Document Type
Article
Publication Date
7-11-2024
Abstract
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.
Recommended Citation
Martin-King, C., Nael, A., Ehwerhemuepha, L. et al. Histopathology imaging and clinical data including remission status in pediatric inflammatory bowel disease. Sci Data 11, 761 (2024). https://doi.org/10.1038/s41597-024-03592-7
Peer Reviewed
1
Copyright
The authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
Digestive System Diseases Commons, Other Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Pediatrics Commons, Therapeutics Commons
Comments
This article was originally published in Scientific Data, volume 11, in 2024. https://doi.org/10.1038/s41597-024-03592-7