Suppr超能文献

微波断层成像与磁共振成像的融合提高了乳房成像效果。

Integration of microwave tomography with magnetic resonance for improved breast imaging.

机构信息

Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755.

出版信息

Med Phys. 2013 Oct;40(10):103101. doi: 10.1118/1.4820361.

Abstract

PURPOSE

Breast magnetic resonance imaging is highly sensitive but not very specific for the detection of breast cancer. Opportunities exist to supplement the image acquisition with a more specific modality provided the technical challenges of meeting space limitations inside the bore, restricted breast access, and electromagnetic compatibility requirements can be overcome. Magnetic resonance (MR) and microwave tomography (MT) are complementary and synergistic because the high resolution of MR is used to encode spatial priors on breast geometry and internal parenchymal features that have distinct electrical properties (i.e., fat vs fibroglandular tissue) for microwave tomography.

METHODS

The authors have overcome integration challenges associated with combining MT with MR to produce a new coregistered, multimodality breast imaging platform--magnetic resonance microwave tomography, including: substantial illumination tank size reduction specific to the confined MR bore diameter, minimization of metal content and composition, reduction of metal artifacts in the MR images, and suppression of unwanted MT multipath signals.

RESULTS

MR SNR exceeding 40 dB can be obtained. Proper filtering of MR signals reduces MT data degradation allowing MT SNR of 20 dB to be obtained, which is sufficient for image reconstruction. When MR spatial priors are incorporated into the recovery of MT property estimates, the errors between the recovered versus actual dielectric properties approach 5%.

CONCLUSIONS

The phantom and human subject exams presented here are the first demonstration of combining MT with MR to improve the accuracy of the reconstructed MT images.

摘要

目的

乳腺磁共振成像具有很高的敏感性,但特异性不高,可用于检测乳腺癌。有机会通过补充更具特异性的模态来补充图像采集,只要能够克服在孔径内满足空间限制、限制乳房进入和电磁兼容性要求的技术挑战。磁共振(MR)和微波层析成像(MT)是互补和协同的,因为 MR 的高分辨率用于对具有不同电特性(即脂肪与纤维腺体组织)的乳腺几何形状和内部实质特征进行空间先验编码,以便微波层析成像使用。

方法

作者已经克服了将 MT 与 MR 结合以产生新的配准、多模态乳腺成像平台——磁共振微波层析成像的集成挑战,包括:针对受限的 MR 孔径直径,大幅减小照明罐的尺寸,最小化金属含量和组成,减少 MR 图像中的金属伪影,并抑制不需要的 MT 多径信号。

结果

可以获得超过 40dB 的 MR SNR。适当的 MR 信号滤波可以减少 MT 数据的降级,从而可以获得 20dB 的 MT SNR,足以进行图像重建。当将 MR 空间先验纳入 MT 特性估计的恢复中时,恢复的与实际介电特性之间的误差接近 5%。

结论

这里呈现的体模和人体受试者检查是首次将 MT 与 MR 结合以提高重建 MT 图像准确性的演示。

相似文献

2
3
3D microwave tomography of the breast using prior anatomical information.
Med Phys. 2016 Apr;43(4):1933. doi: 10.1118/1.4944592.
4
Two-step inversion with a logarithmic transformation for microwave breast imaging.
Med Phys. 2017 Aug;44(8):4239-4251. doi: 10.1002/mp.12384. Epub 2017 Jul 17.
6
Integrating prior information into microwave tomography Part 1: Impact of detail on image quality.
Med Phys. 2017 Dec;44(12):6461-6481. doi: 10.1002/mp.12585. Epub 2017 Oct 23.
10
Comparison of no-prior and soft-prior regularization in biomedical microwave imaging.
J Med Phys. 2011 Jul;36(3):159-70. doi: 10.4103/0971-6203.83482.

引用本文的文献

2
Microwave Imaging and Sensing Techniques for Breast Cancer Detection.
Micromachines (Basel). 2023 Jul 21;14(7):1462. doi: 10.3390/mi14071462.
3
Holographic Microwave Image Classification Using a Convolutional Neural Network.
Micromachines (Basel). 2022 Nov 23;13(12):2049. doi: 10.3390/mi13122049.
4
3D-printed gear system for antenna motion in an MR environment: initial phantom imaging experiments.
Proc (USNC URSI Radio Sci Meet). 2022 Jul;2022:896-897. doi: 10.1109/ap-s/usnc-ursi47032.2022.9886820. Epub 2022 Sep 21.
5
6
Discrete Dipole Approximation-Based Microwave Tomography for Fast Breast Cancer Imaging.
IEEE Trans Microw Theory Tech. 2021 May;69(5):2741-2752. doi: 10.1109/tmtt.2021.3060597. Epub 2021 Mar 5.
7
Toward Image Data-Driven Predictive Modeling for Guiding Thermal Ablative Therapy.
IEEE Trans Biomed Eng. 2020 Jun;67(6):1548-1557. doi: 10.1109/TBME.2019.2939686. Epub 2019 Sep 5.
8
Addressing Multipath Signal Corruption in Microwave Tomography and the Influence on System Design and Algorithm Development.
Open Access J Biomed Eng Biosci. 2018;1(1). doi: 10.32474/OAJBEB.2018.01.000102. Epub 2018 Feb 5.
9
3-D Microwave Tomography Using the Soft Prior Regularization Technique: Evaluation in Anatomically Realistic MRI-Derived Numerical Breast Phantoms.
IEEE Trans Biomed Eng. 2019 Sep;66(9):2566-2575. doi: 10.1109/TBME.2019.2892303. Epub 2019 Jan 10.
10
Toward Electrical Impedance Tomography Coupled Ultrasound Imaging for Assessing Muscle Health.
IEEE Trans Med Imaging. 2019 Jun;38(6):1409-1419. doi: 10.1109/TMI.2018.2886152. Epub 2018 Dec 10.

本文引用的文献

4
Surface wave multipath signals in near-field microwave imaging.
Int J Biomed Imaging. 2012;2012:697253. doi: 10.1155/2012/697253. Epub 2012 Apr 10.
5
Fast 3-d tomographic microwave imaging for breast cancer detection.
IEEE Trans Med Imaging. 2012 Aug;31(8):1584-92. doi: 10.1109/TMI.2012.2197218. Epub 2012 May 2.
7
Comparison of no-prior and soft-prior regularization in biomedical microwave imaging.
J Med Phys. 2011 Jul;36(3):159-70. doi: 10.4103/0971-6203.83482.
8
Dielectric characterization of PCL-based thermoplastic materials for microwave diagnostic and therapeutic applications.
IEEE Trans Biomed Eng. 2012 Mar;59(3):627-33. doi: 10.1109/TBME.2011.2157918. Epub 2011 May 27.
10
Importance of phase unwrapping for the reconstruction of microwave tomographic images.
Biomed Opt Express. 2011 Jan 12;2(2):315-30. doi: 10.1364/BOE.1.000315.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验