Abstract：
Due to the abnormal secretion of adreno-cortico-tropic-hormone (ACTH) by tumors, Cushing\'s disease leads to hypercortisonemia, a precursor to a series of metabolic disorders and serious complications. Cushing\'s disease has high recurrence rate, short recurrence time and undiscovered recurrence reason after surgical resection. Qualitative or quantitative automatic image analysis of histology images can potentially in providing insights into Cushing\'s disease, but still no software has been available to the best of our knowledge. In this study, we propose a quantitative image analysis-based pipeline CRCS, which aims to explore the relationship between the expression level of ACTH in normal cell tissues adjacent to tumor cells and the postoperative prognosis of patients. CRCS mainly consists of image-level clustering, cluster-level multi-modal image registration, patch-level image classification and pixel-level image segmentation on the whole slide imaging (WSI). On both image registration and classification tasks, our method CRCS achieves state-of-the-art performance compared to recently published methods on our collected benchmark dataset. In addition, CRCS achieves an accuracy of 0.83 for postoperative prognosis of 12 cases. CRCS demonstrates great potential for instrumenting automatic diagnosis and treatment for Cushing\'s disease.
摘要：
由于肿瘤分泌的肾上腺促肾上腺皮质激素（ACTH）异常，库欣病导致高可的松血症，一系列代谢紊乱和严重并发症的先兆。库欣病复发率高,手术切除后复发时间短，未发现复发原因。组织学图像的定性或定量自动图像分析可以潜在地提供对库欣病的见解，但是据我们所知，仍然没有软件可用。在这项研究中,我们提出了一种基于定量图像分析的管道CRCS，目的探讨ACTH在癌旁正常细胞组织中的表达水平与患者术后预后的关系。CRCS主要由图像级聚类组成，簇级多模态图像配准，整个幻灯片成像（WSI）上的块级图像分类和像素级图像分割。在图像配准和分类任务上，在我们收集的基准数据集上,与最近发表的方法相比,我们的方法CRCS取得了最先进的性能.此外,CRCS对12例术后预后的准确性为0.83。CRCS显示出用于自动诊断和治疗库欣病的巨大潜力。
