中华皮肤科杂志 ›› 2019, Vol. 52 ›› Issue (2): 111-114.doi: 10.3760/cma.j.issn.0412-4030.2019.02.009

• 技术与方法 • 上一篇    下一篇

皮肤镜毛孔检测方法在2 940 nm铒像素激光治疗毛孔粗大疗效观察中的应用

门月华1    臧琳2    吴雯婷1    李薇薇1    张春雷1   

  1. 1北京大学第三医院皮肤科 100191；2北京沃东天骏信息技术有限公司 101111
  • 收稿日期:2018-04-17 修回日期:2018-12-07 出版日期:2019-02-15 发布日期:2019-01-29
  • 通讯作者: 张春雷 E-mail:zhangchunleius@163.com

Application of dermoscopy to the evaluation of efficacy of 2 940 nm Er pixel laser in the treatment of skin pore widening

Men Yuehua1, Zang Lin2, Wu Wenting1, Li Weiwei1, Zhang Chunlei1   

  1. 1Department of Dermatology, Peking University Third Hospital, Beijing 100191, China; 2Beijing Wodong Tianjun Information Technology Limited Company, Beijing 101111, China
  • Received:2018-04-17 Revised:2018-12-07 Online:2019-02-15 Published:2019-01-29
  • Contact: Zhang Chunlei E-mail:zhangchunleius@163.com

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摘要： 【摘要】 目的 探索基于皮肤镜的面部毛孔量化评估方法，评价该方法的科学性及实用性。方法 对2017年6 - 12月于北京大学第三医院皮肤科就诊的30例毛孔粗大患者，采用2 940 nm铒像素激光治疗，于治疗前后照相及采集皮肤镜图像。参考面部毛孔标准照片评价法比较治疗前后大体照片毛孔粗大的改善情况。建立皮肤镜毛孔检测系统，利用该系统评估治疗前后毛孔面积及色差的量化指标。研究采用自身前后对照，计量资料进行配对样本t检验，等级资料采用两配对样本的非参数检验（Wilcoxon符号秩检验）。结果 30例患者中面部毛孔评级较治疗前降低3级者1例（3.3%），降低2级者7例（23.3%），降低1级者21例（70%），无变化者1例（3.3%），治疗前后评级差异有统计学意义（Z = -4.94，P < 0.01）。皮肤镜毛孔检测系统毛孔检出率为（70.59 ± 3）%，治疗后毛孔面积量化值（712.95 ± 87.45）低于治疗前（831.45 ± 88.92），治疗后色差量化值（23.82 ± 9.43）亦低于治疗前（28.92 ± 9.91），t值分别为5.70、2.76，均P < 0.05。结论 基于皮肤镜的面部毛孔量化评估方法对2 940 nm铒像素激光治疗毛孔粗大的评估结果与面部毛孔标准照片评价结果一致，可进一步在毛孔粗大的评价上验证推广。

关键词: 皮肤镜检查； 图像处理, 计算机辅助； 激光疗法； 毛孔粗大

Abstract: 【Abstract】 Objective To explore and establish a method for quantitative evaluation of facial skin pores based on dermoscopy, and to evaluate the scientificity and practicability of this method. Methods Totally, 30 patients with enlarged facial skin pores were enrolled from Department of Dermatology, Peking University Third Hospital between June 2017 and December 2017, and treated with 2 940 nm Er pixel laser. Photographs were taken, and dermoscopic images were collected before and after treatment. According to the standard photographs of facial pores, the improvement of enlarged facial pores was evaluated by comparing the photos before and after the treatment. A dermoscope-based pore detection system was established, and quantified indices for pore area and color difference before and after the treatment were evaluated by using this system. A pre-post self-contrast study was conducted, and statistical analysis was carried out by using paired t test for the comparison of measurement data and paired non-parametric test （Wilcoxon signed-rank test） for the comparison of ranked data. Results After the treatment, the standard photograph method for the assessment of facial pores showed score reduction by 3 grades in 1 of the 30 patients （3.3%）, by 2 grades in 7（23.3%）, by 1 grade in 21（70%）, and no changes of grades in 1（3.3%）. Additionally, the differences between pre- and post-treatment grades were significant （Z = -4.94, P < 0.01）. The detection rate of skin pores by using the detection system was （70.59 ± 3）%. After the treatment, the quantified values of pore area and color difference both significantly decreased compared with those before the treatment （pore area: 712.95 ± 87.45 vs. 831.45 ± 88.92, t = 5.70, P < 0.05; color difference: 23.82 ± 9.43 vs. 28.92 ± 9.91, t = 2.76, P < 0.05）. Conclusion The dermoscopy-based method for quantitative evaluation of skin pores after the treatment with 2 940 nm Er pixel laser showed highly consistent results with the standard photograph method, which can be further verified and popularized in the evaluation of enlarged skin pores.

Key words: Dermoscopy, Image processing, computer?assisted, Laser therapy, Skin pore widening