Literature DB >> 30729924

Clinimetric analysis of recently applied quantitative tools in evaluation of vitiligo treatment.

Nancy Wadea Mikhael1, Hanan Hasan Sabry1, Asmaa M El-Refaey1, Rehab Mohammed Salem1, Mahmoud Fawzi El-Gendy2, Shaymaa Ahmed Farid3.   

Abstract

BACKGROUND: Vitiligo affects about 1% of the world's population, however, there is currently no universally used standardized measure to assess its response to treatment.
OBJECTIVE: To find the most effective technique for the quantitative assessment of therapeutic results in vitiligo patients.
MATERIALS AND METHODS: The study was performed in three stages: (1) Conducting an adapted Delphi survey to check current dermatologists' attitudes regarding the topic of study. (2) Conducting a pilot study that involves testing the selected digital image analysis software in the laboratory to validate future tasks. (3) The chief clinimetric study that implicates selecting actual vitiligo lesion models and evaluating them.
RESULTS: Regarding the surface area measuring techniques, the most accurate results were gained through the digital image analysis for surface area, followed by point-counting technique. The digital image analysis for color measurement was accurate and reliable in getting a percentage representation of color improvement within the vitiligo lesions, in response to therapy. LIMITATIONS: Many dermatologists lack understanding of basic concepts about imaging techniques. The study does not include a traditional assessment method such as vitiligo area scoring index.
CONCLUSION: Our designated digital image analysis technique was able to efficiently assess the changes that occur both on surface area and the color of vitiligo lesions in response to therapy.

Entities:  

Keywords:  Assessment; digital image analysis; surface area; vitiligo

Mesh:

Substances:

Year:  2019        PMID: 30729924     DOI: 10.4103/ijdvl.IJDVL_63_17

Source DB:  PubMed          Journal:  Indian J Dermatol Venereol Leprol        ISSN: 0378-6323            Impact factor:   2.545


  2 in total

1.  A deep learning-based hybrid artificial intelligence model for the detection and severity assessment of vitiligo lesions.

Authors:  Lifang Guo; Yin Yang; Hui Ding; Huiying Zheng; Hedan Yang; Junxiang Xie; Yong Li; Tong Lin; Yiping Ge
Journal:  Ann Transl Med       Date:  2022-05

Review 2.  Mechanisms of melanocyte death in vitiligo.

Authors:  Jianru Chen; Shuli Li; Chunying Li
Journal:  Med Res Rev       Date:  2020-11-17       Impact factor: 12.944

  2 in total

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