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Smartphone-based optical scanner to physiologically assess diabetic foot ulcers

基于智能手机的光学扫描仪可对糖尿病足溃疡进行生理评估

基本信息

批准号：
10503651
负责人：
ANURADHA GODAVARTY
金额：
$ 52.06万
依托单位：
FLORIDA INTERNATIONAL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-15 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10503651
关键词：
3-Dimensional Accounting Adopted African American population Amputation Assessment tool Beer Caring Caucasians Cellular Phone Characteristics Chronic Chronic Care Clinical Clinical assessments Clinics and Hospitals Collaborations Communities Complement Complications of Diabetes Mellitus Development Devices Diabetes Mellitus Diabetic Foot Ulcer Discipline of Nursing Ethnic Origin Ethnic group Excision Florida Functional Imaging Hispanic Americans Hospitalization Image Image Analysis Imaging technology Incidence International Laws Lesion Light Limb structure Maps Measurement Modeling Native Americans Near-infrared optical imaging Noise Optics Outcome Oxygen Patients Persons Physiological Pigmentation physiologic function Podiatry Positioning Attribute Race Research Research Design Risk SMART health Signs and Symptoms Skin Surface Surgeon Technology Tissues Triage Validation Variant Visual base clinical care computer science flu foot global health healing health care delivery high risk imaging approach in vivo innovation mHealth machine learning algorithm multidisciplinary mutant novel pandemic disease point of care preservation racial and ethnic skin color skin wound statistics tissue mapping tissue oxygenation tissue phantom tool validation studies wound wound care wound treatment

项目摘要

PROJECT SUMMARY One in three people with diabetes mellitus is at risk of diabetic foot ulcers (DFUs), with over 10% amputated. The current global pandemic has driven a significant change in healthcare delivery and disrupted DFU care and limb preservation, leaving many patients with limited or no clinical care. Clinicians must adopt a paradigm shift from the hospital and clinic care to community-based point-of-care (POC) - to best triage chronic DFU cases that are high-risk lesions requiring clinical care or hospitalization. There is an unmet clinical need for smart health assessment tools for POC treatment of patients with DFUs onsite, where no wound care expertise is available. Smartphone technologies for wound care are limited to 2D/3D wound image analysis for size/depth. They are insufficient as stand-alone tools to assess and triage high-risk DFU lesions without wound expertise onsite. Hence, additional clinical assessments (e.g., the extent of oxygen supply to wound) are required during POC of DFUs onsite. Oxygenation measurements provide a sub-clinical physiological assessment that complements clinical visual assessment. We recently developed a smartphone-based NIR imaging approach or SmartPhone Oxygenation Tool (SPOT) to obtain visual tissue oxygenation measurements in wounds. Systematic assessment of the skin tone and wound characteristics is critical during physiological imaging and has not been investigated to date. Hence, our objective is to develop and validate a smartphone-based imaging approach (or Smart Scanner) capable of visual and physiological analysis of DFUs across the spectrum of skin tones and wound features via automated machine learning (ML) algorithms. Developing a smartphone-based optical device via integration of existing NIR imaging technology, but towards smart health platform for physiological assessment of DFUs, while accounting for varying skin colors and wound types using ML algorithms is innovative. The specific aims are: (i) Account for the effect of skin tones on oxygenation measurements by applying light propagation models and machine learning algorithms and validate via phantom and in-vivo studies. (ii) Analyze tissue curvatures and account for depth variations in-vivo oxygenation maps via studies on control subjects (~15 cases). (iii) Differentiate wound tissue types and validate physiological imaging using the SPOT device via DFU studies (~25 cases). The expected outcomes are: (i) Develop our Smart Scanner (SPOT device + app) to obtain accurate tissue oxygenation maps across different skin tones and wound tissue types; (ii) Validate our SPOT device to differentiate DFUs with high-risk lesions that require clinical care, from low-risk cases. Incidence of DFUs and related amputation rates differ by race/ethnicity, and are higher in African Americans, Hispanic and Native Americans compared to Caucasians. In the long term, SPOT can be used as a smart health tool to pre-screen or triage DFUs with high-risk lesions to clinical care and thus minimize potential amputations in any racial/ethnic group (with varying skin tones).

项目总结