Minho Lee PhD, Abstract Co-Author: Nothing to Disclose

Taekjin Jang, Presenter: Nothing to Disclose

Namkug Kim PhD, Abstract Co-Author: Stockholder, Coreline Soft, Inc

Sang Min Lee MD, Abstract Co-Author: Nothing to Disclose

Joon Beom Seo MD, PhD, Abstract Co-Author: Nothing to Disclose

Sang Young Oh MD, Abstract Co-Author: Nothing to Disclose

In patients with chronic obstructive pulmonary disease (COPD), robust size based emphysema analysis is of importance, because size of emphysema cluster would be a surrogate imaging biomarker of etiology and progress of COPD, resulting in the morphological change of the emphysema. In this study, we developed a quantitative analysis on fine-scale size based emphysema in volumetric CT.

Volumetric CT scans of sixty patients with COPD were performed by a more than 16 MDCT scanner (Siemens Sensation 16 and 64) within 0.75mm collimation. Using thresholding by -950 HU, emphysema index (EI) of low attenuation area (LAA) mask within lung except airway was evaluated. Based on these LAA masks, a length scale analysis to estimate each emphysema cluster’s size was performed as follows. At first, Gaussian low pass filter from 30mm to 1mm kernel size with 1mm interval was performed iteratively. No changed voxel in the filtered volume was selected and dilated by the size of the kernel, regarded as the specific size emphysema cluster. In this way, emphysema clusters with specific size range was differentiated and evaluated. The power law D of area and number of size based emphysema cluster (slope of log-log plot) were evaluated and compared with pulmonary function test (PFT). All PFT parameters including DLco, FEV1, and FEV1/FVC were significantly correlated with D (r-values, -0.73, 0.54, 0.69, respectively) and EI (r-values, -0.84, -0.60, -0.68, respectively). In addition, D independently contributed regression for FEV1, FEV1/FVC (adjust R sq.: EI only, 0.70, 0.45; EI and D, 0.71, 0.51, respectively). In addition, size based emphysema clusters was visualized.

Size based emphysema cluster segmentation and analysis evaluated the Ds of area, number, density histogram, extent, and distribution of size based emphysema cluster, which would be an independent factors for predictor of PFT parameters.

In conclusion, we developed the size based emphysema cluster segmentation and analysis platform, which would be useful for estimation of PFT parameters.

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Lee, M, Jang, T, Kim, N, Lee, S, Seo, J, Oh, S, Development of Fine-scale Size based Emphysema Cluster Segmentation and Analysis Platform using Length Scale and Unsupervised Clustering.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14017327.html