Point-of-care wound visioning technology: Reproducibility and accuracy of a wound measurement app

Controlled Pilot Intervention Study on the Effects of an AI-Based Application to Support Incontinence-Associated Dermatitis and Pressure Injury Assessment, Nursing Care and Documentation: Study Protocol

Artificial Intelligence (AI)-based applications have significant potential to differentiate between pressure injuries (PI) and incontinence-associated dermatitis (IAD), common challenges in nursing practice. Within the KIADEKU overall project, we are developing an AI-based application to aid in the nursing care of PI and IAD and to facilitate personalized, evidence-based nursing interventions. The KIADEKU clinical sub-study described in this study protocol is a controlled, non-randomized clinical pilot intervention study investigating the effects of the AI-based application, fully developed in the KIADEKU overall project, on the duration of wound assessment, dressing change and documentation, guideline adherence, and nurse task load. The study utilizes a pre-post design with two data collection periods. During the initial phase, we will observe and survey nurses in the control group as they provide conventional wound care without AI support to adult patients with PI or IAD in the pelvic area across eight wards at the LMU University Hospital. In the following intervention phase, the AI-based application will assist nurses in wound assessment and deliver guideline-based nursing interventions for documented wound types. Observations and surveys will be repeated. Measurements will include the duration of wound assessment, dressing changes, and documentation, adherence to wound care guidelines, and the accuracy of AI predictions in clinical settings, validated by an on-site expert assessment. The survey will assess nurses' task load and other covariates, such as professional experience, overall workload during the shift, and wound severity. Linear regression models will be used to analyze the effects of AI usage on the aforementioned aspects, taking into account these covariates. The accuracy of AI predictions regarding wound type and classification will be measured using the on-site expert's assessment as the ground truth. The usability of the AI-based application and standard clinical documentation systems will be evaluated further. The deployment of the AI application in clinical settings aims to reduce the duration of wound assessments, dressing changes, and documentation; decrease nurse task load; enhance guideline adherence in wound care; and promote AI utilization in nursing. German Clinical Trials Register (DRKS) (DRKS00031355). Registered on April 5th, 2023. TRIAL REGISTRATION: German Clinical Trials Register (DRKS) DRKS00031355. Registered on April 5th 2023. PATIENT OR PUBLIC CONTRIBUTION: Patient representatives contributed to the development of the AI-based application through the use of Delphi methodology, as part of the KIADEKU qualitative sub-study.

Breast cancer wound imaging: evaluation of the cross-localisation method

OBJECTIVE

Wound image acquisition has been widely used in wound care; however, there are few reports on scientifically accurate technology in wound image acquisition for wound evaluation. This study compared the effectiveness of a cross-localisation method with a direct photographic method for image acquisition of breast cancer wounds.

METHOD

The wounds of eligible patients were assessed by direct measurement, direct photography, and by a cross-localisation method using the Bates-Jensen Wound Assessment Tool (BWAT) with 13 items. After four months, the wound images were re-evaluated and re-recorded for consistency assessment.

RESULTS

The experimental cohort comprised 150 patients. The consistency of the total BWAT score between the direct photograph acquisition and direct measurement methods was poor (Kappa=0.375). Only wound size, induration and exudate type presented general consistency. There was a good consistency between the cross-localisation image method and the direct measurement method (Kappa=0.786). The wound size, depth, oedema, induration and granulation tissue demonstrated complete consistency between the direct measurement and cross-localisation methods (Kappa=1.000).

CONCLUSION

Wound imaging using direct photography does not present the wound characteristics with complete clarity; however cross-localisation with an objective reference showed optimal performance in this study. The cross-localisation method can provide more specific and accurate wound evaluation.

Current status, challenges, and prospects of artificial intelligence applications in wound repair theranostics

Skin injuries caused by physical, pathological, and chemical factors not only compromise appearance and barrier function but can also lead to life-threatening microbial infections, posing significant challenges for patients and healthcare systems. Artificial intelligence (AI) technology has demonstrated substantial advantages in processing and analyzing image information. Recently, AI-based methods and algorithms, including machine learning, deep learning, and neural networks, have been extensively explored in wound care and research, providing effective clinical decision support for wound diagnosis, treatment, prognosis, and rehabilitation. However, challenges remain in achieving a closed-loop care system for the comprehensive application of AI in wound management, encompassing wound diagnosis, monitoring, and treatment. This review comprehensively summarizes recent advancements in AI applications in wound repair. Specifically, it discusses AI's role in injury type classification, wound measurement (including area and depth), wound tissue type classification, wound monitoring and prediction, and personalized treatment. Additionally, the review addresses the challenges and limitations AI faces in wound management. Finally, recommendations for the application of AI in wound repair are proposed, along with an outlook on future research directions, aiming to provide scientific evidence and technological support for further advancements in AI-driven wound repair theranostics.

Enhancing Surgical Wound Monitoring: A Paired Cohort Study Evaluating a New AI-Based Application for Automatic Detection of Potential Infections

Background/Objectives: This study assessed the feasibility and security of remote surgical wound monitoring using the RedScar© smartphone app, which employs automated diagnosis for early visual detection of infections without direct healthcare personnel involvement. Additionally, patient satisfaction with telematic care was evaluated as a secondary aim. Surgical site infection (SSI) is the second leading cause of healthcare-associated infections (HAIs), leading to prolonged hospital stays, heightened patient distress, and increased healthcare costs. Methods: The study employed a prospective paired-cohort and single-blinded design, with a sample size of 47 adult patients undergoing abdominal surgery. RedScar© was used for remote telematic monitoring, evaluating the feasibility and security of this approach. A satisfaction questionnaire assessed patient experience. The study protocol was registered at ClinicalTrials.gov under the identifier NCT05485233. Results: Out of 47 patients, 41 successfully completed both remote and in-person follow-ups. RedScar© demonstrated a sensitivity of 100% in detecting SSIs, with a specificity of 83.13%. The kappa coefficient of 0.8171 indicated substantial agreement between the application's results and human observers. Patient satisfaction with telemonitoring was high: 97.6% believed telemonitoring reduces costs, 90.47% perceived it prevents work/school absenteeism, and 80.9% found telemonitoring comfortable. Conclusions: This is the first study to evaluate an automatic smartphone application on real patients for diagnosing postoperative wound infections. It establishes the safety and feasibility of telematic follow-up using the RedScar© application for surgical wound assessment. The high sensitivity suggests its utility in identifying true cases of infection, highlighting its potential role in clinical practice. Future studies are needed to address limitations and validate the efficacy of RedScar© in diverse patient populations.

Application of deep learning in wound size measurement using fingernail as the reference

OBJECTIVE

Most current wound size measurement devices or applications require manual wound tracing and reference markers. Chronic wound care usually relies on patients or caregivers who might have difficulties using these devices. Considering a more human-centered design, we propose an automatic wound size measurement system by combining three deep learning (DL) models and using fingernails as a reference.

MATERIALS AND METHODS

DL models (Mask R-CNN, Yolov5, U-net) were trained and tested using photographs of chronic wounds and fingernails. Nail width was obtained through using Mask R-CNN, Yolov5 to crop the wound from the background, and U-net to calculate the wound area. The system's effectiveness and accuracy were evaluated with 248 images, and users' experience analysis was conducted with 30 participants.

RESULTS

Individual model training achieved a 0.939 Pearson correlation coefficient (PCC) for nail-width measurement. Yolov5 had the highest mean average precision (0.822) with an Intersection-over-Union threshold of 0.5. U-net achieved a mean pixel accuracy of 0.9523. The proposed system recognized 100% of fingernails and 97.76% of wounds in the test datasets. PCCs for converting nail width to measured and default widths were 0.875 and 0.759, respectively. Most inexperienced caregivers consider convenience is the most important factor when using a size-measuring tool. Our proposed system yielded 90% satisfaction in the convenience aspect as well as the overall evaluation.

CONCLUSION

The proposed system performs fast and easy-to-use wound size measurement with acceptable precision. Its novelty not only allows for conveniences and easy accessibility in homecare settings and for inexperienced caregivers; but also facilitates clinical treatments and documentation, and supports telemedicine.

