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For: Tahir BA, Hughes PJ, Robinson SD, Marshall H, Stewart NJ, Norquay G, Biancardi A, Chan H, Collier GJ, Hart KA, Swinscoe JA, Hatton MQ, Wild JM, Ireland RH. Spatial Comparison of CT-Based Surrogates of Lung Ventilation With Hyperpolarized Helium-3 and Xenon-129 Gas MRI in Patients Undergoing Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics 2018;102:1276-86. [DOI: 10.1016/j.ijrobp.2018.04.077] [Cited by in Crossref: 23] [Cited by in F6Publishing: 24] [Article Influence: 4.6] [Reference Citation Analysis]
Number Citing Articles
1 Goodburn RJ, Philippens MEP, Lefebvre TL, Khalifa A, Bruijnen T, Freedman JN, Waddington DEJ, Younus E, Aliotta E, Meliadò G, Stanescu T, Bano W, Fatemi-Ardekani A, Wetscherek A, Oelfke U, van den Berg N, Mason RP, van Houdt PJ, Balter JM, Gurney-Champion OJ. The future of MRI in radiation therapy: Challenges and opportunities for the MR community. Magn Reson Med 2022;88:2592-608. [PMID: 36128894 DOI: 10.1002/mrm.29450] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Astley JR, Biancardi AM, Marshall H, Hughes PJC, Collier GJ, Smith LJ, Eaden JA, Hughes R, Wild JM, Tahir BA. A Dual-Channel Deep Learning Approach for Lung Cavity Estimation From Hyperpolarized Gas and Proton MRI. J Magn Reson Imaging 2022. [PMID: 36373828 DOI: 10.1002/jmri.28519] [Reference Citation Analysis]
3 Ren G, Li B, Lam S, Xiao H, Huang Y, Cheung AL, Lu Y, Mao R, Ge H, Kong F(, Ho W, Cai J. A Transfer Learning Framework for Deep Learning-Based CT-to-Perfusion Mapping on Lung Cancer Patients. Front Oncol 2022;12:883516. [DOI: 10.3389/fonc.2022.883516] [Reference Citation Analysis]
4 Astley JR, Biancardi AM, Hughes PJC, Marshall H, Smith LJ, Collier GJ, Eaden JA, Weatherley ND, Hatton MQ, Wild JM, Tahir BA. Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI. Sci Rep 2022;12:10566. [PMID: 35732795 DOI: 10.1038/s41598-022-14672-2] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
5 Astley JR, Wild JM, Tahir BA. Deep learning in structural and functional lung image analysis. Br J Radiol 2022;95:20201107. [PMID: 33877878 DOI: 10.1259/bjr.20201107] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
6 Niedbalski PJ, Choi J, Hall CS, Castro M. Imaging in Asthma Management. Semin Respir Crit Care Med 2022. [PMID: 35211923 DOI: 10.1055/s-0042-1743289] [Reference Citation Analysis]
7 Ding Y, Yang L, Zhou Q, Bi J, Li Y, Pi G, Wei W, Hu D, Rao Q, Li H, Zhao L, Liu A, Du D, Wang X, Zhou X, Han G, Qing K. A pilot study of function-based radiation therapy planning for lung cancer using hyperpolarized xenon-129 ventilation MRI. J Appl Clin Med Phys 2022;:e13502. [PMID: 35045204 DOI: 10.1002/acm2.13502] [Reference Citation Analysis]
8 Hamedani H, Kadlecek S, Ruppert K, Xin Y, Duncan I, Rizi RR. Ventilation heterogeneity imaged by multibreath wash-ins of hyperpolarized 3 He and 129 Xe in healthy rabbits. J Physiol 2021;599:4197-223. [PMID: 34256417 DOI: 10.1113/JP281584] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
9 Rankine LJ, Wang Z, Kelsey CR, Bier E, Driehuys B, Marks LB, Das SK. Hyperpolarized 129Xe Magnetic Resonance Imaging for Functional Avoidance Treatment Planning in Thoracic Radiation Therapy: A Comparison of Ventilation- and Gas Exchange-Guided Treatment Plans. Int J Radiat Oncol Biol Phys 2021:S0360-3016(21)00871-3. [PMID: 34265395 DOI: 10.1016/j.ijrobp.2021.07.002] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
10 Svenningsen S, McIntosh M, Ouriadov A, Matheson AM, Konyer NB, Eddy RL, McCormack DG, Noseworthy MD, Nair P, Parraga G. Reproducibility of Hyperpolarized 129Xe MRI Ventilation Defect Percent in Severe Asthma to Evaluate Clinical Trial Feasibility. Acad Radiol 2021;28:817-26. [PMID: 32417033 DOI: 10.1016/j.acra.2020.04.025] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 4.5] [Reference Citation Analysis]
11 Matheson AM, Thompson C, Parraga G. Inhaled Gas Magnetic Resonance Imaging: Advances, Applications, Limitations, and New Frontiers. Molecular Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00013-2] [Reference Citation Analysis]
