AccScience Publishing / ARNM / Online First / DOI: 10.36922/arnm.4173
Submit to ARNM
Cite this article
37
Download
1187
Views
Journal Browser
Volume | Year
Issue
Search
Forthcoming Issue
Current Issue
View All
News and Announcements
View All
REVIEW

Advances in molecular imaging for early detection of lung cancer

Dongjun Li1* ,  Mimba Brenda-Ruth1 ,  Bamishaye Oluwabukola1 ,  Jinghui Peng2
Show Less
1 Department of Chemistry, Georgia State University, Atlanta, Georgia, United States of America
2 Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Wuhan University, Hubei, Wuhan, China
ARNM 2024, 2(3), 4173 https://doi.org/10.36922/arnm.4173
Submitted: 9 July 2024 | Accepted: 6 August 2024 | Published: 19 September 2024
© 2024 by the Author (s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Download PDF
Cite
XML
Abstract

Lung cancer remains the second most commonly diagnosed cancer globally and the leading cause of cancer-related deaths, a trend consistent in the United States as of 2023. One of the key reasons for the high mortality rate of lung cancer is its poor prognosis, with 75% of patients diagnosed at middle and advanced stages. Early detection of subclinical lung cancer, metastases, and their fibrotic stroma is crucial for enabling timely treatment, reducing reoccurrence, and stratifying patients. Current diagnostic methods, such as lung biopsy for patients with small nodules, are highly invasive and technically challenging. The radiological gold standard, computed tomography (CT), is associated with ionizing radiation. However, positron emission tomography (PET) and magnetic resonance imaging (MRI) have emerged as promising methodologies for lung cancer diagnosis. PET tracers with a variety of targeting mechanisms are currently under development in human trials. With advancements in hardware and software over the past decades, radiation-free MRI has been clinically and preclinically validated as an alternative to CT. Moreover, novel-targeted MRI contrast agents have been tested in animal models and show strong translational potential. In this review, we summarize the state-of-the-art progress in molecular imaging for the early detection of lung cancer and its potential biomarkers.

Keywords
Early detection
Lung cancer
Molecular imaging
Magnetic resonance imaging
Positron emission tomography
Computed tomography
Funding
Dongjun Li was sponsored by GSU MBD fellowships, while Bamishaye Oluwabukola was sponsored by GSU CDT fellowships.
Conflict of interest
The authors declare no conflicts of interest.
References
  1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. doi: 10.3322/caac.21660

 

  1. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17-48. doi: 10.3322/caac.21763

 

  1. Herbst RS, Heymach JV, Lippman SM. Lung cancer. N Engl J Med. 2008;359(13):1367-1380. doi: 10.1056/NEJMra0802714

 

  1. Herbst RS, Morgensztern D, Boshoff C. The biology and management of non-small cell lung cancer. Nature. 2018;553(7689):446-454. doi: 10.1038/nature25183

 

  1. Wang M, Herbst RS, Boshoff C. Toward personalized treatment approaches for non-small-cell lung cancer. Nat Med. 2021;27(8):1345-1356. doi: 10.1038/s41591-021-01450-2

 

  1. Blandin Knight S, Crosbie PA, Balata H, Chudziak J, Hussell T, Dive C. Progress and prospects of early detection in lung cancer. Open Biol. 2017;7(9):170070. doi: 10.1098/rsob.170070

 

  1. Inage T, Nakajima T, Yoshino I, Yasufuku K. Early lung cancer detection. Clin Chest Med. 2018;39(1):45-55. doi: 10.1016/j.ccm.2017.10.003

 

  1. Tang WF, Wu M, Bao H, et al. Timing and origins of local and distant metastases in lung cancer. J Thorac Oncol. 2021;16(7):1136-1148. doi: 10.1016/j.jtho.2021.02.023

 

  1. Tamura T, Kurishima K, Nakazawa K, et al. Specific organ metastases and survival in metastatic nonsmallcell lung cancer. Mol Clin Oncol. 2015;3(1):217-221. doi: 10.3892/mco.2014.410

 

  1. The National Lung Screening Trial Research Team. Results of initial low-dose computed tomographic screening for lung cancer. N Engl J Med. 2013;368(21):1980-1991. doi: 10.1056/NEJMoa1209120

 

  1. de Koning HJ, van Der Aalst CM, de Jong PA, et al. Reduced lung-cancer mortality with volume CT screening in a randomized trial. N Engl J Med. 2020;382(6):503-513. doi: 10.1056/NEJMoa1911793

 