Co-creation and evaluation of an algorithm for the development of a mobile application for wound care among new graduate nurses: A mixed methods study

Chronic wounds are a growing concern due to aging populations, sedentary lifestyles and increasing rates of obesity and chronic diseases. The impact of such wounds is felt worldwide, posing a considerable clinical, environmental and socioeconomic challenge and impacting the quality of life. The increasing complexity of care requires a holistic approach, along with extensive knowledge and skills. The challenge experienced by health-care professionals is particularly significant for newly graduate nurses, who face a gap between theory and practice. Digital tools, such as mobile applications, can support wound care by facilitating more precise assessments, early treatment, complication prevention and better outcomes. They also aid in clinical decision-making and improve healthcare delivery in remote areas. Several mobile applications have emerged to enhance wound care. However, there are no applications dedicated to newly graduate nurses. The aim of this study was to co-create and evaluate an algorithm for the development of a wound care mobile application supporting clinical decisions for new graduate nurses. The development of this mobile application is envisioned to improve knowledge application and facilitate evidence-based practice. This study is part of a multiphase project that adopted a pragmatic epistemological approach, using the 'Knowledge-to-Action' conceptual model and Duchscher's Stages of Transition Theory. Following a scoping review, an expert consensus, and stakeholder meetings, this study was pursued through a sequential exploratory mixed methods design carried out in two phases. In the initial phase, 21 participants engaged in semi-structured focus groups to explore their needs regarding clinical decision support in wound care, explore their perceptions of the future mobile application's content and identify and categorize essential components. Through descriptive analysis, five overarching themes emerged, serving as guiding principles for conceptual data model development and refinement. These findings confirmed the significance of integrating a comprehensive glossary complemented by photos, ensuring compatibility between the mobile application and existing documentation systems, and providing quick access to information to avoid burdening work routines. Subsequently, the algorithm was created from the qualitative data collected. The second phase involved presenting an online SurveyMonkey® questionnaire to 34 participants who were not part of the initial phase to quantitatively measure the usability of this algorithm among future users. This phase revealed very positive feedback regarding the usability [score of 6.33 (±0.19) on a scale of 1-7], which reinforces its quality. The technology maturation process can now continue with the development of a prototype and subsequent validation in a laboratory setting.

Comparative Analysis of Mathematical Models and App-Based Measurement for Estimating the Cutaneous Wound Areas of Captive Asian Elephants

Objective To evaluate the variation in the area estimation under different mathematical calculations against measurement by a smartphone application in estimating the cutaneous wound areas in captive Asian elephants. Methods The study was conducted on captive Asian elephants (Elephas maximus) with cutaneous wounds reported to Veterinary Hospitals of Kerala Veterinary and Animal Sciences University and elephant camps within and outside Kerala state (mostly southern states of India, namely, Kerala and Tamil Nadu) over the period September 2019 to October 2022. Thirty-five clinical cases diagnosed with skin wounds of different aetiologies at various parts of the body were subjected to measurement, and 111 measurements were taken using a smartphone application, Imito Measure (Imito AG, Zurich, Switzerland). Based on the outer wound perimeters hand-marked on the mobile screen over the image taken, Imito Measure calculated the length, width, perimeter, and area. The length and width measurements from this were applied to four mathematical models of wound measurements. Wound surface area calculations were further done by these models and were compared. Results The observed results indicated no significant difference between the five methods of area measurement in all the studied cases since the P > 0.05. Conclusion The findings revealed no significant difference between the five techniques of wound area measurement. From the practical clinical utility point, the smartphone application has an edge over the mathematical methods in animals, especially captive Asian elephants, as it has the major advantage of being non-contact and thus addresses some major welfare concerns.

Application to Quantify Ulcer Areas and Track Their Progress

Chronic ulcer treatments, such as those for diabetic foot ulcers and pressure sores, require prolonged treatment periods. Availability of effective objective indicators to determine treatment method efficacy is limited. Ulcer area is the agreed-upon indicator for ulcer healing because it contracts and/or undergoes epithelialization as healing occurs. Ulcer surface properties such as healthy or infected granulation and slough or necrotic tissue are also used. This study aimed to develop a user-friendly application automating the ulcer area measurement process and included a graphical time-series display of ulcer components manually classified by users. Images of ulcers photographed with adjacent circular 1.5-cm diameter stickers were prepared. In the application, users manually categorized and color-coded each image into five component types based on different ulcer characteristics. The application calculated the area of each component in pixels and then estimated the actual area using the sticker area as a reference. It also collated color-coded images and presented graphical illustrations of changes in area over time. The results indicated the application successfully automated area measurements of each ulcer component and graphical displays of changes in ulcer component areas over time. It enabled users to visually track quality changes and the chronic ulcer healing process. Historically, ulcer assessments are subjectively conducted via visual examination by physicians, creating less reproducible, objective data. Although ulcer properties still required manual entry by users, our application streamlined ulcer area measurement and time-course visualization and sets the groundwork for a fully automated artificial-intelligence-driven ulcer diagnosis system.

Accuracy of digital measurement for quantitative and qualitative indicators of wound healing and repair: a systematic review protocol

INTRODUCTION

Chronic wound care remains a critical public health challenge in terms of prevalence, quality of life and healthcare costs on a global scale. Currently used methods to assess the size and content of wounds include direct contact techniques based on double-layer film, ruler measurements, digital photography and visual examination. Nowadays, despite these evaluations, close monitoring and tracking of these chronic wounds remain a great challenge. The use of telemonitoring through digital measurement tools may offer a potential means of improving healing management processes. Many studies have evaluated the size and content of the wound through digital devices such as mobile phones and computers. However, the clinical accuracy of these tools remains to be clarified. The objective of this systematic review is to assess and consolidate the current state-of-the-art digital devices for both quantitative (length, width, surface area, perimeter, volume and depth) and qualitative (granulation, fibrin, necrosis and slough) indicators of wound care.

METHODS AND ANALYSIS

We will include studies using digital measurement methods from databases such as EBSCO, Cochrane Library, MEDLINE, Web of Science and EMBASE, limited to French and English publications until November 15, 2023. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines, selection involves two independent reviewers conducting title and abstract screenings, study selections, data extractions and risk-of-bias assessments using QUADAS-2. Discrepancies will be resolved through discussion or a third reviewer.

ETHICS AND DISSEMINATION

Primary data will not be collected in this study; thus, ethical approval will not be required. The study's findings will be published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42023396642.

Is Shock Wave Application Effective on Various Chronic Wounds in the Geriatric Population? Preliminary Clinical Study

Purpose

Extracorporeal shock wave therapy (ESWT) is a beneficial adjunct modality for chronic wounds. Limited research has been conducted on pressure ulcers (PUs), while the majority of studies have focused on diabetic foot ulcers (DFUs) and venous leg ulcers (VLUs). This study aimed to evaluate the short-term effects of radial ESWT in older adults with chronic wounds.

Patients and Methods

This study involved a total of 31 wounds: PUs (n=22), VLUs (n=7), and DFUs (n=2). A single radial ESWT was performed with 300 + 100 shocks per cm2, pressure of 2.5 bar, energy of 0.15 mJ/mm2, and frequency of 5 Hz. Assessments using digital planimetry and clinical methods, utilizing the Wound Bed Score (WBS) and the Bates-Jansen Wound Assessment Tool (BWAT) were performed before the radial ESWT application (M0) and one week after (M1).

Results

A significant wound decrease in planimetry was noted (pre-ESWT vs post-ESWT), with wound area from 9.4 cm2 to 6.2 cm2, length from 6.4 cm to 3.9 cm, and width from 2.8 cm to 2.1 cm (p<0.001). Additionally, a substantial clinical improvement was noted in both the WBS with a 31.25% increase and the BWAT with a 20.00% increase (p<0.001). It was also found a significant correlation between the planimetric and clinical outcomes for both tools: WBS (r=-0.446, p=0.012) and BWAT (r=0.327, p=0.073).

