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Unified spatial normalization method of brain PET images using adaptive probabilistic brain atlas.

Tianhao Zhang1,2, Binbin Nie1,2, Hua Liu1,2

  • 1Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, 100049, China.

European Journal of Nuclear Medicine and Molecular Imaging
|March 8, 2022
PubMed
Summary

This study introduces a novel PET-only spatial normalization method for brain imaging, improving accuracy without MRI. The atlas-based approach offers a unified solution for diverse radiotracers and patient groups.

Keywords:
Brain imagingPETProbabilistic brain atlasSpatial normalization

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Area of Science:

  • Neuroimaging
  • Medical Image Analysis
  • Radiochemistry

Background:

  • Brain positron emission tomography (PET) imaging offers unique insights into biological processes using various radiotracers.
  • Spatial normalization of diverse brain PET image patterns presents a significant challenge.
  • Structural magnetic resonance imaging (MRI) is not always available in clinical settings, limiting current normalization techniques.

Purpose of the Study:

  • To propose and validate a PET-only spatial normalization method for brain PET images using an adaptive probabilistic brain atlas.
  • To address the challenge of spatial normalization when structural MRI is unavailable.
  • To provide a unified approach for normalizing PET images across different radiotracers and patient cohorts.

Main Methods:

  • Developed an atlas-based method comprising an adaptive probabilistic brain atlas generation algorithm and a probabilistic registration framework.
  • Validated the method using 286 brain PET images from four subject groups (Alzheimer disease, Parkinson disease, frontotemporal dementia, healthy control) and seven radiotracers.
  • Compared the proposed method against an MRI-based method (gold standard) and a template-based method (control) using correlation analysis, meta-ROI SUVR analysis, and SPM analysis.

Main Results:

  • The atlas-based method achieved a high Pearson correlation coefficient (0.908 ± 0.005) with the gold standard (MRI-based method).
  • The relative error for meta-region of interest (meta-ROI) standardized uptake value ratio (SUVR) was low (2.12 ± 0.18%).
  • The atlas-based method demonstrated superior consistency with the gold standard compared to the template-based method in statistical parametric mapping (SPM) analysis.

Conclusions:

  • The proposed PET-only atlas-based method accurately normalizes brain PET images across various radiotracers without requiring MR images.
  • This unified approach enhances the reliability of neuroimaging analysis in diverse clinical scenarios.
  • A free MATLAB toolbox is available to facilitate the implementation of this method.