Skip to main content
Top
Published in: Molecular Imaging and Biology 4/2023

27-03-2023 | Research Article

Improved Quantitative Analysis Method for Magnetic Particle Imaging Based on Deblurring and Region Scalable Fitting

Authors: Lu Wang, Yan Huang, Yishen Zhao, Jie Tian, Lu Zhang, Yang Du

Published in: Molecular Imaging and Biology | Issue 4/2023

Login to get access

Abstract   

Purpose

Magnetic particle imaging (MPI) is a technique for imaging magnetic particle concentration distribution. It has the advantages of high sensitivity, no signal attenuation with depth, and no ionizing radiation. Although MPI has been widely used in the biomedical field, accurate image analysis has been challenging due to its anisotropic point spread function (PSF). The purpose of this study is to propose an MPI image restoring and segmentation method to facilitate a more precise quantitative evaluation of the magnetic particle imaging in vivo.

Procedures

We proposed a DeRSF method that combined deblurring and region scalable fitting (RSF) to determine the imaging tracer distribution. Then a uniform erosion and scaling criterion was established based on simulation experiments to correct the segmentation results, which was further validated on phantom imaging. Finally, we imaged the MPI tracer at gradient concentrations to establish the calibration curve between the MPI signal and iron mass for iron quantification in phantom and in vivo imaging.

Results

The phantom imaging experiments showed that our method achieved improved segmentation performance. The mean value of the dice coefficients for segmentation was up to 0.86, demonstrating that our method can accurately map and quantify the distribution of the tracer. Moreover, the iron quantification on both phantom and in vivo mouse imaging was realized with the minimal error of 5.50%, by our established calibration curve.

