Kurugol S, Washko GR, Estepar RSJ.
RANKING AND CLASSIFICATION OF MONOTONIC EMPHYSEMA PATTERNS WITH A MULTI-CLASS HIERARCHICAL APPROACH. Proc IEEE Int Symp Biomed Imaging 2014;2014:1031-1034.
AbstractEmphysema has distinct and well-defined visually apparent CT patterns called centrilobular and panlobular emphysema. Existing studies concentrated on the classification of these patterns but they have not looked at the complete evolution of this disease as the destruction of lung parenchyma progresses from normal lung tissue to mild, moderate, and severe disease with complete effacement of the lung architecture. In this paper, we discretize this continuous process into five classes of increasing disease severity and construct a training set of 1161 CT patches. We exploit three solutions to this monotonic multi-class classification problem: a global rankSVM for ranking, hierarchical SVM for classification and a combination of these two, which we call a hierarchical rankSVM. Results showed that both hierarchical approaches were computationally efficient. The classification accuracies were slightly better for hierarchical SVM. However, in addition to classification, ranking approaches also provided a ranking of patterns, which can be utilized as a continuous disease progression score. In terms of the classification accuracy and ratio of pair-wise constraints satisfied, hierarchical rankSVM outperformed the global rankSVM.
biomedical_imaging_isbi_2014_ieee_11th_international_symposium_on_2014_kurugol-1.pdf Castaldi PJ, Cho MH, San José Estépar R, McDonald M-LN, Laird N, Beaty TH, Washko G, Crapo JD, Silverman EK.
Genome-wide association identifies regulatory Loci associated with distinct local histogram emphysema patterns. Am J Respir Crit Care Med 2014;190(4):399-409.
AbstractRATIONALE: Emphysema is a heritable trait that occurs in smokers with and without chronic obstructive pulmonary disease. Emphysema occurs in distinct pathologic patterns, but the genetic determinants of these patterns are unknown.
OBJECTIVES: To identify genetic loci associated with distinct patterns of emphysema in smokers and investigate the regulatory function of these loci.
METHODS: Quantitative measures of distinct emphysema patterns were generated from computed tomography scans from smokers in the COPDGene Study using the local histogram emphysema quantification method. Genome-wide association studies (GWAS) were performed in 9,614 subjects for five emphysema patterns, and the results were referenced against enhancer and DNase I hypersensitive regions from ENCODE and Roadmap Epigenomics cell lines.
MEASUREMENTS AND MAIN RESULTS: Genome-wide significant associations were identified for seven loci. Two are novel associations (top single-nucleotide polymorphism rs379123 in MYO1D and rs9590614 in VMA8) located within genes that function in cell-cell signaling and cell migration, and five are in loci previously associated with chronic obstructive pulmonary disease susceptibility (HHIP, IREB2/CHRNA3, CYP2A6/ADCK, TGFB2, and MMP12). Five of these seven loci lay within enhancer or DNase I hypersensitivity regions in lung fibroblasts or small airway epithelial cells, respectively. Enhancer enrichment analysis for top GWAS associations (single-nucleotide polymorphisms associated at P < 5 × 10(-6)) identified multiple cell lines with significant enhancer enrichment among top GWAS loci, including lung fibroblasts.
CONCLUSIONS: This study demonstrates for the first time genetic associations with distinct patterns of pulmonary emphysema quantified by computed tomography scan. Enhancer regions are significantly enriched among these GWAS results, with pulmonary fibroblasts among the cell types showing the strongest enrichment.