  1. Han Y, Kim HJ, Kong KA, et al. Diagnosis of small pulmonary lesions by transbronchial lung biopsy with radial endobronchial ultrasound and virtual bronchoscopic navigation versus CT-guided transthoracic needle biopsy: A systematic review and meta-analysis. PLoS One. 2018;13(1):e0191590. doi: 10.1371/journal.pone.0191590

 

  1. Tielemans B, Dekoster K, Verleden SE, et al. From mouse to man and back: Closing the correlation gap between imaging and histopathology for lung diseases. Diagnostics (Basel). 2020;10(9):636. doi: 10.3390/diagnostics10090636

 

  1. Zaw Thin M, Moore C, Snoeks T, Kalber T, Downward J, Behrens A. Micro-CT acquisition and image processing to track and characterize pulmonary nodules in mice. Nat Protoc. 2023;18(3):990-1015. doi: 10.1038/s41596-022-00769-5

 

  1. Brodersen J, Voss T, Martiny F, Siersma V, Barratt A, Heleno B. Overdiagnosis of lung cancer with low-dose computed tomography screening: Meta-analysis of the randomised clinical trials. Breathe (Sheff). 2020;16(1):200013. doi: 10.1183/20734735.0013-2020

 

  1. Lancaster HL, Heuvelmans MA, Oudkerk M. Low‐dose computed tomography lung cancer screening: Clinical evidence and implementation research. J Intern Med. 2022;292(1):68-80. doi: 10.1111/joim.13480

 

  1. Lubbers MM, Kock M, Niezen A, et al. Iodixanol versus iopromide at coronary CT angiography: Lumen opacification and effect on heart rhythm-the randomized isoCOR trial. Radiology. 2018;286(1):71-80. doi: 10.1148/radiol.2017162779

 

  1. Jiang Z, Zhang M, Li P, Wang Y, Fu Q. Nanomaterial-based CT contrast agents and their applications in image-guided therapy. Theranostics. 2023;13(2):483-509. doi: 10.7150/thno.79625

 

  1. Lusic H, Grinstaff MW. X-ray-computed tomography contrast agents. Chem Rev. 2013;113(3):1641-1666. doi: 10.1021/cr200358s

 

  1. Mahajan S, Barker CA, Singh B, Pandit-Taskar N. Clinical value of 18F-FDG-PET/CT in staging cutaneous squamous cell carcinoma. Nucl Med Commun. 2019;40(7):744-751. doi: 10.1097/MNM.0000000000001029

 

  1. Loktev A, Lindner T, Mier W, et al. A tumor-imaging method targeting cancer-associated fibroblasts. J Nucl Med. 2018;59(9):1423-1429. doi: 10.2967/jnumed.118.210435

 

  1. Alwadani B, Dall’Angelo S, Fleming IN. Clinical value of 3’-deoxy-3’-[(18)F]fluorothymidine-positron emission tomography for diagnosis, staging and assessing therapy response in lung cancer. Insights Imaging. 2021;12(1):90. doi: 10.1186/s13244-021-01026-1

 

  1. Niemeijer AN, Leung D, Huisman MC, et al. Whole body PD-1 and PD-L1 positron emission tomography in patients with non-small-cell lung cancer. Nat Commun. 2018;9(1):4664. doi: 10.1038/s41467-018-07131-y

 

  1. Kok IC, Hooiveld JS, van de Donk PP, et al. (89) Zr-pembrolizumab imaging as a non-invasive approach to assess clinical response to PD-1 blockade in cancer. Ann Oncol. 2022;33(1):80-88. doi: 10.1016/j.annonc.2021.10.213

 

  1. Franquet E, Park H. Molecular imaging in oncology: Common PET/CT radiopharmaceuticals and applications. Eur J Radiol Open. 2022;9:100455. doi: 10.1016/j.ejro.2022.100455

 

  1. Biederer J, Ohno Y, Hatabu H, et al. Screening for lung cancer: Does MRI have a role? Eur J Radiol. 2017;86:353-360. doi: 10.1016/j.ejrad.2016.09.016

 

  1. Ohno Y, Koyama H, Yoshikawa T, et al. Standard-, reduced-, and no-dose thin-section radiologic examinations: Comparison of capability for nodule detection and nodule type assessment in patients suspected of having pulmonary nodules. Radiology. 2017;284(2):562-573. doi: 10.1148/radiol.2017161037

 

  1. Burris NS, Johnson KM, Larson PE, et al. Detection of small pulmonary nodules with ultrashort echo time sequences in oncology patients by using a PET/MR system. Radiology. 2016;278(1):239-246. doi: 10.1148/radiol.2015150489

