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For: Clukers J, Lanclus M, Mignot B, Van Holsbeke C, Roseman J, Porter S, Gorina E, Kouchakji E, Lipson KE, De Backer W, De Backer J. Quantitative CT analysis using functional imaging is superior in describing disease progression in idiopathic pulmonary fibrosis compared to forced vital capacity. Respir Res 2018;19:213. [PMID: 30400950 DOI: 10.1186/s12931-018-0918-5] [Cited by in Crossref: 13] [Cited by in F6Publishing: 14] [Article Influence: 3.3] [Reference Citation Analysis]
Number Citing Articles
1 Wells AU, Walsh SLF. Quantitative computed tomography and machine learning: recent data in fibrotic interstitial lung disease and potential role in pulmonary sarcoidosis. Curr Opin Pulm Med 2022. [PMID: 35861463 DOI: 10.1097/MCP.0000000000000902] [Reference Citation Analysis]
2 Tanaka Y, Suzuki Y, Hasegawa H, Yokomura K, Fukada A, Inoue Y, Hozumi H, Karayama M, Furuhashi K, Enomoto N, Fujisawa T, Nakamura Y, Inui N, Suda T. Standardised 3D-CT lung volumes for patients with idiopathic pulmonary fibrosis. Respir Res 2022;23:142. [PMID: 35650599 DOI: 10.1186/s12931-022-02062-1] [Reference Citation Analysis]
3 Handa T, Tanizawa K, Oguma T, Uozumi R, Watanabe K, Tanabe N, Niwamoto T, Shima H, Mori R, Nobashi TW, Sakamoto R, Kubo T, Kurosaki A, Kishi K, Nakamoto Y, Hirai T. Novel Artificial Intelligence-based Technology for Chest Computed Tomography Analysis of Idiopathic Pulmonary Fibrosis. Ann Am Thorac Soc 2021. [PMID: 34410886 DOI: 10.1513/AnnalsATS.202101-044OC] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
4 Devaraj A, Milanese G, Sverzellati N. Thoracic computed tomography in the progressive fibrotic phenotype. Curr Opin Pulm Med 2021;27:350-4. [PMID: 34224434 DOI: 10.1097/MCP.0000000000000804] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
5 Chung JH, Adegunsoye A, Cannon B, Vij R, Oldham JM, King C, Montner SM, Thirkateh P, Barnett S, Karwoski R, Bartholmai BJ, Strek M, Nathan SD. Differentiation of Idiopathic Pulmonary Fibrosis from Connective Tissue Disease-Related Interstitial Lung Disease Using Quantitative Imaging. J Clin Med 2021;10:2663. [PMID: 34204184 DOI: 10.3390/jcm10122663] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Clukers J, Lanclus M, Belmans D, Van Holsbeke C, De Backer W, Vummidi D, Cronin P, Lavon BR, De Backer J, Khanna D. Interstitial lung disease in systemic sclerosis quantification of disease classification and progression with high-resolution computed tomography: An observational study. Journal of Scleroderma and Related Disorders 2021;6:154-64. [DOI: 10.1177/2397198320985377] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
7 Huang H, Wang X, Zhang X, Wang H, Jiang W. Roxadustat attenuates experimental pulmonary fibrosis in vitro and in vivo. Toxicol Lett 2020;331:112-21. [PMID: 32534005 DOI: 10.1016/j.toxlet.2020.06.009] [Cited by in Crossref: 5] [Cited by in F6Publishing: 10] [Article Influence: 2.5] [Reference Citation Analysis]
8 Taha N, D'Amato D, Hosein K, Ranalli T, Sergiacomi G, Zompatori M, Mura M. Longitudinal functional changes with clinically significant radiographic progression in idiopathic pulmonary fibrosis: are we following the right parameters? Respir Res 2020;21:119. [PMID: 32429952 DOI: 10.1186/s12931-020-01371-7] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
9 Walsh SLF, Humphries SM, Wells AU, Brown KK. Imaging research in fibrotic lung disease; applying deep learning to unsolved problems. Lancet Respir Med 2020;8:1144-53. [PMID: 32109428 DOI: 10.1016/S2213-2600(20)30003-5] [Cited by in Crossref: 12] [Cited by in F6Publishing: 19] [Article Influence: 6.0] [Reference Citation Analysis]
10 McLellan T, George PM, Ford P, De Backer J, Van Holsbeke C, Mignot B, Screaton NJ, Ruggiero A, Thillai M. Idiopathic pulmonary fibrosis: airway volume measurement identifies progressive disease on computed tomography scans. ERJ Open Res 2020;6:00290-2019. [PMID: 32083110 DOI: 10.1183/23120541.00290-2019] [Cited by in Crossref: 6] [Cited by in F6Publishing: 8] [Article Influence: 3.0] [Reference Citation Analysis]
11 Sverzellati N, Silva M, Seletti V, Galeone C, Palmucci S, Piciucchi S, Vancheri C, Poletti V, Tomassetti S, Karwoski R, Bartholmai BJ. Stratification of long-term outcome in stable idiopathic pulmonary fibrosis by combining longitudinal computed tomography and forced vital capacity. Eur Radiol 2020;30:2669-79. [PMID: 32006172 DOI: 10.1007/s00330-019-06619-5] [Cited by in Crossref: 6] [Cited by in F6Publishing: 8] [Article Influence: 3.0] [Reference Citation Analysis]
12 Somogyi V, Chaudhuri N, Torrisi SE, Kahn N, Müller V, Kreuter M. The therapy of idiopathic pulmonary fibrosis: what is next? Eur Respir Rev 2019;28:190021. [PMID: 31484664 DOI: 10.1183/16000617.0021-2019] [Cited by in Crossref: 50] [Cited by in F6Publishing: 66] [Article Influence: 16.7] [Reference Citation Analysis]
13 Saito S, Alkhatib A, Kolls JK, Kondoh Y, Lasky JA. Pharmacotherapy and adjunctive treatment for idiopathic pulmonary fibrosis (IPF). J Thorac Dis 2019;11:S1740-54. [PMID: 31632751 DOI: 10.21037/jtd.2019.04.62] [Cited by in Crossref: 30] [Cited by in F6Publishing: 42] [Article Influence: 10.0] [Reference Citation Analysis]
14 Mari P, G. Jones M, Richeldi L. Contemporary Concise Review 2018: Interstitial lung disease. Respirology 2019;24:809-16. [DOI: 10.1111/resp.13572] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 0.7] [Reference Citation Analysis]