Empowering Latino Communities Through the Colorectal Health Research Champions Model: Enhancing Colorectal Cancer Awareness and Screening Advocacy.

Neurodegenerative disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis, impose a considerable social and economic burden on society and have dramatic consequences for individuals and their families. The majority of existing interventions have been found to be capable of only a slight modification of disease progression or to moderately delay significant functional decline in motor, cognitive, or mental domains. To develop effective therapeutic strategies, robust methods for the quantification of neurodegeneration are required. Imaging modalities such as magnetic resonance imaging (MRI) and positron emission tomography (PET) can be used to visually stratify patients, exclude other symptomatic causes of neurodegeneration and assist with differential diagnosis (Schröter et al., 2025). However, these processes have significant limitations when it comes to the exact quantification of neurodegeneration, the prediction of disease trajectories in individual subjects and the tracing of group-level effects in response to therapeutic interventions. Fluorodeoxyglucose PET, tau PET, and amyloid PET are relevant diagnostic tools for AD and atypical Parkinsonism. However, their limited availability restricts their clinical use across countries and health systems. MRI imaging at 3T is now widely available, while ultra-high fields at 7T is increasingly accessible, albeit primarily within specific research centers. Nonetheless, both field strengths offer great potential for further exploration in research and clinical applications. This will facilitate the translation of research into clinical solutions by developing robust biomarkers for tracking neurodegeneration in individual patients and large populations. In addition, the utilization of PET, or the combination of MRI and PET with adaptation of the structural similarity measures (SSM) has the potential to highly advance the field of tools for decision-making at the single-subject level. One such biomarker, however, that is derived from MRI is hippocampal atrophy, which has been developed alongside automatic analysis of the frontal cortex and other regions, as well as measures of regional and global atrophy. These are used for the diagnostic staging and differential diagnosis of AD, atypical Parkinsonism, and other neurodegenerative conditions. These were the first steps in the detection of vulnerable or altered brain regions and networks at the group level, having also further predictive value at the single-subject level. The quantification of regional atrophy is achieved through the measurement the thickness of specific brain regions. This is primarily accomplished by utilizing high-resolution 3D T1-weighted images. Furthermore, fluid-attenuated inversion recovery MRI scans have recently successfully been employed in an increasing number of studies (). This quantification relies on segmentation based on anatomical atlases and the sequent generation of regions of interest, or is frequently performed using deep learning models. The region masks are subsequently utilized to derive structural integrity measurements from single regions. However, regional measures are heterogeneous and fail to account for whole-brain dynamics, which are captured more comprehensively by global atrophy metrics. Furthermore, these approaches disregard fundamental physiological and anatomical principles that are characteristic for neurodegenerative processes in the brain. From a pathophysiological perspective, the neurodegenerative transformation in AD and PD follows specific anatomical patterns. The neurodegenerative transformation affects distinct vulnerable networks, from which it subsequently disseminates following pathological and anatomical patterns. Global measures neglect these principles entirely, and even atlas-based or regional measures can only track the characteristic spreading patterns.