 

  1. Sanchez F, Tyrrell PN, Cheung P, et al. Detection of solid and subsolid pulmonary nodules with lung MRI: Performance of UTE, T1 gradient-echo, and single-shot T2 fast spin echo. Cancer Imaging. 2023;23(1):17. doi: 10.1186/s40644-023-00531-4

 

  1. Caravan P, Yang Y, Zachariah R, et al. Molecular magnetic resonance imaging of pulmonary fibrosis in mice. Am J Respir Cell Mol Biol. 2013;49(6):1120-1126. doi: 10.1165/rcmb.2013-0039OC

 

  1. Ibhagui OY, Li D, Han H, et al. Early detection and staging of lung fibrosis enabled by collagen-targeted MRI protein contrast agent. Chem Biomed Imaging. 2023;1(3):268-285. doi: 10.1021/cbmi.3c00023

 

  1. Waghorn PA, Jones CM, Rotile NJ, et al. Molecular magnetic resonance imaging of lung fibrogenesis with an oxyamine‐based probe. Angew Chem Int Ed. 2017;56(33):9825-9828. doi: 10.1002/anie.201704773

 

  1. Akam EA, Abston E, Rotile NJ, et al. Improving the reactivity of hydrazine-bearing MRI probes for in vivo imaging of lung fibrogenesis. Chem Sci. 2020;11(1):224-231. doi: 10.1039/c9sc04821a

 

  1. Ma H, Zhou IY, Chen YI, et al. Tailored chemical reactivity probes for systemic imaging of aldehydes in fibroproliferative diseases. J Am Chem Soc. 2023;145(38):20825-20836. doi: 10.1021/jacs.3c04964

 

  1. Mazonakis M, Damilakis J. Computed tomography: What and how does it measure? Eur J Radiol. 2016;85(8):1499-1504.

 

  1. Mitsiopoulos N, Baumgartner RN, Heymsfield SB, Lyons W, Gallagher D, Ross R. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. J Appl Physiol (1985). 1998;85(1):115-122. doi: 10.1152/jappl.1998.85.1.115

 

  1. Zhao Y, Wang R, Shi F, Wu J, Jiang F, Song Q. Diagnostic efficacy of CT examination on early detection of lung cancer during pandemic of COVID-19. Diagnostics (Basel). 2022;12(10):2317. doi: 10.3390/diagnostics12102317

 

  1. De Clerck NM, Meurrens K, Weiler H, et al. High-resolution X-ray microtomography for the detection of lung tumors in living mice. Neoplasia. 2004;6(4):374-379. doi: 10.1593/neo.03481

 

  1. Kalinke L, Thakrar R, Janes SM. The promises and challenges of early non‐small cell lung cancer detection: Patient perceptions, low‐dose CT screening, bronchoscopy and biomarkers. Mol Oncol. 2021;15(10):2544-2564. doi: 10.1002/1878-0261.12864

 

  1. Pastorino U, Boeri M, Sestini S, et al. Baseline computed tomography screening and blood microRNA predict lung cancer risk and define adequate intervals in the BioMILD trial. Ann Oncol. 2022;33(4):395-405. doi: 10.1016/j.annonc.2022.01.008

 

  1. Zheng S, Guo J, Cui X, Veldhuis RN, Oudkerk M, Van Ooijen PM. Automatic pulmonary nodule detection in CT scans using convolutional neural networks based on maximum intensity projection. IEEE Trans Med Imaging. 2019;39(3):797-805. doi: 10.1109/TMI.2019.2935553

 

  1. Tian P, He B, Mu W, et al. Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images. Theranostics. 2021;11(5):2098. doi: 10.7150/thno.48027

 

  1. Chaunzwa TL, Hosny A, Xu Y, et al. Deep learning classification of lung cancer histology using CT images. Sci Rep. 2021;11(1):5471. doi: 10.1038/s41598-021-84630-x

 

  1. Bhattacharjee A, Rabea S, Bhattacharjee A, et al. A multi-class deep learning model for early lung cancer and chronic kidney disease detection using computed tomography images. Front Oncol. 2023;13:1193746. doi: 10.3389/fonc.2023.1193746

 

  1. Kirsch DG, Grimm J, Guimaraes AR, et al. Imaging primary lung cancers in mice to study radiation biology. Int J Radiat Oncol Biol Phys. 2010;76(4):973-977. doi: 10.1016/j.ijrobp.2009.11.038

