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Recent research has suggested that one novel mechanism of action for anti-obesity medications is to stimulate the activation of brown adipose tissue (BAT). 18FDG PET/CT remains the gold standard for defining and quantifying BAT. SUVmax is the most often used quantification tool in clinical practice. However, this parameter does not reflect the entire BAT volume. As a potential method for precisely evaluating BAT, we have utilised metabolic tumour volume (MTV) and total lesion glycolysis (TLG) to answer the question: Are MTV and TLG accurate in quantifying the intensity of BAT activation? After analysing the total number of oncological 18F-FDG PET/CT scans between 2021–2023, we selected patients with active BAT. Based on the BAT SUVmax, the patients were divided into BAT-moderate activation (MA) vs. BAT-high activation (HA). Furthermore, we statistically analysed the accuracy of TLG and MTV in assessing BAT activation intensity. The results showed that both parameters increased their predictive value regarding BAT activation, and presented a significantly high sensitivity and specificity for the correct classification of BAT activation intensity. To conclude, these parameters could be important indicators with increased accuracy for classifying BAT expression, and could bring additional information about the volume of BAT to complement the limitations of the SUVmax.

Chronic kidney disease and Alzheimer’s disease are chronic conditions highly prevalent in elderly communities and societies, and a diagnosis of them is devastating and life changing. Demanding therapies and changes, such as non-compliance, cognitive impairment, and non-cognitive anomalies, may lead to supplementary symptoms and subsequent worsening of well-being and quality of life, impacting the socio-economic status of both patient and family. In recent decades, additional hypotheses have attempted to clarify the connection between these two diseases, multifactorial in their nature, but even so, the mechanisms behind this link are still elusive. In this paper, we sought to highlight the current understanding of the mechanisms for cognitive decline in patients with these concurrent pathologies and provide insight into the relationship between markers related to these disease entities and whether the potential biomarkers for renal function may be used for the diagnosis of Alzheimer’s disease. Exploring detailed knowledge of etiologies, heterogeneity of risk factors, and neuropathological processes associated with these conditions opens opportunities for the development of new therapies and biomarkers to delay or slow their progression and validation of whether the setting of chronic kidney disease could be a potential determinant for cognitive damage in Alzheimer’s disease.