Neuroimaging biomarkers, namely hippocampal volume loss, temporoparietal hypometabolism, and neocortical β-amyloid (Aβ) deposition, are included in the recent research criteria for preclinical Alzheimer's disease (AD). However, how to use these biomarkers is still being debated, especially regarding their sequence. Our aim was to characterize the cognitive and brain profiles of elders classified as positive or negative for each biomarker to further our understanding of their use in the preclinical diagnosis of AD. Fifty-four cognitively normal individuals (age = 65.8 ± 8.3 years) underwent neuropsychological tests (structural MRI, FDG-PET, and Florbetapir-PET) and were dichotomized into positive or negative independently for each neuroimaging biomarker. Demographic, neuropsychological, and neuroimaging data were compared between positive and negative subgroups. The MRI-positive subgroup had lower executive performances and mixed patterns of lower volume and metabolism in AD-characteristic regions and in the prefrontal cortex. The FDG-positive subgroup showed only hypometabolism, predominantly in AD-sensitive areas extending to the whole neocortex, compared with the FDG-negative subgroup. The amyloid-positive subgroup was older and included more APOE ε4 carriers compared with the amyloid-negative subgroup. When considering MRI and/or FDG biomarkers together (i.e., the neurodegeneration-positive), there was a trend for an inverse relationship with Aβ deposition such that those with neurodegeneration tended to show less Aβ deposition and the reverse was true as well. Our findings suggest that: (1) MRI and FDG biomarkers provide complementary rather than redundant information and (2) relatively young cognitively normal elders tend to have either neurodegeneration or Aβ deposition, but not both, suggesting additive rather than sequential/causative links between AD neuroimaging biomarkers at this age.

PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice. In parallel, the integration of PET imaging with radionuclide therapy, also known as radiolabeled theranostics, has paved the way towards highly sensitive radionuclide-based precision medicine, with major breakthroughs emerging in neuroendocrine tumors and prostate cancer. PET imaging of tumor immunity and beyond is also emerging, emphasizing the unique capabilities of PET molecular imaging to constantly adapt to emerging oncological challenges. However, these new horizons face the growing complexity of multidimensional data. In the era of precision medicine, statistical and computer sciences are currently revolutionizing image-based decision making, paving the way for more holistic cancer molecular imaging analyses at the whole-body level.