Voxel-based evaluation for [18F] Florbetaben brain β-amyloid positron emission tomography of healthy control, mild cognitive impairment, and Alzheimer's disease

Tse-Hao Lee; Yuh-Feng Wang; Nan-Jing Peng; Syu-Jyun Peng

doi:10.21037/qims-24-1100

Voxel-based evaluation for [¹⁸F] Florbetaben brain β-amyloid positron emission tomography of healthy control, mild cognitive impairment, and Alzheimer's disease

Quant Imaging Med Surg. 2024 Dec 5;14(12):9146-9156. doi: 10.21037/qims-24-1100. Epub 2024 Nov 29.

Authors

Tse-Hao Lee¹, Yuh-Feng Wang^{1

2

3}, Nan-Jing Peng^{1

4}, Syu-Jyun Peng^{5

6}

Affiliations

¹ Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei.
² Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei.
³ Department of Medical Imaging and Radiological Technology, Yuanpei University of Medical Technology, Hsinchu.
⁴ School of Medicine, National Yang Ming Chiao Tung University, Taipei.
⁵ In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei.
⁶ Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei.

Abstract

Background: Positron emission tomography (PET) scans are commonly used to diagnose Alzheimer's disease (AD) by detecting β-amyloid (Aβ) deposition in the cortex; however, brain amyloid plaque load (BAPL) scores based on the visual interpretation of experts are highly subjective. In the current retrospective study, voxel-based processing of [¹⁸F] Florbetaben ([¹⁸F] FBB) Aβ PET scans was used to compare images from patients with AD, patients with mild cognitive impairment (MCI), and healthy controls (HCs). The aim of our study was to highlight the gray matter voxels that were higher uptake than white matter and perform group comparison of the numbers of these voxels among AD, MCI and HC subjects.

Methods: This was a cross-sectional study investigating Aβ PET of AD, MCI and HC subjects from the Global Alzheimer's Association Information Network (GAAIN) database and from Taipei Veterans General Hospital (TVGH) between October 2019 and December 2021. The determination of diagnosis (AD, MCI and HC) from GAAIN database was referred from the notes of this database and that from TVGH was referred from the medical records. Aβ PET scans were processed using statistical parametric mapping software. This analysis identified gray matter voxels presenting [¹⁸F] FBB uptake intensity exceeding 98% of the maximal uptake intensity in white matter (i.e., positive gray matter voxels). Comparison of numbers of positive gray matter voxels among AD, MCI and HC subjects was performed by analysis of variance (ANOVA) (Kruskal-Wallis) test.

Results: Whole brain observations revealed significant differences between AD patients, MCI patients, and elderly HC subjects in terms of the number of positive gray matter voxels (P=0.0281). In addition, more number of positive gray matter voxels were observed in AD patients than in elderly HC subjects (P=0.036). Most of the elderly HC subjects exhibited no positive gray matter voxels.

Conclusions: Our preliminary analysis of [¹⁸F] FBB Aβ PET scans demonstrates proof-of-concept, suggesting that positive gray matter voxels could be used to differentiate among AD, MCI, and HC subjects.

Keywords: Alzheimer’s disease (AD); [18F] florbetaben brain β-amyloid positron emission tomography ([18F] FBB brain Aβ PET); mild cognitive impairment (MCI); voxel-based analysis; β-amyloid (Aβ) deposition.