Complex multi-dimensional integration for T 2 * and R 2 * mapping.

A dual Multi-Dimensional Integration (dMDI) method was proposed and demonstrated for T ₂ * and R ₂ * mapping. By constructing and jointly using both the original MDI term and an inversed MDI term, T ₂ * and R ₂ * mapping can be performed independently with intrinsic background noise suppression and spike elimination, allowing for high quantitative accuracy and robustness over a wide range of T ₂ *. dMDI was compared to original MDI and curve fitting methods in terms of quantitative specificity, accuracy, reliability and computational efficiency. All methods were tested and compared via simulation and in vivo data. With high signal-to-noise-ratio (SNR), the proposed dMDI method yielded T ₂ *and R ₂ * values similar to curve fitting methods. For low SNR and background noise signals, the dMDI yielded low T ₂ * and R ₂ * values, thus effectively suppressing all background noise. Virtually zero spikes were observed in dMDI T ₂ * and R ₂ * maps in all simulation and imaging results. The dMDI method has the potential to provide improved and reliable T ₂ * and R ₂ * mapping results in routine and SNR-challenging scenarios.
Competing Interests: Declaration of competing interest The following authors are employees of the UIH America, Inc., Houston, TX, United States: Yongquan Ye, Jian Xu and Zhongqi Zhang. The following authors are employees of the Beijing United Imaging Intelligent Imaging Technology Research Institute: Yan Zhang.
(Copyright © 2024. Published by Elsevier Inc.)