Share：
Share this content in WeChat
X
[Chinese][PDF]1781
• Review •
Advances in the application of ultrashort echo time sequence pulmonary function imaging
ZHAO Xiuquan  CUI Lei 

Cite this article as: ZHAO X Q, CUI L. Advances in the application of ultrashort echo time sequence pulmonary function imaging[J]. Chin J Magn Reson Imaging, 2025, 16(1): 204-209. DOI:10.12015/issn.1674-8034.2025.01.033.


[Abstract] In recent years, ultra-short echo time (UTE) sequences have addressed a prior deficiency and have been progressively utilised in evaluating lung parenchyma structure, rendering them appropriate for longitudinal monitoring of morphological alterations in lung disorders in neonates and children. A significant benefit of MRI is its capability for functional imaging. Quantitative functional assessments can be conducted by integrating UTE sequences with pulmonary function MRI, which encompasses hyperpolarised gas, perfusion, and oxygen-enhanced imaging. Utilising intrinsic registration pictures to exhibit lung function following bronchiectasis, mucus obstruction, fibrosis, and air entrapment may enhance the diagnosis and prognosis of restrictive and obstructive pulmonary disorders. This article provides a comprehensive review of the advancements in lung structure and function imaging utilizing UTE sequences, elucidating the technical principles and benefits of these sequences, with the objective of serving as a reference for future investigations into the application of UTE sequences in pulmonary diseases.
[Keywords] pulmonary functional imaging；lung magnetic resonance imaging；ultrashort echo-time；cystic fibrosis；bronchopulmonary dysplasia

ZHAO Xiuquan1   CUI Lei2*  

1 Medical College of Nantong University, Nantong 226001, China

2 Department of Radiology, the Second Affiliated Hospital of Nantong University, Nantong 226001, China

Corresponding author: CUI L, E-mail: cuigeleili@126.com

Conflicts of interest   None.

Received  2024-09-30
Accepted  2025-01-10
DOI: 10.12015/issn.1674-8034.2025.01.033
Cite this article as: ZHAO X Q, CUI L. Advances in the application of ultrashort echo time sequence pulmonary function imaging[J]. Chin J Magn Reson Imaging, 2025, 16(1): 204-209. DOI:10.12015/issn.1674-8034.2025.01.033.

