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Related Concept Videos

Positron Emission Tomography01:29

Positron Emission Tomography

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Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body...
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Related Experiment Video

Updated: May 2, 2026

A Dual Tracer PET-MRI Protocol for the Quantitative Measure of Regional Brain Energy Substrates Uptake in the Rat
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A Comparative Analysis of Two Automated Quantification Methods for Regional Cerebral Amyloid Retention: PET-Only and

Sunghwan Kim1, Sheng-Min Wang1, Dong Woo Kang2

  • 1Department of Psychiatry, College of Medicine, Yeouido St. Mary's Hospital, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea.

International Journal of Molecular Sciences
|July 27, 2024
PubMed
Summary

This study compared PET-only and PET-MRI methods for Alzheimer's disease (AD) diagnosis. The PET-MRI approach demonstrated superior accuracy in predicting amyloid-positivity, aiding earlier AD intervention.

Keywords:
Alzheimer’s diseasePET-and-MRI-based methodamyloid retentionautomated quantification

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Area of Science:

  • Neuroimaging
  • Artificial Intelligence in Medicine
  • Alzheimer's Disease Research

Background:

  • Accurate amyloid positron emission tomography (PET) quantification is crucial for early Alzheimer's disease (AD) detection and intervention.
  • Limited studies compare automated methods for amyloid PET quantification.

Purpose of the Study:

  • To compare the performance of PET-only and PET-and-MRI-based methods for amyloid quantification in AD.
  • To evaluate the efficacy of a deep learning segmentation model in these methods.

Main Methods:

  • Analysis of 1180 participants from the Catholic Aging Brain Imaging (CABI) database.
  • Calculation of regional standardized uptake value ratio (SUVR) using PET-only and PET-MRI methods with a deep learning model.
  • Logistic regression and 10-fold cross-validation with AUROC metrics to assess discriminability between amyloid-positive and negative groups.

Main Results:

  • Both methods showed high correlation in SUVR calculations.
  • The PET-MRI method, integrating MRI for anatomical accuracy, exhibited superior performance in predicting amyloid-positivity.
  • Parietal, frontal, and cingulate regions were key predictors of amyloid-positivity.

Conclusions:

  • The PET-MRI method, enhanced by a pre-trained deep learning model, offers an efficient and precise approach for early AD diagnosis.
  • This integrated method can improve intervention strategies along the AD continuum.