Summary: UCLA researchers in the Department of Radiology have developed a novel method to capture time-varying and irregular cardiac motion, producing high-precision, high-quality cine images.
Background: Cine MRI is a specialized imaging technique that captures motion through a series of images, often used to evaluate cardiac function and morphology. In cases of complex arrhythmia, such as atrial fibrillation (AF), cine MRI struggles to capture dynamic changes accurately. AF has a high incidence in the United States, ranging from approximately 1-2%, further highlighting the need for enhanced imaging modalities. Irregular cardiac motion frequently leads to imaging artifacts and premature scan termination, hindering diagnostic accuracy of this imaging application. To improve patient outcome and prognosis, there is a need for an imaging method that considers intrinsic cardiac motion and consistently produces high-quality images for both regular and irregular rhythms.
Innovation: Dr. Kim-Lien Nguyen and her research team have developed an innovative method for capturing smooth transition between dynamic cardiac motion states across a wide variety of motion patterns. The Dynamic Regularized Adaptive Cluster Optimization (DRACO) method is designed to address the limitations of current state-of-the-art techniques for representing cardiac motion. The adaptive system uses cluster grouping to optimize the generation of time-resolved cine images. By employing a probabilistic approach, it achieves smooth transitions while preserving the sequential timing of motion. Extensive testing has demonstrated the resulting images exhibit reduced noise, enhanced continuity of cluster positions, minimal image artifacts, improved edge sharpness, and the effective handling of time varying motion patterns, such as those intrinsic to atrial fibrillation (AF). DRACO thus offers a promising solution for quantifying cardiac function in the setting of atrial fibrillation and overcoming previous limitations in segmented cine MRI techniques.
Potential Applications: ● Improved diagnosis of arrhythmias ● Personalized cardiac treatment planning ● Monitoring disease progression ● Non-invasive cardiac stress testing
Advantages: ● Reduces image artifacts ● Enhances imaging quality and reduces noise ● Improves temporal resolution ● Preserves sequential timing of cardiac phases ● Adapts to a wide range of cardiac motion patterns
State of Development: Successfully replicated with complete experimentation proving hypotheses for increased image quality with the proposed model when compared to reference, existing imaging methods.
Related Papers: 1. Ming Z, Pogosyan A, Gao C, Colbert CM, Wu HH, Finn JP, Ruan D, Hu P, Christodoulou AG, Nguyen KL. ECG‐free cine MRI with data‐driven clustering of cardiac motion for quantification of ventricular function. NMR in Biomedicine. 2024 Jan 9:e5091. doi: 10.1002/nbm.5091 2. Ming Z, Pogosyan A, Christodoulou AG, Finn JP, Ruan D, Nguyen KL. Dynamic Regularized Adaptive Cluster Optimization (DRACO) for Quantitative Cine MRI in Complex Arrhythmias. J Mag Reson Imaging. 2024 May 6. doi: 10.1002/jmri.29425.
Reference: UCLA Case No. 2024-250