[Accuracy of different segmentation methods to quantify cardiac function parameters and left ventricular mass in an...

Area of Science:

• Cardiovascular imaging
• Medical physics
• Animal models

Context:

• Accurate quantification of cardiac function and left ventricular mass is crucial for diagnosing and managing cardiovascular diseases.
• Magnetic Resonance Imaging (MRI) with Steady-State Free Precession (SSFP) sequences is a widely used non-invasive technique for cardiac assessment.
• Segmentation methods are essential for delineating cardiac structures and calculating functional parameters from MRI data.

Purpose:

• To compare the accuracy of manual, semiautomatic, and automatic segmentation techniques for quantifying cardiac function parameters, volumes, and left ventricular mass.
• To evaluate the time efficiency of different segmentation methods in a large animal model.

Summary:

• This study assessed three segmentation methods (manual, semiautomatic, automatic) for cardiac MRI in 10 Goettingen miniature pigs using 1.5T SSFP sequences.
• All methods demonstrated high accuracy (r > 0.8 for most parameters) in quantifying left ventricular volumes, ejection fraction, and mass, with no statistically significant differences.
• Semiautomatic and automatic methods significantly reduced quantification time compared to manual segmentation.

Impact:

• The findings validate the use of SSFP sequences and various segmentation methods for accurate cardiac assessment in large animal research.
• Non-manual segmentation techniques (semiautomatic, automatic) provide a more time-efficient approach to cardiac parameter quantification, potentially accelerating research and clinical workflows.