 

  1. Kozin SV, Kamoun WS, Huang Y, Dawson MR, Jain RK, Duda DG. Recruitment of myeloid but not endothelial precursor cells facilitates tumor regrowth after local irradiation. Cancer Res. 2010;70(14):5679-5685. doi: 10.1158/0008-5472.CAN-09-4446

 

  1. Krupnick AS, Tidwell VK, Engelbach JA, et al. Quantitative monitoring of mouse lung tumors by magnetic resonance imaging. Nat Protoc. 2012;7(1):128-142. doi: 10.1038/nprot.2011.424

 

  1. Lell MM, Wildberger JE, Alkadhi H, Damilakis J, Kachelriess M. Evolution in computed tomography: The battle for speed and dose. Invest Radiol. 2015;50(9):629-644. doi: 10.1097/RLI.0000000000000172

 

  1. Wu Y, Li P, Zhang H, et al. Diagnostic value of fluorine 18 fluorodeoxyglucose positron emission tomography/ computed tomography for the detection of metastases in non-small-cell lung cancer patients. Int J Cancer. 2013;132(2):E37-E47. doi: 10.1002/ijc.27779

 

  1. Vansteenkiste JF, Stroobants SS. PET scan in lung cancer: Current recommendations and innovation. J Thorac Oncol. 2006;1:71-73.

 

  1. Acker M. Utility of FDG PET in evaluating cancers of lung. J Nucl Med Technol. 2005;33(3):69-74.

 

  1. Zhu J, Pan F, Cai H, et al. Positron emission tomography imaging of lung cancer: An overview of alternative positron emission tomography tracers beyond F18 fluorodeoxyglucose. Front Med (Lausanne). 2022;9:945602. doi: 10.3389/fmed.2022.945602

 

  1. Farwell MD, Pryma DA, Mankoff DA. PET/CT imaging in cancer: Current applications and future directions. Cancer. 2014;120(22):3433-3445. doi: 10.1002/cncr.28860

 

  1. Sanchez Salmon A, Barandela Salgado J, Ruibal Morell A. PET in abdominal pathology: Advantages and limitations. Abdom Imaging. 2006;31(2):174-181. doi: 10.1007/s00261-005-0384-7

 

  1. Ambrosini V, Nicolini S, Caroli P, et al. PET/CT imaging in different types of lung cancer: An overview. Eur J Radiol. 2012;81(5):988-1001. doi: 10.1016/j.ejrad.2011.03.020

 

  1. Krarup MMK, Fischer BM, Christensen TN. New PET tracers: Current knowledge and perspectives in lung cancer. Semin Nucl Med. 2022;52(6):781-796. doi: 10.1053/j.semnuclmed.2022.05.002

 

  1. Deppen SA, Blume JD, Kensinger CD, et al. Accuracy of FDG-PET to diagnose lung cancer in areas with infectious lung disease: A meta-analysis. JAMA. 2014;312(12):1227-1236. doi: 10.1001/jama.2014.11488

 

  1. Almuhaideb A, Papathanasiou N, Bomanji J. 18F-FDG PET/ CT imaging in oncology. Ann Saudi Med. 2011;31(1):3-13. doi: 10.4103/0256-4947.75771

 

  1. Borgonje PE, Andrews LM, Herder GJM, de Klerk JMH. Performance and prospects of [(68)Ga]Ga-FAPI PET/CT scans in lung cancer. Cancers (Basel). 2022;14(22):5566. doi: 10.3390/cancers14225566

 

  1. Huang R, Pu Y, Huang S, et al. FAPI-PET/CT in cancer imaging: A potential novel molecule of the century. Front Oncol. 2022;12:854658. doi: 10.3389/fonc.2022.854658

 

  1. Hamson EJ, Keane FM, Tholen S, Schilling O, Gorrell MD. Understanding fibroblast activation protein (FAP): Substrates, activities, expression and targeting for cancer therapy. Proteomics Clin Appl. 2014;8(5-6):454-463. doi: 10.1002/prca.201300095

 

  1. Kratochwil C, Flechsig P, Lindner T, et al. (68)Ga-FAPI PET/ CT: Tracer uptake in 28 different kinds of cancer. J Nucl Med. 2019;60(6):801-805. doi: 10.2967/jnumed.119.227967

 

  1. Giesel FL, Kratochwil C, Schlittenhardt J, et al. Head-to-head intra-individual comparison of biodistribution and tumor uptake of (68)Ga-FAPI and (18)F-FDG PET/CT in cancer patients. Eur J Nucl Med Mol Imaging. 2021;48(13):4377-4385. doi: 10.1007/s00259-021-05307-1

