4.6 Article

Deep Learning Analysis of Histologic Images from Intestinal Specimen Reveals Adipocyte Shrinkage and Mast Cell Infiltration to Predict Postoperative Crohn Disease

期刊

AMERICAN JOURNAL OF PATHOLOGY
卷 192, 期 6, 页码 904-916

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ajpath.2022.03.006

关键词

-

资金

  1. Takeda Science Foundation
  2. Senri Life Science Foundation
  3. Kanae Foundation for the Promotion of Medical Science
  4. Japan Society for the Promotion of Science Grants-in-Aid for Early-Career Scientists [JP20K16192]

向作者/读者索取更多资源

This study successfully predicted postoperative recurrence of Crohn disease (CD) by computational analysis of histopathologic images and identified histologic characteristics associated with recurrence, including adipose cell morphology and subserosal mast cell infiltration.
Most patients with Crohn disease (CD), a chronic inflammatory gastrointestinal disease, experience recurrence despite treatment, including surgical resection. However, methods for predicting recurrence remain unclear. This study aimed to predict postoperative recurrence of CD by computational analysis of histopathologic images and to extract histologic characteristics associated with recurrence. A total of 68 patients who underwent surgical resection of the intestine were included in this study and were categorized into two groups according to the presence or absence of postoperative disease recurrence within 2 years after surgery. Recurrence was defined using the CD Activity Index and the Rutgeerts score. Whole-slide images of surgical specimens were analyzed using deep learning model EfficientNetb5, which achieved a highly accurate prediction of recurrence (area under the curve, 0.995). Moreover, subserosal tissue images with adipose cells enabled highly accurate prediction. Adipose cell morphology showed significant between-group differences in adipose cell size, cell-to-cell distance, and cell flattening values. These findings suggest that adipocyte shrinkage is an important histologic characteristic associated with recurrence. Moreover, there was a significant between-group difference in the degree of mast cell infiltration in the subserosa. These findings show the importance of mesenteric adipose tissue in patient prognosis and CD pathophysiology. These findings also suggest that deep learning-based artificial intelligence enables the extraction of meaningful histologic features. (Am J Pathol 2022, 192: 904-916; https://doi.org/10.1016/j.ajpath.2022.03.006)

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据