Motivation: Alzheimer's Disease hallmarks include amyloid-beta deposits and brain atrophy, detectable via PET and MRI scans, respectively. PET is expensive, invasive and exposes patients to ionizing radiation. MRI is cheaper, non-invasive, and free from ionizing radiation but limited to measuring brain atrophy. Goal: To develop an 3D image translation model that synthesizes amyloid-beta PET images from T1-weighted MRI, exploiting the known relationship between amyloid-beta and brain atrophy. Approach: The model was trained on 616 PET/MRI pairs and validated with 264 pairs. Results: The model synthesized amyloid-beta PET images from T1-weighted MRI with high-degree of similarity showing high SSIM and PSNR metrics (SSIM>0.95&PSNR=28). Impact: Our model proves the feasibility of synthesizing amyloid-beta PET images from structural MRI ones, significantly enhancing accessibility for large-cohort studies and early dementia detection, while also reducing cost, invasiveness, and radiation exposure.

翻译：动机：阿尔茨海默病的典型病理特征包括淀粉样蛋白沉积和脑萎缩，分别可通过PET和MRI扫描检测。PET成本高昂、具有侵入性，且会使患者暴露于电离辐射；MRI则成本较低、无创且无辐射暴露，但仅限于测量脑萎缩。目标：利用淀粉样蛋白与脑萎缩之间的已知关联，开发一种三维图像转换模型，从T1加权MRI中合成淀粉样蛋白PET图像。方法：该模型基于616对PET/MRI图像对进行训练，并在264对图像对上完成验证。结果：模型从T1加权MRI合成的淀粉样蛋白PET图像具有高度相似性，SSIM>0.95且PSNR=28的高指标验证了其性能。影响：本研究证明了从结构性MRI图像合成淀粉样蛋白PET的可行性，显著提升了大规模队列研究与早期痴呆筛查的可及性，同时降低了成本、侵入性和辐射暴露。