 

  1. Chalkidou A, Landau DB, Odell EW, Cornelius VR, O’Doherty MJ, Marsden PK. Correlation between Ki-67 immunohistochemistry and 18F-fluorothymidine uptake in patients with cancer: A systematic review and meta-analysis. Eur J Cancer. 2012;48(18):3499-3513. doi: 10.1016/j.ejca.2012.05.001

 

  1. Sanghera B, Wong WL, Sonoda LI, et al. FLT PET-CT in evaluation of treatment response. Indian J Nucl Med. 2014;29(2):65-73. doi: 10.4103/0972-3919.130274

 

  1. Wang FL, Tan YY, Gu XM, et al. Comparison of positron emission tomography using 2-[18F]-fluoro-2-deoxy-D-glucose and 3-deoxy-3-[18F]-fluorothymidine in Lung Cancer Imaging. Chin Med J (Engl). 2016;129(24):2926-2935. doi: 10.4103/0366-6999.195468

 

  1. Xu X, Nie L, Yao Y, Tu Y, Zhou J. Pre-radiotherapy assessment of non-small cell lung cancer with 18F-FLT PET/CT or 18F-FDG PET/CT. Int J Clin Exp Med. 2016;9:9252-9260.

 

  1. Tian J, Yang X, Yu L, et al. A multicenter clinical trial on the diagnostic value of dual-tracer PET/CT in pulmonary lesions using 3’-deoxy-3’-18F-fluorothymidine and 18F-FDG. J Nucl Med. 2008;49(2):186-194. doi: 10.2967/jnumed.107.044966

 

  1. Wei W, Rosenkrans ZT, Liu J, Huang G, Luo QY, Cai W. ImmunoPET: Concept, design, and applications. Chem Rev. 2020;120(8):3787-3851. doi: 10.1021/acs.chemrev.9b00738

 

  1. De Feo MS, Pontico M, Frantellizzi V, Corica F, De Cristofaro F, De Vincentis G. 89Zr-PET imaging in humans: A systematic review. Clin Trans Imaging. 2021;10(1):23-36. doi: 10.1007/s40336-021-00462-9

 

  1. Dolled-Filhart M, Roach C, Toland G, et al. Development of a companion diagnostic for pembrolizumab in non-small cell lung cancer using immunohistochemistry for programmed death ligand-1. Arch Pathol Lab Med. 2016;140(11):1243-1249. doi: 10.5858/arpa.2015-0542-OA

 

  1. Walker R, Deppen S, Smith G, et al. 68Ga-DOTATATE PET/ CT imaging of indeterminate pulmonary nodules and lung cancer. PLoS One. 2017;12(2):e0171301. doi: 10.1371/journal.pone.0171301

 

  1. Hu X, Li D, Wang R, Wang P, Cai J. Comparison of the application of 18F-FDG and 68Ga-DOTATATE PET/CT in neuroendocrine tumors: A retrospective study. Medicine (Baltimore). 2023;102(19):e33726. doi: 10.1097/MD.0000000000033726

 

  1. Kakhki VRD. Positron emission tomography in the management of lung cancer. Ann Thorac Med. 2007;2(2):69-76. doi: 10.4103/1817-1737.32235

 

  1. Griffeth LK. Use of PETCT scanning in cancer patients technical and practical considerations. Proc (Bayl Univ Med Cent). 2005;18:321-330. doi: 10.1080/08998280.2005.11928089

 

  1. Hatabu H, Ohno Y, Gefter WB, et al. Expanding applications of pulmonary MRI in the clinical evaluation of lung disorders: Fleischner Society position paper. Radiology. 2020;297(2):286-301. doi: 10.1148/radiol.2020201138

 

  1. Rampinelli C, De Marco P, Origgi D, et al. Exposure to low dose computed tomography for lung cancer screening and risk of cancer: Secondary analysis of trial data and risk-benefit analysis. BMJ. 2017;356:j347. doi: 10.1136/bmj.j347

 

  1. Shah DJ, Sachs RK, Wilson DJ. Radiation-induced cancer: A modern view. Br J Radiol. 2012;85(1020):e1166-e1173. doi: 10.1259/bjr/25026140

 

  1. Aziz M, Krishnam M, Madhuranthakam AJ, Rajiah P. Update on MR imaging of the pulmonary vasculature. Int J Cardiovasc Imaging. 2019;35:1483-1497. doi: 10.1007/s10554-019-01603-y