Conclusions

Our proposed DeRSF method was successfully used for improved MPI quantitative analysis. More importantly, this method also showed accurate quantitative results on images with different shapes and tracer concentrations in both phantom and in vivo data, which laid the foundation for the biomedical study of MPI.
Appendix
Available only for authorised users
Literature
1.
go back to reference Gleich B, Weizenecker J (2005) Tomographic imaging using the nonlinear response of magnetic particles. Nature 7046:1214–1217CrossRef Gleich B, Weizenecker J (2005) Tomographic imaging using the nonlinear response of magnetic particles. Nature 7046:1214–1217CrossRef
2.
go back to reference Goodwill PW, Saritas EU, Croft LR et al (2012) X-space MPI: magnetic nanoparticles for safe medical imaging. Adv Mater 28:3870–3877CrossRef Goodwill PW, Saritas EU, Croft LR et al (2012) X-space MPI: magnetic nanoparticles for safe medical imaging. Adv Mater 28:3870–3877CrossRef
3.
go back to reference Knopp T, Sattel TF, Biederer S et al (2010) Model-based reconstruction for magnetic particle imaging. IEEE Trans Med Imaging 1:12–18CrossRef Knopp T, Sattel TF, Biederer S et al (2010) Model-based reconstruction for magnetic particle imaging. IEEE Trans Med Imaging 1:12–18CrossRef
4.
go back to reference Vogel P, Lother S, Rückert MA et al (2014) MRI meets MPI: a bimodal MPI-MRI tomograph. IEEE Trans Med Imaging 10:1954–1959CrossRef Vogel P, Lother S, Rückert MA et al (2014) MRI meets MPI: a bimodal MPI-MRI tomograph. IEEE Trans Med Imaging 10:1954–1959CrossRef
5.
go back to reference Goodwill PW, Conolly SM (2010) The formulation of the magnetic particle imaging process: 1-D signal, resolution, bandwidth, SNR, SAR, and magnetostimulation. IEEE Trans Med Imaging 11:1851–1859CrossRef Goodwill PW, Conolly SM (2010) The formulation of the magnetic particle imaging process: 1-D signal, resolution, bandwidth, SNR, SAR, and magnetostimulation. IEEE Trans Med Imaging 11:1851–1859CrossRef
6.
go back to reference Konkle JJ, Goodwill PW, Carrasco-Zevallos OM, Conolly SM (2013) Projection reconstruction magnetic particle imaging. IEEE Trans Med Imaging 2:338–347CrossRef Konkle JJ, Goodwill PW, Carrasco-Zevallos OM, Conolly SM (2013) Projection reconstruction magnetic particle imaging. IEEE Trans Med Imaging 2:338–347CrossRef
7.
go back to reference Knopp T, Weber A (2013) Sparse reconstruction of the magnetic particle imaging system matrix. IEEE Trans Med Imaging 8:1473–1480CrossRef Knopp T, Weber A (2013) Sparse reconstruction of the magnetic particle imaging system matrix. IEEE Trans Med Imaging 8:1473–1480CrossRef
8.
go back to reference Yin L, Li W, Du Y et al (2022) Recent developments of the reconstruction in magnetic particle imaging. Vis Comput Ind Biomed Art 1:24CrossRef Yin L, Li W, Du Y et al (2022) Recent developments of the reconstruction in magnetic particle imaging. Vis Comput Ind Biomed Art 1:24CrossRef
9.
go back to reference Parkins KM, Melo KP, Chen Y, Ronald JA, Foster PJ (2021) Visualizing tumor self-homing with magnetic particle imaging. Nanoscale 12:6016–6023CrossRef Parkins KM, Melo KP, Chen Y, Ronald JA, Foster PJ (2021) Visualizing tumor self-homing with magnetic particle imaging. Nanoscale 12:6016–6023CrossRef
10.
go back to reference Wang G, Li W, Shi G et al (2022) Sensitive and specific detection of breast cancer lymph node metastasis through dual-modality magnetic particle imaging and fluorescence molecular imaging: a preclinical evaluation. Eur J Nucl Med Mol Imaging 8:2723–2734CrossRef Wang G, Li W, Shi G et al (2022) Sensitive and specific detection of breast cancer lymph node metastasis through dual-modality magnetic particle imaging and fluorescence molecular imaging: a preclinical evaluation. Eur J Nucl Med Mol Imaging 8:2723–2734CrossRef
11.
go back to reference Zhang W, Liang X, Zhu L et al (2022) Optical magnetic multimodality imaging of plectin-1-targeted imaging agent for the precise detection of orthotopic pancreatic ductal adenocarcinoma in mice. EBioMedicine 80:104040CrossRefPubMedPubMedCentral Zhang W, Liang X, Zhu L et al (2022) Optical magnetic multimodality imaging of plectin-1-targeted imaging agent for the precise detection of orthotopic pancreatic ductal adenocarcinoma in mice. EBioMedicine 80:104040CrossRefPubMedPubMedCentral
12.
go back to reference Jiang Z, Han X, Du Y et al (2021) Mixed metal metal-organic frameworks derived carbon supporting ZnFe2O4/C for high-performance magnetic particle imaging. Nano Lett 7:2730–2737CrossRef Jiang Z, Han X, Du Y et al (2021) Mixed metal metal-organic frameworks derived carbon supporting ZnFe2O4/C for high-performance magnetic particle imaging. Nano Lett 7:2730–2737CrossRef
13.
go back to reference Du Y, Liu X, Liang Q, Liang X, Tian J (2019) Optimization and design of magnetic ferrite nanoparticles with uniform tumor distribution for highly sensitive MRI/MPI performance and improved magnetic hyperthermia therapy. Nano Lett 6:3618–3626CrossRef Du Y, Liu X, Liang Q, Liang X, Tian J (2019) Optimization and design of magnetic ferrite nanoparticles with uniform tumor distribution for highly sensitive MRI/MPI performance and improved magnetic hyperthermia therapy. Nano Lett 6:3618–3626CrossRef
