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For: Loeh B, Brylski LT, von der Beck D, Seeger W, Krauss E, Bonniaud P, Crestani B, Vancheri C, Wells AU, Markart P, Breithecker A, Guenther A. Lung CT Densitometry in Idiopathic Pulmonary Fibrosis for the Prediction of Natural Course, Severity, and Mortality. Chest 2019;155:972-81. [DOI: 10.1016/j.chest.2019.01.019] [Cited by in Crossref: 17] [Cited by in F6Publishing: 17] [Article Influence: 5.7] [Reference Citation Analysis]
Number Citing Articles
1 Krauss E, Froehler M, Degen M, Mahavadi P, Dartsch RC, Korfei M, Ruppert C, Seeger W, Guenther A. Exhalative Breath Markers Do Not Offer for Diagnosis of Interstitial Lung Diseases: Data from the European IPF Registry (eurIPFreg) and Biobank. J Clin Med 2019;8:E643. [PMID: 31075945 DOI: 10.3390/jcm8050643] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
2 Zheng Y, Lou Y, Zhu F, Wang X, Wu W, Wu X. Utility of fractional exhaled nitric oxide in interstitial lung disease. J Breath Res 2021;15. [PMID: 34128832 DOI: 10.1088/1752-7163/ac01c1] [Reference Citation Analysis]
3 Nishiyama A, Kawata N, Yokota H, Hayano K, Matsuoka S, Shigeta A, Sugiura T, Tanabe N, Ishida K, Tatsumi K, Suzuki T, Uno T. Heterogeneity of Lung Density in Patients With Chronic Thromboembolic Pulmonary Hypertension (CTEPH). Acad Radiol 2022:S1076-6332(22)00141-6. [PMID: 35466051 DOI: 10.1016/j.acra.2022.03.002] [Reference Citation Analysis]
4 Humphries SM, Mackintosh JA, Jo HE, Walsh SLF, Silva M, Calandriello L, Chapman S, Ellis S, Glaspole I, Goh N, Grainge C, Hopkins PMA, Keir GJ, Moodley Y, Reynolds PN, Walters EH, Baraghoshi D, Wells AU, Lynch DA, Corte TJ. Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis. Respirology. [DOI: 10.1111/resp.14333] [Reference Citation Analysis]
5 Saldana DC, Hague CJ, Murphy D, Coxson HO, Tschirren J, Peterson S, Sieren JP, Kirby M, Ryerson CJ. Association of Computed Tomography Densitometry with Disease Severity, Functional Decline, and Survival in Systemic Sclerosis-associated Interstitial Lung Disease. Annals ATS 2020;17:813-20. [DOI: 10.1513/annalsats.201910-741oc] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
6 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: 44] [Article Influence: 16.7] [Reference Citation Analysis]
7 Krauss E, Tello S, Wilhelm J, Schmidt J, Stoehr M, Seeger W, Dartsch RC, Crestani B, Guenther A. Assessing the Effectiveness of Pirfenidone in Idiopathic Pulmonary Fibrosis: Long-Term, Real-World Data from European IPF Registry (eurIPFreg). J Clin Med 2020;9:E3763. [PMID: 33266405 DOI: 10.3390/jcm9113763] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
8 Krauss E, El-Guelai M, Pons-Kuehnemann J, Dartsch RC, Tello S, Korfei M, Mahavadi P, Breithecker A, Fink L, Stoehr M, Majeed RW, Seeger W, Crestani B, Guenther A. Clinical and Functional Characteristics of Patients with Unclassifiable Interstitial Lung Disease (uILD): Long-Term Follow-Up Data from European IPF Registry (eurIPFreg). J Clin Med 2020;9:E2499. [PMID: 32756496 DOI: 10.3390/jcm9082499] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
9 Chen L, Yang Y, Yan H, Peng X, Zou J. NEDD4L-induced β-catenin ubiquitination suppresses the formation and progression of interstitial pulmonary fibrosis via inhibiting the CTHRC1/HIF-1α axis. Int J Biol Sci 2021;17:3320-30. [PMID: 34512149 DOI: 10.7150/ijbs.57247] [Reference Citation Analysis]
10 Romanov A, Bach M, Yang S, Franzeck FC, Sommer G, Anastasopoulos C, Bremerich J, Stieltjes B, Weikert T, Sauter AW. Automated CT Lung Density Analysis of Viral Pneumonia and Healthy Lungs Using Deep Learning-Based Segmentation, Histograms and HU Thresholds. Diagnostics (Basel) 2021;11:738. [PMID: 33919094 DOI: 10.3390/diagnostics11050738] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Mori M, Palumbo D, De Lorenzo R, Broggi S, Compagnone N, Guazzarotti G, Giorgio Esposito P, Mazzilli A, Steidler S, Pietro Vitali G, Del Vecchio A, Rovere Querini P, De Cobelli F, Fiorino C. Robust prediction of mortality of COVID-19 patients based on quantitative, operator-independent, lung CT densitometry. Phys Med 2021;85:63-71. [PMID: 33971530 DOI: 10.1016/j.ejmp.2021.04.022] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
