Keywords: Urogenital, Bladder, Hydrometry, Time-Volume Curves, AI-segmentation
Motivation: Treatment efficacy in Autosomal Dominant Polycystic Kidney Disease (ADPKD) can be better assessed by measuring bladder urine generation rates, enabled by precise MRI sequence timing for optimal reproducibility.
Goal(s): To identify optimal timeframe that promises the minimum variation and stable urine output growth in the bladder.
Approach: We demonstrated optimized sequence and parameters for pelvis scanning, focusing on bladder. Using deep learning segmentation, we measure urine accumulation at 1-minute intervals to track the dynamic process of bladder filling over time.
Results: A 25-30 minute time window was identified as optimal for achieving stable urine growth rate, with accumulation stability influenced by hydration status.
Impact: This study assists radiologists in assessing treatment efficacy in ADPKD through precise urine generation tracking, supported by the reproducible optimized protocol establishing a 25-30 minute timeframe for stable measurements.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords