https://orcid.org/0000-0003-2623-0317
Abstract
Unsightly scarring after surgery remains a dilemma. One of the challenges is the lack of objective scar assessment tools.
This study aimed to evaluate the efficacy of a novel medicine, Fespixon, for prevention and/or alleviation of post–skin incision scarring. A second aim was to demonstrate the practicality of our digital image analysis system to see if this could serve as a sensitive tool to assess scar improvement.
A prospective, placebo-controlled trial involving patients with postoperative transverse scars was conducted. Each patient received a topical formulation of Fespixon on the left part of the scar and placebo cream on the right. In addition to recording the subjective modified Vancouver Scar Scale and visual analog scale scores, we utilized digital photography for monthly scar analysis, with CIELAB and hue serving as the colorimetric information, and with contrast, correlation, homogeneity, and entropy providing texture information.
Forty-six participants (mean age, 52 years) were enrolled in the trial. All the parameters of subjective assessment showed superior results for the Fespixon-treated side, with significant differences in pigmentation, vascularity, pliability, height, itchiness, and patient satisfaction (P = .043, .013, .026, .002, .039, .012, respectively). The trends in color and texture showed increased relative difference ratios, with significant differences in most of the eigenvalues towards the Fespixon-treated side, including CIELAB-L* (P < 0.001), hue-R,G,B (red, blue, green) values (P = .034, .001, .011), contrast (P < 0.001), homogeneity (P < 0.001), correlation (P = .011), and entropy (P < 0.001).
We validated the efficacy of Fespixon for postoperative scar healing based not only on subjective assessments but also on objective quantitative analyses. The results also indicated that our digital photography quantitative analysis system is an ideal tool for quantification of scar appearance.
Postoperative scar cosmesis may impact quality of life (QoL), particularly in young or female patients who are more likely to undergo thyroid or abdominal surgeries. Consequently, various operative techniques and surgical approaches have been described to improve aesthetics, including minimally invasive video-assisted techniques, transoral surgery, and remote noncervical routes for thyroid surgery.1 However, these procedures are conducted in only a few institutions and are not affordable for every patient. Thus, conventional surgery performed through a transverse incision remains the mainstay, and superior wound cosmesis has become an important issue for surgeons.
Fespixon (Oneness Biotech Co., Ltd; Taipei, Taiwan), a topical agent with recent clinical applications in diabetic foot ulcer treatment, contains 2 pharmaceutical substances extracted from medicinal herbs that have been reported to be efficacious in wound healing, namely PA-F4 from Plectranthus amboinicus and S1 from Centella asiatica.2–5 The wound healing process is complex and involves inflammation, proliferation, and tissue remodeling. PA-F4 has been shown to arrest inflammation by inhibiting the lipopolysaccharides (LPS) priming step and blocking the activation of the NLRP3-mediated inflammasome pathway.6 S1 has shown its efficacy in the wound repair process by promoting fibroblast proliferation and increasing collagen and intracellular fibronectin synthesis, and it has been significantly effective in accelerating surgical wound healing in an in vivo incision model.7–9 However, no study has tested the efficacy of Fespixon in postoperative scar cosmesis.
In current practice, many modalities, both objective and subjective, have been used to assess the efficacy of antiscar technologies. Although quantitative measurements, including mold techniques and 3-dimensional (3D) scanners, are sometimes difficult to obtain, they are still often utilized instead of semiquantitative information, such as the Vancouver Scar Scale (VSS) and the Patient and Observer Scar Assessment Scale (POSAS), which is relatively accessible but imprecise. Although there are a vast number of options, it is crucial to choose reliable measurements that can be effortlessly adapted to clinical practice. Nevertheless, there is no generally accepted, reliable tool for effective evaluation of postoperative scars. One objective method of assessing postoperative scar cosmesis is by recording the change in hue and texture. The color of a scar is deemed to be associated with its healing process, and CIELAB and hue are the universally accepted colorimetric standards for quantification and communication.10 Texture, which can be divided into color, size, and shape, generates perceptions of density, coarseness, fineness, and smoothness.11 In our previous studies, the reliability of quantitative digital photography analysis in assessing the throat and the larynx has been validated; however, its application in postoperative scar cosmesis has not been assessed.12–15
The aim of this prospective, double-blind study was to evaluate the application of Fespixon in postoperative scar cosmesis by means of a quantitative digital photography analysis system. Furthermore, we wanted to demonstrate the practicality of our analysis system by investigating a more sensitive tool for quantification and evaluation of postoperative scar-improving cosmesis.
Methods
Study Design
This study was designed as a prospective, double-blind, placebo-controlled trial involving 46 patients with transverse scars to explore the relation between Fespixon and postsurgical scarring based on subjective and objective assessment. The study was conducted between January 2022 and October 2022. Dividing the scar at the midpoint, each patient received a topical scar formulation of Fespixon cream on the left side of the scar and placebo cream on the right. Treatment was given twice a day for 84 days. Scars were assessed and photographed on a monthly basis for 3 months, at 0, 28, 56, and 84 days following the onset of topical application, by 3 methods: clinical assessment according to the Vancouver Scar Scale (VSS) and the modified Vancouver Scar Scale (mVSS) (Appendix A, available online at www.aestheticsurgeryjournal.com), quantitative digital photography analysis before and after treatment, and a final satisfaction questionnaire completed by patients in combination with a visual analog scale (VAS) at the end of the study period (Appendix B, available online at www.aestheticsurgeryjournal.com). Blinding of the participants, the independent outcome assessor, and the data analyst was strictly maintained through the use of standardized photography settings and encoded images to delink patient identification, visits, or scar site information throughout the study.
Inclusion and Exclusion Criteria
Eligible subjects had transverse scars on their necks or abdomens following elective surgery, including thyroid and parathyroid surgery, excision of neck mass, inguinal hernia repair, or any neck or abdominal surgeries which can be managed by primary closure of clean surgical wounds. The exclusion criteria included: previous trauma or radiation therapy that might affect the surgical incision site; medical history with chemotherapy or targeted therapy for any reason; pregnancy; abnormal laboratory values at screening indicating anemia, sepsis, or autoimmune disease; liver function studies over 3 times the upper limit of normal; renal function studies over 2 times the upper limit of normal; chronic alcohol or drug abuse problems; or the presence of any clinically significant condition that, in the opinion of the investigator, may pose a threat to subject compliance or interfere with wound healing. Finally, a total of 46 healthy patients, composed of both sexes and aged 20 to 80 years, who consented to participate in this study and comply with the study procedures and applicable dressing changes were enrolled between January 1, 2022 and July 14, 2022.
Sample Preparation
The treatment, Fespixon cream, contained 1.25% extracts of P. amboinicus (PA-F4, 0.25%) and C. asiatica (S1, 1%), whereas the placebo cream contained none of these 2 pharmacologic ingredients. Both samples were prepared to be identical in terms of consistency and appearance (yellow-green to light green in color). They were also placed in the same kind of dispenser but labeled left and right, respectively. They were applied twice daily for up to 3 months (84 days) to the transverse wound. The samples were supplied by Oneness Biotech and manufactured in Taiwan, in a facility in compliance with good manufacturing practice as approved by the Pharmaceutical Inspection Cooperation Scheme.
Assessment of Scars
Subjective Scoring for Scar Quality by Semiquantitative Assessment
At the end of the study period (Month 3, Day 84), 3 independent observers—an otolaryngologist, a gynecologist, and a plastic surgeon—made objective clinical assessments of both the left and right scars based on the VSS, which was developed to enable clinicians to grade scars according to 4 parameters: pigmentation, vascularity, pliability, and scar height.16
In addition, the principal investigator utilized the mVSS to assess scars; this scale incorporates additional indicators of subjective symptoms, namely pain and itchiness, and a modified scale for pigmentation (in general, higher VSS and mVSS scores represent uglier scar formation).17
Moreover, the patients completed a final satisfaction questionnaire, which recorded their responses on a VAS, from 0 to 10, to quantify their satisfaction with scar cosmesis and the impact of scar appearance to their QoL. The questionnaire was administered online through a secure platform, and was anonymous, as we only kept track of participants by assigning them a numerical identifier.
The results of the subjective scoring of scar quality by semiquantitative assessment described mentioned are available in the Supplemental Information.
Quantitative Digital Photography Analysis Processing
Image processing
In total, 184 scar photographs—consisting of 4 images for each patient taken before and 3 months after the treatments were applied—were taken in sets in standard anterior posterior view. A Canon EOS 850D camera was employed for all photographs, with the image quality set to the highest possible level to catch the details of the scars. The distance from the subject to the lens barrel was standardized to 30 cm. The digital images were captured and processed by MATLAB. Figure 1 shows the algorithm of the image-processing techniques for quantifying scar variation in terms of color and texture. The photographs of the scars were captured and divided into the scar part and the skin part. The difference between scar and skin was calculated and expressed as delta (Δ), and the photographs taken on Day 0 (Month 0, M0) were used as the baseline. Meanwhile, the difference ratio and relative difference ratio were calculated. The difference ratio represents the difference between the scar and the skin vs the skin (Δ ratio = Δ(scar – skin)/skin). Using the data of M0 as the baseline, the relative Δ ratio represents the difference of the Δ ratio between Mx and M0 vs the baseline (relative Δ ratio = (Mx Δ ratio – M0 Δ ratio)/M0 Δ ratio).
Procedural chart for quantitative digital photography analysis. (A) Digital photographs of the postoperative scars of a 55-year-old female patient were taken on Day 0 (Month 0) as a baseline and at the 3-month follow-up visit. (B) Photographs of the scars taken were divided into scar and skin sections. The color and texture characteristics of the scars were quantified by image-processing techniques. In addition, difference ratios and relative difference ratios were computed.
Hue and CIELAB results
The RGB values were collected from the photographs of each postoperative scar for both the scar and skin regions. The calculation of the RGB color space is rapid and no coordinate conversions are required. CIELAB is a color space modeled on the human vision and designed to be uniform in human perception.18 The CIELAB coordinates are L*, a*, and b*, where L* represents the lightness of the color (L* = 0 indicates black and L* = 100 indicates diffuse white), a* represents the position between red and green (negative values mean green and positive values mean red), and b* represents the position between yellow and blue (negative values mean blue and positive values mean yellow). Conversion between RGB and CIELAB is a 2-stage process, and was performed with equations presented in a previous study.19
Textual features
Skin texture, ie, the perception of roughness due to the directionality of human vision, has a significant effect on scar cosmesis that can be quantified and calculated. The gray-level co-occurrence matrix (GLCM) describes the spatial distribution of the gray levels between adjacent pixels in an image. We utilized second-order statistics based on the GLCM (including 4 different eigenvalues: contrast [Con], homogeneity [Hom], correlation [Cor], and entropy [Ent]) to quantify the skin variation induced by scarring. Normalization was performed before extraction of the GLCM eigenvalues, and the sum of the elements of the GLCM was set to 1 for computing. The eigenvalues used are discussed below.
Con
The Con eigenvalue is used to measure the amount of local gray-level variation in an image, which is the intensity contrast between adjacent pixels in each region. A larger gray-level difference represents a larger Con value of the GLCM.
Homogeneity
The Hom eigenvalue reflects the similarity of image textures and scales the local changes in image texture. High values of Hom denote the absence of intraregional changes and indicate local uniform grayness of the image.
Cor
The Cor eigenvalue is used to measure the gray-level linear dependencies in an image. For example, when the number of textures in the horizontal direction is more than that in other directions, the value of the correlation feature is higher along this direction.
Ent
The Ent eigenvalue originates from thermodynamics and reflects the nonuniformity and randomness of grayscale distribution in image texture processing. The more scattered the grayscale distribution is, the higher the entropy values are.
Statistical Analysis
Differences between the results derived from the Fespixon-treated side and the control side were analyzed by independent t-test performed with SPSS version 22.0 (SPSS Inc.; Chicago, IL). Statistical significance was accepted at P < .05.
Ethical Considerations
The study was conducted in accordance with the Declaration of Helsinki. Written informed consent to publish was obtained from all participants. The research protocol, No. B202105176, has been reviewed and approved by the IRB of Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, Republic of China. The ClinicalTrials.gov identifier NCT05271708, entitled “Explore the Role of Fespixon in Linear Scar Aesthetics,” is registered and will be posted on the ClinicalTrials.gov public website.
Results
We retrieved a total of 46 cases. There were 26 female participants and 20 male participants, with a mean [standard deviation] age of 52 [15] years (range, 20-80 years). The average follow-up time was 102 days (range, 84-170 days). All the enrolled individuals completed the study and were available for final evaluation. Table 1 shows the overall distribution and characteristics of all the samples. No complications or adverse effects such as maceration or infection were observed during the study. All participants tolerated the treatment well and no serious events were reported; and all reported that both creams were easy to apply. Four patients complained of mild pain on the control side (right), and 1 patient complained of mild pain on both sides. About 67% of all the patients experienced no postoperative scar itch or pain. Fifteen patients reported mild itching on the right side and 7 reported itching on the left side. An excellent response of the Fespixon-treated side was observed in all cases, with texture improvement and a reduction in redness (Figure 2).
Representative photographs of 2 subjects’ scars from (A-D) a 57-year-old male and (E-H) a 63-year-old male show postoperative scars at Month 0, 1, 2, and 3 follow-up. The left half of the scar (from the patient's position) was treated with Fespixon and the right half with the control cream which contained no pharmacologic ingredients. L, left; R, right.
Demographic Information and the Assessed Scar Sites
| Characteristics | |
|---|---|
| Gender | |
| Male | 20 |
| Female | 26 |
| Mean age, years (range) | 51.71739 (20-80) |
| Operation | |
| Thyroidectomy | 31 |
| Parathyroidectomy | 1 |
| Neck disscetion | 2 |
| Excision of submandibular gland | 2 |
| Parotidectomy | 3 |
| Excision of neck mass | 4 |
| Inguinal hernia repair | 3 |
| AST (range) | 18.2973 (5-36) |
| ALT (range) | 15.7027 (4-51) |
| Creatinine (range) | 0.8 (0.4-1.3) |
| Characteristics | |
|---|---|
| Gender | |
| Male | 20 |
| Female | 26 |
| Mean age, years (range) | 51.71739 (20-80) |
| Operation | |
| Thyroidectomy | 31 |
| Parathyroidectomy | 1 |
| Neck disscetion | 2 |
| Excision of submandibular gland | 2 |
| Parotidectomy | 3 |
| Excision of neck mass | 4 |
| Inguinal hernia repair | 3 |
| AST (range) | 18.2973 (5-36) |
| ALT (range) | 15.7027 (4-51) |
| Creatinine (range) | 0.8 (0.4-1.3) |
ALT, alanine transaminase; AST, aspartate transaminase. AST and ALT are measured in international units per liter (IU/L).
Demographic Information and the Assessed Scar Sites
| Characteristics | |
|---|---|
| Gender | |
| Male | 20 |
| Female | 26 |
| Mean age, years (range) | 51.71739 (20-80) |
| Operation | |
| Thyroidectomy | 31 |
| Parathyroidectomy | 1 |
| Neck disscetion | 2 |
| Excision of submandibular gland | 2 |
| Parotidectomy | 3 |
| Excision of neck mass | 4 |
| Inguinal hernia repair | 3 |
| AST (range) | 18.2973 (5-36) |
| ALT (range) | 15.7027 (4-51) |
| Creatinine (range) | 0.8 (0.4-1.3) |
| Characteristics | |
|---|---|
| Gender | |
| Male | 20 |
| Female | 26 |
| Mean age, years (range) | 51.71739 (20-80) |
| Operation | |
| Thyroidectomy | 31 |
| Parathyroidectomy | 1 |
| Neck disscetion | 2 |
| Excision of submandibular gland | 2 |
| Parotidectomy | 3 |
| Excision of neck mass | 4 |
| Inguinal hernia repair | 3 |
| AST (range) | 18.2973 (5-36) |
| ALT (range) | 15.7027 (4-51) |
| Creatinine (range) | 0.8 (0.4-1.3) |
ALT, alanine transaminase; AST, aspartate transaminase. AST and ALT are measured in international units per liter (IU/L).
At the end of the study, 4 clinicians performed a clinical assessment with either the VSS or the mVSS, and all parameters were significantly lower for the side treated with Fespixon, with significant differences in pigmentation, vascularity, pliability, height, and itchiness. Patients also rated their overall satisfaction, with results for the Fespixon-treated side showing higher VAS scores, with significant differences and relatively modest effects on QoL (Table 2).
Subjective Scoring of Scar Quality
| Subjective assessment | Left, Fespixon | Right, control | P-value |
|---|---|---|---|
| VAS from patient (0-10 points) | |||
| Satisfaction | 8.43 (1.54) | 7.56 (1.72) | .012 |
| QoL | 1.17 (1.58) | 1.61 (1.68) | .205 |
| VSS from doctors and mVSS from PI | |||
| Pigmentation (0-3 points) | 1.21 (0.79) | 1.57 (0.83) | .043 |
| Vascularity (0-3 points) | 0.92 (0.77) | 1.34 (0.73) | .013 |
| Pliability (0-5 points) | 0.58 (0.69) | 0.95 (0.81) | .026 |
| Height (0-3 points) | 0.36 (0.40) | 0.66 (0.47) | .002 |
| Pain (0-3 points) | 0.02 (0.15) | 0.12 (0.39) | .150 |
| Itchiness (0-3 points) | 0.16 (0.37) | 0.37 (0.54) | .039 |
| Sum of pigmentation, vascularity, height | |||
| VSS at Month 0 (M0) | 7.26 (0.75) | 7.22 (0.87) | |
| VSS at Month 3 (M3) | 2.49 (1.76) | 3.57 (1.76) | |
| VSS gain (Δ = M0 – M3) | 4.78 (1.75) | 3.65 (1.96) | .006 |
| VSS gain ratio (Δ ratio = (M0 – M3)/M0) | 65.62% (23.49) | 48.80% (25.75) | .002 |
| Subjective assessment | Left, Fespixon | Right, control | P-value |
|---|---|---|---|
| VAS from patient (0-10 points) | |||
| Satisfaction | 8.43 (1.54) | 7.56 (1.72) | .012 |
| QoL | 1.17 (1.58) | 1.61 (1.68) | .205 |
| VSS from doctors and mVSS from PI | |||
| Pigmentation (0-3 points) | 1.21 (0.79) | 1.57 (0.83) | .043 |
| Vascularity (0-3 points) | 0.92 (0.77) | 1.34 (0.73) | .013 |
| Pliability (0-5 points) | 0.58 (0.69) | 0.95 (0.81) | .026 |
| Height (0-3 points) | 0.36 (0.40) | 0.66 (0.47) | .002 |
| Pain (0-3 points) | 0.02 (0.15) | 0.12 (0.39) | .150 |
| Itchiness (0-3 points) | 0.16 (0.37) | 0.37 (0.54) | .039 |
| Sum of pigmentation, vascularity, height | |||
| VSS at Month 0 (M0) | 7.26 (0.75) | 7.22 (0.87) | |
| VSS at Month 3 (M3) | 2.49 (1.76) | 3.57 (1.76) | |
| VSS gain (Δ = M0 – M3) | 4.78 (1.75) | 3.65 (1.96) | .006 |
| VSS gain ratio (Δ ratio = (M0 – M3)/M0) | 65.62% (23.49) | 48.80% (25.75) | .002 |
Values are mean [standard deviation]. Participants completed a final satisfaction questionnaire which comprised a VAS (rating from 0 to 10) to quantify their satisfaction with the appearance of their scars and the impact of scar appearance on their QoL. Three blinded surgeons performed an objective clinical scar assessment with the VSS on Day 84. The PI used the mVSS to evaluate the scars. PI, principal investigator. QoL, quality of life; (m)VSS, (modified) Vancouver Scar Scale; VAS, visual analog scale.
Subjective Scoring of Scar Quality
| Subjective assessment | Left, Fespixon | Right, control | P-value |
|---|---|---|---|
| VAS from patient (0-10 points) | |||
| Satisfaction | 8.43 (1.54) | 7.56 (1.72) | .012 |
| QoL | 1.17 (1.58) | 1.61 (1.68) | .205 |
| VSS from doctors and mVSS from PI | |||
| Pigmentation (0-3 points) | 1.21 (0.79) | 1.57 (0.83) | .043 |
| Vascularity (0-3 points) | 0.92 (0.77) | 1.34 (0.73) | .013 |
| Pliability (0-5 points) | 0.58 (0.69) | 0.95 (0.81) | .026 |
| Height (0-3 points) | 0.36 (0.40) | 0.66 (0.47) | .002 |
| Pain (0-3 points) | 0.02 (0.15) | 0.12 (0.39) | .150 |
| Itchiness (0-3 points) | 0.16 (0.37) | 0.37 (0.54) | .039 |
| Sum of pigmentation, vascularity, height | |||
| VSS at Month 0 (M0) | 7.26 (0.75) | 7.22 (0.87) | |
| VSS at Month 3 (M3) | 2.49 (1.76) | 3.57 (1.76) | |
| VSS gain (Δ = M0 – M3) | 4.78 (1.75) | 3.65 (1.96) | .006 |
| VSS gain ratio (Δ ratio = (M0 – M3)/M0) | 65.62% (23.49) | 48.80% (25.75) | .002 |
| Subjective assessment | Left, Fespixon | Right, control | P-value |
|---|---|---|---|
| VAS from patient (0-10 points) | |||
| Satisfaction | 8.43 (1.54) | 7.56 (1.72) | .012 |
| QoL | 1.17 (1.58) | 1.61 (1.68) | .205 |
| VSS from doctors and mVSS from PI | |||
| Pigmentation (0-3 points) | 1.21 (0.79) | 1.57 (0.83) | .043 |
| Vascularity (0-3 points) | 0.92 (0.77) | 1.34 (0.73) | .013 |
| Pliability (0-5 points) | 0.58 (0.69) | 0.95 (0.81) | .026 |
| Height (0-3 points) | 0.36 (0.40) | 0.66 (0.47) | .002 |
| Pain (0-3 points) | 0.02 (0.15) | 0.12 (0.39) | .150 |
| Itchiness (0-3 points) | 0.16 (0.37) | 0.37 (0.54) | .039 |
| Sum of pigmentation, vascularity, height | |||
| VSS at Month 0 (M0) | 7.26 (0.75) | 7.22 (0.87) | |
| VSS at Month 3 (M3) | 2.49 (1.76) | 3.57 (1.76) | |
| VSS gain (Δ = M0 – M3) | 4.78 (1.75) | 3.65 (1.96) | .006 |
| VSS gain ratio (Δ ratio = (M0 – M3)/M0) | 65.62% (23.49) | 48.80% (25.75) | .002 |
Values are mean [standard deviation]. Participants completed a final satisfaction questionnaire which comprised a VAS (rating from 0 to 10) to quantify their satisfaction with the appearance of their scars and the impact of scar appearance on their QoL. Three blinded surgeons performed an objective clinical scar assessment with the VSS on Day 84. The PI used the mVSS to evaluate the scars. PI, principal investigator. QoL, quality of life; (m)VSS, (modified) Vancouver Scar Scale; VAS, visual analog scale.
The results of our quantitative analysis of texture showed a decreasing and increasing trend in the difference ratio and the relative difference ratio, respectively, which coincided with the healing process of the scars, indicating that our quantitative analysis of the digital photographs is an ideal tool with discriminatory power (Table 3). Quantitative analysis of the color included eigenvalues from the CIELAB and RGB systems, calculating differences and relative differences ratio, and graphing the trends (Figure 3). The results demonstrated a significant improvement in the relative difference ratio of color lightness (L* of CIELAB) on the Fespixon-treated side at Month 3 (P < 0.001), suggesting less hyperpigmentation than the control side. There were notable trends towards increased relative difference ratios on the Fespixon-treated side by the end of this study, with significant differences in all RGB trends (R, P = .034; G, P = .001; B, P = .011), suggesting relatively accelerated scar maturation compared with the control side, as the immature scars looked redder.
(A-F) Graphs of trends in the difference ratio (left panels) and relative difference ratio (right panels) of the CIELAB (A-C) and RGB (D-F) systems on the Fespixon-treated side (left, Lt) and the control side (right, Rt). Statistically significant different eigenvalues at each month are marked with an asterisk. At Month 3, there is a noticeable trend towards an increase in the relative difference ratio on the Fespixon-treated side, which indicates a significant improvement compared with the control side.
Trends in Color and Texture Difference Ratios and Relative Difference Ratios
| Difference ratio: Δ ratio = Δ(scar – skin)/skin | Relative difference ratio: relative Δ ratio = (Δ ratio of Mx – Δ ratio of M0)/Δ ratio of M0 | |||||||
|---|---|---|---|---|---|---|---|---|
| M0 | M1 | M2 | M3 | M0 | M1 | M2 | M3 | |
| CIELAB-L* | 0.206996 | 0.186226 | 0.15831 | 0.125118 | 0 | 0.869186 | 0.680006 | 0.57634 |
| CIELAB-a* | 0.981732 | 0.643906 | 0.776719 | 0.500905 | 0 | 1.413148 | 1.151311 | 0.901146 |
| CIELAB-b* | 0.14984 | 0.151838 | 0.125897 | 0.102589 | 0 | 1.797213 | 1.25486 | 1.266351 |
| Hue-R | 0.177208 | 0.151671 | 0.132636 | 0.10264 | 0 | 0.788043 | 0.699152 | 0.60582 |
| Hue-G | 0.23196 | 0.213646 | 0.182837 | 0.14616 | 0 | 0.83073 | 0.637373 | 0.545833 |
| Hue-B | 0.245763 | 0.227621 | 0.190235 | 0.145948 | 0 | 0.938681 | 0.616196 | 0.607824 |
| Contrast | 1.398777 | 0.775644 | 0.366085 | 0.262526 | 0 | 0.669215 | 0.730696 | 0.812308 |
| Homogeneity | 0.763749 | 0.420933 | 0.284099 | 0.17821 | 0 | 0.558188 | 0.72146 | 0.80463 |
| Correlation | 0.052052 | 0.035889 | 0.02085 | 0.019019 | 0 | 0.54906 | 0.72411 | 0.893672 |
| Entropy | 0.132379 | 0.088022 | 0.072313 | 0.047838 | 0 | 0.385284 | 0.717647 | 0.74886 |
| Difference ratio: Δ ratio = Δ(scar – skin)/skin | Relative difference ratio: relative Δ ratio = (Δ ratio of Mx – Δ ratio of M0)/Δ ratio of M0 | |||||||
|---|---|---|---|---|---|---|---|---|
| M0 | M1 | M2 | M3 | M0 | M1 | M2 | M3 | |
| CIELAB-L* | 0.206996 | 0.186226 | 0.15831 | 0.125118 | 0 | 0.869186 | 0.680006 | 0.57634 |
| CIELAB-a* | 0.981732 | 0.643906 | 0.776719 | 0.500905 | 0 | 1.413148 | 1.151311 | 0.901146 |
| CIELAB-b* | 0.14984 | 0.151838 | 0.125897 | 0.102589 | 0 | 1.797213 | 1.25486 | 1.266351 |