[1]
SODHI K S, CIET P, VASANAWALA S, et al. Practical protocol for lung magnetic resonance imaging and common clinical indications[J]. Pediatr Radiol, 2022, 52(2): 295-311. DOI: 10.1007/s00247-021-05090-z.
[2]
TANAKA Y, OHNO Y, HANAMATSU S, et al. State-of-the-art MR imaging for thoracic diseases[J]. Magn Reson Med Sci, 2022, 21(1): 212-234. DOI: 10.2463/mrms.rev.2020-0184.
[3]
BIEDERER J. MR imaging of the airways[J/OL]. Br J Radiol, 2023, 96(1146): 20220630 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/36752590/. DOI: 10.1259/bjr.20220630.
[4]
TORRES L, KAMMERMAN J, HAHN A D, et al. "Structure-function imaging of lung disease using ultrashort echo time MRI"[J]. Acad Radiol, 2019, 26(3): 431-441. DOI: 10.1016/j.acra.2018.12.007.
[5]
WEIGER M, PRUESSMANN K P. Short-T2 MRI: principles and recent advances[J/OL]. Prog Nucl Magn Reson Spectrosc, 2019, 114/115: 237-270 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/31779882/. DOI: 10.1016/j.pnmrs.2019.07.001.
[6]
BAE K, JEON K N, HWANG M J, et al. Comparison of lung imaging using three-dimensional ultrashort echo time and zero echo time sequences: preliminary study[J]. Eur Radiol, 2019, 29(5): 2253-2262. DOI: 10.1007/s00330-018-5889-x.
[7]
LUSTIG M, PAULY J M. SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space[J]. Magn Reson Med, 2010, 64(2): 457-471. DOI: 10.1002/mrm.22428.
[8]
KLEIN S, STARING M, MURPHY K, et al. Elastix: a toolbox for intensity-based medical image registration[J]. IEEE Trans Med Imaging, 2010, 29(1): 196-205. DOI: 10.1109/TMI.2009.2035616.
[9]
HIGANO N S, FLECK R J, SPIELBERG D R, et al. Quantification of neonatal lung parenchymal density via ultrashort echo time MRI with comparison to CT[J]. J Magn Reson Imaging, 2017, 46(4): 992-1000. DOI: 10.1002/jmri.25643.
[10]
HEIDENREICH J F, WENG A M, METZ C, et al. Three-dimensional ultrashort echo time MRI for functional lung imaging in cystic fibrosis[J]. Radiology, 2020, 296(1): 191-199. DOI: 10.1148/radiol.2020192251.
[11]
STEWART N J, HIGANO N S, MUKTHAPURAM S, et al. Initial feasibility and challenges of hyperpolarized 129Xe MRI in neonates with bronchopulmonary dysplasia[J]. Magn Reson Med, 2023, 90(6): 2420-2431. DOI: 10.1002/mrm.29808.
[12]
WANG Z Y, HE M, BIER E, et al. Hyperpolarized129 Xe gas transfer MRI: the transition from 1.5T to 3T[J]. Magn Reson Med, 2018, 80(6): 2374-2383. DOI: 10.1002/mrm.27377.
[13]
QING K, ALTES T A, et al. Pulmonary MRI with hyperpolarized xenon-129 demonstrates novel alterations in gas transfer across the air-blood barrier in asthma[J]. Med Phys, 2024, 51(4): 2413-2423. DOI: 10.1002/mp.17009.
[14]
NOZAWA K, NIWA T, AIDA N. Imaging of cystic lung lesions in infants using pointwise encoding time reduction with radial acquisition (PETRA)[J]. Magn Reson Med Sci, 2019, 18(4): 299-300. DOI: 10.2463/mrms.bc.2018-0080.
[15]
XU P F, MEERSMANN T, WANG J, et al. Review of oxygen-enhanced lung mri: pulse sequences for image acquisition and T1 measurement[J]. Med Phys, 2023, 50(10): 5987-6007. DOI: 10.1002/mp.16553.
[16]
KRUGER S J, FAIN S B, JOHNSON K M, et al. Oxygen-enhanced 3D radial ultrashort echo time magnetic resonance imaging in the healthy human lung[J]. NMR Biomed, 2014, 27(12): 1535-1541. DOI: 10.1002/nbm.3158.
[17]
REPPLINGER M D, NAGLE S K, HARRINGA J B, et al. Clinical outcomes after magnetic resonance angiography (MRA) versus computed tomographic angiography (CTA) for pulmonary embolism evaluation[J]. Emerg Radiol, 2018, 25(5): 469-477. DOI: 10.1007/s10140-018-1609-8.
[18]
ROBBIE H, DACCORD C, CHUA F, et al. Evaluating disease severity in idiopathic pulmonary fibrosis[J/OL]. Eur Respir Rev, 2017, 26(145): 170051 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/28877976/. DOI: 10.1183/16000617.0051-2017.
[19]
