Complexity in applying spatial analysis to describe heterogeneous air-trapping in thoracic imaging data

References

• L. Anselin, Spatial Econometrics: Methods and Models, Kluwer Academic Publishers, Dordrecht, 1988.
   Google Scholar
• S. Banerjee, B.P. Carlin, and A.E. Gelfand, Hierarchical Modeling and Analysis for Spatial Data, 2nd ed., CRC Press, Boca Raton, 2015.
   Google Scholar
• R. Bivand, M. Altman, L. Anselin, R. Assunção, O. Berke, A. Bernat, G. Blanchet, E. Blankmeyer, M. Carvalho, B. Christensen, Y. Chun, C. Dormann, S. Dray, V. Gómez-Rubio, M. Gubri, R. Halbersma, E. Krainski, P. Legendre, N. Lewin-Koh, H. Li, J. Ma, A. Mallik, G. Millo, W. Mueller, H. Ono, P. Peres-Neto, G. Piras, M. Reder, M. Tiefelsdorf, and D. Yu, spdep: Spatial Dependence: Weighting Schemes, Statistics and Models, R package version 0.5-56, 2013. Package available at http://CRAN.R-project.org/package=spdep.
   Google Scholar
• M. Castro, S.B. Fain, E.A. Hoffman, D.S. Gierada, S.C. Erzurum, and S. Wenzel, Lung imaging in asthmatic patients: The picture is clearer, J. Allergy Clin. Immunol. 128 (2011), pp. 467–478.
   PubMed Web of Science ®Google Scholar
• A.D. Cliff and J.K. Ord, Spatial Processes – Models and Applications, Pion, London, 1981.
   Google Scholar
• R.C. Geary, The contiguity ratio and statistical mapping, Incorporated Statist. 5 (1954), pp. 115–145.
   Google Scholar
• W.G.M. Geraets, Comparison of two methods for measuring orientation, Bone 23 (1998), pp. 383–388.
   PubMed Web of Science ®Google Scholar
• A. Getis, Reflections on spatial autocorrelation, Reg. Sci. Urban Econ. 37 (2007), pp. 491–496.
   Web of Science ®Google Scholar
• H.L. Gillis and K.R. Lutchen, Airway remodeling in asthma amplifies heterogeneities in smooth muscle shortening causing hyperresponsiveness, J. Appl. Physiol. 86 (1999), pp. 2001–2012.
   PubMed Web of Science ®Google Scholar
• D.A. Griffith, Spatial Autocorrelation: A Primer, Resource Publications in Geography, PA, 1987.
   Google Scholar
• C.L. Jackson and J.F. Huber, Correlated applied anatomy of the bronchial tree and lungs With a system of nomenclature, Diseases of the Chest 9 (1943), pp. 319–326.
   Google Scholar
• F. Jin and L. Lee, Exploring spatial dependence – starting from Moran’s I and the APLE statistics, 20th annual meetings of the Midwest econometrics Group, Ohio State University, 2010.
   Google Scholar
• M.A. Konerding, B.C. Gibney, J.P. Houdek, K. Chamoto, M. Ackermann, G.S. Lee, M. Lin, A. Tsuda, and S.J. Mentzer, Spatial dependence of alveolar angiogenesis in post-pneumonectomy lung growth, Angiogenesis 15 (2012), pp. 23–32.
   PubMed Web of Science ®Google Scholar
• P.V.A. Krishna Iyer, The first and second moments of some probability distributions arising from points on a lattice, and their applications, Biometrika 36 (1949), pp. 135–141.
   PubMed Web of Science ®Google Scholar
• D. Larsson, B. Luisier, M.E. Kersh, E. Dall’Ara, P.K. Zysset, M.G. Pandy, and D.H. Pahr, Assessment of transverse isotropy in clinical-level CT images of trabecular bone using the gradient structure tensor, Ann. Biomed. Eng. 42 (2014), pp. 950–959.
   PubMed Web of Science ®Google Scholar
• H. Li, C. Calder, and N. Cressie, Beyond Moran’s I: Testing for spatial dependence based on the spatial autoregressive model, Geogr. Anal. 39 (2007), pp. 357–375.
   Web of Science ®Google Scholar
• K.R. Lutchen, A. Jensen, H. Atileh, D.W. Kaczka, E. Israel, B. Suki, and E.P. Ingenito, Airway constriction pattern is a central component of asthma severity, Am. J. Respir. Crit. Care Med. 164(2) (2001), pp. 207–215.
   PubMed Web of Science ®Google Scholar
• P.A.P. Moran, Notes on continuous stochastic phenomena, Biometrika 37 (1950), pp. 17–23.
