligence based grading of renal calculi on dual energy CT in comparison with standard imaging assessmentTimepoint: At baseline at the time of dual energy computed tomography imaging—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactDrSri indira Kumar U

saveetha institute of medical and technial sciences

radiologysaveetha7@gmail.com9841205597

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: May 1, 2026