BAUMAN G, JOHNSON K M, BELL L C, et al. Three-dimensional pulmonary perfusion MRI with radial ultrashort echo time and spatial-temporal constrained reconstruction[J]. Magn Reson Med, 2015, 73(2): 555-564. DOI: 10.1002/mrm.25158.
[20]
KNOBLOCH G, COLGAN T, SCHIEBLER M L, et al. Comparison of gadolinium-enhanced and ferumoxytol-enhanced conventional and UTE-MRA for the depiction of the pulmonary vasculature[J]. Magn Reson Med, 2019, 82(5): 1660-1670. DOI: 10.1002/mrm.27853.
[21]
JIANG W W, ONG F, JOHNSON K M, et al. Motion robust high resolution 3D free-breathing pulmonary MRI using dynamic 3D image self-Navigator[J]. Magn Reson Med, 2018, 79(6): 2954-2967. DOI: 10.1002/mrm.26958.
[22]
JOHNSON K M. Hybrid radial-cones trajectory for accelerated MRI[J]. Magn Reson Med, 2017, 77(3): 1068-1081. DOI: 10.1002/mrm.26188.
[23]
HIGANO N S, HAHN A D, TKACH J A, et al. Retrospective respiratory self-gating and removal of bulk motion in pulmonary UTE MRI of neonates and adults[J]. Magn Reson Med, 2017, 77(3): 1284-1295. DOI: 10.1002/mrm.26212.
[24]
TAN F, ZHU X C, CHAN M, et al. Motion-compensated low-rank reconstruction for simultaneous structural and functional UTE lung MRI[J]. Magn Reson Med, 2023, 90(3): 1101-1113. DOI: 10.1002/mrm.29703.
[25]
DING Z K, CHENG Z H, SHE H J, et al. Dynamic pulmonary MRI using motion-state weighted motion-compensation (MostMoCo) reconstruction with ultrashort TE: a structural and functional study[J]. Magn Reson Med, 2022, 88(1): 224-238. DOI: 10.1002/mrm.29204.
[26]
RAFEEQ M M, MURAD H A S. Cystic fibrosis: current therapeutic targets and future approaches[J/OL]. J Transl Med, 2017, 15(1): 84 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/28449677/. DOI: 10.1186/s12967-017-1193-9.
[27]
CASTELLANI C, ASSAEL B M. Cystic fibrosis: a clinical view[J]. Cell Mol Life Sci, 2017, 74(1): 129-140. DOI: 10.1007/s00018-016-2393-9.
[28]
SANCHEZ F, TYRRELL P N, CHEUNG P, et al. Detection of solid and subsolid pulmonary nodules with lung MRI: performance of UTE, T1 gradient-echo, and single-shotT2 fast spin echo[J/OL]. Cancer Imaging, 2023, 23(1): 17 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/36793094/. DOI: 10.1186/s40644-023-00531-4.
[29]
MARTIN C, GUZIOR D V, GONZALEZ C T, et al. Longitudinal microbial and molecular dynamics in the cystic fibrosis lung after Elexacaftor-Tezacaftor-Ivacaftor therapy[J/OL]. Respir Res, 2023, 24(1): 317 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/38104128/. DOI: 10.1186/s12931-023-02630-z.
[30]
DAVID M, BENLALA I, BUI S, et al. Longitudinal evaluation of bronchial changes in cystic fibrosis patients undergoing elexacaftor/tezacaftor/ivacaftor therapy using lung MRI with ultrashort echo-times[J]. J Magn Reson Imaging, 2024, 60(1): 116-124. DOI: 10.1002/jmri.29041.
[31]
HEIDENREICH J F, KUHL P J, GRUNZ J P, et al. Lung Function in Patients with Cystic Fibrosis before and during CFTR-Modulator Therapy Using 3D Ultrashort Echo Time MRI[J/OL]. Radiology, 2023, 308(1): e230084 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/37404154/. DOI: 10.1148/radiol.230084.
[32]
WILLMERING M M, ROACH D J, KRAMER E L, et al. Sensitive structural and functional measurements and 1-year pulmonary outcomes in pediatric cystic fibrosis[J]. J Cyst Fibros, 2021, 20(3): 533-539. DOI: 10.1016/j.jcf.2020.11.019.
[33]
SCHMIDT A R, RAMAMOORTHY C. Bronchopulmonary dysplasia[J]. Paediatr Anaesth, 2022, 32(2): 174-180. DOI: 10.1111/pan.14365.
[34]
YODER L M, HIGANO N S, SCHAPIRO A H, et al. Elevated lung volumes in neonates with bronchopulmonary dysplasia measured via MRI[J]. Pediatr Pulmonol, 2019, 54(8): 1311-1318. DOI: 10.1002/ppul.24378.
[35]
KATZ S L, PARRAGA G, LUU T M, et al. Pulmonary magnetic resonance imaging of ex-preterm children with and without bronchopulmonary dysplasia[J]. Ann Am Thorac Soc, 2022, 19(7): 1149-1157. DOI: 10.1513/AnnalsATS.202106-691OC.
