Abstract Purpose of Review Chronic Kidney disease (CKD) is a global health concern, affecting over 10% of the population and associated with significant morbidity and mortality, particularly due to cardiovascular complications. CKD is defined by structural or functional kidney abnormalities persisting for over three months, with diagnosis based on reduced glomerular filtration rate (GFR < 60 mL/min/1.73 m²) or markers of renal damage, such as albuminuria (> 30 mg/g creatinine). A critical complication of CKD is mineral and bone disorder, including renal osteodystrophy, which presents diagnostic challenges due to its complex pathophysiology. This review critically evaluates the role of established and emerging imaging modalities in diagnosing renal osteodystrophy, a complex and critical mineral and bone disorder complicating CKD. It aims to guide clinicians in selecting optimal diagnostic strategies by synthesizing current evidence. Recent Findings Conventional diagnostic methods, particularly dual-energy X-ray absorptiometry, are frequently limited in their accuracy due to the confounding effects of vascular calcification and aberrant bone turnover. Recent advancements highlight the potential of radiation-free methods, such as Radiofrequency Echographic Multi-Spectrometry (REMS), to overcome these limitations. Furthermore, advanced imaging techniques including high-resolution peripheral quantitative computed tomography (HR-pQCT) and trabecular bone score (TBS) show significant promise for providing a more comprehensive assessment of bone microarchitecture and strength. Summary The emergence of innovative imaging tools offers the potential to improve the early detection and monitoring of renal osteodystrophy. By moving beyond the limitations of traditional bone density measurement, these technologies may lead to more accurate diagnosis and better management, ultimately enhancing patient outcomes.

Abstract Purpose of Review Neuroimaging, in particular magnetic resonance, has become a pivotal tool in understanding the pathophysiology of dementia, including Alzheimer’s disease (AD) and non-Alzheimer’s dementias (NAD). Combining structural and functional imaging techniques enables us to identify early brain changes, improve differential diagnosis, and monitor disease progression. This review focuses on the role of magnetic resonance imaging (MRI), especially functional MRI (fMRI), in supporting the clinical diagnosis of AD and distinguishing it from other forms of dementia. Recent Findings Advances in imaging techniques, such as structural MRI and fMRI, have significantly improved our ability to visualize pathological alterations associated with neurodegenerative conditions. While neuroimaging alone cannot provide a definitive diagnosis, it is a fundamental tool for clinicians in managing dementia, particularly in the early stages when clinical manifestations may be minimal or non-specific. MRI also plays a key role in monitoring responses to and side effects of therapies. Summary Our work has focused on evaluating the role of functional MRI in the study of Alzheimer’s disease, particularly in supporting the clinical diagnosis process and differential diagnosis with other types of dementia, as well as how MRI helps to monitor the response to new therapies for Alzheimer’s disease, such as anti-amyloid monoclonal antibodies.

Purpose of ReviewThis article will review several cases demonstrating breast imaging findings following the use of glucagon-like peptide-1 (GLP-1) agonists, including the relevant implications in changing breast density and supplemental screening.Recent FindingsGLP-1 agonists may be associated with breast changes and symptoms that warrant further breast imaging, including supplemental screening and/or for problem solving in the appropriate clinical scenario.SummaryBreast imaging findings following the use of GLP-1 agonists may vary, including both significant and insignificant increases in breast density. Patients with increased breast density may warrant further evaluation with supplemental screening. Following the use of GLP-1 agonists, patients may also present with symptoms warranting further targeted imaging evaluation. Knowledge of the spectrum of breast changes associated with GLP-1 agonists is necessary to adequately assess the need for supplemental screening and/or additional targeted breast imaging.

PurposeThis review explores the current landscape of AI applications in imaging for TAVR, emphasizing the potential and limitations of these tools for (1) automating the image analysis and reporting process, (2) improving procedural planning, and (3) offering additional insight into post-TAVR outcomes. Finally, the direction of future research necessary to bridge these tools towards clinical integration is discussed.Recent FindingsTranscatheter aortic valve replacement (TAVR) has become a pivotal treatment option for select patients with severe aortic stenosis, and its indication for use continues to broaden. Noninvasive imaging techniques such as CTA and MRA have become routine for patient selection, preprocedural planning, and predicting the risk of complications. As the current methods for pre-TAVR image analysis are labor-intensive and have significant inter-operator variability, experts are looking towards artificial intelligence (AI) as a potential solution.SummaryAI has the potential to significantly enhance the planning, execution, and post-procedural follow up of TAVR. While AI tools are promising, the irreplaceable value of nuanced clinical judgment by skilled physician teams must not be overlooked. With continued research, collaboration, and careful implementation, AI can become an integral part in imaging for TAVR, ultimately improving patient care and outcomes.