Systematic assessment with I-SCAN magnification endoscopy and acetic acid improves dysplasia detection in patients with Barrett's esophagus

BACKGROUND AND STUDY AIMS: Enhanced endoscopic imaging with chromoendoscopy may improve dysplasia recognition in patients undergoing assessment of Barrett's esophagus (BE). This may reduce the need for random biopsies to detect more dysplasia. The aim of this study was to assess the effect of magnification endoscopy with I-SCAN (Pentax, Tokyo, Japan) and acetic acid (ACA) on dysplasia detection in BE using a novel mucosal and vascular classification system. METHODS: BE segments and suspicious lesions were recorded with high definition white-light and magnification endoscopy enhanced using all I-SCAN modes in combination. We created a novel mucosal and vascular classification system based on similar previously validated classifications for narrow-band imaging (NBI). A total of 27 videos were rated before and after ACA application. Following validation, a further 20 patients had their full endoscopies recorded and analyzed to model use of the system to detect dysplasia in a routine clinical scenario. RESULTS: The accuracy of the I-SCAN classification system for BE dysplasia improved with I-SCAN magnification from 69 % to 79 % post-ACA (P = 0.01). In the routine clinical scenario model in 20 new patients, accuracy of dysplasia detection increased from 76 % using a "pull-through" alone to 83 % when ACA and magnification endoscopy were combined (P = 0.047). Overall interobserver agreement between experts for dysplasia detection was substantial (0.69). CONCLUSIONS: A new I-SCAN classification system for BE was validated against similar systems for NBI with similar outcomes. When used in combination with magnification and ACA, the classification detected BE dysplasia in clinical practice with good accuracy.Trials registered at ISRCTN (58235785)

A deep learning system for detection of early Barrett's neoplasia:a model development and validation study

BACKGROUND: Computer-aided detection (CADe) systems could assist endoscopists in detecting early neoplasia in Barrett's oesophagus, which could be difficult to detect in endoscopic images. The aim of this study was to develop, test, and benchmark a CADe system for early neoplasia in Barrett's oesophagus.METHODS: The CADe system was first pretrained with ImageNet followed by domain-specific pretraining with GastroNet. We trained the CADe system on a dataset of 14 046 images (2506 patients) of confirmed Barrett's oesophagus neoplasia and non-dysplastic Barrett's oesophagus from 15 centres. Neoplasia was delineated by 14 Barrett's oesophagus experts for all datasets. We tested the performance of the CADe system on two independent test sets. The all-comers test set comprised 327 (73 patients) non-dysplastic Barrett's oesophagus images, 82 (46 patients) neoplastic images, 180 (66 of the same patients) non-dysplastic Barrett's oesophagus videos, and 71 (45 of the same patients) neoplastic videos. The benchmarking test set comprised 100 (50 patients) neoplastic images, 300 (125 patients) non-dysplastic images, 47 (47 of the same patients) neoplastic videos, and 141 (82 of the same patients) non-dysplastic videos, and was enriched with subtle neoplasia cases. The benchmarking test set was evaluated by 112 endoscopists from six countries (first without CADe and, after 6 weeks, with CADe) and by 28 external international Barrett's oesophagus experts. The primary outcome was the sensitivity of Barrett's neoplasia detection by general endoscopists without CADe assistance versus with CADe assistance on the benchmarking test set. We compared sensitivity using a mixed-effects logistic regression model with conditional odds ratios (ORs; likelihood profile 95% CIs).FINDINGS: Sensitivity for neoplasia detection among endoscopists increased from 74% to 88% with CADe assistance (OR 2·04; 95% CI 1·73-2·42; p&lt;0·0001 for images and from 67% to 79% [2·35; 1·90-2·94; p&lt;0·0001] for video) without compromising specificity (from 89% to 90% [1·07; 0·96-1·19; p=0·20] for images and from 96% to 94% [0·94; 0·79-1·11; ] for video; p=0·46). In the all-comers test set, CADe detected neoplastic lesions in 95% (88-98) of images and 97% (90-99) of videos. In the benchmarking test set, the CADe system was superior to endoscopists in detecting neoplasia (90% vs 74% [OR 3·75; 95% CI 1·93-8·05; p=0·0002] for images and 91% vs 67% [11·68; 3·85-47·53; p&lt;0·0001] for video) and non-inferior to Barrett's oesophagus experts (90% vs 87% [OR 1·74; 95% CI 0·83-3·65] for images and 91% vs 86% [2·94; 0·99-11·40] for video).INTERPRETATION: CADe outperformed endoscopists in detecting Barrett's oesophagus neoplasia and, when used as an assistive tool, it improved their detection rate. CADe detected virtually all neoplasia in a test set of consecutive cases.FUNDING: Olympus.</p

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

Towards a robust and compact deep learning system for primary detection of early Barrett’s neoplasia: Initial image-based results of training on a multi-center retrospectively collected data set