12 Suzuki M, Kawata N, Abe M, Yokota H, Anazawa R, Matsuura Y, Ikari J, Matsuoka S, Tsushima K, Tatsumi K. Objective quantitative multidetector computed tomography assessments in patients with combined pulmonary fibrosis with emphysema: Relationship with pulmonary function and clinical events. PLoS One 2020;15:e0239066. [PMID: 32941486 DOI: 10.1371/journal.pone.0239066] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
13 Mononen ME, Kettunen HP, Suoranta SK, Kärkkäinen MS, Selander TA, Purokivi MK, Kaarteenaho RL. Several specific high-resolution computed tomography patterns correlate with survival in patients with idiopathic pulmonary fibrosis. J Thorac Dis 2021;13:2319-30. [PMID: 34012581 DOI: 10.21037/jtd-20-1957] [Reference Citation Analysis]
14 Barrera CA, du Plessis AM, Otero HJ, Mahtab S, Githinji LN, Zar HJ, Zhu X, Andronikou S. Quantitative CT analysis for bronchiolitis obliterans in perinatally HIV-infected adolescents-comparison with controls and lung function data. Eur Radiol 2020;30:4358-68. [PMID: 32172382 DOI: 10.1007/s00330-020-06789-7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
15 Tanguy J, Goirand F, Bouchard A, Frenay J, Moreau M, Mothes C, Oudot A, Helbling A, Guillemin M, Bonniaud P, Cochet A, Collin B, Bellaye PS. [18F]FMISO PET/CT imaging of hypoxia as a non-invasive biomarker of disease progression and therapy efficacy in a preclinical model of pulmonary fibrosis: comparison with the [18F]FDG PET/CT approach. Eur J Nucl Med Mol Imaging 2021;48:3058-74. [PMID: 33580818 DOI: 10.1007/s00259-021-05209-2] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Krauss E, Haberer J, Maurer O, Barreto G, Drakopanagiotakis F, Degen M, Seeger W, Guenther A. Exploring the Ability of Electronic Nose Technology to Recognize Interstitial Lung Diseases (ILD) by Non-Invasive Breath Screening of Exhaled Volatile Compounds (VOC): A Pilot Study from the European IPF Registry (eurIPFreg) and Biobank. J Clin Med 2019;8:E1698. [PMID: 31623141 DOI: 10.3390/jcm8101698] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 2.7] [Reference Citation Analysis]
17 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: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
18 Krauss E, Gehrken G, Drakopanagiotakis F, Tello S, Dartsch RC, Maurer O, Windhorst A, von der Beck D, Griese M, Seeger W, Guenther A. Clinical characteristics of patients with familial idiopathic pulmonary fibrosis (f-IPF). BMC Pulm Med 2019;19:130. [PMID: 31319833 DOI: 10.1186/s12890-019-0895-6] [Cited by in Crossref: 11] [Cited by in F6Publishing: 8] [Article Influence: 3.7] [Reference Citation Analysis]
19 Birk G, Kästle M, Tilp C, Stierstorfer B, Klee S. Automatization and improvement of μCT analysis for murine lung disease models using a deep learning approach. Respir Res 2020;21:124. [PMID: 32448249 DOI: 10.1186/s12931-020-01370-8] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
20 Barros MC, Altmayer S, Carvalho AR, Rodrigues R, Zanon M, Mohammed TL, Patel P, Mohammad AA, Mehrad B, Chatkin JM, Hochhegger B. Quantitative Computed Tomography: What Clinical Questions Can it Answer in Chronic Lung Disease? Lung 2022. [PMID: 35751660 DOI: 10.1007/s00408-022-00550-1] [Reference Citation Analysis]
21 Barrera CA, Andronikou S, Tapia IE, White AM, Biko DM, Rapp JB, Zhu X, Otero HJ. Normal age-related quantitative CT values in the pediatric lung: from the first breath to adulthood. Clin Imaging 2021;75:111-8. [PMID: 33524938 DOI: 10.1016/j.clinimag.2020.12.021] [Reference Citation Analysis]