Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Computed Tomography01:10

Computed Tomography

4.5K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
4.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Long-term Impact of a Surgical Innovation and Training Program for High School Students: A 12-Year Follow-Up Study.

Journal of surgical education·2026
Same author

Finding a solution: preliminary results of percutaneous nephrolithotomy outcomes under saline-restricted irrigation conditions.

World journal of urology·2026
Same author

Computed tomography staging of colon cancer: improved patient selection for neoadjuvant therapy with combined radiologic tumor and nodal staging.

BMC cancer·2026
Same author

Characterization of α, β, and muscarinic receptor distribution in porcine ureters: a translational model for pharmacological ureteral dilation.

American journal of physiology. Renal physiology·2026
Same author

Stone Volume: Time for a Paradigm Shift.

Journal of endourology·2026
Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025

Related Experiment Video

Updated: Jul 12, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

875

Efficient and Accurate Computed Tomography-Based Stone Volume Determination: Development of an Automated Artificial

Andrei D Cumpanas1, Chanon Chantaduly2, Kalon L Morgan1

  • 1Department of Urology, University of California Irvine, Orange, California.

The Journal of Urology
|October 27, 2023
PubMed
Summary

An artificial intelligence (AI) algorithm accurately determines kidney stone volume, outperforming traditional ellipsoid formulas. This AI tool offers precise stone burden characterization for improved patient management.

Keywords:
artificial intelligencekidney stonesurolithiasis

More Related Videos

DUCT: Double Resin Casting followed by Micro-Computed Tomography for 3D Liver Analysis
12:39

DUCT: Double Resin Casting followed by Micro-Computed Tomography for 3D Liver Analysis

Published on: September 28, 2021

3.4K
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.8K

Related Experiment Videos

Last Updated: Jul 12, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

875
DUCT: Double Resin Casting followed by Micro-Computed Tomography for 3D Liver Analysis
12:39

DUCT: Double Resin Casting followed by Micro-Computed Tomography for 3D Liver Analysis

Published on: September 28, 2021

3.4K
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.8K

Area of Science:

  • Nephrology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Current methods for characterizing kidney stone burden, such as maximum diameter or ellipsoid formulas, have significant limitations.
  • Accurate stone volume determination is crucial for effective patient management in urolithiasis.

Purpose of the Study:

  • To evaluate the diagnostic accuracy and precision of an artificial intelligence (AI) algorithm developed at the University of California, Irvine for kidney stone volume determination.
  • To compare the AI algorithm's performance against traditional ellipsoid formulas and ground truth measurements.

Main Methods:

  • Retrospective analysis of 322 noncontrast CT scans from patients diagnosed with urolithiasis.
  • Determination of the ground truth 3D stone volume using 3D Slicer technology by a validated reviewer.
  • Comparison of AI-calculated stone volume with ground truth and ellipsoid formula-estimated volumes.

Main Results:

  • The AI algorithm demonstrated a nearly perfect correlation with ground truth volume (R=0.98) and excellent 3D pixel overlap (Dice score=0.90).
  • AI accuracy improved with larger stone sizes, while ellipsoid formulas showed decreased accuracy and significant overestimation (27%-89%).
  • Maximum linear stone measurement showed the poorest correlation with ground truth (R range: 0.41-0.82).

Conclusions:

  • The University of California, Irvine AI algorithm is an accurate, precise, and time-efficient tool for kidney stone volume assessment.
  • Wider clinical adoption of this AI tool could lead to improved guidelines for metabolic and surgical management of urolithiasis.