| Hue-R | 0.177208 | 0.151671 | 0.132636 | 0.10264 | 0 | 0.788043 | 0.699152 | 0.60582 |
| Hue-G | 0.23196 | 0.213646 | 0.182837 | 0.14616 | 0 | 0.83073 | 0.637373 | 0.545833 |
| Hue-B | 0.245763 | 0.227621 | 0.190235 | 0.145948 | 0 | 0.938681 | 0.616196 | 0.607824 |
| Contrast | 1.398777 | 0.775644 | 0.366085 | 0.262526 | 0 | 0.669215 | 0.730696 | 0.812308 |
| Homogeneity | 0.763749 | 0.420933 | 0.284099 | 0.17821 | 0 | 0.558188 | 0.72146 | 0.80463 |
| Correlation | 0.052052 | 0.035889 | 0.02085 | 0.019019 | 0 | 0.54906 | 0.72411 | 0.893672 |
| Entropy | 0.132379 | 0.088022 | 0.072313 | 0.047838 | 0 | 0.385284 | 0.717647 | 0.74886 |
M, month. See text for definitions of CIELAB and hue color space parameters. Quantitative analysis of digital photographs of postoperative scars yielded eigenvalues of color and texture, calculated as the difference ratio (Δ ratio = Δ(scar – skin)/skin) and the relative difference ratio (relative Δ ratio = Δ ratio of Mx – Δ ratio of M0/Δ ratio of M0). Analysis of the difference and relative difference in scar texture showed a decreasing and increasing trend, respectively, which were compatible with the scar healing process and demonstrate the discriminative capability of our digital photographic quantitative analysis.
Trends in Color and Texture Difference Ratios and Relative Difference Ratios
| Difference ratio: Δ ratio = Δ(scar – skin)/skin | Relative difference ratio: relative Δ ratio = (Δ ratio of Mx – Δ ratio of M0)/Δ ratio of M0 | |||||||
|---|---|---|---|---|---|---|---|---|
| M0 | M1 | M2 | M3 | M0 | M1 | M2 | M3 | |
| CIELAB-L* | 0.206996 | 0.186226 | 0.15831 | 0.125118 | 0 | 0.869186 | 0.680006 | 0.57634 |
| CIELAB-a* | 0.981732 | 0.643906 | 0.776719 | 0.500905 | 0 | 1.413148 | 1.151311 | 0.901146 |
| CIELAB-b* | 0.14984 | 0.151838 | 0.125897 | 0.102589 | 0 | 1.797213 | 1.25486 | 1.266351 |
| Hue-R | 0.177208 | 0.151671 | 0.132636 | 0.10264 | 0 | 0.788043 | 0.699152 | 0.60582 |
| Hue-G | 0.23196 | 0.213646 | 0.182837 | 0.14616 | 0 | 0.83073 | 0.637373 | 0.545833 |
| Hue-B | 0.245763 | 0.227621 | 0.190235 | 0.145948 | 0 | 0.938681 | 0.616196 | 0.607824 |
| Contrast | 1.398777 | 0.775644 | 0.366085 | 0.262526 | 0 | 0.669215 | 0.730696 | 0.812308 |
| Homogeneity | 0.763749 | 0.420933 | 0.284099 | 0.17821 | 0 | 0.558188 | 0.72146 | 0.80463 |
| Correlation | 0.052052 | 0.035889 | 0.02085 | 0.019019 | 0 | 0.54906 | 0.72411 | 0.893672 |
| Entropy | 0.132379 | 0.088022 | 0.072313 | 0.047838 | 0 | 0.385284 | 0.717647 | 0.74886 |
| Difference ratio: Δ ratio = Δ(scar – skin)/skin | Relative difference ratio: relative Δ ratio = (Δ ratio of Mx – Δ ratio of M0)/Δ ratio of M0 | |||||||
|---|---|---|---|---|---|---|---|---|
| M0 | M1 | M2 | M3 | M0 | M1 | M2 | M3 | |
| CIELAB-L* | 0.206996 | 0.186226 | 0.15831 | 0.125118 | 0 | 0.869186 | 0.680006 | 0.57634 |
| CIELAB-a* | 0.981732 | 0.643906 | 0.776719 | 0.500905 | 0 | 1.413148 | 1.151311 | 0.901146 |
| CIELAB-b* | 0.14984 | 0.151838 | 0.125897 | 0.102589 | 0 | 1.797213 | 1.25486 | 1.266351 |
| Hue-R | 0.177208 | 0.151671 | 0.132636 | 0.10264 | 0 | 0.788043 | 0.699152 | 0.60582 |
| Hue-G | 0.23196 | 0.213646 | 0.182837 | 0.14616 | 0 | 0.83073 | 0.637373 | 0.545833 |
| Hue-B | 0.245763 | 0.227621 | 0.190235 | 0.145948 | 0 | 0.938681 | 0.616196 | 0.607824 |
| Contrast | 1.398777 | 0.775644 | 0.366085 | 0.262526 | 0 | 0.669215 | 0.730696 | 0.812308 |
| Homogeneity | 0.763749 | 0.420933 | 0.284099 | 0.17821 | 0 | 0.558188 | 0.72146 | 0.80463 |
| Correlation | 0.052052 | 0.035889 | 0.02085 | 0.019019 | 0 | 0.54906 | 0.72411 | 0.893672 |
| Entropy | 0.132379 | 0.088022 | 0.072313 | 0.047838 | 0 | 0.385284 | 0.717647 | 0.74886 |
M, month. See text for definitions of CIELAB and hue color space parameters. Quantitative analysis of digital photographs of postoperative scars yielded eigenvalues of color and texture, calculated as the difference ratio (Δ ratio = Δ(scar – skin)/skin) and the relative difference ratio (relative Δ ratio = Δ ratio of Mx – Δ ratio of M0/Δ ratio of M0). Analysis of the difference and relative difference in scar texture showed a decreasing and increasing trend, respectively, which were compatible with the scar healing process and demonstrate the discriminative capability of our digital photographic quantitative analysis.
Quantification of the texture eigenvalues involved the use of Con, Hom, Cor, and Ent of the GLCM to derive differences and relative difference ratios and to graph trends (Figure 4). The outcomes revealed that at Month 3, the difference ratio of Ent for the Fespixon-treated side decreased significantly (P = .010), indicating less disorganization and more similarity to unbroken intact skin compared with the control side. At the end of this study, there were statistically significant improvements in the relative difference ratios of all texture eigenvalues for the Fespixon-treated side (Con, P < 0.001; Hom, P < 0.001; Cor, P = .011; Ent, P < 0.001), reflecting increased consistency and gray-level linearity with reduced complexities compared with the control side. The trend of color and texture showed increased relative difference ratios and significant differences in most of the eigenvalues towards the Fespixon-treated side, which corresponded to relatively rapid scar healing and suggests that our analysis could be a discriminative as well as an outstanding validation of the efficacy of Fespixon in scar cosmesis.
(A-D) Graphs of trends in the difference ratio (left panels) and relative difference ratio (right panels) of the texture profiles on the Fespixon-treated side (left, Lt) and the control side (right, Rt). Statistically significant eigenvalues for each month are marked with an asterisk. Significant trends towards the Fespixon-treated side are apparent. Cor, correlation; Ent, entropy; Hom, homogeneity.
Discussion
The aesthetics of transverse scars in a visible region impact their appearance and can, like hypertrophic scars, elicit functional disorders or pathologic morbidities, causing patients distress and financial cost. Therefore, postoperative scar cosmesis is a challenge frequently encountered by surgeons. Nowadays, various scar management options are available, including compression therapy, internal agents, surgical resection, intralesional injection, laser therapy, radiotherapy, cryotherapy, and topical drugs.20 Current treatments concentrate on reducing scar formation after surgery, and topical drugs commonly have strong patient compliance due to their noninvasive and painless nature and their ease of application. Topical antiscarring agents include both conventional silicone-based products, corticosteroids, and imiquimod, as well as mitomycin C, onion extract, and so on.21 However, many treatments appear to give poor results, and the effects of surgical scar cosmesis are contentious because previous work has mainly focused on the treatment of hypertrophic scars and keloids.22 To our knowledge, this study is the first prospective clinical trial that aimed to validate Fespixon use in postoperative scar cosmesis. Fespixon, made from 2 medical plant extracts, namely PA-F4 from P. amboinicus and S1 from C. asiatic, has demonstrated superior efficacy in the healing of diabetic foot ulcers by inhibiting NLRP3 signaling and regulating macrophages.2,23,24 The activation of NLRP3 inflammasome gives rise to maturation and release of proinflammatory cytokines, including interleukin-1β (IL-1β) and interleukin-18 (IL-18). PA-F4, which suppresses NLRP3 inflammasome activation, inhibited not only the ATP-induced release of IL-1β, IL-18, and caspase-1 from lipopolysaccharide priming but also the ASC-dependent inflammasome formation, thereby blunting the interaction between NLRP3 and ASC.25,26 The other main ingredient, C. asiatica extract S1, has clinical pharmacologic effects on wound healing by augmenting antioxidant levels and stimulating angiogenesis, and accelerates epithelization by promoting collagen, fibroblast, extracellular matrix synthesis, and keratinocyte migration.8,27–30 Taken together, based on these clinical pharmacologic effects on wound healing, we speculate that Fespixon could be of use in the prevention of postoperative scarring. Accordingly, our study results have clearly validated Fespixon use in postoperative scar cosmesis, not only from the subjective aspect of both patient and surgeon assessments but also from objective quantitative digital photography analysis. These results have also shown that Fespixon, used in scar management, has a significant positive effect on erythema, pigmentation, roughness, and scar thickness compared with the control or no treatment.
