3D diagnosis of Hirschsprung disease using open-top light-sheet microscopy

使用开顶光片显微镜对先天性巨结肠进行 3D 诊断

基本信息

批准号：
10484508
负责人：
Nicholas Reder
金额：
$ 25.25万
依托单位：
ALPENGLOW BIOSCIENCES, INC.
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10484508
关键词：
3-Dimensional Address Affect Antibodies Biological Assay Biopsy Biopsy Specimen CLIA certified Cell Count Chronic Clinical Clinical Trials Complex Congenital Abnormality Congenital Megacolon Constipation Consumption Data Set Diagnosis Diagnostic Diagnostic Errors Disease Distal Dysplasia Enteral Enteric Nervous System Excision Future Ganglia Gold Harvest Human Hypertrophy Image Imaging Techniques Individual Infant Intestines Label Laboratories Length Light Machine Learning Malignant neoplasm of prostate Methods Microscope Microscopy Mucous Membrane Nature Nerve Nerve Fibers Nervous system structure Neurons Pathologist Pathology Pathology processes Patients Phase Positioning Attribute Preparation Process Protocols documentation Readiness Rectum Research Sampling Services Small Business Innovation Research Grant Specimen Stains Structure Submucosa Suction Techniques Technology Testing Three-Dimensional Imaging Time Tissues Training Translating Work analysis pipeline automated analysis density disease diagnosis ganglion cell improved lightspeed machine learning algorithm nerve supply neuromuscular novel rectal

项目摘要

Abstract Hirschsprung disease is a congenital defect that affects an estimated 1:5000 liveborn infants. It is characterized by absent ganglion cells (neurons) in the distal rectum and a variable length of contiguous proximal bowel. The diagnosis of Hirschsprung disease relies upon subjective pathologist interpretation of up to 100 tissue sections from suction rectal biopsies to prove the absence of ganglion cells and the presence of hypertrophic nerves. Due to the labor-intensive and time-consuming nature of the current diagnostic process, there is a need to more efficiently and comprehensively diagnose Hirschsprung disease. Our team has pioneered the use of 3D open-top light-sheet (OTLS) microscopy, which enables rapid, high-throughput imaging of large clinical samples. In combination with cutting-edge machine learning techniques, we hypothesize that 3D OTLS microscopy can provide more accurate and consistent assessment of ganglion cells and hypertrophic nerves in suction rectal biopsies from patients with suspected Hirschsprung disease. We will test this hypothesis by developing a multiplex staining protocol and machine learning analysis pipeline, which will be piloted on 100 rectal biopsy specimens from fresh resection specimens.

抽象的 Hirschsprung病是一种先天性缺陷，影响估计的1：5000名活生生婴儿。它其特征是远端直肠中不存在神经节细胞（神经元），可变长度为连续的近端肠。 Hirschsprung疾病的诊断依赖于主观病理学家对直肠活检的多达100个组织切片的解释以证明没有神经节细胞和肥厚神经的存在。由于劳动密集型以及当前诊断过程的耗时性，需要更有效地并全面诊断出Hirschsprung疾病。我们的团队开创了3D的使用开放式灯页（OTLS）显微镜，可快速，高通量成像大型成像临床样品。结合最先进的机器学习技术，我们假设 3D OTL显微镜可以提供对神经节的更准确和一致的评估来自可疑患者的直肠活检的细胞和肥厚神经 Hirschsprung病。我们将通过制定多重染色协议来检验这一假设和机器学习分析管道，该管道将在100个直肠活检标本上进行试验来自新的切除标本。