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Background/Objectives: Lipedema is a chronic and progressive adipose tissue disorder characterized by the abnormal accumulation of subcutaneous fat, predominantly in the legs and occasionally in the arms. The symptom that most signi cantly affects the quality of life is pain. Ultrasound elastography is an imaging technology that allows for measuring tissue stiffness quantitatively. This study aims to evaluate the relationship between accompanying pain in patients with lipedema and tissue elasticity measured using shear-wave elastography (SWE). Methods: Our study was designed as an observational, analytical and cross-sectional study. The visual analog scale (VAS) was used to assess pain, while the PainDetect questionnaire was utilized to evaluate neuropathic pain. The evaluation of tissue elasticity and brosis was conducted using the SWE method. Results: This research assessed thirty- ve patients, revealing an average age of 45.2 years and an average VKI of 33.6 kg/m². 60% of the patients had a lipedema diagnosis in their family history. Both age (p<0.01) and BMI (p<0.001) values were moderately correlated with all subcutaneous adipose tissue measurements, while no correlation was observed in SWE measurements. Only the level of the thigh in the SWE-Elasticity (SWE-E) values was related to VAS (p=0.03). Additionally, PainDetect data revealed correlations with SWE-Velocity (SWE-V) and SWE-E in both the right and left thighs. Conclusions: While SWE measurements were not correlated with skin adipose tissue, SWE measurements were correlated with pain and neuropathic pain in patients with lipedema. This nding highlights a potentially important relationship between tissue elasticity and pain, which may warrant further exploration.
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Lipedema is a chronic, estrogen-sensitive adipose tissue disorder characterized by disproportionate subcutaneous fat accumulation, fibrosis, inflammation, and resistance to fat mobilization. Despite its high prevalence, lipedema remains poorly understood and frequently misdiagnosed. This narrative review proposes a novel pathophysiological model in which menopause acts as a critical turning point in the progression of lipedema, driven by estrogen receptor imbalance (ERβ predominance over ERα), intracrine estrogen excess, and adipose tissue dysfunction. We demonstrate how menopauseinduced estrogen deficiency amplifies adipose tissue dysfunction by suppressing ERα signaling, enhancing ERβ activity, and disrupting mitochondrial function, insulin sensitivity, and lipid oxidation. Concurrently, the upregulation of aromatase and 17β-HSD1, combined with the suppression of 17β-HSD2, sustains localized estradiol excess, perpetuating inflammation, fibrosis, and immune dysregulation. The molecular signature observed in lipedema closely mirrors that of other estrogen-driven gynecological disorders, such as endometriosis, adenomyosis, and uterine fibroids. Understanding these molecular mechanisms highlights the pivotal role of menopause as a catalyst for disease progression and provides a rationale for targeted therapeutic strategies, including hormonal modulation and metabolic interventions. This review reframes lipedema as an estrogen receptor– driven gynecological disorder, offering a new perspective to improve clinical recognition, diagnosis, and management of this neglected condition.
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Lipedema is a chronic medical condition characterized by a symmetric buildup of adipose tissue (fat) in the legs and arms. A common but under-recognized disorder, Lipedema may cause pain, swelling, easy bruising, and impaired mobility. During the past decade, Lipedema, which occurs almost exclusively in women, has been demonstrated to be a disease that is distinct from obesity, lymphedema, cellulite, and other adipose conditions. The Lipedema Research Roadmap identifies recommendations to strengthen and grow Lipedema research. It presents a forward-looking summary of gaps in knowledge and opportunities for research and development, sourced from “Lipedema: A Current Understanding of Its Pathology and Natural History” (Lipedema Foundation; preprint, forthcoming), as well as input from authors and advisors. Recommendations are organized into six chapters covering key objectives: fostering the research environment, developing reporting standards and best practices, improving diagnosis, broadening understanding of the biology of the disease, identifying potential treatments, and enhancing epidemiology. The Research Roadmap development process incorporated input from more than 60 stakeholders, including researchers, clinicians, and patients. 24 external reviewers provided more than 1,300 comments and recommended edits.
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Background: An adequate dietary energy supply is particularly important in patients with lipedema as it promotes weight and fat loss. Accurate estimation of resting metabolic rate (RMR) allows implementing a proper calorie restriction diet in patients with lipedema. Therefore, an accurate assessment of energy demand in patients with lipedema is crucial in clinical practice. Our study aimed to compare actual resting metabolic rate (aRMR) with predicted resting metabolic rate (pRMR) in women with lipedema and to determine the association between individual anthropometric measurements and aRMR.Methods: A total of 108 women diagnosed with lipedema were enrolled in the study. aRMR was measured by indirect calorimetry (IC) using FitMate WM metabolic system (Cosmed, Rome, Italy). pRMR was estimated with predictive equations and BIA. All anthropometric measurements were based on BIA (bioelectric impedance analysis).Results: The mean aRMR in the study group was 1705.2 ± 320.7 kcal/day. Most methods of predicted RMR measurement used in our study significantly underpredicted aRMR in patients with lipedema. We reported statistically significant high correlations between all anthropometric measurements and aRMR/pRMR and a moderate correlation between visceral fat level (VFL) and aRMR. Conclusions: aRMR in patients with lipedema calculated with predictive equations was significantly lower than aRMR measured with other methods. This study found the agreement of predictive equations compared to IC is low (&lt;60%). Fat-free mass (FFM) is a stronger determinant of RMR in patients with lipedema than fat mass.
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