Search

Purpose To determine the accuracy of registration algorithms, using an anthropomorphic digital phantom, in registering unenhanced and enhanced computed tomography (CT) chest images. Methods Lung subtraction CT generates pulmonary iodine maps by subtracting an unenhanced scan from an enhanced scan after image registration. This technique can be useful for detection of pulmonary embolism, characterization of nodule or mass perfusion, or for evaluation of pulmonary lesion growth at follow-up. The LUMIC challenge is aimed at comparing the performance of algorithms in registering simulated enhanced and unenhanced CT images of the XCAT anthropomorphic digital phantom (Duke University, Durham, North Carolina, U.S.A.). The simulated scans are available with two voxel sizes (anisotropic, 0.6 × 0.6 × 1.0 mm3, and isotropic, 1.0 × 1.0 × 1.0 mm3), and with varying differences in diaphragm levels between the CT scans: 3 mm (small difference), 8 mm (average clinical difference), and 20 mm (large difference), all without pulmonary pathology. Since the voxel-by-voxel true displacement between the unenhanced and enhanced phantom realizations is known, the residual error between the estimated displacement field and the known truth can be determined for all lung voxels. Results The results submitted in response to this challenge will be calculated as the median, 25th and 75th percentile of the residual values. Besides these values, whole residual error images will be generated, which will provide position-specific information on the performance of each algorithm. Three algorithms have already been evaluated, resulting in the following residual errors for the large diaphragm-position difference [median (25th – 75th percentile)]: 0.93 mm (0.52 mm – 1.58 mm), 0.92 mm (0.51 mm – 1.57 mm), and 0.93 mm (0.52 mm – 1.60 mm). For all three algorithms, the largest errors were seen in the paracardiac regions and close to the diaphragm. Conclusions This challenge, based on the use of a digital anthropomorphic phantom, is a useful way to not only determine the current performance level of registration algorithms world-wide, but also to directly compare their performance. In addition, given the availability of the resulting error location information, the participants will be able to identify problematic areas for their registration algorithms that might need further improvement. The challenge is available on https://lumic.grand-challenge.org .

Purpose To determine the impact of patient and acquisition parameters on the quantification of the enhancement of pulmonary parenchyma in subtraction computed tomography pulmonary angiography (CTPA) imaging in patients without pulmonary pathology. Methods 2515 patients underwent clinical CTPA with subtraction imaging on a 320-multidetector row CT scanner (Aquilion ONE VISION or GENESIS, Canon Medical Systems Corporation, Japan) between January 2013 and August 2017 for suspicion of pulmonary embolism. In subtraction CT, an unenhanced chest CT is subtracted from an enhanced CT after motion correction, resulting in an iodine map representing pulmonary perfusion. After examination of patient records and images, 74 patients (2.9 %) without any apparent pulmonary or systemic pathology were selected. The mean enhancement in circular regions of interest (ROI) in all lung lobes of the iodine maps, placed to avoid vessels depicted in the CTPA images, were calculated. Patient age, sex, BMI, and smoking habits, as well as CT scan time, diaphragm position and lung volume changes between the unenhanced and enhanced CT, type and volume of contrast, and enhancement in the aortic arch, pulmonary trunk and left atrium were collected. Linear regression analysis was used to evaluate the correlation between the parameters and the measured enhancement. Results The mean enhancement of the ROIs throughout the whole lung was 32.2 ± 21.6 HU. The enhancement in the lower lobes (39.4 ± 24.3 HU) was significantly higher than in the upper lobes (31.7 ± 22.3 HU, p r 2 = 0.54 p 0.001 ) , and with lung volume changes ( r 2 = 0.73 p 0.001 ) between the scans. No correlation was found between the mean enhancement and all other variables studied. Conclusions The enhancement of the pulmonary parenchyma on subtraction CT imaging in patients without pulmonary pathology varies widely. However, normal enhancement values correlate strongly with changes in diaphragm position and in pulmonary volume between scans. This implies that normalization of lung enhancement based on lung volume changes could improve clinical interpretation and would be the first step towards quantification of enhancement in subtraction CT imaging.