Considering the high prevalence and associated morbidities of scarring, surgeons have become more focused on securing optimal aesthetic results. Hence, there are many therapeutic choices, but little evidence clearly confirming their efficacy. Numerous scar assessment methods have been developed.31 The first validated scale to be widely used in clinical scar evaluation was the VSS, intended for clinicians to perform subjective assessment by a semiquantitative approach.16 The VSS assesses 4 indicators, ie, vascularity, pigmentation, pliability, and height; however, it does not consider patients’ subjective symptoms or psychological concerns. The mVSS added pain and itchiness as supplemental indicators of symptomatic features.17 Beausang et al established the Manchester Scar Scale for linear scar assessment in 1998 to semiquantitatively estimate scar severity in combination with a VAS based on characteristics such as color, contour, radiation, texture, and distortion.32 The POSAS was designed by Draaijers et al in 2004 to provide a broader scale that integrates patient and evaluator perspectives.33 Nevertheless, these semiquantitative subjective assessments inevitably show perceptual bias; additionally, the human vision cannot attribute precise values to the unequal color distribution of scarring. Thus, there is a need to develop objective instruments that use quantitative data to obtain reliable scar evaluation.34 The color of a scar can reflect skin architecture and antiscarring treatment efficacy. Thus, many spectroscopy-based techniques have been exploited to quantify the pigmentation from cutaneous melanin and erythema from remodeled vascularization, which are the major contributors to scar color. In recent years, several objective spectral methods have demonstrated high sensitivity and interrater concordance for quantitative scar assessments. These methods are mainly classified as reflectance spectroscopy, performed with, for example, the Mexameter or the DSM II and III ColorMeter; laser imaging of the microcirculation of the scar; and 2D or 3D digital photography followed by image analysis with, for example, a Colorimeter.35–37 Digital photography is obtainable with any digital camera, and has been extensively applied for postoperative scar documentation and image analysis after the fact to quantify scar pigmentation, erythema, texture, and geometry. Kim et al proposed that the color measurements obtained by digital photography were equivalent to those obtained from colorimetry.38 Baumann et al compared quantitative assessments of burn scars, and demonstrated exceptional reliability for both Mexameter and digital photography analysis; they also noted that digital photographic measurement was more reliable for erythema quantification than the POSAS or the VSS.39
Skin texture, ie, perception of roughness and directionality, has a significant effect on scar cosmesis that can be quantified and calculated from 3D digital models such as Eykona, imaging analysis by the GLCM, or topographic analysis such as PRIMOS.40–42 In addition, computer-assisted image texture analysis can examine quantitative parameters that have proven to be clinically practical in lung cancer, arrhythmia, laryngopharyngeal illness identification, and tumor staging.13,14,43–46 In this study, we utilized second-order statistics based on the GLCM to quantify scar texture from digital photography, which gave us 4 different feature vectors: contrast (variations in the image), homogeneity (similarities in the image), correlation (gray-level linear dependencies), and entropy (randomness of the image). The trend graphs of these 4 eigenvalues showed increased relative delta ratios with significant differences towards the Fespixon-treated side on the third month, which corresponded with the scar healing process and suggests that our analysis could be powerful for quantifying skin texture as well as providing excellent validation of the efficacy of Fespixon use in scar cosmesis.
Although the varieties of quantitative criteria and computer-based system settings from various institutions limit interuser reliability, recent studies have aimed to improve the objectivity of these quantitative assessments with standardized lighting, distance, and computer-based image acquisition which transfigure detailed information into digital data.38,47,48 In this study, we performed digital photography analysis for postoperative scar cosmesis based on CIELAB and hue, which are universally accepted colorimetric systems, and examined the contrast, correlation, homogeneity, and entropy of the texture information. Our measurements are not only easily accessible due to the popularity of clinical photography applications but also provide a convincing scar assessment by quantifying color and texture profiles; these demonstrated significant differences after 3 months in all the hue and texture profile parameters between the Fespixon-treated side and the control side. The results also indicated that our quantitative digital photography analysis system is not only accurate but also discriminatory, and is compatible with semiquantitative subjective assessments, including the mVSS (which gives a doctor's perspective) and a VAS of patient satisfaction, and can be employed for reliable, cost-effective analysis of postoperative scar cosmesis.
There are several limitations to this study. First, the study population was relatively small; it is not easy to find large numbers of patients willing to commit to long-term follow-up of stable postoperative wounds. Despite our results of color and texture profiles showing significant differences in the third month, the progression of scar aesthetic results is known to exhibit changes over time, and taking long-term follow-up pictures as frequently as possible is a considerable task. Second, this study mostly investigated transverse scars after thyroidectomy or abdominal surgeries, thus future studies designed to validate Fespixon use for other scarring types are anticipated. Third, our study did not include a comparison with currently available over-the-counter ointments such as silicone or bio-oil due to the challenges of designing and implementing a double-blind comparison. This is an area for future research. Lastly, quantitative scar assessment was evaluated by 2D photography. Neither the biomechanical properties of scars, which can be assessed by suction, tonometry, or elastometry,35 nor scar height, which can be quantitatively assessed with a 3D scanner, was evaluated in this study. However, the roughness and directionality determined from the texture profile can identify hypertrophic scarring. Moreover, it would be advisable to study the effectiveness of Fespixon on a larger scale in a comparative study with silicone gel or other plant-based scar reduction medications. Despite these limitations, this study is significant as the first prospective, double-blind study to measure the antiscar efficacy of Fespixon in postoperative scar aesthetic outcomes with a quantitative digital photography analysis system.
Conclusions
We have demonstrated the efficacy of Fespixon in postoperative scar healing applications, not only with subjective assessments but also with objective quantitative analyses, and have demonstrated significant positive effects of Fespixon on erythema, pigmentation, roughness, and scar thickness. The results also indicated that our digital photography quantitative analysis system is accurate, reliable, and can be easily integrated into a clinical workflow as a cost-effective and ideal tool for quantitative assessment of scar appearance.
Supplemental Material
This article contains supplemental material located online at www.aestheticsurgeryjournal.com.
Disclosures
The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.
Funding
This research was partially supported by Tri-Service General Hospital, National Defense Medical Center (MND-MAB-D-112127 and TSGH-110161) (New Taipei, Taiwan), and was supported by Oneness Biotech Co. Ltd, Taipei, Taiwan.
