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Introduction <p>Quantification of amyloid plaques (A), neurofibrillary tangles (T<sub>2</sub>), and neurodegeneration (N) using PET and MRI is critical for Alzheimer’s disease (AD) diagnosis and prognosis. Existing pipelines face limitations regarding processing time, tracer variability handling, and multimodal integration.</p> Methods <p>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, T<sub>2</sub>, and N biomarkers. It is implemented in a web-based format, requiring no local computational infrastructure and software usage knowledge.</p> Results <p>petBrain provides reliable, rapid quantification with results comparable to existing pipelines for A and T<sub>2</sub>, showing strong concordance with data processed in ADNI databases. The staging and quantification of A/T<sub>2</sub>/N by petBrain demonstrated good agreements with CSF/plasma biomarkers, clinical status and cognitive performance.</p> Discussion <p>petBrain represents a powerful open platform for standardized AD biomarker analysis, facilitating clinical research applications.</p>

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petBrain: a new pipeline for amyloid, Tau tangles and neurodegeneration quantification using PET and MRI

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月30日

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  • Pierrick Coupé,
  • Boris Mansencal,
  • Floréal Morandat,
  • Sergio Morell-Ortega,
  • Nicolas Villain,
  • Jose V. Manjón,
  • Vincent Planche

摘要

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, tracer variability handling, and 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. It is implemented in a web-based format, requiring no local computational infrastructure and software usage knowledge.

Results

petBrain provides reliable, rapid quantification with results comparable to existing pipelines for A and T2, showing strong concordance with data processed in ADNI databases. The staging and quantification of A/T2/N by petBrain demonstrated good agreements with CSF/plasma biomarkers, clinical status and cognitive performance.

Discussion

petBrain represents a powerful open platform for standardized AD biomarker analysis, facilitating clinical research applications.