Optimizing the Imaging Protocol forEx VivoCoronary Artery Wall Using High-Resolution MRI: An Experimental Study on Porcine and Human
Year: 2013
Type: article
Abstract: OBJECTIVE: To optimize the MR imaging protocol for coronary arterial wall depiction in vitro and characterize the coronary atherosclerotic plaques. MATERIALS AND METHODS: MRI examination was prospectively performed in ten porcine hearts in order to optimize the MR imaging protocol. Various surface coils were used for coronary arterial wall imaging with the same parameters. Then, the image parameters were further optimized for high-resolution coronary wall imaging. The signal-noise ratio (SNR) and contrast-noise ratio (CNR) of images were measured. Finally, 8 human cadaver hearts with coronary atherosclerotic plaques were prospectively performed with MRI examination using optimized protocol in order to characterize the coronary atherosclerotic plaques. RESULTS: The SNR and CNR of MR image with temporomandibular coil were the highest of various surface coils. High-resolution and high SNR and CNR for ex vivo coronary artery wall depiction can be achieved using temporomandibular coil with 512 × 512 in matrix. Compared with histopathology, the sensitivity and specificity of MRI for identifying advanced plaques were: type IV-V (lipid, necrosis, fibrosis), 94% and 95%; type VI (hemorrhage), 100% and 98%; type VII (calcification), 91% and 100%; and type VIII (fibrosis without lipid core), 100% and 98%, respectively. CONCLUSION: Temporomandibular coil appears to be dramatically superior to eight-channel head coil and knee coil for ex vivo coronary artery wall imaging, providing higher spatial resolution and improved the SNR. Ex vivo high-resolution MRI has capability to distinguish human coronary atherosclerotic plaque compositions and accurately classify advanced plaques.
Source: Korean Journal of Radiology
Authors: Jiong Yang, Tao Li, Xiaoming Cui, Weihua Zhou, Xin Li, Xinwu Zhang
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W2128995702