Pilot Study of a Novel Non-invasive Multimodal Imaging System in the Monitoring of Diabetic Foot Ulcer Progression
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 40
- 试验地点
- 1
- 主要终点
- Agreement in Ulcer Surface Area Measurement Between Remote and In-Clinic Assessments
研究概览
简要总结
The goal of this observational pilot study is to evaluate whether a new remote monitoring platform (TASHA) can support accurate and reliable assessment of diabetic foot ulcers in adult patients receiving care in a UK NHS clinic. The main questions it aims to answer are:
Can the TASHA platform provide ulcer assessment data (e.g., size, depth, visible infection) that aligns with in-clinic evaluations by healthcare professionals? Can patients accurately perform self-scanning of their ulcers using the platform under clinical supervision? What is the variation (inc. root mean square error) between clinician-led and patient-led scans?
Participants will:
- Attend a standard in-clinic ulcer assessment as part of their usual care Undergo an additional 3D foot scan using the TASHA platform during their clinic visit.
- Be guided to perform a self-scan using the same platform, with clinical staff present.
- Have their scan data reviewed remotely by a clinician to compare with in-clinic assessments.
- This feasibility study will inform the design of future larger-scale trials and contribute to regulatory development of the TASHA platform as a digital medical device.
详细描述
This is a prospective, single-site, single-arm pilot study designed to evaluate the feasibility, usability, and technical performance of the Tissue Analytics System for Health Assessments (TASHA) platform, a novel investigational medical device developed by Medical Intelligence Group Ltd. The platform integrates a non-invasive, high-resolution 3D scanning module with a secure data interface to generate a digital twin of diabetic foot ulcers (DFUs), allowing clinicians to assess wound status remotely and, in future iterations, support patient-led ulcer self-monitoring.
Study Rationale Diabetic foot ulcers are among the most debilitating and costly complications of diabetes, associated with high risks of infection, hospitalisation, and lower-limb amputation. Early and continuous monitoring of DFUs is critical to guide treatment, detect deterioration, and evaluate healing progression. However, current models of care rely predominantly on in-clinic assessments that are often infrequent due to healthcare capacity limitations, geographic access barriers, or logistical constraints.
Remote monitoring has the potential to increase continuity of care, improve early detection of wound deterioration, and reduce the clinical burden on specialist foot care services. The TASHA platform aims to address these needs by enabling structured, repeatable capture of wound images and clinical metadata for remote review and longitudinal tracking.
Study Design
This is a non-randomised, observational, exploratory pilot study involving up to 30 adult participants with active diabetic foot ulcers, conducted at a single National Health Service (NHS) clinic in the United Kingdom. The study is not powered to demonstrate clinical efficacy but is instead focused on evaluating:
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Adults aged 18 years or older
- •Diagnosed with a diabetic foot ulcer at the time of recruitment
- •Receiving routine care at the participating NHS clinic
- •Able to provide informed consent
- •Able to sit and engage with the TASHA scanning device
- •Willing to attempt a supervised self-scan of the affected foot
排除标准
- •Presence of non-diabetic foot ulcers
- •Severe cognitive or physical impairments that prevent scanning or understanding instructions
- •Active infection or medical instability requiring urgent intervention
- •Participation in another interventional study that may interfere with this assessment
- •Inability to communicate in English (unless appropriate translation or support is available)
结局指标
主要结局
Agreement in Ulcer Surface Area Measurement Between Remote and In-Clinic Assessments
时间窗: At each clinical visit per participant, up to 24 weeks
Comparison of ulcer surface area (cm²) between in-clinic manual measurement and remote assessments using TASHA platform 3D scans. Agreement will be evaluated using Intraclass Correlation Coefficient (ICC) and Bland-Altman analysis to determine alignment between manual and digital assessments. This will help establish whether remote scanning can reliably replicate clinical measurements of DFU size. Unit of measure - Ulcer surface area (cm²)
Agreement in Ulcer Depth Measurement Between Remote and In-Clinic Assessments
时间窗: At each clinical visit per participant, up to 24 weeks
Comparison of ulcer depth (mm) assessed in person by clinicians versus measurements obtained from TASHA platform-generated 3D scans. Statistical agreement will be analysed using Intraclass Correlation Coefficient (ICC) and root mean square error (RMSE). The goal is to determine the level of accuracy and consistency between traditional manual depth estimates and platform-generated data. Unit of measurement - Ulcer depth (mm)
Agreement in Detection of Visible Signs of Infection Between Remote and In-Clinic Assessments
时间窗: At each clinical visit per participant, up to 24 weeks
Comparison of in-clinic and remote assessments in identifying visible infection indicators such as erythema, exudate, and swelling using TASHA platform images. Agreement will be measured using percentage agreement and Cohen's Kappa for categorical variables. This will inform whether remote imaging data supports consistent clinical detection of surface-level infection features. Measured in Percentage agreement / Cohen's Kappa coefficient
Agreement in Ulcer Stage Classification Between Remote and In-Clinic Assessments
时间窗: Each clinical visit per patient unto 24 weeks
Assessment of agreement in diabetic foot ulcer (DFU) stage classification between in-clinic assessments by healthcare professionals and remote assessments based on TASHA platform scan data. Classification will use a standard ulcer staging system (e.g., Wagner or SINBAD). Agreement will be measured using Cohen's Kappa coefficient to evaluate inter-rater reliability for categorical data. This will determine the platform's ability to support accurate remote clinical interpretation. Unit of Measure: Cohen's Kappa coefficient
次要结局
- Root Mean Square Error Between Clinician and Patient Self-Scans of Ulcer Surface Area(At each clinical visit per participant, up to 24 weeks)