Rationale: Smoking-related microvascular loss causes end-organ damage in the kidneys, heart, and brain. Basic research suggests a similar process in the lungs, but no large studies have assessed pulmonary microvascular blood flow (PMBF) in early chronic lung disease.Objectives: To investigate whether PMBF is reduced in mild as well as more severe chronic obstructive pulmonary disease (COPD) and emphysema.Methods: PMBF was measured using gadolinium-enhanced magnetic resonance imaging (MRI) among smokers with COPD and control subjects age 50 to 79 years without clinical cardiovascular disease. COPD severity was defined by standard criteria. Emphysema on computed tomography (CT) was defined by the percentage of lung regions below 2950 Hounsfield units (2950 HU) and by radiologists using a standard protocol. We adjusted for potential confounders, including smoking, oxygenation, and left ventricular cardiac output.Measurements and Main Results: Among 144 participants, PMBF was reduced by 30% in mild COPD, by 29% in moderate COPD, and by 52% in severe COPD (all P , 0.01 vs. control subjects). PMBF was reduced with greater percentage emphysema 2950HU and radiologist-defined emphysema, particularly panlobular and centrilobular emphysema (all P < 0.01). Registration of MRI and CT images revealed that PMBF was reduced in mild COPD in both nonemphysematous and emphysematous lung regions. Associations for PMBF were independent of measures of small airways disease on CT and gas trapping largely because emphysema and small airways disease occurred in different smokers.Conclusions: PMBF was reduced in mild COPD, including in regions of lung without frank emphysema, and may represent a distinct pathological process from small airways disease. PMBF may provide an imaging biomarker for therapeutic strategies targeting the pulmonary microvasculature.

Purpose:To evaluate the relationships of right ventricular (RV) and left ventricular (LV) myocardial perfusion reserves with ventricular function and pulmonary hemodynamics in patients with pulmonary arterial hypertension (PAH) by using adenosine stress perfusion cardiac magnetic resonance (MR) imaging. Materials and Methods:This HIPAA-compliant study was institutional review board approved. Twenty-fi ve patients known or suspected to have PAH underwent right heart catheterization and adenosine stress MR imaging on the same day. Sixteen matched healthy control subjects underwent cardiac MR imaging only. RV and LV perfusion values at rest and at adenosine-induced stress were calculated by using the Fermi function model. The MR imaging-derived RV and LV functional data were calculated by using dedicated software. Statistical testing included KruskalWallis tests for continuous data, Spearman rank correlation tests, and multiple linear regression analyses. Results:Seventeen of the 25 patients had PAH: 11 with sclerodermaassociated PAH, and six with idiopathic PAH. The remaining eight patients had scleroderma without PAH. groups. There were signifi cant correlations between biventricular MPRI and both mean pulmonary arterial pressure (mPAP) (RV MPRI: r = 2 0.59, Bonferroni P = .036; LV MPRI: r = 2 0.79, Bonferroni P , .002) and RV stroke work index (RV MPRI: r = 2 0.63, Bonferroni P = .01; LV MPRI: r = 2 0.75, Bonferroni P , .002). In linear regression analysis, mPAP and RV ejection fraction were independent predictors of RV MPRI. mPAP was an independent predictor of LV MPRI. Conclusion:Biventricular vasoreactivity is signifi cantly reduced with PAH and inversely correlated with RV workload and ejection fraction, suggesting that reduced myocardial perfusion reserve may contribute to RV dysfunction in patients with PAH.q RSNA, 2010

Abstract. We introduce a new method for location recovery from pairwise directions that leverages an efficient convex program that comes with exact recovery guarantees, even in the presence of adversarial outliers. When pairwise directions represent scaled relative positions between pairs of views (estimated for instance with epipolar geometry) our method can be used for location recovery, that is the determination of relative pose up to a single unknown scale. For this task, our method yields performance comparable to the state-of-the-art with an order of magnitude speed-up. Our proposed numerical framework is flexible in that it accommodates other approaches to location recovery and can be used to speed up other methods. These properties are demonstrated by extensively testing against state-of-the-art methods for location recovery on 13 large, irregular collections of images of real scenes in addition to simulated data with ground truth.

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Accurate and fast quantification of myocardial blood flow (MBF) with MR first-pass perfusion imaging techniques on a pixel-bypixel basis remains difficult due to relatively long calculation times and noise-sensitive algorithms. In this study, Zierler's central volume principle was used to develop an algorithm for the calculation of MBF with few assumptions on the shapes of residue curves. Simulation was performed to evaluate the accuracy of this algorithm in the determination of MBF. To examine our algorithm in vivo, studies were performed in nine normal dogs. Two first-pass perfusion imaging sessions were performed with the administration of the intravascular contrast agent Gadomer at rest and during dipyridamole-induced vasodilation. Radiolabeled microspheres were injected to measure MBF at the same time. MBF measurements in dogs using MR methods correlated well with the microsphere measurements (R 2 ‫؍‬ 0.96, slope ‫؍‬ 0.9), demonstrating a fair accuracy in the perfusion measurements at rest and during the vasodilation stress. In addition to its accuracy, this method can also be optimized to run relatively fast, providing potential for fast and Quantification of myocardial blood flow (MBF) has been shown to be an effective tool for diagnosing blood flow defects (regional or global myocardium) and monitoring the effectiveness of therapeutic treatment (1-5). In particular, the application of first-pass techniques to each pixel of an image to produce an accurate blood flow map allows visualization of regional differences in blood flow with relatively high resolution, and is a noninvasive approach of assessing the severity of coronary artery blockage (6 -9).MBF is quantified by deconvolving tissue residue curves measured by dynamic first-pass images and by finding the peak of the resulting impulse response. Consequently, the accuracy of a first-pass algorithm depends largely on its ability to represent a wide variety of impulse response curves. For this reason, model-independent algorithms (10,11), which make few assumptions about the shape of the impulse response, are advantageous. However, because model-independent algorithms require curve-fitting of many parameters, they require special techniques to control noise susceptibility (10). One common way of stabilizing these methods is to introduce a set of smoothing constraints with a weight that depends on the noise level of the data. This "regularization method" is similar to applying a low-pass filter (10). While this technique substantially improves the conditioning of the deconvolution, it increases computation time and strong regularization can lead to underestimation of parameters to be measured.In this study we investigated a new model-independent technique that can be performed with relatively few parameters and does not require regularization. Like other quantification methods it utilizes a deconvolution based on Zierler's central volume principle. However, by choosing a simple representation of the impulse response curve we can achieve low noise sensiti...