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

Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
Herniated Intervertebral Disc l: Introduction01:29

Herniated Intervertebral Disc l: Introduction

Intervertebral disc herniation refers to the displacement of the nucleus pulposus (the gel-like inner core of the disc) through a tear or weakened area in the annulus fibrosus (the outer fibrous ring). The displaced disc material extends beyond the normal boundaries of the disc space and may compress or irritate nearby spinal nerve roots or, less commonly, the spinal cord.Etiology and Risk FactorsHerniation commonly results from degeneration, in which aging reduces disc hydration and...

You might also read

Related Articles

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

Sort by
Same author

Are magnetic resonance imaging features associated with intermittent and constant pain in knee osteoarthritis? A cross-sectional study.

Osteoarthritis and cartilage open·2026
Same author

Spatially identifying regions of tumor recurrence in patients with suspected recurrent glioma using physiologic MRI and machine learning.

NPJ digital medicine·2026
Same author

Hip Joint Loading During Walking Is Associated With Cartilage Defect Severity in Young Adult Football Players With Hip/Groin Pain.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society·2026
Same author

Regional and depth-dependent associations between subchondral bone and cartilage in hip osteoarthritis: a preliminary [<sup>18</sup>F]-NaF PET-MR study exploring bone-cartilage cross-talk.

Skeletal radiology·2026
Same author

Clinical utility of foundation models in musculoskeletal MRI for biomarker fidelity and predictive outcomes.

NPJ digital medicine·2026
Same author

Artificial Intelligence-Based Proximal Bone Shape Asymmetry Analysis and Clinical Correlation with Cartilage Relaxation Times and Functional Activity.

Bioengineering (Basel, Switzerland)·2026

Related Experiment Video

Updated: Jun 8, 2026

Ovine Lumbar Intervertebral Disc Degeneration Model Utilizing a Lateral Retroperitoneal Drill Bit Injury
07:25

Ovine Lumbar Intervertebral Disc Degeneration Model Utilizing a Lateral Retroperitoneal Drill Bit Injury

Published on: May 25, 2017

12.0K

Lumbar intervertebral disc characterization through quantitative MRI analysis: An automatic voxel-based relaxometry

Claudia Iriondo1,2, Valentina Pedoia1, Sharmila Majumdar1

  • 1Department of Radiology and Biomedical Imaging, University of California, San Francisco, California.

Magnetic Resonance in Medicine
|February 16, 2020
PubMed
Summary

This study introduces an automated MRI analysis pipeline to assess disc degeneration and its link to lower back pain. The method accurately measures biochemical changes, correlating them with patient disability levels.

Keywords:
deep learningregistrationrelaxometrysegmentationspine

More Related Videos

Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain
06:31

Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain

Published on: August 8, 2019

7.6K
A Mouse Model of Lumbar Spine Instability
05:28

A Mouse Model of Lumbar Spine Instability

Published on: April 23, 2021

8.8K

Related Experiment Videos

Last Updated: Jun 8, 2026

Ovine Lumbar Intervertebral Disc Degeneration Model Utilizing a Lateral Retroperitoneal Drill Bit Injury
07:25

Ovine Lumbar Intervertebral Disc Degeneration Model Utilizing a Lateral Retroperitoneal Drill Bit Injury

Published on: May 25, 2017

12.0K
Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain
06:31

Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain

Published on: August 8, 2019

7.6K
A Mouse Model of Lumbar Spine Instability
05:28

A Mouse Model of Lumbar Spine Instability

Published on: April 23, 2021

8.8K

Area of Science:

  • Biomedical Imaging
  • Artificial Intelligence in Medicine
  • Musculoskeletal Radiology

Background:

  • Lumbar intervertebral disc degeneration is a major cause of lower back pain.
  • Current assessment methods are often subjective and time-consuming.
  • Understanding the biochemical basis of degeneration is crucial for targeted treatments.

Purpose of the Study:

  • To develop an automated pipeline using convolutional neural networks for lumbar disc segmentation.
  • To characterize disc biochemical composition via voxel-based relaxometry (T1ρ and T2).
  • To establish associations between disc degeneration, disability, and lower back pain symptoms.

Main Methods:

  • Utilized MRI data from 31 patients with varying disc degeneration.
  • Combined deep learning segmentation, atlas-based registration, and statistical parametric mapping.
  • Analyzed T1ρ and T2 relaxation time maps on a voxel-by-voxel basis.

Main Results:

  • Achieved accurate, high-confidence lumbar disc segmentation.
  • Demonstrated strong agreement between manual and automated relaxation time measurements.
  • Found significant negative correlations between degenerative grades and T1ρ/T2 values, especially in the nucleus.
  • Identified distinct differences in relaxation maps between minimal/moderate and severe disability groups.

Conclusions:

  • Presented a scalable, automated pipeline for disc relaxation time assessment.
  • Voxel-based relaxometry overcomes limitations of traditional region-of-interest methods.
  • The pipeline offers potential for deeper insights into disc degeneration, disability, and lower back pain associations.