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

The field effect in Barrett's Esophagus: A macroscopic view using white light endoscopy and deep learning

Over the past few decades, primarily developed countries witnessed an increased incidence of esophageal adenocarcinoma (EAC). Screening and surveillance of Barrett's esophagus (BE), which is known to augment the probability of developing EAC, can significantly improve survival rates. This is because early-stage dysplasia in BE can be treated effectively, while each subsequent stage complicates successful treatment and seriously reduces survival rates. This study proposes a convolutional neural network-based algorithm, which classifies images of BE visualized with White Light Endoscopy (WLE) as either dysplastic or non-dysplastic. To this end, we use merely pixels surrounding the dysplastic region, while excluding the pixels covering the dysplastic region itself. The phenomenon where the diagnosis of a patient can be determined from tissue other than the clearly observable diseased area, is termed the field effect. With its potential to identify missed lesions, it may prove to be a helpful innovation in the screening and surveillance process of BE. A statistical significant difference test indicates the presence of the field effect in WLE, when comparing the distribution of the algorithm classifications of unseen data and the distribution obtained by a random classification

First steps into endoscopic video analysis for Barrett's cancer detection: Challenges and opportunities

Routine surveillance endoscopies are currently used to detect dysplasia in patient with Barrett's Esophagus (BE). However, most of these procedures are performed by non-expert endoscopists in community hospitals. Leading to many missed dysplastic lesions, which can progress into advanced esophageal adenocarcinoma if left untreated.1 In recent years, several successful algorithms have been proposed for the detection of cancer in BE using high-quality overview images. This work addresses the first steps towards clinical application on endoscopic surveillance videos. Several challenges are identified that occur when moving from image-based to video-based analysis. (1) It is shown that algorithms trained on high-quality overview images do not naively transfer to endoscopic videos due to e.g. non-informative frames. (2) Video quality is shown to be an important factor in algorithm performance. Specifically, temporal location performance is highly correlated with video quality. (3) When moving to real-time algorithms, the additional compute necessary to address the challenges in videos will become a burden on the computational budget. However, in addition to challenges, videos also bring new opportunities not available in the current image-based methods such as the inclusion of temporal information. This work shows that a multi-frame approach increases performance compared to a naive single-image method when the above challenges are addressed

Tissue segmentation in volumetric laser endomicroscopy data using FusionNet and a domain-specific loss function

Volumetric Laser Endomicroscopy (VLE) is a promising balloon-based imaging technique for detecting early neoplasia in Barretts Esophagus. Especially Computer Aided Detection (CAD) techniques show great promise compared to medical doctors, who cannot reliably find disease patterns in the noisy VLE signal. However, an essential pre-processing step for the CAD system is tissue segmentation. At present, tissue is segmented manually but is not scalable for the entire VLE scan consisting of 1,200 frames of 4,096 × 2,048 pixels. Furthermore, the current CAD methods cannot use the VLE scans to their full potential, as only a small segment of the esophagus is selected for further processing, while an automated segmentation system results in significantly more available data. This paper explores the possibility of automatically segmenting relevant tissue for VLE scans using FusionNet and a domain-specific loss function. The contribution of this work is threefold. First, we propose a tissue segmentation algorithm for VLE scans. Second, we introduce a weighted ground truth that exploits the signal-to-noise ratio characteristics of the VLE data. Third, we compare our algorithm segmentation against two additional VLE experts. The results show that our algorithm annotations are indistinguishable from the expert annotations and therefore the algorithm can be used as a preprocessing step for further classification of the tissue

Laparoscopic ileocaecal resection versus infliximab for terminal ileitis in Crohn's disease: a randomised controlled, open-label, multicentre trial

