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  • Hendesi, F. (2026). Modern approaches to the diagnosis and multimodal management of lipedema: A phlebology-oriented clinical framework. Phlebology, 2683555261451571. https://doi.org/10.1177/02683555261451571

    BackgroundLipedema is a chronic and progressive disorder of subcutaneous adipose tissue that predominantly affects women and is frequently misdiagnosed as obesity, lymphedema, or venous disease. Increasing evidence indicates that lipedema represents a systemic vascular-lymphatic-inflammatory disorder rather than a cosmetic or metabolic condition. Delayed diagnosis often results in progressive fibrosis, lymphatic dysfunction, chronic pain, and functional impairment.ObjectiveThis review aims to present a structured, clinically applicable framework for the diagnosis and multimodal management of lipedema within phlebology practice, with an emphasis on stage-specific assessment and integrated therapeutic strategies.MethodsA narrative clinical review of peer-reviewed literature in phlebology, vascular medicine, lymphatic disorders, and adipose tissue pathology was conducted. Diagnostic criteria, clinical staging, and differential diagnostic features were synthesized into a practical, stage-based framework. A multilayer therapeutic approach targeting inflammation, lymphatic function, adipose tissue pathology, extracellular matrix remodeling, and post-treatment rehabilitation is proposed.ResultsAccurate diagnosis of lipedema relies primarily on clinical evaluation, including pain assessment, tissue palpation, characteristic fat distribution, and exclusion of lymphedema and simple obesity. Early-stage identification enables effective intervention focused on inflammation control and lymphatic unloading, potentially preventing irreversible fibrosis. Advanced stages require targeted adipose tissue interventions, fibrosis management, and structured rehabilitation to preserve mobility and quality of life.ConclusionLipedema should be recognized as a systemic vascular-lymphatic-inflammatory disorder within phlebology practice. Early diagnosis and implementation of a structured, stage-specific multimodal treatment framework may significantly alter disease progression and reduce the risk of long-term disability.

  • Hendesi, F., & Nazem, A. (2026). LipoVena AI framework: A physician-centered artificial intelligence-assisted approach for longitudinal assessment in lipedema and chronic venous disorders. Phlebology, 2683555261499792. https://doi.org/10.1177/02683555261499792

    BackgroundChronic venous disorders and lipedema are complex and frequently underdiagnosed conditions characterized by heterogeneous clinical presentations, progressive tissue remodeling, and substantial variability in treatment response assessment. Despite advances in minimally invasive vascular interventions, longitudinal evaluation in routine clinical practice continues to rely heavily on subjective interpretation, non-standardized comparative imaging, and physician-dependent assessment pathways. The integration of multimodal vascular data into structured longitudinal clinical workflows remains limited.ObjectiveThis study introduces the LipoVena AI Framework, a physician-centered conceptual artificial intelligence-assisted clinical support architecture designed to facilitate multimodal integration, longitudinal treatment-response evaluation, and personalized monitoring in lipedema and chronic venous disease management.MethodsA retrospective observational clinical dataset consisting of 32 patients with chronic venous insufficiency, lipedema, reticular veins, spider veins, and mixed venous-lymphatic phenotypes was reviewed. Standardized standing-position photography, duplex ultrasound imaging, procedural documentation, and longitudinal 1-month follow-up assessments were integrated within a conceptual AI-assisted workflow. Representative patients underwent multimodal minimally invasive treatment strategies including endovenous laser therapy (EVLT), CLACS-guided sclerotherapy, radiofrequency-based tissue remodeling, and compression therapy. The proposed framework conceptually integrates multimodal imaging analysis, vascular mapping, comparative longitudinal assessment, and physician-supervised AI-assisted interpretation.ResultsRepresentative 1-month follow-up observations demonstrated visible improvements in contour harmonization, superficial venous prominence, tissue irregularity, skin texture uniformity, and vascular burden across multiple venous and lipedema phenotypes. Comparative multimodal analysis integrating clinical photography and duplex ultrasound findings enabled structured longitudinal assessment of therapeutic response patterns. Upper-extremity lipedema cases additionally demonstrated measurable contour and tissue-texture improvement following multimodal treatment strategies. The proposed framework illustrated the potential role of AI-assisted longitudinal comparison and multimodal integration in supporting objective treatment-response evaluation within physician-centered vascular care workflows.ConclusionThe LipoVena AI Framework presents a conceptual translational model for future AI-assisted vascular and lipedema medicine by integrating standardized clinical imaging, duplex ultrasound evaluation, multimodal treatment documentation, and longitudinal follow-up analysis within a physician-centered ecosystem. Although prospective multicenter validation and quantitative AI modeling remain necessary, the present framework highlights the potential of explainable and physician-supervised artificial intelligence systems to support personalized, data-driven, and longitudinally optimized vascular care.

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Last update from database: 11/1/26, 8:25 AM (UTC)

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