Introduction: Endoscopic detection of early neoplasia in Barrett's esophagus is difficult. Computer Aided Detection (CADe) systems may assist in neoplasia detection. The aim of this study was to report the first steps in the development of a CADe system for Barrett's neoplasia and to evaluate its performance when compared with endoscopists. Methods: This CADe system was developed by a consortium, consisting of the Amsterdam University Medical Center, Eindhoven University of Technology, and 15 international hospitals. After pretraining, the system was trained and validated using 1.713 neoplastic (564 patients) and 2.707 non-dysplastic Barrett's esophagus (NDBE; 665 patients) images. Neoplastic lesions were delineated by 14 experts. The performance of the CADe system was tested on three independent test sets. Test set 1 (50 neoplastic and 150 NDBE images) contained subtle neoplastic lesions representing challenging cases and was benchmarked by 52 general endoscopists. Test set 2 (50 neoplastic and 50 NDBE images) contained a heterogeneous case-mix of neoplastic lesions, representing distribution in clinical practice. Test set 3 (50 neoplastic and 150 NDBE images) contained prospectively collected imagery. The main outcome was correct classification of the images in terms of sensitivity. Results: The sensitivity of the CADe system on test set 1 was 84%. For general endoscopists, sensitivity was 63%, corresponding to a neoplasia miss-rate of one-third of neoplastic lesions and a potential relative increase in neoplasia detection of 33% for CADe-assisted detection. The sensitivity of the CADe system on test sets 2 and 3 was 100% and 88%, respectively. The specificity of the CADe system varied for the three test sets between 64% and 66%. Conclusion: This study describes the first steps towards the establishment of an unprecedented data infrastructure for using machine learning to improve the endoscopic detection of Barrett's neoplasia. The CADe system detected neoplasia reliably and outperformed a large group of endoscopists in terms of sensitivity

Gaia Data Release 1: Testing parallaxes with local Cepheids and RR Lyrae stars

Context. Parallaxes for 331 classical Cepheids, 31 Type II Cepheids, and 364 RR Lyrae stars in common between Gaia and the Hipparcos and Tycho-2 catalogues are published in Gaia Data Release 1 (DR1) as part of the Tycho-Gaia Astrometric Solution (TGAS). Aims. In order to test these first parallax measurements of the primary standard candles of the cosmological distance ladder, which involve astrometry collected by Gaia during the initial 14 months of science operation, we compared them with literature estimates and derived new period-luminosity (PL), period-Wesenheit (PW) relations for classical and Type II Cepheids and infrared PL, PL-metallicity (PLZ), and optical luminosity-metallicity (M V -[Fe/H]) relations for the RR Lyrae stars, with zero points based on TGAS. Methods. Classical Cepheids were carefully selected in order to discard known or suspected binary systems. The final sample comprises 102 fundamental mode pulsators with periods ranging from 1.68 to 51.66 days (of which 33 with σ Ω /Ω < 0.5). The Type II Cepheids include a total of 26 W Virginis and BL Herculis stars spanning the period range from 1.16 to 30.00 days (of which only 7 with σ Ω /Ω < 0.5). The RR Lyrae stars include 200 sources with pulsation period ranging from 0.27 to 0.80 days (of which 112 with σ Ω /Ω < 0.5). The new relations were computed using multi-band (V,I,J,K s ) photometry and spectroscopic metal abundances available in the literature, and by applying three alternative approaches: (i) linear least-squares fitting of the absolute magnitudes inferred from direct transformation of the TGAS parallaxes; (ii) adopting astrometry-based luminosities; and (iii) using a Bayesian fitting approach. The last two methods work in parallax space where parallaxes are used directly, thus maintaining symmetrical errors and allowing negative parallaxes to be used. The TGAS-based PL,PW,PLZ, and M V - [Fe/H] relations are discussed by comparing the distance to the Large Magellanic Cloud provided by different types of pulsating stars and alternative fitting methods. Results. Good agreement is found from direct comparison of the parallaxes of RR Lyrae stars for which both TGAS and HST measurements are available. Similarly, very good agreement is found between the TGAS values and the parallaxes inferred from the absolute magnitudes of Cepheids and RR Lyrae stars analysed with the Baade-Wesselink method. TGAS values also compare favourably with the parallaxes inferred by theoretical model fitting of the multi-band light curves for two of the three classical Cepheids and one RR Lyrae star, which were analysed with this technique in our samples. The K-band PL relations show the significant improvement of the TGAS parallaxes for Cepheids and RR Lyrae stars with respect to the Hipparcos measurements. This is particularly true for the RR Lyrae stars for which improvement in quality and statistics is impressive. Conclusions. TGAS parallaxes bring a significant added value to the previous Hipparcos estimates. The relations presented in this paper represent the first Gaia-calibrated relations and form a work-in-progress milestone report in the wait for Gaia-only parallaxes of which a first solution will become available with Gaia Data Release 2 (DR2) in 2018. © ESO, 2017

Gaia Data Release 1: Open cluster astrometry: performance, limitations, and future prospects

