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Related Concept Videos

Imaging Studies II: Ultrasonography01:24

Imaging Studies II: Ultrasonography

IntroductionUltrasonography, or renal ultrasound, is a noninvasive medical imaging technique that uses high-frequency sound waves to visualize the kidneys, ureters, bladder, and surrounding tissues.Indications for Urinary System UltrasonographyUrinary system ultrasonography is indicated in various clinical scenarios, such as:Kidney Stones (Urolithiasis): To detect and monitor the size and presence of kidney or urinary tract stones.Hydronephrosis: To assess the dilation of the renal pelvis and...
Imaging Studies I: Kidney, Ureter, and Bladder Studies01:28

Imaging Studies I: Kidney, Ureter, and Bladder Studies

Kidney, Ureter, and Bladder (KUB) StudiesKidney, Ureter, and Bladder (KUB) studies are standard diagnostic imaging procedures used to assess the anatomy of the urinary system. They are commonly utilized for patients experiencing abdominal pain or urinary symptoms. By using a simple X-ray of the abdomen, KUB studies can reveal structural and pathological abnormalities within the kidneys, ureters, and bladder. These studies are particularly valuable in diagnosing kidney stones, urinary...
Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...

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Related Experiment Video

Updated: May 14, 2026

Use of 3D Robotic Ultrasound for In Vivo Analysis of Mouse Kidneys
08:21

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Published on: August 12, 2021

Multiparametric Ultrasound and Machine Learning for Predicting Renal Scarring in Children.

Zeynep Ayvat Ocal1, Ozgur Ozdemir Simsek2, Cemal Bilir3

  • 1Department of Radiology, Faculty of Medicine, Çiğli Training and Research Hospital, Bakırçay University, İzmir 35620, Türkiye.

Diagnostics (Basel, Switzerland)
|May 13, 2026
PubMed
Summary

Multiparametric ultrasound combined with machine learning can predict renal scarring in children, offering a noninvasive alternative to radiation-heavy DMSA scintigraphy for risk assessment.

Keywords:
DMSArenal scarringshear wave elastographyultrasonography

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Area of Science:

  • Pediatric Nephrology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Renal scarring in children can lead to serious long-term health issues like hypertension and chronic kidney disease.
  • Dimercaptosuccinic acid (DMSA) scintigraphy is the standard for detecting renal scarring but involves radiation exposure.
  • Developing noninvasive methods to predict renal scarring is crucial for pediatric patient care.

Purpose of the Study:

  • To evaluate the efficacy of multiparametric ultrasound and machine learning in predicting DMSA-detected renal scarring in children.
  • To explore the role of renal morphometric, volumetric, and elastography parameters in predicting scarring.
  • To assess the potential of AI-driven analysis to reduce reliance on DMSA scintigraphy.

Main Methods:

  • Retrospective analysis of 192 pediatric patients who underwent both renal ultrasound and DMSA scintigraphy.
  • Analysis of renal morphometric, volumetric parameters, and shear wave elastography.
  • Development and validation of supervised machine learning models using data augmentation to predict renal scarring.

Main Results:

  • Kidney volume indexed to body surface area and asymmetry index were significantly associated with renal scarring.
  • Shear wave elastography improved predictive performance when integrated into machine learning models post-data augmentation.
  • Ensemble-based machine learning models demonstrated high accuracy and area under the ROC curve for predicting renal scarring.

Conclusions:

  • Multiparametric ultrasound combined with machine learning presents a promising noninvasive approach for predicting pediatric renal scarring.
  • This AI-driven method can assist in risk stratification and clinical decision-making, potentially minimizing radiation exposure.
  • While not a substitute for DMSA scintigraphy, it offers a valuable complementary tool in pediatric nephrology.