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PET/CT analysis connects metabolic activities to an aggressive uterus.

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Aggressive According to Norwegian studies, the Norwegian study, which will be published in the 38th Congress of the European Nuclear Medical Association (EANM ’25) in Barcelona on October 5, may be associated with high metabolic activities of visceral provinces.

Discovery comes from the analysis of PET/CT image of 274 women with macrocytectary cancer that measures glucose absorption from visceral fat tissue. Visual fats (surrounding internal organs) are known to affect metabolism and inflammation.

According to Jostein sæterstøl, A, women with high metabolic active women (absorption of glucose) were more likely to represent advanced stage diseases and lymph node metastasis. Ph.D. Haukeland University Hospital Mohn Medical Imaging and Gimization Center and Radiation of Bergen University.

“Chronic inflammation of visceral fat can release cytokine and fatty acids that promote tumor growth and avoidance of immune.” “Inflammation is also known to induce insulin resistance, which is another risk factor for cancer progression.”

In addition, signaling molecules, known as adipisin and cross -stoke between adipose tissue and tumor cells, can support cancer spreads, especially lymph nodes, Sæterstøl said.

Memorial cancer in the uterus is the most common wife and cancer in Europe, Increased incidence Obesity.

According to researchers, the usual use of visceral fat metabolism with technical tasks and variability limit PET/CT, especially when the absorption signal of adipose tissue is low. But they said they could help to identify high -risk patients, guide treatment decisions, and monitor the disease progression, including standardized imaging analysis, advanced quantitative PET technology and AI.

The group plans to improve the accuracy through refining methods and AI -based segmentation and to focus on exploring connections between visceral metabolism and cyclic biomarkers such as cytokine and hormones. They also try to explore the connection with the tumor genome profile.



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