Conclusion

The ESWT application yields substantial immediate clinical effects that support the healing of chronic wounds in older adults. Even a single ESWT session can prove to be clinically effective and beneficial in the management of chronic wounds.

The clinical value of intelligent wound measurement devices in patients with chronic wounds: A scoping review

Chronic wounds are common in clinical practice, with long treatment cycle and high treatment cost. Changes in wound area can well predict the effectiveness of treatment and the possibility of healing. Therefore, continuous wound monitoring and evaluation are particularly important. Traditional manual wound measurement tends to overestimate wound area. Recently, various intelligent wound measurement devices have been introduced into clinical practice. This review aims to summarise the reliability, validity, types and measurement principles of different intelligent wound measurement devices, so as to analyse the clinical value and application prospect. Articles numbering 2610 were retrieved from the database, and 14 articles met the inclusion criteria. The results showed that the intelligent wound measurement devices included in the study reported good reliability and validity. Contact devices can lead to wound bed damage, wound deformation, patient pain, and is not convenient for electronic wound recording; partial contact devices can complete continuous monitoring and recording of wounds, but are not sensitive to wound depth measurement. Non-contact devices are more accurate in capturing wound images. In addition to wound measurement, they also have the function of wound assessment. In general, handheld and portable non-contact devices have great clinical value and promotion prospects.

Towards an AI-Based Objective Prognostic Model for Quantifying Wound Healing

Chronic wounds affect millions of people worldwide every year. An adequate assessment of a wound's prognosis is critical to wound care, guiding clinical decision making by helping clinicians understand wound healing status, severity, triaging and determining the efficacy of a treatment regimen. The current standard of care involves using wound assessment tools, such as Pressure Ulcer Scale for Healing (PUSH) and Bates-Jensen Wound Assessment Tool (BWAT), to determine wound prognosis. However, these tools involve manual assessment of a multitude of wound characteristics and skilled consideration of a variety of factors, thus, making wound prognosis a slow process which is prone to misinterpretation and high degree of variability. Therefore, in this work we have explored the viability of replacing subjective clinical information with deep learning-based objective features derived from wound images, pertaining to wound area and tissue amounts. These objective features were used to train prognostic models that quantified the risk of delayed wound healing, using a dataset consisting of 2.1 million wound evaluations derived from more than 200,000 wounds. The objective model, which was trained exclusively using image-based objective features, achieved at minimum a 5% and 9% improvement over PUSH and BWAT, respectively. Our best performing model, that used both subjective and objective features, achieved at minimum an 8% and 13% improvement over PUSH and BWAT, respectively. Moreover, the reported models consistently outperformed the standard tools across various clinical settings, wound etiologies, sexes, age groups and wound ages, thus establishing the generalizability of the models.

Machine Learning Approaches for the Image-Based Identification of Surgical Wound Infections: Scoping Review

BACKGROUND

Surgical site infections (SSIs) occur frequently and impact patients and health care systems. Remote surveillance of surgical wounds is currently limited by the need for manual assessment by clinicians. Machine learning (ML)-based methods have recently been used to address various aspects of the postoperative wound healing process and may be used to improve the scalability and cost-effectiveness of remote surgical wound assessment.

OBJECTIVE

The objective of this review was to provide an overview of the ML methods that have been used to identify surgical wound infections from images.

METHODS

We conducted a scoping review of ML approaches for visual detection of SSIs following the JBI (Joanna Briggs Institute) methodology. Reports of participants in any postoperative context focusing on identification of surgical wound infections were included. Studies that did not address SSI identification, surgical wounds, or did not use image or video data were excluded. We searched MEDLINE, Embase, CINAHL, CENTRAL, Web of Science Core Collection, IEEE Xplore, Compendex, and arXiv for relevant studies in November 2022. The records retrieved were double screened for eligibility. A data extraction tool was used to chart the relevant data, which was described narratively and presented using tables. Employment of TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guidelines was evaluated and PROBAST (Prediction Model Risk of Bias Assessment Tool) was used to assess risk of bias (RoB).

RESULTS

In total, 10 of the 715 unique records screened met the eligibility criteria. In these studies, the clinical contexts and surgical procedures were diverse. All papers developed diagnostic models, though none performed external validation. Both traditional ML and deep learning methods were used to identify SSIs from mostly color images, and the volume of images used ranged from under 50 to thousands. Further, 10 TRIPOD items were reported in at least 4 studies, though 15 items were reported in fewer than 4 studies. PROBAST assessment led to 9 studies being identified as having an overall high RoB, with 1 study having overall unclear RoB.

CONCLUSIONS

Research on the image-based identification of surgical wound infections using ML remains novel, and there is a need for standardized reporting. Limitations related to variability in image capture, model building, and data sources should be addressed in the future.

Is my wound infected? A study on the use of hyperspectral imaging to assess wound infection

Introduction

Clinical signs and symptoms (CSS) of infection are a standard part of wound care, yet they can have low specificity and sensitivity, which can further vary due to clinician knowledge, experience, and education. Wound photography is becoming more widely adopted to support wound care. Thermography has been studied in the medical literature to assess signs of perfusion and inflammation for decades. Bacterial fluorescence has recently emerged as a valuable tool to detect a high bacterial load within wounds. Combining these modalities offers a potential objective screening tool for wound infection.

Methods

A multi-center prospective study of 66 outpatient wound care patients used hyperspectral imaging to collect visible light, thermography, and bacterial fluorescence images. Wounds were assessed and screened using the International Wound Infection Institute (IWII) checklist for CSS of infection. Principal component analysis was performed on the images to identify wounds presenting as infected, inflamed, or non-infected.

Results

The model could accurately predict all three wound classes (infected, inflamed, and non-infected) with an accuracy of 74%. They performed best on infected wounds (100% sensitivity and 91% specificity) compared to non-inflamed (sensitivity 94%, specificity 70%) and inflamed wounds (85% sensitivity, 77% specificity).

Discussion

Combining multiple imaging modalities enables the application of models to improve wound assessment. Infection detection by CSS is vulnerable to subjective interpretation and variability based on clinicians' education and skills. Enabling clinicians to use point-of-care hyperspectral imaging may allow earlier infection detection and intervention, possibly preventing delays in wound healing and minimizing adverse events.

Implementation of a patient-centered remote wound monitoring system for management of diabetic foot ulcers

Background

Regular clinical assessment is critical to optimize lower extremity wound healing. However, family and work obligations, socioeconomic, transportation, and time barriers often limit patient follow-up. We assessed the feasibility of a novel, patient-centered, remote wound management system (Healthy.io Minuteful for Wound Digital Management System) for the surveillance of lower extremity wounds.

Methods

We enrolled 25 patients from our outpatient multidisciplinary limb preservation clinic with a diabetic foot ulcer, who had undergone revascularization and podiatric interventions prior to enrollment. Patients and their caregivers were instructed on how to use the digital management system and asked to perform one at-home wound scan per week for a total of 8 weeks using a smartphone application. We collected prospective data on patient engagement, smartphone app useability, and patient satisfaction.

Results

Twenty-five patients (mean age 65.5 ± 13.7 years, 60.0% male, 52.0% Black) were enrolled over 3 months. Mean baseline wound area was 18.0 ± 15.2 cm2, 24.0% of patients were recovering from osteomyelitis, and post-surgical WiFi stage was 1 in 24.0%, 2 in 40.0%, 3 in 28.0%, and 4 in 8.00% of patients. We provided a smartphone to 28.0% of patients who did not have access to one that was compatible with the technology. Wound scans were obtained by patients (40.0%) and caregivers (60.0%). Overall, 179 wound scans were submitted through the app. The mean number of wound scans acquired per patient was 0.72 ± 0.63 per week, for a total mean of 5.80 ± 5.30 scans over the course of 8 weeks. Use of the digital wound management system triggered an early change in wound management for 36.0% of patients. Patient satisfaction was high; 94.0% of patients reported the system was useful.

