小儿胆道闭锁和其他胆汁淤积症的综合图像和血清生物标志物。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Shuyi Liu, Rui Zhang, Yongshang Yu, Chunyixue Geng, Hongbin Ma, Yuyun Liu, Wenhua Qin, Yue Zhang, Qiqiao Zhang, Wenjing Gao
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引用次数: 0

摘要

胆道闭锁(BA)和其他儿童胆汁淤积症是罕见但严重的疾病,需要早期和准确的诊断。超声已成为BA的主要诊断方法,特别是通过空腹和餐后比较来评估胆囊收缩性。然而,目前缺乏公开可用的数据集,其中包含配对的空腹-餐后胆囊超声图像、其他关键超声特征和相关的血清生化指标。该数据集包括来自1,019名诊断为胆汁淤积性疾病的婴儿的2,759张超声图像。其中包括377例BA病例(664例禁食和328例餐后图像)和642例非BA病例(1004例禁食和580例餐后图像)。同时收集了三角索征、肝动脉扩张、肝门部肝囊肿等异常声像图及相关肝脏生化指标183张。该研究采用nnU-Net在空腹和餐后超声检查中进行自动胆囊分割。该数据集为提高BA的诊断准确性和促进临床决策支持系统的开发提供了宝贵的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comprehensive images and serum biomarkers for biliary atresia and other cholestasis in pediatrics.

Biliary atresia (BA) and other pediatric cholestatic diseases are rare but serious conditions that require early and accurate diagnosis. Ultrasound has become the primary diagnostic method for BA, particularly for evaluating gallbladder contractility through fasting and postprandial comparisons. However, there is currently a lack of publicly available datasets containing paired fasting-postprandial gallbladder ultrasound images, other key sonographic features, and relevant serum biochemical indicators. The dataset consisted of 2,759 ultrasound images obtained from 1,019 infants diagnosed with cholestatic diseases. This included 377 BA cases (664 fasting and 328 post-prandial images) and 642 non-BA cases (1,004 fasting and 580 post-prandial images). Additionally, 183 images documenting abnormal ultrasonographic findings such as triangular cord sign, dilated hepatic artery, and hilar hepatic cysts, and relevant hepatic biochemical indicators were also collected. The study implemented nnU-Net to perform automated gallbladder segmentation across both fasting and postprandial ultrasound examinations. The dataset represents a valuable resource for enhancing the diagnostic accuracy of BA and facilitating the development of clinical decision-support system.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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