Related Experiment Video For adipose tissue
Updated: Jul 5, 2025

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
Published on: April 4, 2012
Fat Matters: Exploring Cancer Risk through the Lens of Computed Tomography and Visceral Adiposity
Federico Greco1,2, Claudia Lucia Piccolo2,3, Valerio D'Andrea2,3
1Department of Radiology, Cittadella della Salute Azienda Sanitaria Locale di Lecce, Piazza Filippo Bottazzi 2, 73100 Lecce, Italy.
Abstract:
Obesity is an established risk factor for cancer. However, conventional measures like body mass index lack precision in assessing specific tissue quantities, particularly of the two primary abdominal fat compartments, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Computed tomography (CT) stands as the gold standard for precisely quantifying diverse tissue types. VAT, distinguished by heightened hormonal and metabolic activity, plays a pivotal role in obesity-related tumor development. Excessive VAT is linked to aberrant secretion of adipokines, proinflammatory cytokines, and growth factors, fostering the carcinogenesis of obesity-related tumors. Accurate quantification of abdominal fat compartments is crucial for understanding VAT as an oncological risk factor. The purpose of the present research is to elucidate the role of CT, performed for staging purposes, in assessing VAT (quantity and distribution) as a critical factor in the oncogenesis of obesity-related tumors. In the field of precision medicine, this work takes on considerable importance, as quantifying VAT in oncological patients becomes fundamental in understanding the influence of VAT on cancer development-the potential "phenotypic expression" of excessive VAT accumulation. Previous studies analyzed in this research showed that VAT is a risk factor for clear cell renal cell carcinoma, non-clear cell renal cell carcinoma, prostate cancer, and hepatocarcinoma recurrence. Further studies will need to quantify VAT in other oncological diseases with specific mutations or gene expressions, in order to investigate the relationship of VAT with tumor genomics.
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