12 Fain SB, Carey K, Barton GP, Sorkness RL. Basics and Clinical Application of the MR Assessment of Ventilation. Medical Radiology 2021. [DOI: 10.1007/978-3-030-43539-4_5] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
13 Marshall H, Stewart NJ, Chan HF, Rao M, Norquay G, Wild JM. In vivo methods and applications of xenon-129 magnetic resonance. Prog Nucl Magn Reson Spectrosc 2021;122:42-62. [PMID: 33632417 DOI: 10.1016/j.pnmrs.2020.11.002] [Cited by in Crossref: 12] [Cited by in F6Publishing: 13] [Article Influence: 4.0] [Reference Citation Analysis]
14 Capaldi DPI, Guo F, Xing L, Parraga G. Pulmonary Ventilation Maps Generated with Free-breathing Proton MRI and a Deep Convolutional Neural Network. Radiology 2021;298:427-38. [PMID: 33289613 DOI: 10.1148/radiol.2020202861] [Cited by in Crossref: 5] [Cited by in F6Publishing: 7] [Article Influence: 1.7] [Reference Citation Analysis]
15 Castillo E, Castillo R, Vinogradskiy Y, Nair G, Grills I, Guerrero T, Stevens C. Technical Note: On the spatial correlation between robust CT-ventilation methods and SPECT ventilation. Med Phys 2020;47:5731-8. [PMID: 33007118 DOI: 10.1002/mp.14511] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
16 Eddy RL, Parraga G. Pulmonary xenon-129 MRI: new opportunities to unravel enigmas in respiratory medicine. Eur Respir J 2020;55:1901987. [PMID: 31699844 DOI: 10.1183/13993003.01987-2019] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 0.8] [Reference Citation Analysis]
17 Westcott A, Capaldi DPI, McCormack DG, Ward AD, Fenster A, Parraga G. Chronic Obstructive Pulmonary Disease: Thoracic CT Texture Analysis and Machine Learning to Predict Pulmonary Ventilation. Radiology 2019;293:676-84. [PMID: 31638491 DOI: 10.1148/radiol.2019190450] [Cited by in Crossref: 13] [Cited by in F6Publishing: 14] [Article Influence: 3.3] [Reference Citation Analysis]
18 Kim M, Doganay O, Matin TN, Povey T, Gleeson FV. CT-based Airway Flow Model to Assess Ventilation in Chronic Obstructive Pulmonary Disease: A Pilot Study. Radiology 2019;293:666-73. [PMID: 31617794 DOI: 10.1148/radiol.2019190395] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 2.8] [Reference Citation Analysis]
19 Szmul A, Matin T, Gleeson FV, Schnabel JA, Grau V, Papież BW. Patch-based lung ventilation estimation using multi-layer supervoxels. Comput Med Imaging Graph 2019;74:49-60. [PMID: 31009928 DOI: 10.1016/j.compmedimag.2019.04.002] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 0.8] [Reference Citation Analysis]
20 Westcott AR, Capaldi DPI, Mccormack DG, Fenster A, Parraga G. Texture analysis of thoracic CT to predict hyperpolarized gas MRI lung function. Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019. [DOI: 10.1117/12.2512851] [Reference Citation Analysis]
21 Tahir BA, Marshall H, Hughes PJC, Brightling CE, Collier G, Ireland RH, Wild JM. Comparison of CT ventilation imaging and hyperpolarised gas MRI: effects of breathing manoeuvre. Phys Med Biol 2019;64:055013. [PMID: 30673634 DOI: 10.1088/1361-6560/ab0145] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
22 Kipritidis J, Tahir BA, Cazoulat G, Hofman MS, Siva S, Callahan J, Hardcastle N, Yamamoto T, Christensen GE, Reinhardt JM, Kadoya N, Patton TJ, Gerard SE, Duarte I, Archibald-Heeren B, Byrne M, Sims R, Ramsay S, Booth JT, Eslick E, Hegi-Johnson F, Woodruff HC, Ireland RH, Wild JM, Cai J, Bayouth JE, Brock K, Keall PJ. The VAMPIRE challenge: A multi-institutional validation study of CT ventilation imaging. Med Phys 2019;46:1198-217. [PMID: 30575051 DOI: 10.1002/mp.13346] [Cited by in Crossref: 38] [Cited by in F6Publishing: 38] [Article Influence: 9.5] [Reference Citation Analysis]
23 Hughes PJC, Smith L, Chan HF, Tahir BA, Norquay G, Collier GJ, Biancardi A, Marshall H, Wild JM. Assessment of the influence of lung inflation state on the quantitative parameters derived from hyperpolarized gas lung ventilation MRI in healthy volunteers. J Appl Physiol (1985) 2019;126:183-92. [PMID: 30412033 DOI: 10.1152/japplphysiol.00464.2018] [Cited by in Crossref: 19] [Cited by in F6Publishing: 20] [Article Influence: 3.8] [Reference Citation Analysis]