Research Institute, Children's Health Orange County (CHOC), Orange, CA, USA.
Department of Pathology, CHOC, Orange, CA, USA.
Sci Data. 2024 Jul 11;11(1):761. doi: 10.1038/s41597-024-03592-7.
The incidence of inflammatory bowel disease (IBD) is increasing annually. Children with IBD often suffer significant morbidity due to physical and emotional effects of the disease and treatment. Corticosteroids, often a component of therapy, carry undesirable side effects with long term use. Steroid-free remission has become a standard for care-quality improvement. Anticipating therapeutic outcomes is difficult, with treatments often leveraged in a trial-and-error fashion. Artificial intelligence (AI) has demonstrated success in medical imaging classification tasks. Predicting patients who will attain remission will help inform treatment decisions. The provided dataset comprises 951 tissue section scans (167 whole-slides) obtained from 18 pediatric IBD patients. Patient level structured data include IBD diagnosis, 12- and 52-week steroid use and name, and remission status. Each slide is labelled with biopsy site and normal or abnormal classification per the surgical pathology report. Each tissue section scan from an abnormal slide is further classified by an experienced pathologist. Researchers utilizing this dataset may select from the provided outcomes or add labels and annotations from their own institutions.
炎症性肠病（IBD）的发病率正在逐年上升。患有 IBD 的儿童常常因疾病和治疗的身体和情绪影响而遭受严重的发病。皮质类固醇通常是治疗的组成部分，但长期使用会带来不良的副作用。无类固醇缓解已成为改善护理质量的标准。由于治疗方法通常是试错式的，因此预测治疗效果具有一定难度。人工智能（AI）在医学影像分类任务中已取得成功。预测能够达到缓解的患者将有助于为治疗决策提供信息。提供的数据集包含 18 名儿科 IBD 患者的 951 个组织切片扫描（167 个全切片）。患者水平的结构化数据包括 IBD 诊断、12 周和 52 周皮质类固醇的使用情况和名称以及缓解状态。根据外科病理报告，每张幻灯片均标记有活检部位和正常或异常分类。异常幻灯片上的每个组织切片扫描均由经验丰富的病理学家进一步分类。研究人员可以从提供的结果中进行选择，或者从自己的机构添加标签和注释。
