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Zhao W, Liu Q, Sun J, Pan W, Pylypenko D, Wang W. Evaluating the image quality and local tumor invasion of uterine cancer by MUSE DWI with RPG. Heliyon 2024; 10:e35440. [PMID: 39170139 PMCID: PMC11336590 DOI: 10.1016/j.heliyon.2024.e35440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 07/28/2024] [Accepted: 07/29/2024] [Indexed: 08/23/2024] Open
Abstract
Diffusion-weighted imaging (DWI) is widely utilized for evaluating uterine diseases. However, the prevalent technique, single-shot echo planar imaging (ssEPI), is hindered by notable image distortion and low spatial resolution. Therefore, optimizing uterine DWI sequences is vital for improving image quality. To investigate the efficacy of multiplexed sensitivity encoding (MUSE) combined with reverse polarity gradient (RPG) in enhancing uterine DWI quality and assessing local invasion in endometrial and cervical cancer, we included 149 patients. Each patient underwent DWI of the uterus using ssEPI, MUSE, and RPG-MUSE techniques. We compared these three sequences regarding image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), geometric distortion rate (GDR), ADC values, accuracy in determining the extent of cancer invasion, and the Area Under the Curve (AUC) for identifying endometrial cancer and benign endometrial lesions using ADC values. The results indicated that RPG-MUSE DWI had less artifacts than MUSE and ssEPI (P < 0.05). Lesions were more apparent in MUSE and RPG-MUSE sequences compared to ssEPI (P < 0.05), with RPG-MUSE providing clearer lesion edges (P < 0.05). Additionally, RPG-MUSE DWI demonstrated higher SNR and CNR than ssEPI and MUSE (P < 0.05), along with a lower GDR (P < 0.05). The ADC values did not show significant differences among the three sequences (P > 0.05). Furthermore, the AUC of the ROC for detecting endometrial cancer and benign endometrial lesions using ADC values showed no significant differences across the sequences (P = 0.7609, 0.7186, and 0.8706, respectively). When combining each DWI sequence with T2WI for FIGO staging, RPG-MUSE and MUSE exhibited better alignment with pathology findings compared to ssEPI (P < 0.05). Overall, RPG-MUSE DWI showed fewer artifacts, higher SNR and CNR, reduced geometric distortion, and clearer lesion visualization compared to ssEPI and MUSE, leading to a more precise assessment of endometrial and cervical cancer invasion extent.
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Affiliation(s)
- Wenjing Zhao
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | - Qing Liu
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | - Jining Sun
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | - Wenhui Pan
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
| | | | - Wenjuan Wang
- Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China
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Chen Z, Liao C, Cao X, Poser BA, Xu Z, Lo WC, Wen M, Cho J, Tian Q, Wang Y, Feng Y, Xia L, Chen W, Liu F, Bilgic B. 3D-EPI blip-up/down acquisition (BUDA) with CAIPI and joint Hankel structured low-rank reconstruction for rapid distortion-free high-resolution T 2 * mapping. Magn Reson Med 2023; 89:1961-1974. [PMID: 36705076 PMCID: PMC10072851 DOI: 10.1002/mrm.29578] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 01/28/2023]
Abstract
PURPOSE This work aims to develop a novel distortion-free 3D-EPI acquisition and image reconstruction technique for fast and robust, high-resolution, whole-brain imaging as well as quantitativeT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. METHODS 3D Blip-up and -down acquisition (3D-BUDA) sequence is designed for both single- and multi-echo 3D gradient recalled echo (GRE)-EPI imaging using multiple shots with blip-up and -down readouts to encode B0 field map information. Complementary k-space coverage is achieved using controlled aliasing in parallel imaging (CAIPI) sampling across the shots. For image reconstruction, an iterative hard-thresholding algorithm is employed to minimize the cost function that combines field map information informed parallel imaging with the structured low-rank constraint for multi-shot 3D-BUDA data. Extending 3D-BUDA to multi-echo imaging permitsT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. For this, we propose constructing a joint Hankel matrix along both echo and shot dimensions to improve the reconstruction. RESULTS Experimental results on in vivo multi-echo data demonstrate that, by performing joint reconstruction along with both echo and shot dimensions, reconstruction accuracy is improved compared to standard 3D-BUDA reconstruction. CAIPI sampling is further shown to enhance image quality. ForT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping, parameter values from 3D-Joint-CAIPI-BUDA and reference multi-echo GRE are within limits of agreement as quantified by Bland-Altman analysis. CONCLUSIONS The proposed technique enables rapid 3D distortion-free high-resolution imaging andT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. Specifically, 3D-BUDA enables 1-mm isotropic whole-brain imaging in 22 s at 3T and 9 s on a 7T scanner. The combination of multi-echo 3D-BUDA with CAIPI acquisition and joint reconstruction enables distortion-free whole-brainT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping in 47 s at 1.1 × 1.1 × 1.0 mm3 resolution.
