An observational study in Urinary Stone, Renal Colic and Obstruction Ureter, sponsored by Oslo University Hospital. Active, not recruiting at 1 site in Norway. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-08-11.
Sponsored by Oslo University Hospital · Observational
Kidney stone disease causes significant morbidity, and stones obstructing the ureter can have serious consequences. Imaging diagnostics with computed tomography (CT) are crucial for diagnosis, treatment selection, and follow-up. Segmentation of CT images can provide objective data on stone burden and signs of obstruction. Artificial intelligence (AI) can automate such segmentation but can also be used for the diagnosis of stone disease and obstruction.
In this project, the aim is to investigate if:
Manual segmentation of CT scans can provide more accurate information about kidney stone disease compared to conventional interpretation.
AI segmentation yields valid results compared to manual segmentation. AI can detect ureteral stones and obstruction or predict spontaneous passage.
Background:
Goals and Objectives:
The project aims to contribute to personalized and improved treatment and follow-up of patients with kidney stones using radiomics and the development of an artificial intelligence tool for CT examination assessment. The objectives are to assess:
Method:
Cohort:
Patients are recruited to the study at Oslo University Hospital, Radiology Department, Section Aker, which performs approximately 1350 CT examinations for urinary tract stones in approximately 1000 patients each year. Approximately 500 patients with a new episode or newly occurring colic pain and clinical suspicion of kidney stones are expected to be included.
Clinical data (where available):
Image data:
Clinical radiology report:
509 studies on the registry are indexed under Kidney Calculi; 146 are open to participants now.
This study's enrollment of 522 is above the median of 160 across 96 observational studies indexed under Kidney Calculi.
Browse Kidney Calculi studies →Oslo University Hospital is the lead sponsor of 834 studies on the registry; 149 are open to participants now.
Compared within Kidney Calculi, this study's primary condition as ClinicalTrials.gg classifies it; the registry's first condition term is Urinary Calculi. The counts are of registry records indexed under each term, refreshed daily. How we classify →
Patients referred for CT for new/acute episode of renal colic and suspicion of /or known urinary stone disease.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Newly occurring colic pain and clinical suspicion of kidney stones or known kidney stone with new/increasing symptoms. Age ≥ 18 years
Comparison of stone diameter from manual segmentation with radiology report
Stone diameter (in mm) compared between manual segmentation and radiology report (paired t-test or wilcoxon rank sum test if non-normally distributed data)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of stones (DICE-score) with manual segmentation
DICE-score for AI-segmentation of stones, compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Prospective performance (diagnostic accuracy) of AI detection of ureteral stone (compared to radiology report (gold standard)
Comparison of differences in dicotomous proportions in paired data according to Newcombe
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of stone density from manual segmentation with radiology report
Stone density (in Hounsfield Units) compared between manual segmentation and radiology report (paired t-test or wilcoxon rank sum test if non-normally distributed data)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of distention of renal pelvis from manual segmentation with radiology report
Distention of renal pelvis (in mm) compared between manual segmentation and radiology report (paired t-test or wilcoxon rank sum test if non-normally distributed data)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of stones (Hausdorff distance) with manual segmentation
Haussdorff distance for AI-segmentation of stones, compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of stones (diagnostic accuracy) with manual segmentation
Diagnostic accuracy for AI-segmentation of stones compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of renal pelvis (Dice-score) with manual segmentation
DICE-score for AI-segmentation of renal pelvis compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of renal pelvis (Hausdorff distance) with manual segmentation
Hausdorff distance for AI-segmentation of renal pelvis compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of renal pelvis (diagnostic accuracy) with manual segmentation
Diagnostic accuracy for AI-segmentation of renal pelvis compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of renal parenchyma (DICE-score) with manual segmentation
DICE-score for AI-segmentation of renal parenchyma compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of renal parenchyma (Hausdorff distance) with manual segmentation
Hausdorff distance for AI-segmentation of renal parenchyma compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Comparison of AI-segmentation of renal parenchyma (diagnostic accuracy) with manual segmentation
Diagnostic accuracy for AI-segmentation of renal parenchyma compared to manual segmenation (gold standard)
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
Prospective performance (diagnostic accuracy) of AI detection of ureteral obstruction (compared to radiology report (gold standard)
Comparison of differences in dicotomous proportions in paired data according to Newcombe
Time frame: At time of CT examination (inclusion and follow up - expected average 12 weeks)
PDFs hosted by the registry, ClinicalTrials.gov.
Plan to share: No
Started May 2024 (actual). Primary completion is estimated for Aug 2025, 14 months after the start.
Of 39 observational studies under Kidney Calculi, half reached primary completion within 42 months of starting (the median), counting those still running; a quarter within 14 and three quarters within 52. This study's planned 14 months is below that.
How these figures are worked out, and which studies are left out of them.
This study is active, not recruiting, as verified in Aug 2025. You cannot join it, but the record below documents what was studied.
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