What type of study is this?

This is a Quantitative Study study.

September 17, 2025

AV1451 Tau PET Synthesis from T1-weighted MR Images with U-NET

Key Points

The model synthesized tau PET images with high similarity, achieving a mean SSIM of 0.96, indicating strong performance.
Validation on 128 image pairs demonstrated reliable synthesis with low MAE for SUVR, supporting model effectiveness.
Leveraging non-invasive MRI data for synthesizing PET images could facilitate large cohort studies and enhance patient safety.
The synthesized AV1451 PET images can reduce costs associated with traditional PET imaging methodologies.

Abstract

Motivation: Alzheimer's Disease hallmarks include tau deposits and brain atrophy, detectable via PET and MRI, respectively. PET is expensive, invasive, exposes patients to ionizing radiation, whereas MRI is a cheaper, non-invasive, free from ionizing radiation but limited to measuring structural changes. Goal(s): Develop a three-dimensional image-translation model synthesizing tau PET images from T1-weighted MRI, capitalizing on the relationship between tau and brain atrophy. Approach: The model was trained with 297 PET/MRI pairs and validated with 128 pairs Results: The model synthesized tau-PET images from T1-weighter MRI with high-degree of similarity reflected in high mean SSIM and PSNR (SSIM=0.96&PSNR=29.76), and low MAE in SUVR synthesis. Impact: Our model proves the feasibility of synthesizing AV-1451 PET images from T1-weighted MRI, an approach that could enhance the accessibility for large cohort-studies and early dementia detection, while also reducing costs, invasiveness, and enhancing patient safety by limiting radiation exposure.

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