Share:
Share this content in WeChat
X
Technical Article
Effect of compressed sensing on the imaging of breast T1 high resolution isotropic volume excitation sequence and its sequence optimization
NING Ning  LIANG Hongbing  ZHANG Lina  ZHANG Nan  TIAN Jiahe  SONG Qingwei  WU Qi  WANG Zhuo  LI Yuanfei  ZHAO Siqi  YANG Jie 

Cite this article as: NING N, LIANG H B, ZHANG L N, et al. Effect of compressed sensing on the imaging of breast T1 high resolution isotropic volume excitation sequence and its sequence optimization[J]. Chin J Magn Reson Imaging, 2023, 14(10): 116-121, 131. DOI:10.12015/issn.1674-8034.2023.10.020.


[Abstract] Objective To investigate the impact of compressed sensing (CS) technology on breast enhanced-T1 high resolution isotropic volume excitation imaging quality and scan time, and to optimize isotropic e-THRIVE sequence.Materials and Methods A total of 43 patients isotropic DCE-MRI examination in our hospital were prospectively included, which type of time signal intensity curve of tumor was platform type. On the basis of T1 high resolution isotropic volume excitation (e-THRIVE), different acceleration factors (AF) [sensitivity encoding (SENSE) AF=4, CS AF=4, CS AF=5, CS AF=6, CS AF=7] were used with 3.0 T MRI equipment. The sequence optimization was carried out on the delayed e-THRIVE sequence. Subjective evaluation and objective measurements of the images were performed by two observers. The image signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and relative contrast (RC) were calculated. Friedman test were used to analyze the SNR, CNR, RC and subjective scores of images between different groups. P<0.05 was that the difference was statistically significant, if the difference was statistically significant, follow-up multiple comparison.Results The objective and subjective scores were consistent between the two observers, and there were significant differences in SNRfibroglandular, CNRfibroglandular, SNRlesion, CNRlesion and subjective scores among different AF (P<0.05). There were no significant differences in RCfibroglandulars-to-lesion, RClesion-to-muscle and RCfibroglandulars-to-muscle among different AF (P>0.05). The results of pairwise comparison showed that SNRfibroglandulars, CNRfibroglandulars, SNRlesion, CNRlesion and subjective scores of sense AF=4, CS AF=4 and CS AF=5 images were higher than those of CS AF=6 and CS AF=7 images (P<0.05).Conclusions During clinical practice, in consideration scanning time and image quality, the CS AF=5 is recommended for breast e-THRIVE sequence, which saves 26.7% of scanning time compared with conventional parallel acquisition.
[Keywords] breast;breast cancer;breast fibroadenoma;dynamic contrast enhanced;compressed sensing;signal to noise ratio;contrast to noise ratio;magnetic resonance imaging

NING Ning1   LIANG Hongbing1   ZHANG Lina1*   ZHANG Nan2   TIAN Jiahe3   SONG Qingwei1   WU Qi1   WANG Zhuo1   LI Yuanfei1   ZHAO Siqi1   YANG Jie4  

1 Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian 116011, China

2 Department of Radiology, Zhongshan Hospital of Fudan University, Shanghai 200032, China

3 Zhongshan College, Dalian Medical University, Dalian 116085, China

4 School of Public Health, Dalian Medical University, Dalian 116044, China

Corresponding author: ZHANG L N, E-mail: zln201045@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS 2022 Teaching Reform of Continuing Education of Liaoning Adult Education Society (No. LCYJGZXYB22100); University-Level Teaching Reform Research General Project of Dalian Medical University (No. DYLX21036); 2022 General Project of "Peak Climbing Plan" of Dalian city key specialty of medicine (No. 2022DF042).
Received  2023-02-11
Accepted  2023-09-14
DOI: 10.12015/issn.1674-8034.2023.10.020
Cite this article as: NING N, LIANG H B, ZHANG L N, et al. Effect of compressed sensing on the imaging of breast T1 high resolution isotropic volume excitation sequence and its sequence optimization[J]. Chin J Magn Reson Imaging, 2023, 14(10): 116-121, 131. DOI:10.12015/issn.1674-8034.2023.10.020.

