Affiliation:
1. Department of Chemical and Biological Physics Weizmann Institute of Science Rehovot Israel
2. Siemens Healthcare Ltd. Rosh Ha'ayeen Israel
Abstract
PurposeConventional sequences are static in nature, fixing measurement parameters in advance in anticipation of a wide range of expected tissue parameter values. We set out to design and benchmark a new, personalized approach—termed adaptive MR—in which incoming subject data is used to update and fine‐tune the pulse sequence parameters in real time.MethodsWe implemented an adaptive, real‐time multi‐echo (MTE) experiment for estimating T2s. Our approach combined a Bayesian framework with model‐based reconstruction. It maintained and continuously updated a prior distribution of the desired tissue parameters, including T2, which was used to guide the selection of sequence parameters in real time.ResultsComputer simulations predicted accelerations between 1.7‐ and 3.3‐fold for adaptive multi‐echo sequences relative to static ones. These predictions were corroborated in phantom experiments. In healthy volunteers, our adaptive framework accelerated the measurement of T2 for n‐acetyl‐aspartate by a factor of 2.5.ConclusionAdaptive pulse sequences that alter their excitations in real time could provide substantial reductions in acquisition times. Given the generality of our proposed framework, our results motivate further research into other adaptive model‐based approaches to MRI and MRS.
Funder
Israel Science Foundation
Subject
Radiology, Nuclear Medicine and imaging
Cited by
1 articles.
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