Prevalence of Age-Related Macular Degeneration in Europe: The Past and the Future

Purpose Age-related macular degeneration (AMD) is a frequent, complex disorder in elderly of European ancestry. Risk profiles and treatment options have changed considerably over the years, which may have affected disease prevalence and outcome. We determined the prevalence of early and late AMD in Europe from 1990 to 2013 using the European Eye Epidemiology (E3) consortium, and made projections for the future. Design Meta-analysis of prevalence data. Participants A total of 42 080 individuals 40 years of age and older participating in 14 population-based cohorts from 10 countries in Europe. Methods AMD was diagnosed based on fundus photographs using the Rotterdam Classification. Prevalence of early and late AMD was calculated using random-effects meta-analysis stratified for age, birth cohort, gender, geographic region, and time period of the study. Best-corrected visual acuity (BCVA) was compared between late AMD subtypes; geographic atrophy (GA) and choroidal neovascularization (CNV). Main Outcome Measures Prevalence of early and late AMD, BCVA, and number of AMD cases. Results Prevalence of early AMD increased from 3.5% (95% confidence interval [CI] 2.1%–5.0%) in those aged 55–59 years to 17.6% (95%

Quantitative accuracy of virtual non-contrast images derived from spectral detector computed tomography: an abdominal phantom study

Dual-energy CT allows for the reconstruction of virtual non-contrast (VNC) images. VNC images have the potential to replace true non-contrast scans in various clinical applications. This study investigated the quantitative accuracy of VNC attenuation images considering different parameters for acquisition and reconstruction. An abdomen phantom with 7 different tissue types (different combinations of 3 base materials and 5 iodine concentrations) was scanned using a spectral detector CT (SDCT). Different phantom sizes (S, M, L), volume computed tomography dose indices (CTDIvol 10, 15, 20 mGy), kernel settings (soft, standard, sharp), and denoising levels (low, medium, high) were tested. Conventional and VNC images were reconstructed and analyzed based on regions of interest (ROI). Mean and standard deviation were recorded and differences in attenuation between corresponding base materials and VNC was calculated (VNCerror). Statistic analysis included ANOVA, Wilcoxon test and multivariate regression analysis. Overall, the VNCerror was - 1.4 ± 6.1 HU. While radiation dose, kernel setting, and denoising level did not influence VNCerror significantly, phantom size, iodine content and base material had a significant effect (e.g. S vs. M: - 1.2 ± 4.9 HU vs. - 2.1 ± 6.0 HU; 0.0 mg/ml vs. 5.0 mg/ml: - 4.0 ± 3.5 HU vs. 5.1 ± 5.0 HU and 35-HU-base vs. 54-HU-base: - 3.5 ± 4.4 HU vs. 0.7 ± 6.5; all p ≤ 0.05). The overall accuracy of VNC images from SDCT is high and independent from dose, kernel, and denoising settings; however, shows a dependency on patient size, base material, and iodine content; particularly the latter results in small, yet, noticeable differences in VNC attenuation

Quantification of metal artifacts in computed tomography: methodological considerations

Numerous methods for artifact quantification in computed tomography (CT) imaging have been suggested. This study evaluated their utility with regards to correspondence with visual artifact perception and reproducibility. Two titanium rods (5 and 10 mm) were examined with 25 different scanning- and imagereconstruction parameters resulting in different types and extents of artifacts. Four radiologists evaluated every image against each other using an in-house developed software. Rating was repeated two times (2,400 comparisons = 2 times x 4 readers x 300 comparisons). Rankings were combined to obtain a reference ranking. Proposed approaches for artifact quantification include manual measurement of attenuation, standard deviation and noise and sophisticated algorithm-based approaches within the image- and frequencydomain. Two radiologists conducted manual measurements twice while the aforementioned algorithms were implemented within the Matlab-Environment allowing for automated image analysis. The reference ranking was compared to all aforementioned methods for artifact quantification to identify suited approaches. Besides visual analysis, Kappa-statistics and intraclass correlation coefficients (ICC) were used. Intra- and Interreader agreements of visual artifact perception were excellent (ICC 0.85-0.92). No quantitative method was able to represent the exact ranking of visually perceived artifacts; however, ICC for manual measurements were low (ICC 0.25-0.97). The method that showed best correspondence and reproducibility used a Fouriertransformed linear ROI and lower-end frequency bins. Automated measurements of artifact extent should be preferred over manual measurements as the latter show a limited reproducibility. One method that allows for automated quantification of such artefacts is made available as an electronic supplement

DiODe: Directional Orientation Detection of Segmented Deep Brain Stimulation Leads: A Sequential Algorithm Based on CT Imaging