Conclusion

The Healthy.io Minuteful for Wound Digital Management System is a feasible means of remote wound monitoring for use by patients and/or their caregivers.

Clinical validation of a smartphone application for automated wound measurement in patients with venous leg ulcers

Chronic wounds are associated with significant clinical, economic and quality-of-life burden. Despite the variety of wound imaging systems available in the market for wound assessment and surveillance, few are clinically validated among patients of Asian ethnicity. We aimed to clinically validate the accuracy of a smartphone wound application (Tissue Analytics [TA], Net Health Systems Inc, Florida, USA), versus conventional wound measurements (visual approximation and paper rulers), in patients of Asian ethnicity with venous leg ulcers (VLU). A prospective cohort study of patients presenting with VLU to a specialist wound nurse clinic over a 5-week duration was conducted. Each patient received seven wound measurements: one by a trained wound nurse clinician, and three separate wound measurements using TA on each of the iOS and Android operating systems. Inter-rater and intra-rater reliability between clinical and TA-based measurements were analysed using intra-class correlation statistics, with values of <0.5, 0.5 to 0.75, 0.75 to 0.9, and >0.9 indicating poor, moderate, good and excellent reliability, respectively. 82 patients (51% males), with a mean age at 65.8 years, completed the 5-week study duration. 25 (30%) had underlying diabetes mellitus. Chinese, Malay and Indian ethnicity comprised 68%, 12% and 11%, respectively. The VLU healed in 26 (32%) of patients within the study period. In total, 358 wound episodes with 2334 wound images were analysed. Inter-rater reliability for length, width and area between wound nurse measurements and TA application measurements was good (range 0.799-0.919, P < 0.001). Separate measurements of intra-rater reliability for length, width and area within the iOS or Android systems were excellent (range 0.967-0.985 and range 0.977-0.984 respectively, P < 0.001). Inter-rater reliability between TA used on the iOS and Android systems was also excellent (0.987-0.989, P < 0.001). Tissue Analytics, a smartphone wound application, is a useful adjunct for wound assessment and surveillance in VLU patients of Asian ethnicity.

Performance of portable objective wound assessment tools: a systematic review

OBJECTIVE

Accurate wound assessment is crucial for determining the progression of healing and guides treatment strategies. Portable wound assessment devices can be useful in providing an accurate evaluation in the community where most cases are treated. The objective of this review was to compare the performance of various portable wound assessment techniques used for wound healing assessment described in the literature.

METHOD

In April 2020, electronic databases were searched, using appropriate search terms, for all available publications on the use of portable wound assessment devices on human and artificial wounds. The primary outcome was the reliability and reproducibility of measurement while the secondary outcome was the feasibility of the instrument. All studies underwent quality assessment of diagnostic accuracy studies (QUADAS) to examine the quality of data.

RESULTS

A total of 129 articles were identified and 24 were included in the final review; 17 articles discussed two-dimensional (2D) devices; three articles discussed three-dimensional (3D) devices; and four articles discussed application-based devices. Most studies (n=8) reported on a 2D device that had an ICC of 0.92-0.99 for area measurement and a coefficient of variance of 3.1% with an error of 2.3% in human wounds and 1.55-3.7% in artificial wounds. The inter/intra observer reliability was 0.998 and 0.985, respectively with a scan time of two minutes per wound. The median QUADAS score was 12.

CONCLUSION

Based on the presented evidence, 2D-based portable wound assessment devices were the most studied and demonstrated good performance. Further studies are required for 3D and application-based measurement instruments.

Automatic segmentation and measurement of pressure injuries using deep learning models and a LiDAR camera

Pressure injuries are a common problem resulting in poor prognosis, long-term hospitalization, and increased medical costs in an aging society. This study developed a method to do automatic segmentation and area measurement of pressure injuries using deep learning models and a light detection and ranging (LiDAR) camera. We selected the finest photos of patients with pressure injuries, 528 in total, at National Taiwan University Hospital from 2016 to 2020. The margins of the pressure injuries were labeled by three board-certified plastic surgeons. The labeled photos were trained by Mask R-CNN and U-Net for segmentation. After the segmentation model was constructed, we made an automatic wound area measurement via a LiDAR camera. We conducted a prospective clinical study to test the accuracy of this system. For automatic wound segmentation, the performance of the U-Net (Dice coefficient (DC): 0.8448) was better than Mask R-CNN (DC: 0.5006) in the external validation. In the prospective clinical study, we incorporated the U-Net in our automatic wound area measurement system and got 26.2% mean relative error compared with the traditional manual method. Our segmentation model, U-Net, and area measurement system achieved acceptable accuracy, making them applicable in clinical circumstances.

The Immediate Clinical Effects Following a Single Radial Shock Wave Therapy in Pressure Ulcers: A Preliminary Randomized Controlled Trial of The SHOWN Project

OBJECTIVE

Recent preliminary reports indicate that extracorporeal shock wave therapy (ESWT) might be useful for chronic wounds, especially venous leg ulcers (VLUs) and diabetic foot ulcers (DFUs). However, there is limited evidence for the utility and safety of ESWT in pressure ulcers (PUs). Therefore, this randomized controlled trial (RCT) aimed to assess immediate planimetric and clinical effects following a single radial ESWT session in PUs.

APPROACH

A group of 40 patients with PUs was randomly assigned into two groups: active ESWT (n=20), which underwent a single treatment with radial ESWT (300+100 impulses per 1 cm2, 2.5 bars, 0.15 mJ/mm2, and 5 Hz) and placebo ESWT (n=20) which was exposed to sham-radial ESWT. All patients continued standard wound care procedures. The planimetric assessment and clinical outcomes using Wound Bed Score (WBS) and Bates-Jansen Wound Assessment Tool (BWAT) were assessed before (M0) and after ESWT sessions (M1).

RESULTS

There was a significant planimetric enhancement observed after active ESWT reported as a reduction in all metric parameters: wound area from 11.51 cm2 to 8.09 cm2 (p<0.001), wound length from 4.97 cm to 4.41 cm (p<0.001), and wound width from 3.15 cm to 2.49 cm (p<0.0001). Also, there was a significant beneficial clinical improvement observed with a WBS as an increased score from 3.85 to 9.65 points (p<0.001) and with the BWAT as a decreased score from 45.45 to 30.70 points (p<0.001). In turn, a regression in the placebo ESWT group was observed in all studied outcomes.

INNOVATION

This study is the first RCT to provide the positive and immediate clinical effects of radial ESWT in promoting the healing of PUs.

CONCLUSION

This preliminary RCT showed that even a single session of ESWT is a promising and clinically effective modality in managing PUs. However, there is still limited data regarding the usefulness of ESWT in PUs, and further studies are in demand.

A time motion study of manual versus artificial intelligence methods for wound assessment

OBJECTIVES

This time-motion study explored the amount of time clinicians spent on wound assessments in a real-world environment using wound assessment digital application utilizing Artificial Intelligence (AI) vs. manual methods. The study also aimed at comparing the proportion of captured quality wound images on the first attempt by the assessment method.

METHODS

Clinicians practicing at Valley Wound Center who agreed to join the study were asked to record the time needed to complete wound assessment activities for patients with active wounds referred for a routine evaluation on the follow-up days at the clinic. Assessment activities included: labelling wounds, capturing images, measuring wounds, calculating surface areas, and transferring data into the patient's record.

RESULTS

A total of 91 patients with 115 wounds were assessed. The average time to capture and access wound image with the AI digital tool was significantly faster than a standard digital camera with an average of 62 seconds (P<0.001). The digital application was significantly faster by 77% at accurately measuring and calculating the wound surface area with an average of 45.05 seconds (P<0.001). Overall, the average time to complete a wound assessment using Swift was significantly faster by 79%. Using the AI application, the staff completed all steps in about half of the time (54%) normally spent on manual wound evaluation activities. Moreover, acquiring acceptable wound image was significantly more likely to be achieved the first time using the digital tool than the manual methods (92.2% vs. 75.7%, P<0.004).

CONCLUSIONS

Using the digital assessment tool saved significant time for clinicians in assessing wounds. It also successfully captured quality wound images at the first attempt.

