Diabetes mellitus affected 285 million adults worldwide in 2010 and is expected to increase in prevalence to 439 million people by the year 2030. Foot ulceration continues to be a major comorbidity of diabetes and afflicts as many as 15 to 25% of subjects with type 1 and 2 during their lifetime. In fact, roughly 85% of all lower extremity amputations in patients with diabetes mellitus are preceded by a foot ulcer. Untreated diabetic foot ulceration and subsequent amputation has a profound impact on the quality of life of the diabetic patient. Finally, in 2007, the treatment of diabetes and its complications in the United States generated at least $116 billion in direct costs;at least 33% of these costs were linked to the treatment of foot ulcers. Tissue perfusion, oximetry, and hydration have been shown to predict ulcer healing and formation. These quantities provide insight into the metabolism, microstructure and health of the skin. One promising technology for measuring local tissue perfusion, oxygenation, hydration, and microstructure in-vivo is diffuse optical spectroscopy (DOS). DOS is a quantitative near-infrared (NIR) spectroscopy technique that can determine absolute concentrations of chromophores such as oxy &deoxy hemoglobin, fat and water. Modulated Imaging (MI) is a NIR imaging method invented at BLI that is based on the principles of DOS and employs patterned illumination to interrogate biological tissues. This non-contact approach enables rapid quantitative determination of the optical properties and in-vivo concentrations of chromophores over a wide field-of-view. More importantly, MI can also be used to measure the tissue's reduced scattering coefficient and thus gain insight into microstructural changes in the tissue during ulcer formation and healing due to collage scarring, callus formation, necrosis, or inflammation. The central aim of the proposed research is to prove Modulated Imaging (MI) as a means to predict/monitor complications of the diabetic foot. We propose to develop two-layer computational techniques that will enhance the accuracy and precision of data obtained from foot skin having strong melanin pigmentation or thick callus. Once this MI system, algorithm, and software have been validated on tissue simulating phantoms, we will collect data from subjects exhibiting diabetic foot ulceration. A predictive model for ulcer formation and healing will be developed using this data. Results from this pilot study will be used to carefully design a Phase II study to establish the predictive power of MI-based models to predict ulcer formation and healing.
Foot ulceration continues to be a major co-morbidity of diabetes and afflicts as many as 15 to 25% of subjects with type 1 and type 2 during their lifetime. We propose to use novel imaging technology (Modulated Imaging) to facilitate prediction of ulcer formation or non-healing. Our technology has the potential to significantly reduce the human and financial cost of diabetic foot ulceration.