Treatment of Porphyria Cutanea Tarda Scarring With Combination Laser Treatment and a Pilot Use of Artificial Intelligence to Quantify Laser Results

IF 2.3 4区医学 Q2 DERMATOLOGY

Journal of Cosmetic Dermatology Pub Date : 2025-04-01 DOI:10.1111/jocd.70056

Chelsea E. Kesty, Katarina R. Kesty

{"title":"Treatment of Porphyria Cutanea Tarda Scarring With Combination Laser Treatment and a Pilot Use of Artificial Intelligence to Quantify Laser Results","authors":"Chelsea E. Kesty, Katarina R. Kesty","doi":"10.1111/jocd.70056","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Porphyria cutanea tarda (PCT) is the most common subtype of porphyria and results from a deficiency of the enzyme uroporphyrinogen decarboxylase. Even after successful treatment, patients can be left with significant scarring, and there is little published data on the safety and efficacy of light-based or laser-based therapies.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>This report examines a case of a 47-year-old male with PCT secondary to HCV, treated with a combination of fractionated erbium-doped yttrium-aluminum-garnet (Er:YAG), intense pulsed light (IPL), and carbon dioxide (CO<sub>2</sub>) lasers to address significant scarring and residual skin damage. An artificial intelligence model was used to quantify the results of the laser procedures.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>After combination laser treatment, the patient exhibited marked improvements in skin texture, reduction in scar visibility, and diminished hyperpigmentation. The artificial intelligence algorithm quantified the laser results and showed improvements in the scores used in the large language model.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>In this patient, customizing a combination of lasers to target different layers of the skin to achieve comprehensive improvement: erbium primarily addressed superficial irregularities and pigmentation, while CO<sub>2</sub> promoted deeper collagen remodeling. The use of artificial intelligence to quantify the positive results in this case is in line with the clinical evaluations and photos.</p>\n </section>\n </div>","PeriodicalId":15546,"journal":{"name":"Journal of Cosmetic Dermatology","volume":"24 4","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jocd.70056","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cosmetic Dermatology","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jocd.70056","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"DERMATOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Background

Porphyria cutanea tarda (PCT) is the most common subtype of porphyria and results from a deficiency of the enzyme uroporphyrinogen decarboxylase. Even after successful treatment, patients can be left with significant scarring, and there is little published data on the safety and efficacy of light-based or laser-based therapies.

Methods

This report examines a case of a 47-year-old male with PCT secondary to HCV, treated with a combination of fractionated erbium-doped yttrium-aluminum-garnet (Er:YAG), intense pulsed light (IPL), and carbon dioxide (CO₂) lasers to address significant scarring and residual skin damage. An artificial intelligence model was used to quantify the results of the laser procedures.

Results

After combination laser treatment, the patient exhibited marked improvements in skin texture, reduction in scar visibility, and diminished hyperpigmentation. The artificial intelligence algorithm quantified the laser results and showed improvements in the scores used in the large language model.

Conclusion

In this patient, customizing a combination of lasers to target different layers of the skin to achieve comprehensive improvement: erbium primarily addressed superficial irregularities and pigmentation, while CO₂ promoted deeper collagen remodeling. The use of artificial intelligence to quantify the positive results in this case is in line with the clinical evaluations and photos.

Abstract Image

查看原文本刊更多论文

联合激光治疗迟发性皮肤卟啉症瘢痕及人工智能量化激光结果的试点应用

背景：迟发性皮肤卟啉症（PCT）是卟啉症中最常见的亚型，是由酶-尿卟啉原脱羧酶缺乏引起的。即使在成功治疗后，患者也可能留下明显的疤痕，而且关于光基或激光治疗的安全性和有效性的公开数据很少。方法：本报告报告了一例47岁男性继发于HCV的PCT，采用掺铒钇铝石榴石（Er:YAG）、强脉冲光（IPL）和二氧化碳（CO2）激光联合治疗，以解决显著的疤痕和残留的皮肤损伤。人工智能模型被用来量化激光手术的结果。结果经激光联合治疗后，患者皮肤质地明显改善，瘢痕可见性降低，色素沉着减轻。人工智能算法量化了激光结果，并显示了在大型语言模型中使用的分数的改进。在该患者中，针对不同皮肤层定制激光组合以实现全面改善：铒主要解决表面不规则和色素沉着，而CO2促进深层胶原重塑。使用人工智能量化本病例的阳性结果与临床评估和照片一致。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Cosmetic Dermatology DERMATOLOGY-

CiteScore

4.30

自引率

13.00%

发文量

818

审稿时长

>12 weeks

期刊介绍： The Journal of Cosmetic Dermatology publishes high quality, peer-reviewed articles on all aspects of cosmetic dermatology with the aim to foster the highest standards of patient care in cosmetic dermatology. Published quarterly, the Journal of Cosmetic Dermatology facilitates continuing professional development and provides a forum for the exchange of scientific research and innovative techniques. The scope of coverage includes, but will not be limited to: healthy skin; skin maintenance; ageing skin; photodamage and photoprotection; rejuvenation; biochemistry, endocrinology and neuroimmunology of healthy skin; imaging; skin measurement; quality of life; skin types; sensitive skin; rosacea and acne; sebum; sweat; fat; phlebology; hair conservation, restoration and removal; nails and nail surgery; pigment; psychological and medicolegal issues; retinoids; cosmetic chemistry; dermopharmacy; cosmeceuticals; toiletries; striae; cellulite; cosmetic dermatological surgery; blepharoplasty; liposuction; surgical complications; botulinum; fillers, peels and dermabrasion; local and tumescent anaesthesia; electrosurgery; lasers, including laser physics, laser research and safety, vascular lasers, pigment lasers, hair removal lasers, tattoo removal lasers, resurfacing lasers, dermal remodelling lasers and laser complications.