 

  1. Krupnick AS, Tidwell VK, Engelbach JA, et al. Quantitative monitoring of murine lung tumors by magnetic resonance imaging. Nat Protoc. 2012;7(1):128-42. doi: 10.1038/nprot.2011.424

 

  1. Wild JM, Marshall H, Bock M, et al. MRI of the lung (1/3): Methods. Insights Imaging. 2012;3:345-353. doi: 10.1007/s13244-012-0176-x

 

  1. Uto T, Takehara Y, Nakamura Y, et al. Higher sensitivity and specificity for diffusion-weighted imaging of malignant lung lesions without apparent diffusion coefficient quantification. Radiology. 2009;252(1):247-254. doi: 10.1148/radiol.2521081195

 

  1. Qi LP, Zhang XP, Tang L, Li J, Sun YS, Zhu GY. Using diffusion-weighted MR imaging for tumor detection in the collapsed lung: A preliminary study. Eur Radiol. 2009;19:333-341. doi: 10.1007/s00330-008-1134-3

 

  1. Satoh S, Kitazume Y, Ohdama S, Kimula Y, Taura S, Endo Y. Can malignant and benign pulmonary nodules be differentiated with diffusion-weighted MRI? Am J Roentgenol. 2008;191(2):464-470. doi: 10.2214/AJR.07.3133

 

  1. Coolen J, De Keyzer F, Nafteux P, et al. Malignant pleural disease: Diagnosis by using diffusion-weighted and dynamic contrast-enhanced MR imaging-initial experience. Radiology. 2012;263(3):884-892. doi: 10.1148/radiol.12110872

 

  1. Hu N, Yin S, Li Q, et al. Evaluating heterogeneity of primary lung tumor using clinical routine magnetic resonance imaging and a tumor heterogeneity index. Front Oncol. 2021;10:591485. doi: 10.3389/fonc.2020.591485

 

  1. Olson JD, Walb MC, Moore JE, et al. A gated-7T MRI technique for tracking lung tumor development and progression in mice after exposure to low doses of ionizing radiation. Radiat Res. 2012;178(4):321-327. doi: 10.1667/rr2800.1

 

  1. Meier-Schroers M, Homsi R, Gieseke J, Schild HH, Thomas D. Lung cancer screening with MRI: Evaluation of MRI for lung cancer screening by comparison of LDCT-and MRI-derived Lung-RADS categories in the first two screening rounds. Eur Radiol. 2019;29:898-905. doi: 10.1007/s00330-018-5607-8

 

  1. Ohno Y, Koyama H, Yoshikawa T, Matsumoto S, Sugimura K. Lung cancer assessment using MR imaging: An update. Magn Reson Imaging Clin N Am. 2015;23(2):231-244. doi: 10.1016/j.mric.2015.01.012

 

  1. Robson MD, Gatehouse PD, Bydder M, Bydder GM. Magnetic resonance: An introduction to ultrashort TE (UTE) imaging. J Comput Assist Tomogr. 2003;27(6):825-846. doi: 10.1097/00004728-200311000-00001

 

  1. Balasch A. Functional lung magnetic resonance imaging with ultra-short echo-time (UTE). 2022.Ýoi: http://dx.doi. org/10.18725/OPARU-42430

 

  1. Ma Y, Jang H, Jerban S, et al. Making the invisible visible-ultrashort echo time magnetic resonance imaging: Technical developments and applications. Appl Phys Rev. 2022;9(4):041303. doi: 10.1063/5.0086459

 

  1. Johnson KM, Fain SB, Schiebler ML, Nagle S. Optimized 3D ultrashort echo time pulmonary MRI. Magn Reson Med. 2013;70(5):1241-1250. doi: 10.1002/mrm.24570

 

  1. Bergin CJ, Pauly JM, Macovski A. Lung parenchyma: Projection reconstruction MR imaging. Radiology. 1991;179(3):777-781. doi: 10.1148/radiology.179.3.2027991

 

  1. Geiger J, Zeimpekis KG, Jung A, Moeller A, Kellenberger CJ. Clinical application of ultrashort echo-time MRI for lung pathologies in children. Clin Radiol. 2021;76(9):708. e9-e17. doi: 10.1016/j.crad.2021.05.015

 

  1. Ohno Y, Takenaka D, Yoshikawa T, et al. Efficacy of ultrashort echo time pulmonary MRI for lung nodule detection and lung-RADS classification. Radiology. 2022;302(3):697-706. doi: 10.1148/radiol.211254

 

  1. Voskrebenzev A, Vogel‐Claussen J. Proton MRI of the lung: How to tame scarce protons and fast signal decay. J Magn Reson Imaging. 2021;53(5):1344-1357. doi: 10.1002/jmri.27122

 

  1. Stecker IR, Freeman MS, Sitaraman S, et al. Preclinical MRI to quantify pulmonary disease severity and trajectories in poorly characterized mouse models: A pedagogical example using data from novel transgenic models of lung fibrosis. J Magn Reson Open. 2021;6:100013.

