Automatic estimation of noise parameters in Fourier-domain optical coherence tomography cross sectional images using statistical information

We present an application and sample independent method for the automatic discrimination of noise and signal in optical coherence tomography Bscans. The proposed algorithm models the observed noise probabilistically and allows for a dynamic determination of image noise parameters and the choice of appropriate image rendering parameters. This overcomes the observer variability and the need for a priori information about the content of sample images, both of which are challenging to estimate systematically with current systems. As such, our approach has the advantage of automatically determining crucial parameters for evaluating rendered image quality in a systematic and task independent way. We tested our algorithm on data from four different biological and nonbiological samples (index finger, lemon slices, sticky tape, and detector cards) acquired with three different experimental spectral domain optical coherence tomography (OCT) measurement systems including a swept source OCT. The results are compared to parameters determined manually by four experienced OCT users. Overall, our algorithm works reliably regardless of which system and sample are used and estimates noise parameters in all cases within the confidence interval of those found by observers.

Standard model cross-over on the lattice

With the physical Higgs mass the standard model symmetry restoration phase transition is a smooth cross-over. We study the thermodynamics of the cross-over using numerical lattice Monte Carlo simulations of an effective SU(2)×U(1) gauge+Higgs theory, significantly improving on previously published results. We measure the Higgs field expectation value, thermodynamic quantities like pressure, energy density, speed of sound and heat capacity, and screening masses associated with the Higgs and Z fields. While the cross-over is smooth, it is very well defined with a width of only ∼5  GeV. We measure the cross-over temperature from the maximum of the susceptibility of the Higgs condensate, with the result Tc=159.5±1.5  GeV. Outside of the narrow cross-over region the perturbative results agree well with nonperturbative ones.

Circulating oxidized low-density lipoprotein is associated with echolucent plaques in the femoral artery independently of hsCRP in 61-year-old men.

OBJECTIVES The aim of the study was to test the hypothesis that circulating markers of inflammation (high-sensitive C-reactive protein, hsCRP) and oxidative modification of lipids (oxidized low-density lipoprotein, oxLDL) were associated with the occurrence of echolucent rather than echogenic femoral artery plaques in a cross-sectional population based cohort of 513, 61-year-old men. BACKGROUND The relationships between circulating oxLDL, hsCRP and the occurrence of echolucent plaques in the femoral artery have not previously been investigated. METHODS The levels of circulating oxLDL and hsCRP were determined in plasma by ELISA. Plaque occurrence, size and echogenicity were measured by B-mode ultrasound in the right femoral artery. Assessment of plaque echogenicity was based on the classification (grades 1-4) proposed by Gray-Weale et al. RESULTS A higher frequency of echolucent femoral plaques was observed in subjects with the metabolic syndrome and current smokers (p=0.01 and p<0.001, respectively) as well as with increasing levels of oxLDL and hsCRP (p=0.002 and p=0.005, respectively). In a multiple logistic regression analysis oxLDL and current smokers turned out to be independent associated with the presence of echolucent femoral artery plaques. CONCLUSIONS The results of the present study support our hypothesis that circulating oxLDL is a marker of an unstable echolucent plaque phenotype in the femoral artery in man.

Further reductions in nonvertebral fracture rate with long-term denosumab treatment in the FREEDOM open-label extension and influence of hip bone mineral density after 3 years

Limited data exist on the efficacy of long-term therapies for osteoporosis. In osteoporotic postmenopausal women receiving denosumab for 7 years, nonvertebral fracture rates significantly decreased in years 4-7 versus years 1-3. This is the first demonstration of a further benefit on fracture outcomes with long-term therapy for osteoporosis. INTRODUCTION This study aimed to evaluate whether denosumab treatment continued beyond 3 years is associated with a further reduction in nonvertebral fracture rates. METHODS Participants who completed the 3-year placebo-controlled Fracture REduction Evaluation of Denosumab in Osteoporosis every 6 Months (FREEDOM) study were invited to participate in an open-label extension. The present analysis includes 4,074 postmenopausal women with osteoporosis (n = 2,343 long-term; n = 1,731 cross-over) who enrolled in the extension, missed ≤1 dose during their first 3 years of denosumab treatment, and continued into the fourth year of treatment. Comparison of nonvertebral fracture rates during years 1-3 of denosumab with that of the fourth year and with the rate during years 4-7 was evaluated. RESULTS For the combined group, the nonvertebral fracture rate per 100 participant-years was 2.15 for the first 3 years of denosumab treatment (referent) and 1.36 in the fourth year (rate ratio [RR] = 0.64; 95 % confidence interval (CI) = 0.48 to 0.85, p = 0.003). Comparable findings were observed in the groups separately and when nonvertebral fracture rates during years 1-3 were compared to years 4-7 in the long-term group (RR = 0.79; 95 % CI = 0.62 to 1.00, p = 0.046). Fracture rate reductions in year 4 were most prominent in subjects with persisting low hip bone mineral density (BMD). CONCLUSIONS Denosumab treatment beyond 3 years was associated with a further reduction in nonvertebral fracture rate that persisted through 7 years of continuous denosumab administration. The degree to which denosumab further reduces nonvertebral fracture risk appears influenced by the hip bone density achieved with initial therapy.

Differentiation of Diabetic Macular Edema From Pseudophakic Cystoid Macular Edema by Spectral-Domain Optical Coherence Tomography.

PURPOSE: To differentiate diabetic macular edema (DME) from pseudophakic cystoid macular edema (PCME) based solely on spectral-domain optical coherence tomography (SD-OCT). METHODS: This cross-sectional study included 134 participants: 49 with PCME, 60 with DME, and 25 with diabetic retinopathy (DR) and ME after cataract surgery. First, two unmasked experts classified the 25 DR patients after cataract surgery as either DME, PCME, or mixed-pattern based on SD-OCT and color-fundus photography. Then all 134 patients were divided into two datasets and graded by two masked readers according to a standardized reading-protocol. Accuracy of the masked readers to differentiate the diseases based on SD-OCT parameters was tested. Parallel to the masked readers, a computer-based algorithm was established using support vector machine (SVM) classifiers to automatically differentiate disease entities. RESULTS: The masked readers assigned 92.5% SD-OCT images to the correct clinical diagnose. The classifier-accuracy trained and tested on dataset 1 was 95.8%. The classifier-accuracy trained on dataset 1 and tested on dataset 2 to differentiate PCME from DME was 90.2%. The classifier-accuracy trained and tested on dataset 2 to differentiate all three diseases was 85.5%. In particular, higher central-retinal thickness/retinal-volume ratio, absence of an epiretinal-membrane, and solely inner nuclear layer (INL)-cysts indicated PCME, whereas higher outer nuclear layer (ONL)/INL ratio, the absence of subretinal fluid, presence of hard exudates, microaneurysms, and ganglion cell layer and/or retinal nerve fiber layer cysts strongly favored DME in this model. CONCLUSIONS: Based on the evaluation of SD-OCT, PCME can be differentiated from DME by masked reader evaluation, and by automated analysis, even in DR patients with ME after cataract surgery. The automated classifier may help to independently differentiate these two disease entities and is made publicly available.