ArticleUrolithiasis2017
Development of a novel magnetic resonance imaging acquisition and analysis workflow for the quantification of shock wave lithotripsy-induced renal hemorrhagic injury.
Article in Urolithiasis, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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The trial behind it
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- Artificial intelligence in urolithiasis: a systematic review of utilization and effectiveness.World journal of urology · 2024Pooled it
- The Ascent of Artificial Intelligence in Endourology: a Systematic Review Over the Last 2 Decades.Current urology reports · 2021Pooled it
- Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review.Asian journal of urology · 2023Review
- Functional and Morphological Changes Associated with Burst Wave Lithotripsy-Treated Pig Kidneys.Journal of endourology · 2022Article
- Renal Protection Phenomenon Observed in a Porcine Model After Electromagnetic Lithotripsy Using a Treatment Pause.Journal of endourology · 2021Article
- Evaluation of Renal Stone Comminution and Injury by Burst Wave Lithotripsy in a Pig Model.Journal of endourology · 2019Article
- Detection and Evaluation of Renal Injury in Burst Wave Lithotripsy Using Ultrasound and Magnetic Resonance Imaging.Journal of endourology · 2017Article
- Percutaneous nephrolithotomy in new versus those patients with previous history of Extracorporeal Shock Wave Lithotripsy on ipsilateral side.Pakistan journal of medical sciencesArticle
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
The current accepted standard for quantifying shock wave lithotripsy (SWL)-induced tissue damage is based on morphometric detection of renal hemorrhage in serial tissue sections from fixed kidneys. This methodology is time and labor intensive and is tissue destructive. We have developed a non-destructive magnetic resonance imaging (MRI) method that permits rapid assessment of SWL-induced hemorrhagic lesion volumes in post-mortem kidneys using native tissue contrast to reduce cycle time. Kidneys of anesthetized pigs were targeted with shock waves using the Dornier Compact S lithotripter. Harvested kidneys were then prepared for tissue injury quantification. T1 weighted (T1W) and T2 weighted (T2W) images were acquired on a Siemens 3T Tim Trio MRI scanner. Images were co-registered, normalized, difference (T1W - T2W) images generated, and volumes classified and segmented using a Multi-Spectral Neural Network (MSNN) classifier. Kidneys were then subjected to standard morphometric analysis for the measurement of lesion volumes. Classifications of T1W, T2W and difference image volumes were correlated with morphometric measurements of whole kidney and parenchymal lesion volumes. From these relationships, a mathematical model was developed that allowed predictions of the morphological parenchymal lesion volume from MRI whole kidney lesion volumes. Predictions and morphology were highly correlated (R = 0.9691, n = 20) and described by the relationship y = 0.84x + 0.09, and highly accurate with a sum of squares difference error of 0.79%. MRI and the MSNN classifier provide a semi-automated segmentation approach, which provide a rapid and reliable means to quantify renal injury lesion volumes due to SWL.
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Registered trials
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