Background Skin flap transfer is a commonly used technique by surgeons; however, compromised blood flow may result in flap ischemia and necrosis. We describe the use of closed incision negative pressure therapy (ciNPT) to help manage skin flap reconstructions with indocyanine green fluorescence angiography (ICG-FA) to assess perfusion of the flaps before and after ciNPT. Methods Three female and 5 male patients underwent various skin flap reconstructions, including local flaps, pedicled flaps, and propeller flaps, for wound defects related to trauma, infection, or cancer. After flap setting and suturing, ciNPT (−125 mm Hg) was applied to the closed incision for 7 days. Perfusion was assessed using ICG-FA before applying ciNPT and again at 24 hours later. The Shapiro-Wilk test and Wilcoxon signed rank test were used in statistical analysis. Results Initial postoperative survival was observed for all skin flaps; however, 1 flap failed after 2 weeks due to uncontrolled infection. The remaining 7 flaps healed well without any surgical revision. All patients were initially determined to have impaired flap perfusion; however, skin flap perfusion was significantly higher after ciNPT than before ciNPT in each case (P = 0.012). Conclusions This study showed good healing outcomes for skin flap reconstructions without complications, despite the fact that each flap had compromised flap perfusion to some extent during the surgery. This case series is novel in that it used laser-assisted ICG-FA to provide a real-time assessment of skin flap perfusion before and after ciNPT.

Background: As we all know, the numbers of aesthetic surgery are increasing around the world. After the surgery, the scar would be a problematic issue for both the surgeons and the patients. Silicone has proven to be effective for keloids, hypertrophic scars, and prevention of scar formation in many literatures for a long time. In terms of scar prevention, silicone has been used in the form of silicone sheets in early times, which is later improved to be the form of silicone gel with the advantage of easier usage. Although silicone gel has improved greatly in the aspect of appearance and convenience of the silicone sheets, there are still some disadvantages of the gel form. Therefore, the LeniScar silicone stick (AnsCare) is invented. Objective: This article aimed to compare the results of scar treatment and prevention of the AnsCare LeniScar Silicone Stick versus the traditional silicone gel (Dermatix Ultra). Methods: This study was a prospective, nonblinded, randomized clinical study. There were a total of 68 patients from September 2018 to January 2020. Patients were divided into 2 groups with AnsCare (n = 43) and Dermatix (n = 25), who both were required to schedule regular outpatient clinic follow-up, and photographs were taken before use, 1, 2, and 3 months later after the usage for the record. The physician assessed the scar condition by the Vancouver Scar Scale (VSS). The scores of the VSS were further analyzed and compared. Results: The overall P value of total score of VSS was 0.635, which indicates that there is no significant difference in using AnsCare LeniScar Silicone Stick versus Dermatix Ultra silicone gel in terms of scar prevention and treatment. Individual items of VSS such as pliability, height, vascularity, and pigmentation all show no significant statistical difference in the 2 treatment products, with P = 0.980, 0.778, 0.528, and 0.366, respectively. Conclusion: Traditional Dermatix Ultra silicone gel has been effective in the treatment of scar formation. AnsCare LeniScar Silicone Stick is statistically not different from the Dermatix Ultra silicone gel when comparing the treatment results of scar prevention. Furthermore, the AnsCare LeniScar Silicone Stick has the advantages of being time-saving with no need to wait for it to dry and application of precise amount to precise location, preventing waste or overuse.

Background and Objectives: Traditionally, we evaluate the size of a wound by using Opsite Flexigrid transparent film dressing, placing it over the wound, tracing the edges of the wound, and then calculating the area. However, this method is both time-consuming and subjective, often leading to varying results depending on the individual performing the assessment. In this study, our goal is to provide an objective method to calculate the wound size and solve variations in photo-taking distance caused by different medical practitioners or at different times, as these can lead to inaccurate wound size assessments. To evaluate this, we employed K-means clustering and used a QR code as a reference to analyze images of the same wound captured at varying distances, objectively quantifying the areas of 40 wounds. This study aims to develop an objective method for calculating the wound size, addressing variations in photo-taking distance that occur across different medical personnel or time points—factors that can compromise measurement accuracy. By improving consistency and reducing the manual workload, this approach also seeks to enhance the efficiency of healthcare providers. We applied K-means clustering for wound segmentation and used a QR code as a spatial reference. Images of the same wounds taken at varying distances were analyzed, and the wound areas of 40 cases were objectively quantified. Materials and Methods: We employed K-means clustering and used a QR code as a reference to analyze wound photos taken by different medical practitioners in the outpatient consulting room. K-means clustering is a machine learning algorithm that segments the wound region by grouping pixels in an image according to their color similarity. It organizes data points into clusters based on shared features. Based on this algorithm, we can use it to identify the wound region and determine its pixel area. We also used a QR code as a reference because of its unique graphical pattern. We used the printed QR code on the patient’s identification sticker as a reference for length. By calculating the ratio of the number of pixels within the square area of the QR code to its actual area, we applied this ratio to the detected wound pixel area, enabling us to calculate the wound’s actual size. The printed patient identification stickers were all uniform in size and format, allowing us to apply this method consistently to every patient. Results: The results support the accuracy of our algorithm when tested on a standard one-cent coin. The paired t-test comparing the first and second photos shot yielded a p-value of 0.370, indicating no significant difference between the two. Similarly, the t-test comparing the first and third photos shot produced a p-value of 0.179, also showing no significant difference. The comparison between the second and third photos shot resulted in a p-value of 0.547, again indicating no significant difference. Since all p-values are greater than 0.05, none of the test pairs show statistically significant differences. These findings suggest that the three randomly taken photo shots produce consistent results and can be considered equivalent. Conclusions: Our algorithm for wound area assessment is highly reliable, interchangeable, and consistently produces accurate results. This objective and practical method can aid clinical decision-making by tracking wound progression over time.