Smartphone-based wound dressings: A mini-review

In spite of remarkable progress in the field of wound curation, treatment of chronic wounds remains a challenge for medical services. The constant rise in the number of patients with chronic wounds and their related financial burden has caused concern for the healthcare system. The complicated and dynamic nature of chronic wounds has increased the curation time and difficulty of wound healing with conventional bandages. Efficient healing of these wounds requires new bandages with the ability of real-time monitoring, data analysis, and drug delivery, which protect the wound against infection and accelerate the treatment process. The recent development of smartphone applications and digital equipment in medicine provides an opportunity for significant improvement in wound care through the incorporation of “smart” technologies into clinical practice. The focus of this review is to provide an overview of the current status of smartphones and digital technology in the management of wounds.

Stretchable printed device for the simultaneous sensing of temperature and strain validated in a mouse wound healing model

Temperature and strain are two vital parameters that play a significant role in wound diagnosis and healing. As periodic temperature measurements with a custom thermometer or strain measurements with conventional metallic gauges became less feasible for the modern competent health monitoring, individual temperature and strain measurement modalities incorporated into wearables and patches were developed. The proposed research in the article shows the development of a single sensor solution which can simultaneously measure both the above mentioned parameters. This work integrates a thermoelectric principle based temperature measurement approach into wearables, ensuring flexibility and bendability properties without affecting its thermo-generated voltage. The modified thermoelectric material helped to achieve stretchability of the sensor, thanks to its superior mechano-transduction properties. Moreover, the stretch-induced resistance changes become an additional marker for strain measurements so that both the parameters can be measured with the same sensor. Due to the independent measurement parameters (open circuit voltage and sensor resistance), the sensing model is greatly attractive for measurements without cross-sensitivity. The highly resilient temperature and strain sensor show excellent linearity, repeatability and good sensitivity. Besides, due to the compatibility of the fabrication scheme to low-temperature processing of the flexible materials and to mass volume production, printed fabrication methodologies were adopted to realize the sensor. This promises low-cost production and a disposable nature (single use) of the sensor patch. For the first time, this innovative temperature-strain dual parameter sensor concept has been tested on mice wounds in vivo. The preliminary experiments on mice wounds offer prospects for developing smart, i.e. sensorized, wound dressings for clinical applications.

Infrared Thermography in Wound Care, Surgery, and Sports Medicine: A Review

For many years, the role of thermometry was limited to systemic (core body temperature) measurements (e.g., pulmonary catheter) or its approximation using skin/mucosa (e.g., axillary, oral, or rectal) temperature measurements. With recent advances in material science and technology, thermal measurements went beyond core body temperature measurements and found their way in many medical specialties. The article consists of two primary parts. In the first part we overviewed current clinical thermal measurement technologies across two dimensions: (a) direct vs. indirect and (b) single-point vs. multiple-point temperature measurements. In the second part, we focus primarily on clinical applications in wound care, surgery, and sports medicine. The primary focus here is the thermographic imaging modality. However, other thermal modalities are included where relevant for these clinical applications. The literature review identified two primary use scenarios for thermographic imaging: inflammation-based and perfusion-based. These scenarios rely on local (topical) temperature measurements, which are different from systemic (core body temperature) measurements. Quantifying these types of diseases benefits from thermographic imaging of an area in contrast to single-point measurements. The wide adoption of the technology would be accelerated by larger studies supporting the clinical utility of thermography.

Reshaping wound care: Evaluation of an artificial intelligence app to improve wound assessment and management amid the COVID-19 pandemic

Wound documentation is integral to effective wound care, health data coding and facilitating continuity of care. This study evaluated the usability and effectiveness of an artificial intelligence application for wound assessment and management from a clinician‐and‐patient user perspective. A quasi‐experimental design was conducted in four settings in an Australian health service. Data were collected from patients in the standard group (n = 166, 243 wounds) and intervention group (n = 124, 184 wounds), at baseline and post‐intervention. Clinicians participated in a survey (n = 10) and focus group interviews (n = 13) and patients were interviewed (n = 4). Wound documentation data were analysed descriptively, and bivariate statistics were used to determine between‐group differences. Thematic analysis of interviews was conducted. Compared with the standard group, wound documentation in the intervention group improved significantly (more than two items documented 24% vs 70%, P < .001). During the intervention, 101 out of 132 wounds improved (mean wound size reduction = 53.99%). Positive evaluations identified improvements such as instantaneous objective wound assessment, shared wound plans, increased patient adherence and enhanced efficiency in providing virtual care. The use of the application facilitated remote patient monitoring and reduced patient travel time while maintaining optimal wound care.

Infection Probability Index: Implementation of an Automated Chronic Wound Infection Marker

The number of people suffering from chronic wounds is increasing due to demographic changes and the global epidemics of obesity and diabetes. Innovative imaging techniques within the field of chronic wound diagnostics are required to improve wound care by predicting and detecting wound infections to accelerate the application of treatments. For this reason, the infection probability index (IPI) is introduced as a novel infection marker based on thermal wound imaging. To improve usability, the IPI was implemented to automate scoring. Visual and thermal image pairs of 60 wounds were acquired to test the implemented algorithms on clinical data. The proposed process consists of (1) determining various parameters of the IPI based on medical hypotheses, (2) acquiring data, (3) extracting camera distortions using camera calibration, and (4) preprocessing and (5) automating segmentation of the wound to calculate (6) the IPI. Wound segmentation is reviewed by user input, whereas the segmented area can be refined manually. Furthermore, in addition to proof of concept, IPIs’ correlation with C-reactive protein (CRP) levels as a clinical infection marker was evaluated. Based on average CRP levels, the patients were clustered into two groups, on the basis of the separation value of an averaged CRP level of 100. We calculated the IPIs of the 60 wound images based on automated wound segmentation. Average runtime was less than a minute. In the group with lower average CRP, a correlation between IPI and CRP was evident.

A Review of Recent Advances in Flexible Wearable Sensors for Wound Detection Based on Optical and Electrical Sensing

Chronic wounds that are difficult to heal can cause persistent physical pain and significant medical costs for millions of patients each year. However, traditional wound care methods based on passive bandages cannot accurately assess the wound and may cause secondary damage during frequent replacement. With advances in materials science and smart sensing technology, flexible wearable sensors for wound condition assessment have been developed that can accurately detect physiological markers in wounds and provide the necessary information for treatment decisions. The sensors can implement the sensing of biochemical markers and physical parameters that can reflect the infection and healing process of the wound, as well as transmit vital physiological information to the mobile device through optical or electrical signals. Most reviews focused on the applicability of flexible composites in the wound environment or drug delivery devices. This paper summarizes typical biochemical markers and physical parameters in wounds and their physiological significance, reviews recent advances in flexible wearable sensors for wound detection based on optical and electrical sensing principles in the last 5 years, and discusses the challenges faced and future development. This paper provides a comprehensive overview for researchers in the development of flexible wearable sensors for wound detection.

Use of thermal imaging and a dedicated wound imaging smartphone app as an adjunct to staging hidradenitis suppurativa

Hidradenitis suppurativa (HS) presents with painful nodules, draining tunnels, abscesses, ulcers, and fistula formation¹ . Grading systems, (e.g. Hurley Staging System, International Hidradenitis Suppurativa Severity Score System (IHS4), Severity Assessment of Hidradenitis Suppurativa Score (HS-PGA score), and Hidradenitis Suppurativa Area and Severity Index (HASI)) assess disease severity in terms of lesion count, extension and morphology.

