用AI统一分析阿尔茨海默病三种核心生物标志物，快速准确且无需专业设备。
petBrain: A New Pipeline for Amyloid, Tau Tangles and Neurodegeneration Quantification Using PET and MRI
- 基于深度学习的端到端处理，融合PET与MRI数据自动分割与量化。
- 在阿兹海默症队列中与脑脊液/血液指标、认知能力高度一致，结果可靠。
- 开源网页平台，无须本地部署，适合临床研究者和医生使用。
利用正电子发射断层扫描（PET）和磁共振成像（MRI）量化淀粉样蛋白斑块（A）、神经纤维缠结（T2）和神经退行性变（N）对阿尔茨海默病（AD）的诊断与预后至关重要。现有流程存在处理时间长、示踪剂类型差异大、多模态整合困难等问题。我们开发了petBrain，一个用于淀粉样蛋白-PET、tau-PET和结构MRI的新型端到端分析管道。该系统采用基于深度学习的分割方法，实现标准化生物标志物量化（Centiloid、CenTauR、HAVAs），并同步估计A、T2和N生物标志物。其以网络平台形式实现，无需本地计算资源或专业软件知识。结果表明，petBrain在A和T2量化上表现可靠，与ADNI数据库处理结果高度一致。基于A/T2/N的分期与量化与脑脊液/血浆生物标志物、临床状态及认知表现具有良好一致性。petBrain是一个强大且开放可用的标准化阿尔茨海默病生物标志物分析平台，适用于临床研究应用。
原文摘要 · Abstract (English)
INTRODUCTION: Quantification of amyloid plaques (A), neurofibrillary tangles (T2), and neurodegeneration (N) using PET and MRI is critical for Alzheimer's disease (AD) diagnosis and prognosis. Existing pipelines face limitations regarding processing time, variability in tracer types, and challenges in multimodal integration. METHODS: We developed petBrain, a novel end-to-end processing pipeline for amyloid-PET, tau-PET, and structural MRI. It leverages deep learning-based segmentation, standardized biomarker quantification (Centiloid, CenTauR, HAVAs), and simultaneous estimation of A, T2, and N biomarkers. The pipeline is implemented as a web-based platform, requiring no local computational infrastructure or specialized software knowledge. RESULTS: petBrain provides reliable and rapid biomarker quantification, with results comparable to existing pipelines for A and T2. It shows strong concordance with data processed in ADNI databases. The staging and quantification of A/T2/N by petBrain demonstrated good agreement with CSF/plasma biomarkers, clinical status, and cognitive performance. DISCUSSION: petBrain represents a powerful and openly accessible platform for standardized AD biomarker analysis, facilitating applications in clinical research.
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