Artificial Intelligence-assisted Analysis of Pan-enteric Capsule Endoscopy in Patients with Suspected Crohn’s Disease: A Study on Diagnostic Performance

胶囊内镜 医学 克罗恩病 内窥镜检查 炎症性肠病 胃肠病学 溃疡性结肠炎 内科学 金标准(测试) 诊断准确性 预测值 结肠镜检查 疾病 结直肠癌 癌症
作者
Jacob Broder Brodersen,Michael Dam Jensen,Romain Leenhardt,Jens Kjeldsen,Aymeric Histace,Torben Knudsen,Xavier Dray
出处
期刊:Journal of Crohn's and Colitis [Oxford University Press]
卷期号:18 (1): 75-81 被引量:15
标识
DOI:10.1093/ecco-jcc/jjad131
摘要

Abstract Background and Aim Pan-enteric capsule endoscopy [PCE] is a highly sensitive but time-consuming tool for detecting pathology. Artificial intelligence [AI] algorithms might offer a possibility to assist in the review and reduce the analysis time of PCE. This study examines the agreement between PCE assessments aided by AI technology and standard evaluations, in patients suspected of Crohn’s disease [CD]. Method PCEs from a prospective, blinded, multicentre study, including patients suspected of CD, were processed by the deep learning solution AXARO® [Augmented Endoscopy, Paris, France]. Based on the image output, two observers classified the patient’s PCE as normal or suggestive of CD, ulcerative colitis, or cancer. The primary outcome was per-patient sensitivities and specificities for detecting CD and inflammatory bowel disease [IBD]. Complete reading of PCE served as the reference standard. Results A total of 131 patients’ PCEs were analysed, with a median recording time of 303 min. The AXARO® framework reduced output to a median of 470 images [2.1%] per patient, and the pooled median review time was 3.2 min per patient. For detecting CD, the observers had a sensitivity of 96% and 92% and a specificity of 93% and 90%, respectively. For the detection of IBD, both observers had a sensitivity of 97% and had a specificity of 91% and 90%, respectively. The negative predictive value was 95% for CD and 97% for IBD. Conclusions Using the AXARO® framework reduced the initial review time substantially while maintaining high diagnostic accuracy—suggesting its use as a rapid tool to rule out IBD in PCEs of patients suspected of Crohn’s disease.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
嘟嘟发布了新的文献求助10
刚刚
星xing发布了新的文献求助10
刚刚
张CEO发布了新的文献求助10
刚刚
shanjianjie发布了新的文献求助10
1秒前
2秒前
smartsamen完成签到 ,获得积分10
2秒前
2秒前
Rinne发布了新的文献求助10
2秒前
mrz发布了新的文献求助10
5秒前
Cole完成签到,获得积分10
6秒前
JamesPei应助Enri采纳,获得20
6秒前
小胖完成签到 ,获得积分10
6秒前
Owen应助pluto采纳,获得10
6秒前
6秒前
肖战的笑完成签到,获得积分10
7秒前
高手中的糕手完成签到,获得积分10
7秒前
noture发布了新的文献求助30
8秒前
爆米花应助zddddd采纳,获得10
9秒前
打打应助shanjianjie采纳,获得10
9秒前
alho完成签到 ,获得积分10
9秒前
若水应助mrz采纳,获得10
11秒前
11秒前
cl发布了新的文献求助10
12秒前
13秒前
小菜鸡完成签到,获得积分10
13秒前
13秒前
13秒前
爆米花应助于芋菊采纳,获得10
13秒前
泽锦臻发布了新的文献求助10
14秒前
英姑应助believe采纳,获得10
15秒前
15秒前
16秒前
16秒前
16秒前
Eliauk完成签到 ,获得积分10
17秒前
热心乐驹发布了新的文献求助10
17秒前
阳光万声发布了新的文献求助10
17秒前
棋1发布了新的文献求助10
19秒前
852应助lixl0725采纳,获得10
19秒前
高分求助中
BIOLOGY OF NON-CHORDATES 1000
进口的时尚——14世纪东方丝绸与意大利艺术 Imported Fashion:Oriental Silks and Italian Arts in the 14th Century 800
Zeitschrift für Orient-Archäologie 500
Play from birth to twelve: Contexts, perspectives, and meanings – 3rd Edition 300
Equality: What It Means and Why It Matters 300
A new Species and a key to Indian species of Heirodula Burmeister (Mantodea: Mantidae) 300
Apply error vector measurements in communications design 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3348652
求助须知:如何正确求助?哪些是违规求助? 2974814
关于积分的说明 8666508
捐赠科研通 2655578
什么是DOI,文献DOI怎么找? 1454071
科研通“疑难数据库(出版商)”最低求助积分说明 673211
邀请新用户注册赠送积分活动 663545