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Related Concept Videos

Imaging Studies VI: Voiding Cystourethrography and Cystography01:22

Imaging Studies VI: Voiding Cystourethrography and Cystography

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Voiding Cystourethrography (VCUG) and Cystography are specialized radiographic procedures used to examine the structure and function of the bladder and urethra.Voiding Cystourethrography (VCUG)A Voiding Cystourethrogram (VCUG) is a diagnostic imaging procedure that assesses the anatomy and function of the lower urinary tract. It focuses on the bladder, bladder neck, and urethra, helping detect abnormalities such as vesicoureteral reflux (VUR)—the backward or reverse flow of urine into the...
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Imaging Studies V: Intravenous Urography and Retrograde Pyelography01:22

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IntroductionIntravenous Urography (IVU) and Retrograde Pyelography (RP) are important diagnostic imaging techniques used to evaluate the urinary system. These methods help identify structural abnormalities, obstructions, and functional issues in the kidneys, ureters, and bladder. Both procedures use iodine-based contrast media to enhance the visibility of urinary tract structures on X-ray images, though they differ in their methods and indications.1. Intravenous Urography (IVU)Intravenous...
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Urodynamic Studies: Uroflowmetry01:19

Urodynamic Studies: Uroflowmetry

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Uroflowmetry is a non-invasive urodynamic test designed to measure various aspects of urination, including volume, flow rate, and the time to void. This test is crucial for diagnosing and assessing conditions such as bladder outlet obstruction, bladder dysfunction, incomplete bladder emptying, incontinence, and urinary tract blockages caused by benign prostatic hyperplasia (BPH) and urethral strictures.Pre-Test Instructions:Before a uroflowmetry test, patients are typically advised to drink...
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Urinary Tract Calculi I: Introduction01:28

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Renal calculi, or kidney stones, are solid deposits of minerals and salts formed inside the kidneys. In medical terminology, "calculus" refers to the stone itself, while "lithiasis" describes the process of stone formation. Depending on their location within the urinary system, these stones may be classified as either urolithiasis, when situated within the urinary tract, or nephrolithiasis, when located within the kidneys. Each term signifies the specific impact of the stone.Predisposition...
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Imaging Studies I: Kidney, Ureter, and Bladder Studies01:28

Imaging Studies I: Kidney, Ureter, and Bladder Studies

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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...
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Urinary Tract Calculi III: Medical Management01:30

Urinary Tract Calculi III: Medical Management

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The diagnosis of renal calculi involves several imaging techniques, including non-contrast CT scans and ultrasound. These methods help visualize kidney stones, assess their size and location, and detect possible obstructions. Additionally, Measuring urine pH is useful for diagnosing specific stone types, such as struvite (alkaline pH) and uric acid stones (acidic pH). Cystine stones are primarily linked to cystinuria, a genetic condition. A urinalysis helps detect blood in the urine (hematuria)...
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Related Experiment Video

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Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
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Quantification of vesicoureteral reflux using machine learning.

Saidul Kabir1, J L Pippi Salle2, Muhammad E H Chowdhury3

  • 1Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, 1000, Bangladesh.

Journal of Pediatric Urology
|November 18, 2023
PubMed
Summary
This summary is machine-generated.

A machine learning model accurately grades voiding cystourethrogram (VCUG) images for vesicoureteral reflux (VUR). This objective approach aids in determining clinical course and treatment for VUR patients.

Keywords:
Feature extractionMachine learningVesicoureteral reflux (VUR)Voiding cystourethrogram (VCUG)

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Area of Science:

  • Radiology
  • Medical Imaging
  • Machine Learning

Background:

  • Voiding cystourethrogram (VCUG) grading is crucial for managing vesicoureteral reflux (VUR).
  • Current VCUG image evaluation is subjective, leading to potential inconsistencies in VUR assessment.
  • Objective grading of VUR is needed to standardize patient care.

Purpose of the Study:

  • To develop and validate a supervised machine learning model for objective VCUG image grading.
  • To automate the assessment of VUR severity from radiographic images.
  • To improve the accuracy and consistency of VUR diagnosis.

Main Methods:

  • A dataset of 113 VCUG images was curated.
  • Expert pediatric radiologists and urologists graded VUR severity to establish ground truth.
  • Nine image features were extracted and used to train six machine learning models with cross-validation.

Main Results:

  • Machine learning models, particularly Support Vector Machine (SVM) and Multi-layer Perceptron (MLP), achieved high accuracy.
  • F1-scores reached 91.14% for MLP and 90.27% for SVM using the highest-ranked features.
  • A distorted renal calyce pattern was identified as a key predictor of high-grade VUR.

Conclusions:

  • Machine learning offers a promising avenue for objective VUR grading from VCUG images.
  • The developed model demonstrates high accuracy in assessing VUR severity.
  • Future enhancements to machine learning protocols can further refine objective VUR grading.