14.
go back to reference Hayat H, Sun A, Hayat H et al (2021) Artificial intelligence analysis of magnetic particle imaging for islet transplantation in a mouse model. Mol Imaging Biol 1:18–29CrossRef Hayat H, Sun A, Hayat H et al (2021) Artificial intelligence analysis of magnetic particle imaging for islet transplantation in a mouse model. Mol Imaging Biol 1:18–29CrossRef
15.
go back to reference Sun A, Hayat H, Liu S et al (2021) 3D in vivo magnetic particle imaging of human stem cell-derived islet organoid transplantation using a machine learning algorithm. Front Cell Dev Biol 9:704483CrossRefPubMedPubMedCentral Sun A, Hayat H, Liu S et al (2021) 3D in vivo magnetic particle imaging of human stem cell-derived islet organoid transplantation using a machine learning algorithm. Front Cell Dev Biol 9:704483CrossRefPubMedPubMedCentral
16.
go back to reference Shen YS, Hu CE, Zhang P, Tian J, Hui H (2022) A novel software framework for magnetic particle imaging reconstruction. Int J Imaging Syst Tech 4:1119–1132CrossRef Shen YS, Hu CE, Zhang P, Tian J, Hui H (2022) A novel software framework for magnetic particle imaging reconstruction. Int J Imaging Syst Tech 4:1119–1132CrossRef
17.
go back to reference Liu S, Chiu-Lam A, Rivera-Rodriguez A et al (2021) Long circulating tracer tailored for magnetic particle imaging. Nanotheranostics 3:348–361CrossRef Liu S, Chiu-Lam A, Rivera-Rodriguez A et al (2021) Long circulating tracer tailored for magnetic particle imaging. Nanotheranostics 3:348–361CrossRef
18.
go back to reference Lu K, Goodwill P, Zheng B, Conolly S (2018) Multi-channel acquisition for isotropic resolution in magnetic particle imaging. IEEE Trans Med Imaging 9:1989–1998CrossRef Lu K, Goodwill P, Zheng B, Conolly S (2018) Multi-channel acquisition for isotropic resolution in magnetic particle imaging. IEEE Trans Med Imaging 9:1989–1998CrossRef
19.
go back to reference Chan T, Wong C (1998) Total variation blind deconvolution. IEEE Trans Image Process 3:370–375CrossRef Chan T, Wong C (1998) Total variation blind deconvolution. IEEE Trans Image Process 3:370–375CrossRef
20.
go back to reference Wen F, Ying R, Liu Y, Tk T (2020) A simple local minimal intensity prior and an improved algorithm for blind image deblurring. IEEE Trans Circuits Syst Video Technol 99:1–1 Wen F, Ying R, Liu Y, Tk T (2020) A simple local minimal intensity prior and an improved algorithm for blind image deblurring. IEEE Trans Circuits Syst Video Technol 99:1–1
21.
go back to reference Pan J, Sun D, Pfister H, Yang M-H (2016) Blind image deblurring using dark channel prior [abstract]. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition. CVPR, Las Vegas, Nevada, pp 1628–1636 Pan J, Sun D, Pfister H, Yang M-H (2016) Blind image deblurring using dark channel prior [abstract]. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition. CVPR, Las Vegas, Nevada, pp 1628–1636
22.
go back to reference Oh K, Shin CS, Kim J, Yoo SK (2019) Level-set segmentation-based respiratory volume estimation using a depth camera. IEEE J Biomed Health Inform 4:1674–1682CrossRef Oh K, Shin CS, Kim J, Yoo SK (2019) Level-set segmentation-based respiratory volume estimation using a depth camera. IEEE J Biomed Health Inform 4:1674–1682CrossRef
23.
go back to reference Ma J, Nie Z, Wang C et al (2020) Active contour regularized semi-supervised learning for COVID-19 CT infection segmentation with limited annotations. Phys Med Biol 22:225034CrossRef Ma J, Nie Z, Wang C et al (2020) Active contour regularized semi-supervised learning for COVID-19 CT infection segmentation with limited annotations. Phys Med Biol 22:225034CrossRef
24.
go back to reference Li C, Kao C, Gore JC, Ding Z (2008) Minimization of region-scalable fitting energy for image segmentation. IEEE Trans Image Process 10:1940–1949 Li C, Kao C, Gore JC, Ding Z (2008) Minimization of region-scalable fitting energy for image segmentation. IEEE Trans Image Process 10:1940–1949
25.
go back to reference Sanchez-Salvador JL, Campano C, Lopez-Exposito P et al (2021) Enhanced morphological characterization of cellulose nano/microfibers through image skeleton analysis. Nanomaterials (Basel) 8:2077CrossRef Sanchez-Salvador JL, Campano C, Lopez-Exposito P et al (2021) Enhanced morphological characterization of cellulose nano/microfibers through image skeleton analysis. Nanomaterials (Basel) 8:2077CrossRef
26.
go back to reference Cheng H, Xue M, Shi X (2003) Contrast enhancement based on a novel homogeneity measurement. Pattern Recogn 11:2687–2697CrossRef Cheng H, Xue M, Shi X (2003) Contrast enhancement based on a novel homogeneity measurement. Pattern Recogn 11:2687–2697CrossRef
Metadata
Title
Improved Quantitative Analysis Method for Magnetic Particle Imaging Based on Deblurring and Region Scalable Fitting
Authors
Lu Wang
Yan Huang
Yishen Zhao
Jie Tian
Lu Zhang
Yang Du
Publication date
27-03-2023
Publisher
Springer International Publishing
Published in
Molecular Imaging and Biology / Issue 4/2023
Print ISSN: 1536-1632
Electronic ISSN: 1860-2002
DOI
https://doi.org/10.1007/s11307-023-01812-x

Other articles of this Issue 4/2023

Molecular Imaging and Biology 4/2023 Go to the issue