title: Improved pulmonary nodule classification utilizing quantitative lung parenchyma features.
abstract: Current computer-aided diagnosis (CAD) models for determining pulmonary nodule malignancy characterize nodule shape, density, and border in computed tomography (CT) data. Analyzing the lung parenchyma surrounding the nodule has been minimally explored. We hypothesize that improved nodule classification is achievable by including features quantified from the surrounding lung tissue. To explore this hypothesis, we have developed expanded quantitative CT feature extraction techniques, including volumetric Laws texture energy measures for the parenchyma and nodule, border descriptors using ray-casting and rubber-band straightening, histogram features characterizing densities, and global lung measurements. Using stepwise forward selection and leave-one-case-out cross-validation, a neural network was used for classification. When applied to 50 nodules (22 malignant and 28 benign) from high-resolution CT scans, 52 features (8 nodule, 39 parenchymal, and 5 global) were statistically significant. Nodule-only features yielded an area under the ROC curve of 0.918 (including nodule size) and 0.872 (excluding nodule size). Performance was improved through inclusion of parenchymal (0.938) and global features (0.932). These results show a trend toward increased performance when the parenchyma is included, coupled with the large number of significant parenchymal features that support our hypothesis: the pulmonary parenchyma is influenced differentially by malignant versus benign nodules, assisting CAD-based nodule characterizations.
authors: University of Iowa, Department of Biomedical Engineering, 3100 Seamans Center for the Engineering Arts and Sciences, Iowa City, Iowa 52242, United States; University of Iowa, Department of Radiology, 200 Hawkins Drive, Iowa City, Iowa 52242, United States; University of Iowa, Holden Comprehensive Cancer Center, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: Samantha K N
authors: SK
authors: Dilger
authors: University of Iowa, Department of Biomedical Engineering, 3100 Seamans Center for the Engineering Arts and Sciences, Iowa City, Iowa 52242, United States; University of Iowa, Department of Radiology, 200 Hawkins Drive, Iowa City, Iowa 52242, United States; University of Iowa, Holden Comprehensive Cancer Center, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: Johanna
authors: J
authors: Uthoff
authors: University of Iowa, Department of Biomedical Engineering, 3100 Seamans Center for the Engineering Arts and Sciences, Iowa City, Iowa 52242, United States; University of Iowa, Department of Radiology, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: Alexandra
authors: A
authors: Judisch
authors: University of Iowa, Department of Biomedical Engineering, 3100 Seamans Center for the Engineering Arts and Sciences, Iowa City, Iowa 52242, United States; University of Iowa, Department of Radiology, 200 Hawkins Drive, Iowa City, Iowa 52242, United States; University of Iowa, Holden Comprehensive Cancer Center, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: Emily
authors: E
authors: Hammond
authors: University of Iowa , Holden Comprehensive Cancer Center, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: Sarah L
authors: SL
authors: Mott
authors: University of Iowa, Holden Comprehensive Cancer Center, 200 Hawkins Drive, Iowa City, Iowa 52242, United States; University of Iowa, Department of Biostatistics, 145 North Riverside Drive, Iowa City, Iowa 52242, United States.
authors: Brian J
authors: BJ
authors: Smith
authors: University of Iowa, Department of Biomedical Engineering, 3100 Seamans Center for the Engineering Arts and Sciences, Iowa City, Iowa 52242, United States; University of Iowa, Department of Radiology, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: John D
authors: JD
authors: Newell
authors: University of Iowa, Department of Biomedical Engineering, 3100 Seamans Center for the Engineering Arts and Sciences, Iowa City, Iowa 52242, United States; University of Iowa, Department of Radiology, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: Eric A
authors: EA
authors: Hoffman
authors: University of Iowa, Department of Biomedical Engineering, 3100 Seamans Center for the Engineering Arts and Sciences, Iowa City, Iowa 52242, United States; University of Iowa, Department of Radiology, 200 Hawkins Drive, Iowa City, Iowa 52242, United States; University of Iowa, Holden Comprehensive Cancer Center, 200 Hawkins Drive, Iowa City, Iowa 52242, United States.
authors: Jessica C
authors: JC
authors: Sieren
keywords: cancer screening; computed tomography; computer-aided diagnosis; lung cancer; lung nodules; lung parenchyma; texture analysis