[36]
YANG X Y, YU P X, SUN H S, et al. Assessment of lung deformation in patients with idiopathic pulmonary fibrosis with elastic registration technique on pulmonary three-dimensional ultrashort echo time MRI[J/OL]. Insights Imaging, 2024, 15(1): 17 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/38253739/. DOI: 10.1186/s13244-023-01555-x.
[37]
LANDINI N, ORLANDI M, CALISTRI L, et al. Advanced and traditional chest MRI sequence for the clinical assessment of systemic sclerosis related interstitial lung disease, compared to CT: disease extent analysis and correlations with pulmonary function tests[J/OL]. Eur J Radiol, 2024, 170: 111239 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/38056347/. DOI: 10.1016/j.ejrad.2023.111239.
[38]
LEE S, LEE H Y, PARK J, et al. Assessment of pulmonary ventilation using 3D ventilation flow capacity-weighted and ventilation-weighted maps from 3D ultrashort echo time (UTE) MRI[J]. J Magn Reson Imaging, 2024, 60(2): 483-494. DOI: 10.1002/jmri.29129.
[39]
ROACH D J, CRÉMILLIEUX Y, SERAI S D, et al. Morphological and quantitative evaluation of emphysema in chronic obstructive pulmonary disease patients: a comparative study of MRI with CT[J]. J Magn Reson Imaging, 2016, 44(6): 1656-1663. DOI: 10.1002/jmri.25309.
[40]
OHNO Y, TAKENAKA D, YOSHIKAWA T, et al. Efficacy of ultrashort echo time pulmonary MRI for lung nodule detection and lung-RADS classification[J]. Radiology, 2022, 302(3): 697-706. DOI: 10.1148/radiol.211254.
[41]
CHA M J, PARK H J, PAEK M Y, et al. Free-breathing ultrashort echo time lung magnetic resonance imaging using stack-of-spirals acquisition: a feasibility study in oncology patients[J/OL]. Magn Reson Imaging, 2018, 51: 137-143 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/29775663/. DOI: 10.1016/j.mri.2018.05.002.
[42]
LIU H, ZHENG L Y, SHI G F, et al. Pulmonary functional imaging for lung adenocarcinoma: combined MRI assessment based on IVIM-DWI and OE-UTE-MRI[J/OL]. Front Oncol, 2021, 11: 677942 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/34307146/. DOI: 10.3389/fonc.2021.677942.
[43]
ZHANG Z W, LI H D, XIAO S, et al. Hyperpolarized gas imaging in lung diseases: functional and artificial intelligence perspective[J]. Acad Radiol, 2024, 31(10): 4203-4216. DOI: 10.1016/j.acra.2024.01.014.
[44]
GENKIN D, ZANETTE B, GRZELA P, et al. Semiautomated segmentation and analysis of airway lumen in pediatric patients using ultra short echo time MRI[J]. Acad Radiol, 2024, 31(2): 648-659. DOI: 10.1016/j.acra.2023.07.009.
[45]
GUO F M, CAPALDI D P, MCCORMACK D G, et al. Ultra-short echo-time magnetic resonance imaging lung segmentation with under-Annotations and domain shift[J/OL]. Med Image Anal, 2021, 72: 102107 [2024-09-29]. https://pubmed.ncbi.nlm.nih.gov/34153626/. DOI: 10.1016/j.media.2021.102107.
[46]
DUAN C H, DENG H, XIAO S, et al. Fast and accurate reconstruction of human lung gas MRI with deep learning[J]. Magn Reson Med, 2019, 82(6): 2273-2285. DOI: 10.1002/mrm.27889.
[47]
LUNDERVOLD A S, LUNDERVOLD A. An overview of deep learning in medical imaging focusing on MRI[J]. Z Med Phys, 2019, 29(2): 102-127. DOI: 10.1016/j.zemedi.2018.11.002.
[48]
WESTCOTT A, CAPALDI D P I, MCCORMACK D G, et al. Chronic obstructive pulmonary disease: thoracic CT texture analysis and machine learning to predict pulmonary ventilation[J]. Radiology, 2019, 293(3): 676-684. DOI: 10.1148/radiol.2019190450.

PREV Progress in the application of artificial intelligence in the diagnosis and treatment of glaucoma: from traditional eye examination to MRI technology
NEXT Research progress of multimodal MRI in the assessment of hypoxia in the microenvironment of breast cancer
  


LINK


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