 

  1. Babin AL, Cannet C, Gérard C, et al. Bleomycin‐induced lung injury in mice investigated by MRI: Model assessment for target analysis. Magn Reson Med. 2012;67(2):499-509. doi: 10.1016/j.jmro.2021.100013

 

  1. Wahsner J, Gale EM, Rodríguez-Rodríguez A, Caravan P. Chemistry of MRI contrast agents: Current challenges and new frontiers. Chem Rev. 2018;119(2):957-1057. doi: 10.1021/acs.chemrev.8b00363

 

  1. Li D, Kirberger M, Qiao J, et al. Protein MRI contrast agents as an effective approach for precision molecular imaging. Invest Radiol. 2024;59(2):170-186. doi: 10.1097/RLI.0000000000001057

 

  1. Pauls S, Mottaghy FM, Schmidt SA, et al. Evaluation of lung tumor perfusion by dynamic contrast-enhanced MRI. Magn Reson Imaging. 2008;26(10):1334-1341. doi: 10.1016/j.mri.2008.04.005

 

  1. Pauls S, Breining T, Muche R, et al. The role of dynamic, contrast-enhanced MRI in differentiating lung tumor subtypes. Clin Imaging. 2011;35(4):259-265. doi: 10.1016/j.clinimag.2010.07.002

 

  1. Thangudu S, Yu CC, Lee CL, Liao MC, Su CH. Magnetic, biocompatible FeCO3 nanoparticles for T2-weighted magnetic resonance imaging of in vivo lung tumors. J Nanobiotechnology. 2022;20(1):157. doi: 10.1186/s12951-022-01355-3

 

  1. Wahyudi H, Reynolds AA, Li Y, Owen SC, Yu SM. Targeting collagen for diagnostic imaging and therapeutic delivery. J Control Release. 2016;240:323-331. doi: 10.1016/j.jconrel.2016.01.007

 

  1. Erstad DJ, Sojoodi M, Taylor MS, et al. Fibrotic response to neoadjuvant therapy predicts survival in pancreatic cancer and is measurable with collagen-targeted molecular MRI. Clin Cancer Res. 2020;26(18):5007-5018. doi: 10.1158/1078-0432.CCR-18-1359

 

  1. Cox TR. The matrix in cancer. Nat Rev Cancer. 2021;21(4):217-238. doi: 10.1038/s41568-020-00329-7

 

  1. Wynn TA, Ramalingam TR. Mechanisms of fibrosis: Therapeutic translation for fibrotic disease. Nat Med. 2012;18(7):1028-1040. doi: 10.1038/nm.2807

 

  1. Xu S, Xu H, Wang W, et al. The role of collagen in cancer: From bench to bedside. J Transl Med. 2019;17:1-22.

 

  1. Scodellaro R, Bouzin M, Mingozzi F, et al. Whole-section tumor micro-architecture analysis by a two-dimensional phasor-based approach applied to polarization-dependent second harmonic imaging. Front Oncol. 2019;9:527. doi: 10.3389/fonc.2019.00527

 

  1. Martins Cavaco AC, Dâmaso S, Casimiro S, Costa L. Collagen biology making inroads into prognosis and treatment of cancer progression and metastasis. Cancer Metastasis Rev. 2020;39:603-623. doi: 10.1007/s10555-020-09888-5

 

  1. Kinoshita T, Goto T. Molecular mechanisms of pulmonary fibrogenesis and its progression to lung cancer: A review. Int J Mol Sci. 2019;20(6):1461. doi: 10.3390/ijms20061461

 

  1. de Sousa VML, Carvalho L. Heterogeneity in lung cancer. Pathobiology. 2018;85(1-2):96-107. doi: 10.1159/000487440

 

  1. Collins LG, Haines C, Perkel R, Enck RE. Lung cancer: diagnosis and management. Am Fam Physician. 2007;75(1):56-63.

 

  1. Chong IW, Chang MY, Chang HC, et al. Great potential of a panel of multiple hMTH1, SPD, ITGA11 and COL11A1 markers for diagnosis of patients with non-small cell lung cancer. Oncol Rep. 2006;16(5):981-988.