[1]
SUNG H, FERLAY J, SIEGEL R L, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
[2]
WANG X R, WANG C, GUAN J H, et al. Progress of Breast Cancer basic research in China[J]. Int J Biol Sci, 2021, 17(8): 2069-2079. DOI: 10.7150/ijbs.60631.
[3]
MANN R M, CHO N, MOY L. Breast MRI: state of the art[J]. Radiology, 2019, 292(3): 520-536. DOI: 10.1148/radiol.2019182947.
[4]
COMSTOCK C E, GATSONIS C, NEWSTEAD G M, et al. Comparison of abbreviated breast MRI vs digital breast tomosynthesis for breast cancer detection among women with dense breasts undergoing screening[J]. JAMA, 2020, 323(8): 746-756. DOI: 10.1001/jama.2020.0572.
[5]
KANG S R, KIM H W, KIM H S. Evaluating the relationship between dynamic contrast-enhanced MRI (DCE-MRI) parameters and pathological characteristics in breast cancer[J]. J Magn Reson Imaging, 2020, 52(5): 1360-1373. DOI: 10.1002/jmri.27241.
[6]
CHENG Q, HUANG J, LIANG J, et al. The Diagnostic Performance of DCE-MRI in Evaluating the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer: A Meta-Analysis[J/OL]. Front Oncol, 2020, 10: 93 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/32117747/. DOI: 10.3389/fonc.2020.00093.
[7]
BOYARKO A C, DILLMAN J R, TKACH J A, et al. Comparison of compressed SENSE and SENSE for quantitative liver MRI in children and young adults[J]. Abdom Radiol (NY), 2021, 46(10): 4567-4575. DOI: 10.1007/s00261-021-03092-x.
[8]
IKEDA H, OHNO Y, MURAYAMA K, et al. Compressed sensing and parallel imaging accelerated T2 FSE sequence for head and neck MR imaging: Comparison of its utility in routine clinical practice[J/OL]. Eur J Radiol, 2021, 135: 109501 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/33395594/. DOI: 10.1016/j.ejrad.2020.109501.
[9]
LACHNER S, UTZSCHNEIDER M, ZARIC O, et al. Compressed sensing and the use of phased array coils in 23Na MRI: a comparison of a SENSE-based and an individually combined multi-channel reconstruction[J]. Z Med Phys, 2021, 31(1): 48-57. DOI: 10.1016/j.zemedi.2020.10.003.
[10]
DELATTRE B M A, BOUDABBOUS S, HANSEN C, et al. Compressed sensing MRI of different organs: ready for clinical daily practice?[J]. Eur Radiol, 2020, 30(1): 308-319. DOI: 10.1007/s00330-019-06319-0.
[11]
YARACH U, SAEKHO S, SETSOMPOP K, et al. Feasibility of accelerated 3D T1-weighted MRI using compressed sensing: application to quantitative volume measurements of human brain structures[J]. MAGMA, 2021, 34(6): 915-927. DOI: 10.1007/s10334-021-00939-8.
[12]
PAN K, LIU Q Q, TANG L L, et al. Study on acceleration efficiency and image quality of artificial intelligence compressed sensing and compressed sensing in knee MRI[J]. Chin J Magn Reson Imag, 2022, 13(5): 94-98. DOI: 10.12015/issn.1674-8034.2022.05.017.
[13]
LIN L, LI Y, WANG J, et al. Free-breathing cardiac cine MRI with compressed sensing real-time imaging and retrospective motion correction: clinical feasibility and validation[J/OL]. Eur Radiol, 2022 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/36357691/. DOI: 10.1007/s00330-022-09210-7.
[14]
YOSHIMARU D, ARAKI Y, MATSUDA C, et al. Evaluation of liver tumor identification rate of volumetric-interpolated breath-hold images using the compressed sensing method and qualitative evaluation of tumor contrast effect via visual evaluation[J]. Quant Imaging Med Surg, 2022, 12(5): 2649-2657. DOI: 10.21037/qims-21-850.
[15]
UEDA T, OHNO Y, YAMAMOTO K, et al. Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice[J/OL]. Eur J Radiol, 2021, 134: 109430 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/33276249/. DOI: 10.1016/j.ejrad.2020.109430.
[16]
ONISHI N, KATAOKA M, KANAO S, et al. Ultrafast dynamic contrast-enhanced MRI of the breast using compressed sensing: breast cancer diagnosis based on separate visualization of breast arteries and veins[J]. J Magn Reson Imaging, 2018, 47(1): 97-104. DOI: 10.1002/jmri.25747.
[17]
VREEMANN S, RODRIGUEZ-RUIZ A, NICKEL D, et al. Compressed sensing for breast MRI: resolving the trade-off between spatial and temporal resolution[J]. Invest Radiol, 2017, 52(10): 574-582. DOI: 10.1097/RLI.0000000000000384.
[18]
HONDA M, KATAOKA M, ONISHI N, et al. New parameters of ultrafast dynamic contrast-enhanced breast MRI using compressed sensing[J]. J Magn Reson Imaging, 2020, 51(1): 164-174. DOI: 10.1002/jmri.26838.
[19]
WU X Y, ZHAN S H, GONG Z G, et al. Comparison study between united compressed sensing and parallel imaging in breast MRI[J]. Chin Imag J Integr Tradit West Med, 2020, 18(4): 387-390. DOI: 10.3969/j.issn.1672-0512.2020.04.017.
[20]
