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Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment
Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment
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Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment
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Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment
Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment

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Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment
Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment
Journal Article

Comparison of Amyloid-PET Analysis Software Using sup.18F-Florbetaben PET in Patients with Cognitive Impairment

2025
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Overview
Background/Objectives: Quantitative analysis of amyloid PET imaging plays a crucial role in diagnosing Alzheimer’s disease (AD), particularly in cases where visual interpretation is equivocal. Multiple commercial software tools are available for this purpose, yet differences in their quantification and diagnostic performance remain understudied, especially for Neurophet SCALE PET. Methods: We retrospectively analyzed [sup.18]F-florbetaben PET/CT scans from 129 patients with cognitive impairment, comprising 39 patients with AD and 90 with non-AD diagnoses, using three software tools: MIMneuro, CortexID Suite, and Neurophet SCALE PET. Standardized uptake value ratios (SUVRs) were obtained for six brain regions known for amyloid accumulation. Diagnostic accuracy was evaluated using ROC curve analysis, while inter-software correlations and reliability were assessed via Pearson correlation coefficients and intraclass correlation coefficients (ICC). Results: All three software programs significantly distinguished AD from non-AD patients in most brain regions. MIMneuro and Neurophet SCALE PET demonstrated the highest diagnostic performance, with MIMneuro achieving an AUC of 1.000 in the anterior cingulate gyrus. While MIMneuro and Neurophet SCALE PET showed moderate-to-strong SUVR correlations (r = 0.715–0.865), CortexID Suite showed limited correlation with the other tools. Inter-software reliability was moderate only in selected regions (ICC ≈ 0.5), indicating potential variability in SUVR measurements across platforms. Conclusions: MIMneuro, CortexID Suite, and Neurophet SCALE PET are effective for the semi-quantitative analysis of amyloid PET and can aid in the diagnosis of AD. However, clinicians should be cautious when interpreting SUVRs across different software tools due to limited inter-software consistency. Standardization efforts or consistent use of a single platform are recommended to avoid diagnostic discrepancies.