Wound Size Imaging: Ready for Smart Assessment and Monitoring

Significance: We introduce and evaluate emerging devices and modalities for wound size imaging and also promising image processing tools for smart wound assessment and monitoring. Recent Advances: Some commercial devices are available for optical wound assessment but with limited possibilities compared to the power of multimodal imaging. With new low-cost devices and machine learning, wound assessment has become more robust and accurate. Wound size imaging not only provides area and volume but also the proportion of each tissue on the wound bed. Near-infrared and thermal spectral bands also enhance the classical visual assessment. Critical Issues: The ability to embed advanced imaging technology in portable devices such as smartphones and tablets with tissue analysis software tools will significantly improve wound care. As wound care and measurement are performed by nurses, the equipment needs to remain user-friendly, enable quick measurements, provide advanced monitoring, and be connected to the patient data management system. Future Directions: Combining several image modalities and machine learning, optical wound assessment will be smart enough to enable real wound monitoring, to provide clinicians with relevant indications to adapt the treatments and to improve healing rates and speed. Sharing the wound care histories of a number of patients on databases and through telemedicine practice could induce a better knowledge of the healing process and thus a better efficiency when the recorded clinical experience has been converted into knowledge through deep learning.

Use of mHealth apps by nurses in the management of chronic wounds: a scoping review protocol

OBJECTIVE

The objective of this scoping review is to explore the existing literature related to nurses' use of mHealth apps in the management of chronic wounds and chart if and how these apps are being evaluated.

INTRODUCTION

mHealth technology is increasingly used within health care facilities. There is now a variety of wound care apps available to support nurses delivering wound care. These promise many benefits, but little is known about their use.

INCLUSION CRITERIA

Studies involving nurses of all grades, in all clinical settings using mHealth apps in the care and management of chronic wounds will be included. Criteria used to evaluate these apps will also be considered. The context will be all primary care, hospital, and community settings, which includes general practice, nurse-led clinics, public health services, nursing and care homes, and all hospital settings. There will be no limit on the geographical setting of the research. All studies and reports that focus on qualitative, quantitative, and mixed methods will be included, as will text and opinion papers and published gray literature.

METHODS

An initial search of MEDLINE, CINAHL, and Embase will be undertaken to identify index terms. This will be followed by an analysis of the text words contained in the title. A search of commercial app stores (eg, Apple's App Store and Google's Play Store) will not be carried out. A data extraction form will be used and piloted on the first 10 articles. Results will be reported in tabular form and presented in a PRISMA flow diagram.

Wound Image Quality From a Mobile Health Tool for Home-Based Chronic Wound Management With Real-Time Quality Feedback: Randomized Feasibility Study

Background

Travel to clinics for chronic wound management is burdensome to patients. Remote assessment and management of wounds using mobile and telehealth approaches can reduce this burden and improve patient outcomes. An essential step in wound documentation is the capture of wound images, but poor image quality can have a negative influence on the reliability of the assessment. To date, no study has investigated the quality of remotely acquired wound images and whether these are suitable for wound self-management and telemedical interpretation of wound status.

Objective

Our goal was to develop a mobile health (mHealth) tool for the remote self-assessment of digital ulcers (DUs) in patients with systemic sclerosis (SSc). We aimed to define and validate objective measures for assessing the image quality, evaluate whether an automated feedback feature based on real-time assessment of image quality improves the overall quality of acquired wound images, and evaluate the feasibility of deploying the mHealth tool for home-based chronic wound self-monitoring by patients with SSc.

Methods

We developed an mHealth tool composed of a wound imaging and management app, a custom color reference sticker, and a smartphone holder. We introduced 2 objective image quality parameters based on the sharpness and presence of the color checker to assess the quality of the image during acquisition and enable a quality feedback mechanism in an advanced version of the app. We randomly assigned patients with SSc and DU to the 2 device groups (basic and feedback) to self-document their DU at home over 8 weeks. The color checker detection ratio (CCDR) and color checker sharpness (CCS) were compared between the 2 groups. We evaluated the feasibility of the mHealth tool by analyzing the usability feedback from questionnaires, user behavior and timings, and the overall quality of the wound images.

Results

A total of 21 patients were enrolled, of which 15 patients were included in the image quality analysis. The average CCDR was 0.96 (191/199) in the feedback group and 0.86 (158/183) in the basic group. The feedback group showed significantly higher (P<.001) CCS compared to the basic group. The usability questionnaire results showed that the majority of patients were satisfied with the tool, but could benefit from disease-specific adaptations. The median assessment duration was <50 seconds in all patients, indicating the mHealth tool was efficient to use and could be integrated into the daily routine of patients.

Conclusions

We developed an mHealth tool that enables patients with SSc to acquire good-quality DU images and demonstrated that it is feasible to deploy such an app in this patient group. The feedback mechanism improved the overall image quality. The introduced technical solutions consist of a further step towards reliable and trustworthy digital health for home-based self-management of wounds.

Usability of a Novel Instrument to Measure Damaged Peristomal Skin in Patients with an Ostomy

OBJECTIVE

To evaluate the usability of a novel instrument (stoma ruler) to measure damaged peristomal skin in patients with an ostomy.

METHODS

A wound ostomy and continence nurse used both the stoma ruler and a linear ruler to assess DET (discoloration, erosion, tissue overgrowth) scores and the height of protrusion above the skin of 10 patients with ileostomies and took photographs. The photographs were presented to five ostomy care nurses for reliability testing. The difference between the two methods was determined using paired Wilcoxon signed ranks test.

PRIMARY OUTCOME MEASURE

Interrater reliability of the linear versus stoma ruler.

RESULTS

The interrater reliabilities of the stoma ruler versus the linear ruler for the domain-area DET score were 0.95 (95% confidence interval, 0.89-0.99) and 0.68 (95% confidence interval, 0.42-0.89), respectively. Only nurse 5 reported a significant difference between the two rulers (z = -2.24, P = .03).

CONCLUSIONS

In busy clinical settings, the stoma ruler is easy for ostomy care nurses to use to obtain accurate DET scores and the height of stoma protrusion above the skin. Observing the position of damaged skin using the clock marks on the stoma ruler enhance clinical description and reduce assessment variation among professionals.

Wearable Sensors and Systems for Wound Healing-Related pH and Temperature Detection

Wound healing is a complex tissue regeneration process involving many changes in multiple physiological parameters. The pH and temperature of a wound site have long been recognized as important biomarkers for assessing wound healing status. For effective wound management, wound dressings integrated with wearable sensors and systems used for continuous monitoring of pH and temperature have received much attention in recent years. Herein, recent advances in the development of wearable pH and temperature sensors and systems based on different sensing mechanisms for wound status monitoring and treatment are comprehensively summarized. Challenges in the areas of sensing performance, infection identification threshold, large-area 3-dimensional detection, and long-term reliable monitoring in current wearable sensors/systems and emerging solutions are emphasized, providing critical insights into the development of wearable sensors and systems for wound healing monitoring and management.

Smartphone application for wound area measurement in clinical practice

A total of 85 consecutive patients had their wound area measured. The procedure was executed in two parts. The first was to take photographs of the wound using a smartphone and measure the area using the imitoMeasure application (imito; imito AG, Zurich, Switzerland) by two raters. The second was to take photographs of the same wound using a 10-megapixel digital camera and posterior measurement of the area using ImageJ software (National Institutes of Health, Bethesda, Md) by one operator. The mean area of the wounds was 12.20 ± 10.45 cm² for imito and 12.67 ± 10.86 cm² for ImageJ measurement. The interclass correlation coefficient (ICC) between ImageJ and imito was 0.978 for a single measure and 0.989 for the average measure. Considering the two measurements, the ICC demonstrated excellent interobserver correlation using imito (0.987). Larger wounds had a greater difference between the methods (4.28% greater with the ImageJ measurement when considering areas >9 cm²). No difference was found between iOS (ICC, 0.995) and android (ICC, 0.970) smartphone operating systems. The smartphone application is a useful method for area measurement with excellent accuracy compared with digital photography and the ImageJ processing tool.

mHealth App for Pressure Ulcer Wound Assessment in Patients With Spinal Cord Injury: Clinical Validation Study

Background

Clinical evaluation of a pressure ulcer is based on quantitative and qualitative evaluation. In clinical practice, acetate tracing is the standard technique used to measure wound surface area; however, it is difficult to use in daily practice (because of material availability, data storage issues, and time needed to calculate the surface area). Planimetry techniques developed with mobile health (mHealth) apps can be used to overcome these difficulties.