Background Treatment of patients with ileocaecal Crohn's disease who have not responded to conventional therapy is commonly scaled up to biological agents, but surgery can also offer excellent short-term and long-term results. We compared laparoscopic ileocaecal resection with infliximab to assess how they affect health-related quality of life. Methods In this randomised controlled, open-label trial, in 29 teaching hospitals and tertiary care centres in the Netherlands and the UK, adults with non-stricturing, ileocaecal Crohn's disease, in whom conventional therapy has failed were randomly allocated (1:1) by an internet randomisation module with biased-coin minimisation for participating centres and perianal fistula to receive laparoscopic ileocaecal resection or infliximab. Eligible patients were aged 18–80 years, had active Crohn's disease of the terminal ileum, and had not responded to at least 3 months of conventional therapy with glucocorticosteroids, thiopurines, or methotrexate. Patients with diseased terminal ileum longer than 40 cm or abdominal abscesses were excluded. The primary outcome was quality of life on the Inflammatory Bowel Disease Questionnaire (IBDQ) at 12 months. Secondary outcomes were general quality of life, measured by the Short Form-36 (SF-36) health survey and its physical and mental component subscales, days unable to participate in social life, days on sick leave, morbidity (additional procedures and hospital admissions), and body image and cosmesis. Analyses of the primary outcome were done in the intention-to-treat population, and safety analyses were done in the per-protocol population. This trial is registered at the Dutch Trial Registry (NTR1150). Findings Between May 2, 2008, and October 14, 2015, 73 patients were allocated to have resection and 70 to receive infliximab. Corrected for baseline differences, the mean IBDQ score at 12 months was 178·1 (95% CI 171·1–185·0) in the resection group versus 172·0 (164·3–179·6) in the infliximab group (mean difference 6·1 points, 95% CI −4·2 to 16·4; p=0·25). At 12 months, the mean SF-36 total score was 112·1 (95% CI 108·0–116·2) in the resection group versus 106·5 (102·1–110·9) in the infliximab group (mean difference 5·6, 95% CI −0·4 to 11·6), the mean physical component score was 47·7 (45·7–49·7) versus 44·6 (42·5–46·8; mean difference 3·1, 4·2 to 6·0), and the mean mental component score was 49·5 (47·0–52·1) versus 46·1 (43·3–48·9; mean difference 3·5, −0·3 to 7·3). Mean numbers of days of sick leave were 3·4 days (SD 7·1) in the resection group versus 1·4 days (4·7) in the infliximab group (p<0·0001), days not able to take part in social life were 1·8 days (6·3) versus 1·1 days (4·5; p=0·20), days of scheduled hospital admission were 6·5 days (3·8) versus 6·8 days (3·2; p=0·84), and the number of patients who had unscheduled hospital admissions were 13 (18%) of 73 versus 15 (21%) of 70 (p=0·68). Body-image scale mean scores in the patients who had resection were 16·0 (95% CI 15·2–16·8) at baseline versus 17·8 (17·1–18·4) at 12 months, and cosmetic scale mean scores were 17·6 (16·6–18·6) versus 18·6 (17·6–19·6). Surgical intervention-related complications classified as IIIa or worse on the Clavien-Dindo scale occurred in four patients in the resection group. Treatment-related serious adverse events occurred in two patients in the infliximab group. During a median follow-up of 4 years (IQR 2–6), 26 (37%) of 70 patients in the infliximab group had resection, and 19 (26%) of 73 patients in the resection group received anti-TNF. Interpretation Laparoscopic resection in patients with limited (diseased terminal ileum <40 cm), non-stricturing, ileocaecal Crohn's disease in whom conventional therapy has failed could be considered a reasonable alternative to infliximab therapy. Funding Netherlands Organisation for Health Research and Development

Treatment of Perianal Fistulas in Crohn's Disease, Seton Versus Anti-TNF Versus Surgical Closure Following Anti-TNF [PISA]: A Randomised Controlled Trial

BACKGROUND AND AIMS: Most patients with perianal Crohn's fistula receive medical treatment with anti-tumour necrosis factor [TNF], but the results of anti-TNF treatment have not been directly compared with chronic seton drainage or surgical closure. The aim of this study was to assess if chronic seton drainage for patients with perianal Crohn's disease fistulas would result in less re-interventions, compared with anti-TNF and compared with surgical closure. METHODS: This randomised trial was performed in 19 European centres. Patients with high perianal Crohn's fistulas with a single internal opening were randomly assigned to: i] chronic seton drainage for 1 year; ii] anti-TNF therapy for 1 year; and iii] surgical closure after 2 months under a short course anti-TNF. The primary outcome was the cumulative number of patients with fistula-related re-intervention[s] at 1.5 years. Patients declining randomisation due to a specific treatment preference were included in a parallel prospective PISA registry cohort. RESULTS: Between September 14, 2013 and November 20, 2017, 44 of the 126 planned patients were randomised. The study was stopped by the data safety monitoring board because of futility. Seton treatment was associated with the highest re-intervention rate [10/15, versus 6/15 anti-TNF and 3/14 surgical closure patients, p = 0.02]. No substantial differences in perianal disease activity and quality of life between the three treatment groups were observed. Interestingly, in the PISA prospective registry, inferiority of chronic seton treatment was not observed for any outcome measure. CONCLUSIONS: The results imply that chronic seton treatment should not be recommended as the sole treatment for perianal Crohn's fistulas