A three-dimensional T1 mapping imaging method for realizing magnetic resonance full kidney coverage

By combining adiabatic nonselective inversion pulses and multiple three-dimensional equilibrium steady-state free precession readouts with Bloch simulation dictionary matching, the problems of multiple breath-holds and long scanning times in the diagnosis of kidney diseases in existing technologies are solved, and efficient and accurate three-dimensional T1 mapping imaging of the whole kidney is achieved.

CN122398260APending Publication Date: 2026-07-17SOUTHERN MEDICAL UNIVERSITY
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Patent Information

Application Number
CN202610474023.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-11
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In the diagnosis of kidney diseases, existing technologies such as three-dimensional T1 mapping imaging require multiple breath-holdings, resulting in low patient comfort and spatial misalignment. Furthermore, the scanning time of IR magnetization-based methods is too long, making it difficult to achieve efficient full kidney coverage.

Method used

A combination of adiabatic nonselective inversion pulses and multiple three-dimensional equilibrium steady-state free precession readouts was used to generate multiple T1-weighted images. Voxel-by-voxel matching was performed using a dictionary generated by Bloch simulation to achieve high-resolution three-dimensional T1 mapping imaging of the whole kidney.

Benefits of technology

It achieves high-resolution three-dimensional T1 mapping covering the entire kidney within two breath-holds, reduces estimation bias caused by T2 relaxation, improves the accuracy of quantitative T1, and simplifies the operation process.

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Abstract

本发明提供一种实现磁共振全肾脏覆盖的三维T1 mapping成像方法,属于磁共振成像技术领域,先进行非选择性反转磁化制备脉冲,再进行平衡稳态自由进动读出采集反转脉冲后多个反转时间的信号演变,生成多幅T1加权图像;再使用布洛赫模拟离线生成字典,将T1加权图像的体素与字典进行逐体素匹配得到T1定量图,实现了临床可用的全肾脏高分辨率三维T1 mapping技术,序列无需复杂的参数调节与流程优化,被检测对象只需两次屏气即可完成全过程,操作更便捷和快速。另外,布洛赫方程内在地涵盖了信号演化过程中的T2弛豫效应,有助于降低T1量化中因T2弛豫引起的估计偏差,使定量T1定量更加准确。
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