Background: Directional deep brain stimulation (DBS) allows steering the stimulation in an axial direction which offers greater flexibility in programming. However, accurate anatomical visualization of the lead orientation is required for interpreting the observed stimulation effects and to guide programming. Objectives: In this study we aimed to develop and test an accurate and robust algorithm for determining the orientation of segmented electrodes based on standard postoperative CT imaging used in DBS. Methods: Orientation angles of directional leads (Cartesia (TM); Boston Scientific, Marlborough, MA, USA) were determined using CT imaging. Therefore, a sequential algorithm was developed that quantitatively compares the similarity of the observed CT artifacts with calculated artifact patterns based on the lead's orientation marker and a geometric model of the segmented electrodes. Measurements of seven ground truth phantoms and three leads with 60 different configurations of lead implantation and orientation angles were analyzed for validation. Results: The accuracy of the determined electrode orientation angles was -0.6 +/- 1.5 degrees (range: -5.4 to 4.2 degrees). This accuracy proved to be sufficiently high to resolve even subtle differences between individual leads. Conclusions: The presented algorithm is user independent and provides highly accurate results for the orientation of the segmented electrodes for all angular constellations that typically occur in clinical cases. (C) 2018 S. Karger AG, Base

Precision and reliability of liver iodine quantification from spectral detector CT: evidence from phantom and patient data

ObjectiveTo comprehensively assess precision, reproducibility, and repeatability of iodine maps from spectral detector CT (SDCT) in a phantom and in patients with repetitive examination of the abdomen.MethodsSeventy-seven patients who underwent examination two (n=52) or three (n=25) times according to clinical indications were included in this IRB-approved, retrospective study. The anthropomorphic liver phantom and all patients were scanned with a standardized protocol (SSDE in patients 15.8mGy). In patients, i.v. contrast was administered and portal venous images were acquired using bolus-tracking technique. The phantom was scanned three times at three time points; in one acquisition, image reconstruction was repeated three times. Region of interest (ROI) were placed automatically (phantom) or manually (patients) in the liver parenchyma (mimic) and the portal vein; attenuation in conventional images (CI [HU]) and iodine map concentrations (IM [mg/ml]) were recorded. The coefficient of variation (CV [%]) was used to compare between repetitive acquisitions. If present, additional ROI were placed in cysts (n=29) and hemangioma (n=29).ResultsDifferences throughout all phantom examinations were <2%. In patients, differences between two examinations were higher (CV for CI/IM: portal vein, 2.5%/3.2%; liver parenchyma, -0.5%/-3.0% for CI/IM). In 80% of patients, these differences were within a 20% limit. Differences in benign liver lesions were even higher (68% and 38%, for CI and IM, respectively).ConclusionsIodine maps from SDCT allow for reliable quantification of iodine content in phantoms; while in patients, rather large differences between repetitive examinations are likely due to differences in biological distribution. This underlines the need for careful clinical interpretation and further protocol optimization.Key Points center dot Spectral detector computed tomography allows for reliable quantification of iodine in phantoms.center dot In patients, the offset between repetitive examinations varies by 20%, likely due to differences in biological distribution. center dot Clinically, iodine maps should be interpreted with caution and should take the intra-individual variability of iodine distribution over time into account

Fluorescence characteristics of human Barrett tissue specimens grafted on chick chorioallantoic membrane

To improve (pre)malignant lesion identification in Barrett's esophagus (BE), recent research focuses on new developments in fluorescence imaging and spectroscopy to enhance tissue contrast. Our aim was to validate the chorioallantoic membrane (CAM) model as a preclinical tool to study the fluorescence characteristics such as autofluorescence and exogenously induced fluorescence of human Barrett's tissue. Therefore, esophageal biopsy specimens from Barrett's patients were freshly grafted onto the CAM of fertilized hen's eggs to simulate the in vivo situation. The BE biopsy specimens stayed between 1 and 9 days on the CAM to study the persistence of vitality. Fluorescence spectroscopy was performed using six excitation wavelengths (369, 395, 400, 405, 410, 416 nm). Obtained autofluorescence spectra were compared with in vivo spectra of an earlier study. Exogenous administration of 5-aminolevulinic-acid to the biopsy specimens was followed by fluorescence spectroscopy at several time points. Afterwards, the biopsy specimens were harvested and histologically evaluated. In total, 128 biopsy specimens obtained from 34 patients were grafted on the CAM. Biopsy specimens which stayed on average 1.7 days on the CAM were still vital. Autofluorescence spectra of the specimens correlated well with in vivo spectra. Administered 5-aminolevulinic-acid to the biopsy specimens showed conversion into protoporphyrin-IX. In conclusion, we showed that grafting freshly collected human BE biopsy specimens on the CAM is feasible. Our results suggest that the CAM model might be used to study the fluorescence behavior of human tissue specimens. Therefore, the CAM model might be a preclinical research tool for new photosensitizer