Objective

The goal of this study was to evaluate the metrological properties of a free-access mHealth app, called imitoMeasure, to assess pressure ulcers.

Methods

This was a noninterventional, validation study. We included patients with spinal cord injury presenting with a pressure ulcer, regardless of its stage or location. We performed wound measurements with a ruler, and we performed acetate tracing using a transparent dressing with a wound measurement grid. Wound evaluation via the mHealth app was conducted twice by the main investigator and also by a coinvestigator to determine validity, intrarater reproducibility, and interrater reproducibility. Bland-Altman plots and intraclass correlation coefficients were used to compute the minimal detectable change percentage.

Results

Overall, 61 different pressure ulcers were included. The validity, intrarater reproducibility, and interrater reproducibility of the mHealth app vs acetate tracing (considered the method of reference) were good, with intraclass correlation coefficients of 0.97 (95% CI 0.93-0.99), 0.99 (95% CI 0.98-0.99), and 0.98 (95% CI 0.96-0.99), respectively, and minimal detectable change percentages between 17% and 35%.

Conclusions

The imitoMeasure app had good validity and reproducibility. It could be an alternative to standard wound assessment methods. Further studies on larger and more diverse wounds are needed.

Trial Registration

ClinicalTrials.gov NCT04402398; http://clinicaltrials.gov/ct2/show/NCT04402398

Hyperspectral imaging in wound care: A systematic review

Multispectral and hyperspectral imaging (HSI) are emerging imaging techniques with the potential to transform the way patients with wounds are cared for, but it is not clear whether current systems are capable of delivering real-time tissue characterisation and treatment guidance. We conducted a systematic review of HSI systems that have been assessed in patients, published over the past 32 years. We analysed 140 studies, including 10 different HSI systems. Current in vivo HSI systems generate a tissue oxygenation map. Tissue oxygenation measurements may help to predict those patients at risk of wound formation or delayed healing. No safety concerns were reported in any studies. A small number of studies have demonstrated the capabilities of in vivo label-free HSI, but further work is needed to fully integrate it into the current clinical workflow for different wound aetiologies. As an emerging imaging modality for medical applications, HSI offers great potential for non-invasive disease diagnosis and guidance when treating patients with both acute and chronic wounds.

Hyperspectral imaging in wound care: A systematic review

Multispectral and hyperspectral imaging (HSI) are emerging imaging techniques with the potential to transform the way patients with wounds are cared for, but it is not clear whether current systems are capable of delivering real-time tissue characterisation and treatment guidance. We conducted a systematic review of HSI systems that have been assessed in patients, published over the past 32 years. We analysed 140 studies, including 10 different HSI systems. Current in vivo HSI systems generate a tissue oxygenation map. Tissue oxygenation measurements may help to predict those patients at risk of wound formation or delayed healing. No safety concerns were reported in any studies. A small number of studies have demonstrated the capabilities of in vivo label-free HSI, but further work is needed to fully integrate it into the current clinical workflow for different wound aetiologies. As an emerging imaging modality for medical applications, HSI offers great potential for non-invasive disease diagnosis and guidance when treating patients with both acute and chronic wounds.

The Promise of Smartphone Applications in the Remote Monitoring of Postsurgical Wounds: A Literature Review

OBJECTIVE

To review the clinical and scientific literature on remote monitoring and management of postsurgical wounds using smartphone applications (apps).

DATA SOURCES

MEDLINE, PubMed, EMBASE, and Cochrane libraries were searched for relevant articles on patients who received surgery and were monitored postdischarge via an app.

STUDY SELECTION

Articles were selected with the terms "mobile phones," "smartphones," "wounds," "monitor," and "patient preference."

DATA EXTRACTION

The authors found 276 review articles related to telemedicine in wound care. Investigators reviewed the titles and abstracts of the search results and selected 83 articles that were relevant to the remote monitoring of wounds using smartphone apps.

DATA SYNTHESIS

The topics explored in selected literature included smartphone app importance to telemedicine, benefits (medical and financial), app examples, and challenges in the context of wound monitoring and management. The authors identified several challenges and limitations that future studies in the field need to address.

CONCLUSIONS

Remote monitoring and management of wounds using smartphone apps is a valuable technique to enhance the quality of and access to healthcare. However, although some patients may prefer this technology, some lack technological competence, limiting telemedicine's applicability. In addition, issues remain with the reliable interpretation of data collected through apps.

Mobile application-based guidelines to enhance patient care and provider education in trauma and acute care surgery

Introduction

Providing up-to-date, universally accessible care guidelines and education within a quaternary care center is challenging. At our institution, trauma and acute care surgery guidelines have historically been published using a paper-based format. Mobile application-based guidelines were developed to address the shortcomings of paper-based guidelines.

Methods

We assessed the utility, usability, and satisfaction of healthcare providers towards paper-based versus mobile application-based guidelines. A survey was administered to providers within the emergency department and intensive care unit.

Results

Fifty of 137 providers responded (36.5% response rate). Nearly half (47.4%, 9 of 19) of those who received a copy of the paper-based guidelines lost the guidelines at least once. Regarding usage of the mobile application-based guidelines, 92.6% (25 of 27) were aware of the application; 92.6% (25 of 27) considered the application comprehensive, 85.2% (23 of 27) thought the application was organized, and 66.7% (18 of 27) thought the application was easy to use. Additionally, 88.9% (24 of 27) found the application moderately, very, or extremely helpful and 85.2% (23 of 27) judged the application moderately, very, or extremely necessary. Overall, 88.9% (24 of 27) were satisfied with the application and indicated likeliness to recommend to a colleague. Seventeen of 27 (63.0%) agreed or strongly agreed that the application improved their provision of trauma and acute care.

Conclusion

This survey demonstrates positive usability, utility, and satisfaction among trauma healthcare providers with the mobile application-based guidelines. Additionally, this quality improvement initiative highlights the importance of having comprehensive, organized, and easy-to-use trauma and acute care surgery guidelines and targeted educational materials available on demand. The successful transition from paper to mobile application-based guidelines serves as a model for other institutions to modernize and improve patient care and provider education.

Level of evidence

IV.

Development of a computer-based quantification method for immunohistochemically-stained tissues and its application to study mast cells in equine wound healing (proof of concept)

Background

There is a growing interest in the scientific community to use computer-based software programs for the quantification of cells during physiological and pathophysiological processes. Drawbacks of computer-based methods currently used to quantify immunohistochemical staining are the complexity of use, expense of software and overly-simplified descriptions of protocol thereby limiting reproducibility. The precise role of mast cells in equine cutaneous wound healing is unknown. Given the contribution of mast cells to the chronic inflammation observed in human keloid, a pathology similar to exuberant granulation tissue (EGT) in horses, mast cells might be present in high numbers in equine limb wounds predisposed to EGT. The main goal of this study was to develop a reliable and reproducible quantification method for immunostained tissues using a computer software that is widely available, at no cost, to the scientific community. A secondary goal was to conduct a proof of concept using the newly-established method to quantify mast cells during wound healing at different anatomical sites (body and limb) in horses to see if a different pattern is observed in limb wounds, which are predisposed to EGT.

Results

A good intraclass correlation coefficient (ICC, 0.67 p < 0.05) was found between the computer-based ImageJ method and manual counting. An excellent intra-operator ICC of 0.90 (p < 0.01) was found for the ImageJ quantification method while a good interoperator ICC of 0.69 (p < 0.01) was measured. No significant difference was observed between the variation of the ImageJ and that of the manual counting method. Mast cells were localized below the epidermis, around cutaneous appendages and blood vessels. Mast cell numbers did not differ significantly in relation to anatomical location or time of healing.

Conclusions

The computer-based quantification method developed is reliable, reproducible, available, cost-free and could be used to study different physiological and pathological processes using immunohistochemistry.

The impact of an mHealth app on knowledge, skills and anxiety about dressing changes: A randomized controlled trial

AIMS

To evaluate the effectiveness of a mobile health (mHealth) application, based on self-regulation theory, on patients' knowledge of wound care, skills in changing dressings and anxiety.

