petBrain: A New Pipeline for Amyloid, Tau Tangles and Neurodegeneration Quantification Using PET and MRI
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Abstract (arXiv)
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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References · 5
- 2019AssemblyNet: A large ensemble of CNNs for 3D Whole Brain MRI Segmentationcited by 21
- 2020DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentationcited by 15
- 2022Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementiacited by 5
- 2020Deep ICE: A Deep learning approach for MRI Intracranial Cavity Extractioncited by 4
- 2025SPM 25: open source neuroimaging analysis softwarecited by 2
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