   PubMed Web of Science ®Google Scholar
• N.L. Muller, C.A. Staples, R.R. Miller, and R.T. Abboud, ‘Density mas’. An objective method to quantitate emphysema using computed tomography, Chest 94 (1988), pp. 782–787.
   PubMed Web of Science ®Google Scholar
• R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, 2013. Available at http://www.R-project.org/.
   Google Scholar
• M. Rotter, A. Berg, H. Langenberger, S. Grampp, H. Imhof, and E. Moser, Autocorrelation analysis of bone structure, J. Magn. Reson. Imging 14 (2001), pp. 87–93.
   PubMed Web of Science ®Google Scholar
• R.R. Sokal and N.L. Oden, Spatial autocorrelation in biology I: Methodology, Biol. J. Linn. Soc. 10 (1978), pp. 199–228.
   Web of Science ®Google Scholar
• Z. Tabor, On the equivalence of two methods of determining fabric tensor, Med. Eng. Phys. 31 (2009), pp. 1313–1322.
   PubMed Web of Science ®Google Scholar
• D.P. Tashkin, The role of small airway inflammation in asthma, Allergy Asthma Proc. 23 (2002), pp. 233–242.
   PubMed Web of Science ®Google Scholar
• N.T. Tgavalekos, M. Tawhai, R.S. Harris, G. Musch, M. Vidal-Melo, J.G. Venegas, and K.R. Lutchen, Identifying airways responsible for heterogeneous ventilation and mechanical dysfunction in asthma: An image functional modeling approach, J. Appl. Physiol. 99 (2005), pp. 2388–2397.
   PubMed Web of Science ®Google Scholar
• Y.S. Tzeng, K. Lutchen, and M. Albert, The difference in ventilation heterogeneity between asthmatic and healthy subjects quantified using hyperpolarized 3He MRI, J. Appl. Physiol. 106 (2009), pp. 813–822.
   PubMed Web of Science ®Google Scholar
• J.C. Veen, A.J. Beekman, E.H. Bel, and P.J. Sterk, Recurrent exacerbations in severe asthma are associated with enhanced airway closure during stable episodes, Am. J. Respir. Crit. Care Med. 161 (2000), pp. 1902–1906.
   PubMed Web of Science ®Google Scholar
• M.J. Wald, J.F. Magland, C.S. Rajapakse, and F.W. Wehrli, Structural and mechanical parameters of trabecular bone estimated from in vivo high-resolution magnetic resonance images at 3 Tesla field strength, J. Magn. Reson. Imaging 31 (2010), pp. 1157–1168.
   PubMed Web of Science ®Google Scholar
• M. Wald, B. Vasilic, P.K. Saha, and F.W. Wehrli, Study of trabecular bone microstructure using spatial autocorrelation analysis, in Physiology, Function, and Structure from Medical Images, A.A. Amini and A. Manduca, eds., Proceedings of SPIE Vol. 5746, Medical Imaging, San Diego, CA, 2005.
   Google Scholar
• M.J. Wald, B. Vasilic, P.K. Saha, and F.W. Wehrli, Spatial auto-correlation and mean intercept length analysis of trabecular bone anisotropy applied to in vivo magnetic resonance imaging, Med. Phys. 34 (2007), pp. 1110–1120.
   PubMed Web of Science ®Google Scholar
• C. Yilmaz, D.M. Dane, N.C. Patel, and C.C.W. Hsia, Quantifying heterogeneity in emphysema from high-resolution computed tomography: A lung tissue research consortium study, Acad. Radiol. 20 (2013), pp. 181–193.
   PubMed Web of Science ®Google Scholar
• C. Yilmaz, P. Ravikumar, D.M. Dane, D.J. Bellotto, R.L. Johnson, and C.C.W. Hsia, Noninvasive quantification of heterogeneous lung growth following extensive lung resection by high-resolution computed tomography, J. Appl. Physiol. 107 (2009), pp. 1569–1578.
   PubMed Web of Science ®Google Scholar
• C. Yilmaz, S.S. Watharkar, A. Diaz de Leon, C.K. Garcia, N.C. Patel, K.G. Jordan, and C.C.W. Hsia, Quantification of regional interstitial lung disease from CT-derived fractional tissue volume: A lung tissue research consortium study, Acad. Radiol. 18 (2011), pp. 1014–1023.
   PubMed Web of Science ®Google Scholar
• M.R. Zeidler, E.C. Kleerup, J.G. Goldin, H.J. Kim, D.A. Truong, M.D. Simmons, J.W. Sayre, W. Liu, R. Elashoff, and D.P. Tashkin, Montelukast improves regional air-trapping due to small airways obstruction in asthma, Eur. Respir. J. 27 (2006), pp. 307–315.
   PubMed Web of Science ®Google Scholar