 

  1. Shen L, Yang M, Lin Q, Zhang Z, Zhu B, Miao C. COL11A1 is overexpressed in recurrent non-small cell lung cancer and promotes cell proliferation, migration, invasion and drug resistance. Oncol Rep. 2016;36(2):877-885. doi: 10.3892/or.2016.4869

 

  1. Yi X, Luo L, Zhu Y, et al. SPP1 facilitates cell migration and invasion by targeting COL11A1 in lung adenocarcinoma. Cancer Cell Int. 2022;22(1):324. doi: 10.1186/s12935-022-02749-x

 

  1. Jin Y, Zhu H, Cai W, et al. B-Myb is up-regulated and promotes cell growth and motility in non-small cell lung cancer. Int J Mol Sci. 2017;18(6):860. doi: 10.3390/ijms18060860

 

  1. Turkowski K, Herzberg F, Günther S, et al. Fibroblast growth factor-14 acts as tumor suppressor in lung adenocarcinomas. Cells. 2020;9(8):1755. doi: 10.3390/cells9081755

 

  1. Sun Y, Liu Z, Huang L, Shang Y. MiR-144-3p inhibits the proliferation, migration and invasion of lung adenocargen cancer cells by targeting COL11A1. J Chemother. 2021;33(6):409-419. doi: 10.1080/1120009x.2021.1906031

 

  1. Chen M, Zhang J, Zeng J, Yu Y, Gu C. Circular circRANGAP1 contributes to non-small cell lung cancer progression by increasing COL11A1 expression through sponging miR- 653-5p. Biochem Genet. 2023;61(6):2580-2598. doi: 10.1007/s10528-023-10393-x

 

  1. Qiao H, Feng Y, Tang H. COL6A6 inhibits the proliferation and metastasis of non-small cell lung cancer through the JAK signalling pathway. Transl Cancer Res. 2021;10(10):4514-4522. doi: 10.21037/tcr-21-2002

 

  1. Ma Y, Qiu M, Guo H, et al. Comprehensive analysis of the immune and prognostic implication of COL6A6 in lung adenocarcinoma. Front Oncol. 2021;11:633420. doi: 10.3389/fonc.2021.633420

 

  1. Gong L, Wu D, Zou J, et al. Prognostic impact of serum and tissue MMP-9 in non-small cell lung cancer: A systematic review and meta-analysis. Oncotarget. 2016;7(14):18458-68. doi: 10.18632/oncotarget.7607

 

  1. Vandooren J, Van den Steen PE, Opdenakker G. Biochemistry and molecular biology of gelatinase B or matrix metalloproteinase-9 (MMP-9): The next decade. Crit Rev Biochem Mol Biol. 2013;48(3):222-272. doi: 10.3109/10409238.2013.770819

 

  1. Qiao X, Gu Y, Yu J, et al. The combination of CD147 and MMP-9 serum levels is identified as novel chemotherapy response markers of advanced non-small-cell lung cancer. Dis Markers. 2020;2020:8085053. doi: 10.1155/2020/8085053

 

  1. Han L, Chen Y, Huang N, et al. Cancer-educated neutrophils promote lung cancer progression via PARP- 1-ALOX5-mediated MMP-9 expression. Cancer Biol Med. 2024;21(2):175-92. doi: 10.20892/j.issn.2095-3941.2023.0248

 

  1. Wang CY, Chen CL, Tseng YL, et al. Annexin A2 silencing induces G2 arrest of non-small cell lung cancer cells through p53-dependent and -independent mechanisms. J Biol Chem. 2012;287(39):32512-32524. doi: 10.1074/jbc.M112.351957

 

  1. Ling X, Qi C, Cao K, et al. METTL3-mediated deficiency of lncRNA HAR1A drives non-small cell lung cancer growth and metastasis by promoting ANXA2 stabilization. Cell Death Discov. 2024;10(1):203. doi: 10.1038/s41420-024-01965-w

 

  1. Wang Y, Wang Y, Liu W, et al. TIM-4 orchestrates mitochondrial homeostasis to promote lung cancer progression via ANXA2/PI3K/AKT/OPA1 axis. Cell Death Dis. 2023;14(2):141. doi: 10.1038/s41419-023-05678-3
Share
Back to top
Advances in Radiotherapy & Nuclear Medicine, Electronic ISSN: 2972-4392 Published by AccScience Publishing
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here
Accept