Ventilation heterogeneity in smokers: role of unequal lung expansion and peripheral lung structure.

Smoking-induced ventilation heterogeneity measured at the mouth via established washout indices [lung clearance index (LCI) and alveolar mixing efficiency (AME)] potentially results from unequal expansion, which can be quantified by computer tomography (CT), and structural changes down to the lung periphery, characterized by CT parametric response mapping indices [percentage of lung affected by functional small airway disease (PRMfSAD) and emphysema (PRMEmph)]. By combining CT imaging and nitrogen (N2) washout tests in smokers, we specifically examined the roles of unequal lung expansion and peripheral structure. We first extracted three-dimensional maps of local lung expansion from registered inspiratory/expiratory CT images in 50 smokers (GOLD 0-IV) to compute for each smoker the theoretical N2 washout concentration curve solely attributable to unequal local expansion. By a head-on comparison with washout N2 concentrations measured at the mouth in the same smokers supine, we observed that 1) LCI increased from 4.8 ± 0.2 (SD) to 6.6 ± 0.8 (SD) due to unequal lung expansion alone and further increased to 9.0 ± 1.5 (SD) independent of local expansion and 2) AME decreased (from 100% by definition) to 95 ± 2 (SD)% due to unequal expansion alone and further decreased to 75 ± 7(SD)% independent of local expansion. In a multiple regression between the washout indices and CT-derived PRMfSAD and PRMEmph, LCI was related to PRMfSAD (r = +0.58; P < 0.001), whereas AME was related to both PRMfSAD (rpartial = -0.44; P = 0.002) and PRMEmph (rpartial = -0.31; P = 0.033), in line with AME being dominated by alterations in peripheral structure. We conclude that smokers showing an increased LCI without corresponding AME decrease are predominantly affected by unequal lung expansion, whereas an AME decrease with a commensurate LCI increase indicates a smoking-induced alteration of peripheral structure.NEW & NOTEWORTHY A head-on comparison between imaging and multiple breath washout in supine smokers shows that computer tomography-measured unequal local lung expansion accounts for 50% or less of smoking-induced increase in ventilation heterogeneity. The contributions from unequal lung expansion and peripheral structure to the two main washout indices also explain their respective association with parametric response mapping indices.

Intrasubject multimodal groupwise registration with the conditional template entropy.

Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting remains difficult, due to the lack of generally applicable similarity metrics. In this work, a novel similarity metric for such groupwise registration problems is proposed. The metric calculates the sum of the conditional entropy between each image in the group and a representative template image constructed iteratively using principal component analysis. The proposed metric is validated in extensive experiments on synthetic and intrasubject clinical image data. These experiments showed equivalent or improved registration accuracy compared to other state-of-the-art (dis)similarity metrics and improved transformation consistency compared to pairwise mutual information.

Registration strategies for multi-modal whole-body MRI mosaicing.

PURPOSE: To test and compare different registration approaches for performing whole-body diffusion-weighted (wbDWI) image station mosaicing, and its alignment to corresponding anatomical T1 whole-body image. METHODS: Four different registration strategies aiming at mosaicing of diffusion-weighted image stations, and their alignment to the corresponding whole-body anatomical image, were proposed and evaluated. These included two-step approaches, where diffusion-weighted stations are first combined in a pairwise (Strategy 1) or groupwise (Strategy 2) manner and later non-rigidly aligned to the anatomical image; a direct pairwise mapping of DWI stations onto the anatomical image (Strategy 3); and simultaneous mosaicing of DWI and alignment to the anatomical image (Strategy 4). Additionally, different images driving the registration were investigated. Experiments were performed for 20 whole-body images of patients with bone metastases. RESULTS: Strategies 1 and 2 showed significant improvement in mosaicing accuracy with respect to the non-registered images (P < 0.006). Strategy 2 based on ADC images increased the alignment accuracy between DWI stations and the T1 whole-body image (P = 0.0009). CONCLUSIONS: A two-step registration strategy, relying on groupwise mosaicing of the ADC stations and subsequent registration to T1 , provided the best compromise between whole-body DWI image quality and multi-modal alignment. Magn Reson Med 79:1684-1695, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Development and validation of an automated and marker-free CT-based spatial analysis method (CTSA) for assessment of femoral hip implant migration: In vitro accuracy and precision comparable to that of radiostereometric analysis (RSA).

BACKGROUND AND PURPOSE: We developed a marker-free automated CT-based spatial analysis (CTSA) method to detect stem-bone migration in consecutive CT datasets and assessed the accuracy and precision in vitro. Our aim was to demonstrate that in vitro accuracy and precision of CTSA is comparable to that of radiostereometric analysis (RSA). MATERIAL AND METHODS: Stem and bone were segmented in 2 CT datasets and both were registered pairwise. The resulting rigid transformations were compared and transferred to an anatomically sound coordinate system, taking the stem as reference. This resulted in 3 translation parameters and 3 rotation parameters describing the relative amount of stem-bone displacement, and it allowed calculation of the point of maximal stem migration. Accuracy was evaluated in 39 comparisons by imposing known stem migration on a stem-bone model. Precision was estimated in 20 comparisons based on a zero-migration model, and in 5 patients without stem loosening. RESULTS: Limits of the 95% tolerance intervals (TIs) for accuracy did not exceed 0.28 mm for translations and 0.20° for rotations (largest standard deviation of the signed error (SD(SE)): 0.081 mm and 0.057°). In vitro, limits of the 95% TI for precision in a clinically relevant setting (8 comparisons) were below 0.09 mm and 0.14° (largest SD(SE): 0.012 mm and 0.020°). In patients, the precision was lower, but acceptable, and dependent on CT scan resolution. INTERPRETATION: CTSA allows detection of stem-bone migration with an accuracy and precision comparable to that of RSA. It could be valuable for evaluation of subtle stem loosening in clinical practice.