Related Experiment Video
Updated: May 6, 2026

10:44
Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
Published on: June 21, 2024
476
Bi-parametric MRI of the Diaphragm Using Dynamic and Static Images: The Initial Experience
Murat Tepe1, Ibrahim Inan2, Safiye Kafadar3
1Radiology, Mediclinic City Hospital, Dubai, ARE.
Cureus
|July 2, 2024
Summary
Bi-parametric magnetic resonance imaging (MRI) shows strong agreement for diagnosing diaphragmatic dysfunctions. This advanced MRI technique effectively visualizes diaphragm motion and soft tissues, aiding in abnormality detection.
Area of Science:
- Medical Imaging
- Diagnostic Radiology
- Anatomy
Background:
- Recent advancements in magnetic resonance imaging (MRI) enable real-time evaluation of anatomical structure motion.
- Diaphragmatic dysfunctions require accurate diagnostic methods for effective management.
- Bi-parametric MRI combines dynamic and static sequences for comprehensive diaphragm visualization.
Purpose of the Study:
- To assess the interobserver agreement in diagnosing diaphragmatic dysfunctions using bi-parametric MRI.
- To evaluate the utility of combined dynamic and static MRI sequences for diaphragm assessment.
Main Methods:
- Retrospective analysis of 29 bi-parametric MRI examinations.
- Inclusion of coronal T2 single-shot turbo spin echo and coronal SENSE single-shot balanced turbo field echo real-time sequences.
- Assessment of images by two independent observers and calculation of Cohen's kappa coefficient for interobserver agreement.
Main Results:
- The study included 29 patients with a mean age of 44.86 years (range 18-80).
- A Cohen's kappa coefficient of 0.889 was calculated.
- This value indicates a strong agreement between the two independent observers.
Conclusions:
- Bi-parametric MRI demonstrates high interobserver agreement for diagnosing diaphragmatic abnormalities.
- This imaging approach is a promising tool for evaluating diaphragmatic dysfunctions.
- The combination of dynamic and static sequences enhances visualization and diagnostic accuracy.

