arXiv:2504.00175eess.SPeess.IV2025-04

提出可精确局部恢复化学物质浓度的成像方法,解决传统MRI定量不一致问题。

Exact local recovery for Chemical Shift Imaging

  • 基于光滑非凸优化与凸约束,实现参数的精确局部重建
  • 理论证明在特定条件下化学物质浓度可被唯一识别
  • 适用于脂肪量化等临床场景,对采集参数不敏感

化学位移成像(CSI)或化学位移编码磁共振成像(CSE-MRI)可用于人体内不同化学物质的定量,是量化体脂最广泛使用的成像技术之一。尽管信号采集协议设计和参数恢复方法已有显著改进,但在整个视场范围内仍难以实现一致可靠的定量。不同方法间存在结果差异,且对回波时间等采集参数敏感。这些问题部分源于信号模型本身的非线性,导致多个参数组合可能匹配同一测量信号。本文分析了CSI的信号模型,明确了参数不可辨识的来源,并提出一种基于光滑非凸优化与凸约束的重建方法,在合适条件下可实现精确局部恢复。一个意外发现是:即使其他参数不可辨识,样品中化学物质的浓度仍可能被唯一确定。数值实验验证了理论结果对新型采集方案设计的指导意义,且所提方法性能达到当前最优水平。

原文摘要 · Abstract (English)

Chemical Shift Imaging (CSI) or Chemical Shift Encoded Magnetic Resonance Imaging (CSE-MRI) enables the quantification of different chemical species in the human body, and it is one of the most widely used imaging modalities used to quantify fat in the human body. Although there have been substantial improvements in the design of signal acquisition protocols and the development of a variety of methods for the recovery of parameters of interest from the measured signal, it is still challenging to obtain a consistent and reliable quantification over the entire field of view. In fact, there are still discrepancies in the quantities recovered by different methods, and each exhibits a different degree of sensitivity to acquisition parameters such as the choice of echo times. Some of these challenges have their origin in the signal model itself. In particular, it is non-linear, and there may be different sets of parameters of interest compatible with the measured signal. For this reason, a thorough analysis of this model may help mitigate some of the remaining challenges, and yield insight into novel acquisition protocols. In this work, we perform an analysis of the signal model underlying CSI, focusing on finding suitable conditions under which recovery of the parameters of interest is possible. We determine the sources of non-identifiability of the parameters, and we propose a reconstruction method based on smooth non-convex optimization under convex constraints that achieves exact local recovery under suitable conditions. A surprising result is that the concentrations of the chemical species in the sample may be identifiable even when other parameters are not. We present numerical results illustrating how our theoretical results may help develop novel acquisition techniques, and showing how our proposed recovery method yields results comparable to the state-of-the-art.

医学成像信号恢复非线性优化定量MRI

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。