Work

Prospective cardiac motion self-gating

Year: 2017

Type: article

Abstract: BACKGROUND: To develop a prospective cardiac motion self-gating method that provides robust and accurate cardiac triggers in real time. METHODS: The proposed self-gating method consists of an "imaging mode" that acquires the k-space segments and a "self-gating mode" that captures the cardiac motion by repeatedly sampling the k-space centerline. A training based principal component analysis algorithm is utilized to process the self-gating data where the projection onto the first principal component was used as the self-gating signal. Retrospective studies using a sequence with self-gating mode only was performed on 8 healthy subjects to validate the accuracy and reliability of the self-gating triggers. Prospective studies using both ECG-gated and self-gated cardiac CINE sequences were conducted on 6 healthy subjects to compare the image quality. RESULTS: Using the ECG as the reference, the proposed method was able to detect self-gating triggers within ±10 ms accuracy on all 8 subjects in the retrospective study. The prospectively self-gated CINE sequence successfully detected 100% of the cardiac triggers and provided excellent CINE image quality without using ECG signals. CONCLUSIONS: The proposed cardiac self-gating method is a robust and accurate alternative to conventional ECG-based gating method for a number of cardiac MRI applications.

Source: Quantitative Imaging in Medicine and Surgery

DOI: 10.21037/qims.2017.03.02

Authors: Fei Han, Stanislas Rapacchi, Peng Hu

Institutions: University of California, Los Angeles, Centre de Résonance Magnétique Biologique et Médicale

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funders: American Heart Association, National Institutes of Health, National Heart, Lung, and Blood Institute