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

You might also read

Related Articles

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

Sort by
Same author

3D Aerohydrogel Scaffolds for Brain Tissue Engineering and <i>In Vitro</i> Neuroscience.

Chem & bio engineering·2026
Same author

Hemostatic Tough Adhesives seal tissue and control hemorrhage.

Nature communications·2026
Same author

Selective muscle involvement quantification in late-onset Tay Sachs and Sandhoff disease using neuromuscular ultrasound imaging.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026
Same author

Marine-Derived Medical Devices and Therapeutic Delivery Systems.

Advanced healthcare materials·2026
Same author

Intervertebral disc degeneration.

Nature reviews. Disease primers·2026
Same author

Advancing Scaffold Architecture for Bone Tissue Engineering: A Comparative Study of 3D-Printed β-TCP Constructs in Dynamic Culture with pBMSC.

Journal of functional biomaterials·2025

Related Experiment Video

Updated: May 17, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

Predicting three-dimensional patellofemoral kinematics from static imaging-based alignment measures.

Benjamin R Freedman1, Frances T Sheehan

  • 1Functional and Applied Biomechanics, Department of Rehabilitation Medicine, NIH, CRC Room 1-1469, 10 Center Drive MSC 1604, Bethesda, Maryland 10892-1604, USA.

Journal of Orthopaedic Research : Official Publication of the Orthopaedic Research Society
|October 26, 2012
PubMed
Summary

Static magnetic resonance imaging (MRI) measures show limited ability to predict three-dimensional patellofemoral kinematics in patients with patellofemoral pain syndrome. Further development of dynamic imaging techniques for clinical use is essential.

More Related Videos

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
06:09

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

Published on: March 12, 2021

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

Related Experiment Videos

Last Updated: May 17, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
06:09

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

Published on: March 12, 2021

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

Area of Science:

  • Biomedical Engineering
  • Radiology
  • Orthopedics

Background:

  • Patellofemoral pain syndrome (PFPS) is a prevalent condition causing significant discomfort and disability.
  • Advanced 3D dynamic imaging can assess pathological patellofemoral motion but is costly for clinical use.
  • Predicting 3D kinematics from simpler 2D static measures could offer a cost-effective diagnostic alternative.

Purpose of the Study:

  • To investigate if 3D patellofemoral kinematics can be predicted from 2D static MRI measures of joint alignment.
  • To evaluate the correlation between static patellofemoral alignment and dynamic 3D kinematics in PFPS patients and controls.

Main Methods:

  • Acquired static 3D sagittal T1-weighted MRI and dynamic cine-phase contrast MRI in 26 PFPS patients and 26 controls.
  • Quantified static 2D patellofemoral alignment from MRI data in full knee extension.
  • Derived 3D patellofemoral kinematics from dynamic MRI scans during cyclic knee flexion-extension.
  • Performed regression analyses to assess the predictive power of static measures on kinematic variables.

Main Results:

  • Static MRI measures of patellofemoral alignment were reliable but only partially predicted 3D patellofemoral kinematics.
  • The predictive power (r-squared values) ranged from 16% to 77%, indicating significant unexplained variance.
  • Static measures alone are insufficient for accurately characterizing dynamic patellofemoral joint behavior.

Conclusions:

  • Routine 2D static MRI measures have limited accuracy in predicting 3D patellofemoral kinematics.
  • Precise, accurate, 3D dynamic imaging techniques are necessary for comprehensive assessment of PFPS.
  • Translating advanced dynamic MRI technologies into accessible clinical tools is imperative for improved PFPS diagnostics.