一种基于PSA-SQP混合算法的MRI磁体被动摆振优化方法。

IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Jie Zhao, Minhua Zhu, Ling Xia, Yifeng Fan, Feng Liu
{"title":"一种基于PSA-SQP混合算法的MRI磁体被动摆振优化方法。","authors":"Jie Zhao, Minhua Zhu, Ling Xia, Yifeng Fan, Feng Liu","doi":"10.1038/s41598-025-13751-4","DOIUrl":null,"url":null,"abstract":"<p><p>In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B<sub>0</sub>) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B<sub>0</sub> uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using Linear Programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming. This work aims to improve the efficacy of passive shimming by optimally balancing field quality, iron usage, and harmonics, leading to a smoother field profile. This study introduces a hybrid algorithm that combines a Pattern Search Algorithm with Sequential Quadratic Programming (PSA-SQP) to enhance shimming performance. Additionally, a regularization method is employed to effectively reduce the use of iron pieces. The magnetic field improved from 462 ppm to 6.7 ppm, utilizing merely 0.8 kg of iron in a 400 mm Diameter of Spherical Volume (DSV) of a 7T MRI magnet. Compared to traditional LP optimization techniques, this method notably enhanced magnetic field uniformity by 98.5% and reduced the iron weight requirement by 91.7%, showcasing impressive performance. The proposed new passive shimming algorithm is more effective in improving magnetic field uniformity for MRI applications.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"28419"},"PeriodicalIF":3.9000,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322119/pdf/","citationCount":"0","resultStr":"{\"title\":\"A novel passive shimming optimization method of MRI magnet based on a PSA-SQP hybrid algorithm.\",\"authors\":\"Jie Zhao, Minhua Zhu, Ling Xia, Yifeng Fan, Feng Liu\",\"doi\":\"10.1038/s41598-025-13751-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B<sub>0</sub>) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B<sub>0</sub> uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using Linear Programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming. This work aims to improve the efficacy of passive shimming by optimally balancing field quality, iron usage, and harmonics, leading to a smoother field profile. This study introduces a hybrid algorithm that combines a Pattern Search Algorithm with Sequential Quadratic Programming (PSA-SQP) to enhance shimming performance. Additionally, a regularization method is employed to effectively reduce the use of iron pieces. The magnetic field improved from 462 ppm to 6.7 ppm, utilizing merely 0.8 kg of iron in a 400 mm Diameter of Spherical Volume (DSV) of a 7T MRI magnet. Compared to traditional LP optimization techniques, this method notably enhanced magnetic field uniformity by 98.5% and reduced the iron weight requirement by 91.7%, showcasing impressive performance. The proposed new passive shimming algorithm is more effective in improving magnetic field uniformity for MRI applications.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"15 1\",\"pages\":\"28419\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322119/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-025-13751-4\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-13751-4","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

在磁共振成像(MRI)中,获得高度均匀的主磁场(B0)对于产生详细的人体解剖图像至关重要。被动摆振(PS)是一种通过在磁孔内有策略地布置摆振铁片来提高B0均匀性的技术。传统上,PS优化是使用线性规划(LP)来实现的,这给平衡现场质量和用于摆振的铁的数量带来了挑战。这项工作旨在通过最佳地平衡场质量、铁的使用和谐波来提高被动振荡的效率,从而获得更平滑的场剖面。本文提出了一种将模式搜索算法与序列二次规划(PSA-SQP)相结合的混合算法来提高游动性能。此外,采用正则化方法,有效地减少了铁片的使用。磁场从462 ppm提高到6.7 ppm,仅使用0.8 kg的铁在400毫米直径的球形体积(DSV)的7T MRI磁铁。与传统LP优化技术相比,该方法显著提高了98.5%的磁场均匀性,降低了91.7%的铁重要求,表现出令人满意的性能。该算法在提高磁场均匀性方面更为有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A novel passive shimming optimization method of MRI magnet based on a PSA-SQP hybrid algorithm.

A novel passive shimming optimization method of MRI magnet based on a PSA-SQP hybrid algorithm.

A novel passive shimming optimization method of MRI magnet based on a PSA-SQP hybrid algorithm.

A novel passive shimming optimization method of MRI magnet based on a PSA-SQP hybrid algorithm.

In Magnetic Resonance Imaging (MRI), achieving a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive Shimming (PS) is a technique used to enhance B0 uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using Linear Programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming. This work aims to improve the efficacy of passive shimming by optimally balancing field quality, iron usage, and harmonics, leading to a smoother field profile. This study introduces a hybrid algorithm that combines a Pattern Search Algorithm with Sequential Quadratic Programming (PSA-SQP) to enhance shimming performance. Additionally, a regularization method is employed to effectively reduce the use of iron pieces. The magnetic field improved from 462 ppm to 6.7 ppm, utilizing merely 0.8 kg of iron in a 400 mm Diameter of Spherical Volume (DSV) of a 7T MRI magnet. Compared to traditional LP optimization techniques, this method notably enhanced magnetic field uniformity by 98.5% and reduced the iron weight requirement by 91.7%, showcasing impressive performance. The proposed new passive shimming algorithm is more effective in improving magnetic field uniformity for MRI applications.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Scientific Reports
Scientific Reports Natural Science Disciplines-
CiteScore
7.50
自引率
4.30%
发文量
19567
审稿时长
3.9 months
期刊介绍: We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections. Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021). •Engineering Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live. •Physical sciences Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics. •Earth and environmental sciences Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems. •Biological sciences Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants. •Health sciences The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信