A Quantitative Comparison of Contrast-To-Noise in Rib Suppressed Images
J Luce*, T Bray, J Roeske, Loyola Univ Medical Center, Maywood, ILSU-E-J-25 Sunday 3:00PM - 6:00PM Room: Exhibit Hall
Purpose: To compare the contrast to noise ratio (CNR) of two different rib suppression methodologies - dual-energy (DE) image subtraction and blind signal separation (BSS)- used for lung cancer patients receiving image-guided radiotherapy.
Methods: A database consisting of 28 planar radiographs obtained at 60 kVp and 120 kVp were used in this study. DE subtraction imaging was performed by taking a weighted logarithmic subtraction of the individual images. A weighting parameter of 2.1 was chosen to produce the optimal soft tissue (rib suppressed) images for each image pair. Similarly, BSS was used to extract the soft tissue and bony image components from a patient image. An open source program for performing BSS, called FastICA, was used in conjunction with the same 60 kVp and 120 kVp images. Regions of interest (ROIs) were contoured on the resultant images and the CNR from each technique was calculated and compared.
Results: A paired t-test was run on the CNR values, resulting in a p value < 0.05, indicated there was a statistically significant difference in the CNRs generated by the two methods. For 24 of the 28 image sets that were evaluated, the CNR values were found to be higher for the DE subtraction images. Of these 24 images, 9 had CNR values > 20% higher, and 4 had CNR values > 40% higher.
Conclusion: Based on this study, DE image subtraction creates images with higher CNR values than those generated with FastICA. This is likely due, at least in part, to the ability to customize the weighting factor of the DE subtraction images. However, there are numerous methods for performing BSS outside of FastICA, and further study is warranted to determine if alternative BSS methods could produce better rib suppressed images.
Funding Support, Disclosures, and Conflict of Interest: This research was supported by Varian Medical Systems.