ERCPMP-Gx：用于结直肠息肉病形态学、组织病理学和基因组学表征的内镜图像与视频数据集

中文摘要 AI 辅助

遗传性息肉病综合征可能是结直肠癌的前驱病变，并与广泛的结肠外肿瘤相关。早期识别和准确分类这些综合征对于及时诊断、个体化患者管理以及针对受影响家庭的靶向监测策略至关重要。然而，公开的内镜数据集主要围绕单个散发性息肉组织，且没有一个在患者层面将息肉病表型与组织病理学和胚系发现联系起来。在此，我们介绍ERCPMP-Gx，这是一个内镜、组织病理学和基因组学数据集，旨在支持人工智能（AI）在结直肠息肉病的识别、表征和分类中的应用。大多数手术使用Olympus EVIS X1系统进行，采用白光内镜（WLE）、窄带成像（NBI）、放大NBI（M-NBI）和近焦模式NBI，产生了160张图像和伴随的视频片段。约百分之八十的病例代表临床和/或基因确诊的遗传性息肉病综合征（PG），包括家族性腺瘤性息肉病（FAP）、Peutz-Jeghers综合征（PJS）、幼年性息肉病综合征（JPS）和神经节瘤综合征（GNS），而其余百分之二十包括非遗传性息肉和具有重叠形态特征的息肉样病变（Non-PG），纳入以支持鉴别分类。每条发布的记录在可用的情况下，与标准化的内镜注释、代表性组织病理学和临床报告的胚系发现相关联，形成一个AI就绪、患者级别的注释框架。该数据集可在Mendeley公开访问（此https URL）。有关最新更新和更多信息，读者可参阅DataBioX网站：此https URL。

英文摘要

Hereditary polyposis syndromes can be precursor lesions to colorectal cancer and are associated with a broad spectrum of extracolonic tumors. Early identification and accurate classification of these syndromes are essential for timely diagnosis, individualized patient management, and targeted surveillance strategies for affected families. However, public endoscopic datasets are largely organized around the individual sporadic polyp, and none links the polyposis phenotype to histopathology and germline findings at the patient level. Here, we present ERCPMP-Gx, an endoscopic, histopathological, and genomic dataset developed to support the application of artificial intelligence (AI) in the recognition, characterization, and classification of colorectal polyposis. Most procedures were performed using the Olympus EVIS X1 system with white-light endoscopy (WLE), narrow-band imaging (NBI), magnifying NBI (M-NBI), and NBI with near focus modes, yielding 160 images and accompanying video clips. Approximately eighty percent of cases represent clinically and/or genetically confirmed hereditary polyposis syndromes (PG), including familial adenomatous polyposis (FAP), Peutz-Jeghers syndrome (PJS), juvenile polyposis syndrome (JPS), and ganglioneuroma syndrome (GNS), while the remaining twenty percent comprise non-hereditary polyps and polyp-mimicking lesions with overlapping morphological features (Non-PG), included to support differential classification. Each released record is linked, where available, to standardized endoscopic annotations, representative histopathology, and clinically reported germline findings, forming an AI-ready, patient-level annotation framework. The dataset is publicly accessible at Mendeley (https://doi.org/10.17632/nzyfc544bx.2). For the latest updates and further information, readers are referred to the DataBioX website: https://databiox.com.

发表机构

• Shahid Beheshti University of Medical Sciences（沙希德·贝赫什提医科大学）
• Familial & Hereditary Cancers Institute（家族与遗传性癌症研究所）
• Shiraz University of Medical Sciences（设拉子医科大学）
• DataBioX Research（DataBioX研究院）

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