Context. The first Gaia Data Release contains the Tycho-Gaia Astrometric Solution (TGAS). This is a subset of about 2 million stars for which, besides the position and photometry, the proper motion and parallax are calculated using Hipparcos and Tycho-2 positions in 1991.25 as prior information.Aims. We investigate the scientific potential and limitations of the TGAS component by means of the astrometric data for open clusters.Methods. Mean cluster parallax and proper motion values are derived taking into account the error correlations within the astrometric solutions for individual stars, an estimate of the internal velocity dispersion in the cluster, and, where relevant, the effects of the depth of the cluster along the line of sight. Internal consistency of the TGAS data is assessed.Results. Values given for standard uncertainties are still inaccurate and may lead to unrealistic unit-weight standard deviations of least squares solutions for cluster parameters. Reconstructed mean cluster parallax and proper motion values are generally in very good agreement with earlier HIPPARCOS-based determination, although the Gaia mean parallax for the Pleiades is a significant exception. We have no current explanation for that discrepancy. Most clusters are observed to extend to nearly 15 pc from the cluster centre, and it will be up to future Gaia releases to establish whether those potential cluster-member stars are still dynamically bound to the clusters.Conclusions. The Gaia DR1 provides the means to examine open clusters far beyond their more easily visible cores, and can provide membership assessments based on proper motions and parallaxes. A combined HR diagram shows the same features as observed before using the HIPPARCOS data, with clearly increased luminosities for older A and F dwarfs

The Gaia mission

Gaia is a cornerstone mission in the science programme of the EuropeanSpace Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page. http://www.cosmos.esa.int/gai

Narrow band imaging and serology in the assessment of premalignant gastric pathology

BACKGROUND: Patient outcomes in gastric adenocarcinoma are poor due to late diagnosis. Detecting and treating at the premalignant stage has the potential to improve this. Helicobacter pylori is also a strong risk factor for this disease. AIMS: Primary aims were to assess the diagnostic accuracy of magnified narrow band imaging (NBI-Z) endoscopy and serology in detecting normal mucosa, H. pylori gastritis and gastric atrophy. Secondary aims were to compare the diagnostic accuracies of two classification systems using both NBI-Z and white light endoscopy with magnification (WLE-Z) and evaluate the inter-observer agreement. METHODS: Patients were prospectively recruited. Images of gastric mucosa were stored with histology and serum for IgG H. pylori and Pepsinogen (PG) I/II ELISAs. Blinded expert endoscopists agreed on mucosal pattern. Mucosal images and serological markers were compared with histology. Kappa statistics determined inter-observer variability for randomly allocated images among four experts and four non-experts. RESULTS: 116 patients were prospectively recruited. Diagnostic accuracy of NBI-Z for determining normal gastric mucosa was 0.87(95%CI 0.82-0.92), H. pylori gastritis 0.65(95%CI 0.55-0.75) and gastric atrophy 0.88(95%CI 0.81-0.94). NBI-Z was superior to serology at detecting gastric atrophy: NBI-Z gastric atrophy 0.88(95%CI 0.81-0.94) vs PGI/II ratio < 3 0.74(95%CI 0.62-0.85) p<.0001. Overall NBI-Z was superior to WLE-Z in detecting disease using two validated classifications. Inter-observer agreement was 0.63(95%CI 0.51-0.73). CONCLUSIONS: NBI-Z accurately detects changes in the GI mucosa which currently depend on histology. NBI-Z is useful in the detection of precancerous conditions, potentially improving patient outcomes with early intervention to prevent gastric cancer

Radiofrequency ablation for low-grade dysplasia in Barrett's esophagus: long-term outcome of a randomized trial

Background and Aims: A prior randomized study (Surveillance versus Radiofrequency Ablation study [SURF study]) demonstrated that radiofrequency ablation (RFA) of Barrett's esophagus (BE) with confirmed low-grade dysplasia (LGD) significantly reduces the risk of esophageal adenocarcinoma. Our aim was to report the long-term outcomes of this study. Methods: The SURF study randomized BE patients with confirmed LGD to RFA or surveillance. For this retrospective cohort study, all endoscopic and histologic data acquired at the end of the SURF study in May 2013 until December 2017 were collected. The primary outcome was rate of progression to high-grade dysplasia (HGD)/cancer. All 136 patients randomized to RFA (n = 68) or surveillance (n = 68) in the SURF study were included. After closure of the SURF study, 15 surveillance patients underwent RFA based on patient preference and study outcomes. Results: With 40 additional months (interquartile range, 12-51), the total median follow-up from randomization to last endoscopy was 73 months (interquartile range, 46-85). HGD/cancer was diagnosed in 1 patient in the RFA group (1.5%) and in 23 in the surveillance group (33.8%) (P = .000), resulting in an absolute risk reduction of 32.4% (95% confidence interval [CI], 22.4%-44.2%) with a number needed to treat of 3.1 (95% CI, 2.3-4.5). Seventy-five of 83 patients (90%; 95% CI, 82.1%-95.0%) treated with RFA for BE reached complete clearance of BE and dysplasia. BE recurred in 7 of 75 patients (9%; 95% CI, 4.6%-18.0%), mostly minute islands or tongues, and LGD in 3 of 75 (4%; 95% CI, 1.4%-11.1%). Conclusions: RFA of BE with confirmed LGD significantly reduces the risk of malignant progression, with sustained clearance of BE in 91% and LGD in 96% of patients, after a median follow-up of 73 months. (Clinical trial registration number: NTR1198.