LI H, SUN H, LIU S Q, et al. Assessing the performance of benign and malignant breast lesion classification with bilateral TIC differentiation and other effective features in DCE-MRI[J]. J Magn Reson Imaging, 2019, 50(2): 465-473. DOI: 10.1002/jmri.26646.
[21]
LIN T T, DONG J N, DENG K X, et al. Comparison study of the imaging quality of SE-EPI-DWI and STIR-DWI in breast lesions[J]. Acta Univ Med Anhui, 2017, 52(8): 1188-1191. DOI: 10.19405/j.cnki.issn1000-1492.2017.08.019.
[22]
LIANG X, CHEN X, YANG Z, et al. Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer[J/OL]. BMC Cancer, 2022, 22(1): 1250 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/36460972/. DOI: 10.1186/s12885-022-10315-x.
[23]
TANG W J, KONG Q C, CHENG Z X, et al. Performance of radiomics models for tumour-infiltrating lymphocyte (TIL) prediction in breast cancer: the role of the dynamic contrast-enhanced (DCE) MRI phase[J]. Eur Radiol, 2022, 32(2): 864-875. DOI: 10.1007/s00330-021-08173-5.
[24]
PÖTSCH N, VATTERONI G, CLAUSER P, et al. Contrast-enhanced mammography versus contrast-enhanced breast MRI: a systematic review and meta-analysis[J]. Radiology, 2022, 305(1): 94-103. DOI: 10.1148/radiol.212530.
[25]
WANG S, SUN K, WANG L, et al. Breast Tumor Segmentation in DCE-MRI With Tumor Sensitive Synthesis[J/OL]. IEEE Trans Neural Netw Learn Syst, 2021, PP [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/34874872/. DOI: 10.1109/tnnls.2021.3129781.
[26]
ZHANG J, LI L, ZHE X, et al. The Diagnostic Performance of Machine Learning-Based Radiomics of DCE-MRI in Predicting Axillary Lymph Node Metastasis in Breast Cancer: A Meta-Analysis[J/OL]. Front Oncol, 2022, 12: 799209 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/35186739/. DOI: 10.3389/fonc.2022.799209.
[27]
LEITHNER D, MOY L, MORRIS E A, et al. Abbreviated MRI of the Breast: Does It Provide Value?[J/OL]. J Magn Reson Imaging, 2019, 49(7): e85-e100 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/30194749/. DOI: 10.1002/jmri.26291.
[28]
ZHOU W, JIAN W, CEN X, et al. Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Contrast-Enhanced MR and 3D Convolutional Neural Networks[J/OL]. Front Oncol, 2021, 11: 588010 [2023-02-14]. https://pubmed.ncbi.nlm.nih.gov/33854959/. DOI: 10.3389/fonc.2021.588010.
[29]
LIU Y, HOU J, ZHU Z, et al. Assessment of breast arteries and lymph nodes by 3D MR angiography enhancement imaging: feasibility and pilot clinical results [J/OL]. BMC Med Imaging, 2021, 21(1): 97 [2023-02-14]. https://pubmed.ncbi.nlm.nih.gov/34098896/. DOI: 10.1186/s12880-021-00629-w.
[30]
FENG L, BENKERT T, BLOCK K T, et al. Compressed sensing for body MRI[J]. J Magn Reson Imaging, 2017, 45(4): 966-987. DOI: 10.1002/jmri.25547.
[31]
JASPAN O N, FLEYSHER R, LIPTON M L. Compressed sensing MRI: a review of the clinical literature[J/OL]. Br J Radiol, 2015, 88(1056): 20150487 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/26402216/. DOI: 10.1259/bjr.20150487.
[32]
SARTORETTI E, SARTORETTI T, BINKERT C, et al. Reduction of procedure times in routine clinical practice with Compressed SENSE magnetic resonance imaging technique[J/OL]. PLoS One, 2019, 14(4): e0214887 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/30978232/. DOI: 10.1371/journal.pone.0214887.
[33]
KIM J J, KIM J Y, HWANGBO L, et al. Ultrafast dynamic contrast-enhanced MRI using compressed sensing: associations of early kinetic parameters with prognostic factors of breast cancer[J]. AJR Am J Roentgenol, 2021, 217(1): 56-63. DOI: 10.2214/AJR.20.23457.
[34]
DIETRICH O, RAYA J G, REEDER S B, et al. Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters[J]. J Magn Reson Imaging, 2007, 26(2): 375-385. DOI: 10.1002/jmri.20969.
[35]
YOON J K, KIM M J, LEE S. Compressed sensing and parallel imaging for double hepatic arterial phase acquisition in gadoxetate-enhanced dynamic liver magnetic resonance imaging[J]. Invest Radiol, 2019, 54(6): 374-382. DOI: 10.1097/RLI.0000000000000548.
[36]
MEISTER R L, GROTH M, JÜRGENS J H W, et al. Compressed SENSE in pediatric brain tumor MR imaging: assessment of image quality, examination time and energy release[J]. Clin Neuroradiol, 2022, 32(3): 725-733. DOI: 10.1007/s00062-021-01112-3.
[37]
SUN W, WANG W, ZHU K, et al. Feasibility of compressed sensing technique for isotropic dynamic contrast-enhanced liver magnetic resonance imaging[J/OL]. Eur J Radiol, 2021, 139: 109729 [2023-02-06]. https://pubmed.ncbi.nlm.nih.gov/33905976/. DOI: 10.1016/j.ejrad.2021.109729.

PREV Application value of intelligent quick magnetic resonance technique in magnetic resonance scanning of cervical vertebra
NEXT Imaging features of sarcomatoid carcinoma in the paranasal sinus: One case report
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn