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Related Experiment Videos

Technical Optimization Strategies for Amyloid PET Under Challenging Acquisition Conditions: A Comprehensive Narrative

Luca Camoni1, Francesco Dondi2, Agata Pietrzak3,4

  • 1Allied Health and Social Care Professions Directorate, ASST Spedali Civili di Brescia, University of Brescia, 25123 Brescia, Italy.

Diagnostics (Basel, Switzerland)
|July 15, 2026
PubMed
Summary

Standard amyloid PET imaging can be challenging. While reduced scan times and AI image enhancement show promise, they require careful validation and should not replace standard protocols, especially in difficult patient cases.

Keywords:
Alzheimer’s diseaseacquisition-time reductionamyloidartificial intelligencedeep learningimage restorationlow-count imagingmotion correctionpositron emission tomography

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Area of Science:

  • Nuclear Medicine
  • Neuroimaging
  • Radiochemistry

Background:

  • Cerebral amyloid burden assessment via amyloid PET is crucial for diagnosing neurodegenerative diseases.
  • Standard amyloid PET acquisition protocols can be compromised by factors like head motion, low patient cooperation, and reduced effective counts.

Purpose of the Study:

  • To comprehensively review evidence on optimizing amyloid PET acquisition under challenging conditions.
  • To evaluate strategies including acquisition time reduction, low-count imaging, motion correction, and AI-based image enhancement.

Main Methods:

  • A structured narrative review using an evidence-mapping approach.
  • Literature search conducted in PubMed/MEDLINE, Scopus, and Web of Science up to March 2026.
  • Inclusion of clinical, phantom, and hybrid studies addressing acquisition optimization.

Main Results:

  • Moderate reductions in acquisition time or effective counts generally maintained semiquantitative performance but impacted visual interpretation.
  • Artificial intelligence-based restoration improved image quality and aided interpretation of reduced-protocol scans, though model-specific.
  • Motion correction showed potential but requires further replication.

Conclusions:

  • Cautious, task-specific optimization is recommended over universal protocol reduction for challenging amyloid PET acquisitions.
  • Reduced protocols, AI restoration, and motion correction are supportive strategies requiring local validation, not replacements for standard acquisition.