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

Semiautomated Renal Cortex Volumetry in Multislice Computed Tomography: Effect of Slice Thickness and Iterative Reconstruction Algorithms

Objective The aim of the study was to evaluate the effect of slice thickness, iterative reconstruction (IR) algorithm, and kernel selection on measurement accuracy and interobserver variability for semiautomated renal cortex volumetry (RCV) with multislice computed tomography (CT). Methods Ten patients (62.4 +/- 17.2 years) undergoing abdominal biphasic multislice computed tomography were enrolled in this retrospective study. Computed tomography data sets were reconstructed at 1-, 2-, and 5-mm slice thickness with 2 different IR algorithms (iDose, IMRST) and 2 different kernels (IMRS and IMRR) (Philips, the Netherlands). Two readers independently performed semiautomated RCV for each reconstructed data set to calculate left kidney volume (LKV) and split renal function (SRF). Statistics were calculated using analysis of variance with Geisser-Greenhouse correction, followed by Tukey multiple comparisons post hoc test. Statistical significance was defined as P = P >= 0.99). Conclusions Semiautomated RCV measurements of LKV and SRF are independent of slice thickness, IR algorithm, and kernel selection. These findings suggest that comparisons between studies using different slice thicknesses and reconstruction algorithms for RCV are valid

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 imaging for the detection of early neoplasia in Barrett's esophagus: old looks or new vision?

Early neoplasia arising from Barrett's esophagus is often small, focally distributed and endoscopically poorly visible, and random four-quandrant biopsies may easily miss early lesions. Advanced imaging techniques, such as (auto)fluorescence-based modalities, aim to increase the detection rate of early lesions or the yield of random biopsies. Fluorescence-based light-tissue interaction has been designed successfully in point-probe differentiating spectroscopy systems or integrated into wide-field endoscopic systems such as autofluorescence imaging (AFI). In this review, we discuss the most recent advances in fluorescence spectroscopy and imaging for detecting early Barrett's neoplasia. A spectroscopy probe, integrated into regular biopsy forceps, was shown to offer decent discriminatory capabilities, while ensuring spot-on correlation between the measured area and the corresponding histology. With this tool, surveillance endoscopy with random biopsies may become more efficient and sensitive. AFI was shown to increase the targeted detection of early neoplasia. However, random biopsies could compensate for this effect. The clinical impact of AFI on the diagnosis and the treatment of early neoplasia is limited, and yet AFI may offer a novel approach in biomarker-based risk-stratification models. Moreover, in combination with new, readily available contrast agents such as fluorescent lectins, fluorescence imaging may receive renewed interes

Bone marrow edema in traumatic vertebral compression fractures: Diagnostic accuracy of dual-layer detector CT using calcium suppressed images

Purpose: To evaluate calcium suppressed images (CaSupp) in dual-layer detector computed tomography (DLCT) for the detection of bone marrow edema (BME) in vertebral fractures. Materials and methods: The retrospective study was approved by the institutional review board. 34 patients with synchronous DLCT and MRI, who were diagnosed with one or more acute vertebral fractures, were included. MRI were systematically analyzed as reference standard. Two blinded and independent readers evaluated CaSupp for vertebral BME. Additionally, both readers determined the optimal calcium suppression indices (CaSupp-I) for visualization of BME in consensus and correlated the CaSupp-I with parallel measurement of trabecular density as surrogate parameter for bone mineral density. ROI-based measurements of the contrast-to-noise ratios (CNR) were also conducted. Interrater agreement was determined by kappa-statistics. CNR were analyzed using Wilcoxon signed rank test. Results: Fifty-seven acute fractured vertebrae out of 383 vertebrae (14.9%) were found. CaSupp yielded an average sensitivity of 87% and specificity of 99%, a positive predictive value of 95%, a negative predictive value of 98% and an accuracy of 97% for the detection of fracture-associated edema. Interrater agreement was excellent (kappa 0.91). Increase in CNR of BME correlated with increasing CaSupp-I. Edema adjacent to the cortical endplates was better visualized using CaSupp-I of 70 and 80, while extensive edema was better visualized using a CaSupp-I of 90 and 100 (chi2 0.2). Conclusion: CaSupp reconstructed from DLCT enable visualization and detection of BME in traumatic fractured vertebrae with high diagnostic accuracy using CaSupp-I of 70-100