DESIGN

A prospective randomized controlled trial.

METHODS

Seventy patients (or family members) at a 1,500-bed university hospital in Taiwan were randomized into an experimental (N = 35) or control group (N = 35) from March to December 2016. The experimental group used a mHealth application for wound care; the control group received verbal instructions and a booklet. Instruments to collect data were a wound care knowledge scale, wound care skills scale, State-Trait Anxiety Inventory, and a digital heart variability device. Data were collected at baseline, after three additional demonstrations and before discharge. The generalized estimating equation was used for statistical analysis.

RESULTS

The experimental group showed significantly higher levels of wound care knowledge, improved wound care skills, lower levels of state anxiety, and lower heart rate variability than the control group after baseline data collection.

CONCLUSIONS

Results support hat a mHealth application may be effective in health education. Clinicians can use the results to promote patients' wound care knowledge, enhance their wound care skills, and reduce anxiety related to dressing changes.

IMPACT

Lack of wound care knowledge and skills can affect the willingness and ability to perform effective wound dressing changes, producing anxiety and having an impact on a patient's self-care after hospital discharge. mHealth applications (apps) have the potential to deliver health information in targeted and tailored ways that strengthen the self-management of diseases. mHealth app can increase wound care knowledge, improve care skills, and reduce anxiety related to wound care. mHealth app effectively supports self-monitoring of the wound healing process, self-judgement of the wound condition, and self-reaction of wound care accuracy. mHealth app provides step-by-step visual tutorials on wound care that allow patients and family caregivers to take pictures of the wounds and monitor the wound healing process. mHealth app for wound care knowledge is an effective and individualized method for learning.

CLINICAL TRIAL

This study was registered by U.S. National Library of Medicine, ClinicalTrials.gov (ID: NCT03683303).

The Utility of Smartphone Applications and Technology in Wound Healing

Appropriate management of both acute and chronic wounds is a dynamic practice that consumes large amounts of time and financial resources within the health care system. Traditionally, wounds were measured clinically and subjectively, leading to inaccuracies in assessing wound progression and healing over time. The recent development of mobile applications and digital equipment in medicine provides an opportunity for significant improvement in wound care through the incorporation of “smart” technologies in clinical practice. The utility of these technologies has been assessed regarding the treatment of diabetic foot ulcers, burns, and general wounds. The focus of this review is to provide an update on the current status of mobile applications and digital technology in the management of wounds.

Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing

We review some emerging trends in transduction, connectivity and data analytics for Point-of-Care Testing (POCT) of infectious and non-communicable diseases. The patient need for POCT is described along with developments in portable diagnostics, specifically in respect of Lab-on-chip and microfluidic systems. We describe some novel electrochemical and photonic systems and the use of mobile phones in terms of hardware components and device connectivity for POCT. Developments in data analytics that are applicable for POCT are described with an overview of data structures and recent AI/Machine learning trends. The most important methodologies of machine learning, including deep learning methods, are summarised. The potential value of trends within POCT systems for clinical diagnostics within Lower Middle Income Countries (LMICs) and the Least Developed Countries (LDCs) are highlighted.

Improving the quality of pressure ulcer management in a skilled nursing facility

Pressure ulcers (PUs) are a serious health care problem for nursing home residents and a key quality metric for regulators. Three initiatives were introduced at a 128-bed facility to improve PU prevention. First, a Quality Assurance and Performance Improvement project and a Root Cause Analysis were conducted to improve the facility's wound care programme. Second, a digital wound care management solution was adopted to track wound management. Third, the role of skin integrity coordinator was created as a central point of accountability for wound care-related activities and related performance metrics. Improvements in PU prevention were tracked using Centers of Medicare and Medicaid data, specifically (a) the percentage of long-stay high-risk residents with PUs and (b) the percentage of short-stay residents with PUs that are new or have worsened. PU prevalence for long-stay high-risk residents was 12.99% (Q4 2016), and upon implementation of these initiatives, the facility saw continued reductions in PU prevalence to 2.9% (Q4 2017), while PUs for short-stay residents were maintained at zero throughout this period. This study highlights the power of effective management combined with real-time data analytics, as enabled by digital wound care management, to make significant improvements in health care delivery.

Promoting Self-Care of Diabetic Foot Ulcers Through a Mobile Phone App: User-Centered Design and Evaluation

Background

Without effective self-care, people with diabetic foot ulcers (DFUs) are at risk of prolonged healing times, hospitalization, amputation, and reduced quality of life. Despite these consequences, adherence to DFU self-care remains low. New strategies are needed to engage people in the self-care of their DFUs.

Objective

This study aimed to evaluate the usability and potential usefulness of a new mobile phone app to engage people with DFUs in self-care.

Methods

We developed a new mobile phone app, MyFootCare, to engage people with DFUs through goals, progress monitoring, and reminders in self-care. Key features included novel visual analytics that automatically extract and monitor DFU size information from mobile phone photos of the foot. A functional prototype of MyFootCare was created and evaluated through a user-centered design process with 11 participants with DFUs. Data were collected through semistructured interviews discussing existing self-care practices and observations of MyFootCare with participants. Data were analyzed qualitatively through thematic analysis.

Results

Key themes were as follows: (1) participants already used mobile phone photos to monitor their DFU progress; (2) participants had limited experience with using mobile phone apps; (3) participants desired the objective DFU size data provided by the tracking feature of MyFootCare to monitor their DFU progress; (4) participants were ambivalent about the MyFootCare goal image and diary features, commenting that these features were useful but also that it was unlikely that they would use them; and (5) participants desired to share their MyFootCare data with their clinicians to demonstrate engagement in self-care and to reflect on their progress.

Conclusions

MyFootCare shows promising features to engage people in DFU self-care. Most notably, ulcer size data are useful to monitor progress and engage people. However, more work is needed to improve the usability and accuracy of MyFootCare, that is, by refining the process of taking and analyzing photos of DFUs and removing unnecessary features. These findings open the door for further work to develop a system that is easy to use and functions in everyday life conditions and to test it with people with DFUs and their carers.

Genetically-modified bone mesenchymal stem cells with TGF-β3 improve wound healing and reduce scar tissue formation in a rabbit model

Extensive scar tissue formation often occurs after severe burn injury, trauma, or as one of complications after surgical intervention. Despite significant therapeutic advances, it is still a significant challenge to manage massive scar tissue formation while also promoting normal wound healing. The goal of this study was to investigate the therapeutic effect of bone mesenchymal stem cells (BMSCs) that were genetically modified to overexpress transforming growth factor-beta 3 (TGF-β₃), an inhibitor of myofibroblast proliferation and collagen type I deposition, on full-thickness cutaneous wound healing in a rabbit model. Twenty-four rabbits with surgically-induced full-thickness cutaneous wounds created on the external ear (1.5 × 1.5 cm, two wounds/ear) were randomized into four groups: (G1), wounds with no special treatment but common serum-free culture medium as negative controls; (G2), topically-applied recombinant adenovirus, expressing TGF-β₃/GFP; (G3), topically-applied BMSCs alone; (G4), topically-applied BMSCs transfected with Ad-TGF-β₃/GFP (BMSCs^TGF-β3); and (G5), an additional normal control (n = 2) with neither wound nor treatment on the external ear skin. The sizes of wounds on the ear tissues were grossly examined, and the scar depth and density of wounds were histologically evaluated 21, 45, and 90 days after surgical wound creation. Our results demonstrated that G4 significantly reduced the wound scar depth and density, compared to G1~3. Numbers of cells expressing GFP significantly increased in G4, compared to G2. The protein expression of TGF-β₃ and type III collagen in G4 significantly increased, while the ratio of type I to type III collagen was also significantly reduced, which is similar to the tissue architecture found in G5, as compared the other treatment groups. In conclusion, transplantation of BMSCs^TGF-β3 remarkably improves wound healing and reduces skin scar tissue formation in an animal model, which may potentially provide an alternative in the treatment of extensive scar tissue formation after soft tissue injury.