Health Condition 1: N29- Other disorders of kidney and ureter in diseases classified elsewhere
Conditions
Interventions
Intervention1: Artificial Intelligence Based Hydroureteronephrosis Grading Tool: Automated detection and grading of hydroureteronephrosis on CT KUB using ONEN classification
Intervention2: Nil: Nil
In
Sponsors
Dr Priya Dharshini R
Eligibility
Inclusion criteria
Inclusion criteria: Adult patients aged 18 years and above who underwent CT abdomen or CT KUB imaging for evaluation of abdominal pain flank pain or suspected urinary tract pathology at the study center. CT scans with adequate visualization of kidneys and ureters and acceptable image quality were included. Patients with presence or absence of hydroureteronephrosis were included.
Exclusion criteria
Exclusion criteria: Patients with CT scans having significant motion artifacts or poor image quality were excluded. Patients with previous renal surgery urinary diversion or congenital renal anomalies affecting renal anatomy were excluded. CT scans with space occupying lesions causing gross distortion of renal anatomy were excluded. Pregnant patients and patients with severe cognitive impairment were excluded.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diagnostic accuracy of artificial intelligence based application for detection and grading of hydroureteronephrosis on CT KUB imaging measured using sensitivity specificity positive predictive value negative predictive value and area under receiver operating characteristic curve.Timepoint: At baseline at the time of CT KUB imaging and radiological interpretation. | — |
Secondary
| Measure | Time frame |
|---|---|
| Agreement between Artificial Intelligence based grading and radiologist interpretation of Hydroureteronephrosis using ONEN classification.Timepoint: At the time of CT KUB image analysis during the study period.;Detection of morphological features of Hydroureteronephrosis including renal pelvic dilatation calyceal dilatation ureteric dilatation and renal parenchymal thinning by Artificial Intelligence application.Timepoint: At the time of CT KUB image analysis during the study period. | — |
Countries
India
Contacts
Public ContactDr Priya Dharshini R
Saveetha Medical College and Hospital, Chennai
Outcome results
None listed