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Affiliation(s)
- Zhifeng Chen
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Charlestown, MA, USA
- Department of Data Science and AI, Faculty of IT, Monash University, Clayton, VIC, Australia
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Benedikt A. Poser
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, University of Maastricht, the Netherlands
| | - Zhongbiao Xu
- Department of Radiotherapy, Cancer Center, Guangdong Provincial People’s Hospital & Guangdong Academy of Medical Science, Guangzhou, China
| | | | - Manyi Wen
- Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong, China
| | - Jaejin Cho
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Charlestown, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Charlestown, MA, USA
| | - Yaohui Wang
- Division of Superconducting Magnet Science and Technology, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Ling Xia
- Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China
| | - Wufan Chen
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Feng Liu
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Charlestown, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
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Bai Y, Pei Y, Liu WV, Liu W, Xie S, Wang X, Zhong L, Chen J, Zhang L, Masokano IB, Li W. MRI: Evaluating the Application of FOCUS-MUSE Diffusion-Weighted Imaging in the Pancreas in Comparison With FOCUS, MUSE, and Single-Shot DWIs. J Magn Reson Imaging 2023; 57:1156-1171. [PMID: 36053895 DOI: 10.1002/jmri.28382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Diffusion-weighted imaging (DWI) is a useful technique to detect pancreatic lesion. In DWIs, field-of-view optimized and constrained undistorted single-shot (FOCUS) can improve the spatial resolution and multiplexed sensitivity-encoding (MUSE) can gain a high signal-to-noise ratio (SNR). Based on the advantage of FOCUS and MUSE, a new DWI sequence-named FOCUS-MUSE DWI (FOCUS combined with MUSE)-was developed to delineate the pancreas. PURPOSE To investigate the reliability of FOCUS-MUSE DWI compared to FOCUS, MUSE and single-shot (SS) DWI via the systematical evaluation of the apparent diffusion coefficient (ADC) measurements, SNR and image quality. STUDY TYPE Prospective. SUBJECTS A total of 33 healthy volunteers and 9 patients with pancreatic lesion. FIELD STRENGTH/SEQUENCE A 3.0 T scanner. FOCUS-MUSE DWI, FOCUS DWI, MUSE DWI, SS DWI. ASSESSMENT For volunteers, ADC and SNR were measured by two readers in the pancreatic head, body, and tail. For all subjects, the diagnostic image quality score was assessed by three other readers on above four DWIs. STATISTICAL TESTS Paired-sample T-test, intraclass correlation (ICC), Bland-Altman method, Friedman test, Dunn-Bonferroni post hoc test and kappa coefficient. A significance level of 0.05 was used. RESULTS FOCUS-MUSE DWI had the best intersession repeatability of ADC measurements (head: 59.53, body: 101.64, tail: 42.30) among the four DWIs, and also maintained the significantly highest SNR (reader 1 [head: 19.68 ± 3.23, body: 23.42 ± 5.00, tail: 28.85 ± 4.96], reader 2 [head: 19.93 ± 3.52, body: 23.02 ± 5.69, tail: 29.77 ± 6.33]) except for MUSE DWI. Furthermore, it significantly achieved better image quality in volunteers (median value: 4 score) and 9 patients (most in 4 score). DATA CONCLUSION FOCUS-MUSE DWI improved the reliability of pancreatic images with the most stable ADC measurement, best image quality score and sufficient SNR among four DWIs. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yu Bai
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Yigang Pei
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | | | - Wenguang Liu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Simin Xie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Xiao Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Linhui Zhong
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Juan Chen
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Lijuan Zhang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Ismail Bilal Masokano
- Radiology Department, the Xiangya Third Hospital, Central South University, Changsha, Hunan, China
| | - Wenzheng Li
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
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Liu Q, Xu Z, Zhao K, Hoge WS, Zhang X, Mei Y, Lu Q, Niendorf T, Feng Y. Diffusion-weighted magnetic resonance imaging in rat kidney using two-dimensional navigated, interleaved echo-planar imaging at 7.0 T. NMR IN BIOMEDICINE 2022; 35:e4652. [PMID: 34820933 DOI: 10.1002/nbm.4652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 10/29/2021] [Accepted: 10/30/2021] [Indexed: 06/13/2023]
Abstract
The purpose of this study was to investigate the feasibility of two-dimensional (2D) navigated, interleaved multishot echo-planar imaging (EPI) to enhance kidney diffusion-weighted imaging (DWI) in rats at 7.0 T. Fully sampled interleaved four-shot EPI with 2D navigators was tailored for kidney DWI (Sprague-Dawley rats, n = 7) on a 7.0-T small bore preclinical scanner. The image quality of four-shot EPI was compared with T2 -weighted rapid acquisition with relaxation enhancement (RARE) (reference) and single-shot EPI (ss-EPI) without and with parallel imaging (PI). The contrast-to-noise ratio (CNR) was examined to assess the image quality for the EPI approaches. The Dice similarity coefficient and the Hausdorff distance were used for evaluation of image distortion. Mean diffusivity (MD) and fractional anisotropy (FA) were calculated for renal cortex and medulla for all DWI approaches. The corticomedullary difference of MD and FA were assessed by Wilcoxon signed-rank test. Four-shot EPI showed the highest CNR among the three EPI variants and lowest geometric distortion versus T2 -weighted RARE (mean Dice: 0.77 for ss-EPI without PI, 0.88 for ss-EPI with twofold undersampling, and 0.92 for four-shot EPI). The FA map derived from four-shot EPI clearly identified a highly anisotropic region corresponding to the inner stripe of the outer medulla. Four-shot EPI successfully discerned differences in both MD and FA between renal cortex and medulla. In conclusion, 2D navigated, interleaved multishot EPI facilitates high-quality rat kidney DWI with clearly depicted intralayer and interlayer structure and substantially reduced image distortion. This approach enables the anatomic integrity of DWI-MRI in small rodents and has the potential to benefit the characterization of renal microstructure in preclinical studies.
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Affiliation(s)
- Qiang Liu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Zhongbiao Xu
- Department of Radiation Oncology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Kaixuan Zhao
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - W Scott Hoge
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Xinyuan Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Yingjie Mei
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Qiqi Lu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
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