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AI-Powered and Robot-Assisted Opto-Acoustic Evaluation of Systemic Microangiopathy for Ulcer Healing Outcomes in Type 2 Diabetes

Cel

Type 2 diabetes mellitus (T2DM) contributes to chronic non-healing ulcers (NHUs), leading to infections and amputations. Key challenges for vascular surgeons are predicting the development of NFUs and most importantly choosing between limb salvage and timely amputation to enhance the patient's long-term quality of life. Often, the focus is on correcting atherosclerotic lesions in macrovessels, while the impact of small vessel damage, known as diabetes-associated microangiopathy (DAM), remains largely overlooked. DAM not only affects the structure but also the function of microvessels, disrupting the balance between local perfusion and energy needs, which is crucial for NHUs development. Although previous studies have explored DAM in central organs such as the kidneys, nerves, and eyes, its effects on ulcer-related tissues—including skin, adipose tissue, and skeletal muscle—are not well understood and are absent from clinical management strategies. To bridge this gap, I propose an innovative approach to investigate soft tissue DAM and place it at the forefront of vascular care in NFUs. My plan involves creating a robot-assisted, light-based platform for the non-invasive assessment of 'global' DAM through microvascular and vasometabolic features that reflect blood perfusion and oxygen kinetics in soft tissues. I will develop a practical tool for analyzing complementary optical and optoacoustic data alongside clinical information, culminating in the novel ARETEOS concept—a unique framework for monitoring DAM and predicting outcomes in NFUs. ARETEOS will be validated in individuals with T2DM and NHUs by using artificial intelligence to predict ulcer development, healing outcomes, limb salvage potential, and the success of peripheral revascularization. This innovative strategy aims to transform patient management in vascular surgery and is further applicable to other cardiovascular and metabolic diseases, shifting the paradigm in relevant research and clinical care.

Dziedzina nauki (EuroSciVoc)

Projekt nie został jeszcze sklasyfikowany według klasyfikacji EuroSciVoc.
Wskaż dziedziny nauki, które twoim zdaniem są najbardziej istotne z punktu widzenia tego projektu i pomóż nam usprawnić naszą usługę klasyfikacji.

Program(-y)

Temat(-y)

System finansowania

HORIZON-ERC - HORIZON ERC Grants

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Zaproszenie do składania wniosków

(odnośnik otworzy się w nowym oknie) ERC-2026-STG

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Instytucja przyjmująca

UNIVERSITATSKLINIKUM ERLANGEN
Wkład UE netto
€ 1 499 068,00
Koszt całkowity
€ 1 499 068,00

Beneficjenci (1)