Efficacy, Safety, and Predictive Value of Quantitative Histopathology in Picosecond Laser Therapy for Congenital Melanocytic Nevi: A Prospective Clinical Trial

Vollständiger Abstract

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ABSTRACT In this single‐arm prospective study, we evaluated the efficacy and safety of a 1064/532‐nm Nd:YAG picosecond laser for congenital melanocytic nevi (CMN) and investigated the association between clinical response and quantitative histopathologic findings. Thirteen Japanese patients with a median age of 4 years were enrolled and received up to five laser treatment sessions at 1‐ to 3‐month intervals. Clinical efficacy was primarily assessed using the Investigator Global Assessment (IGA) score at 3 months after treatment, supplemented by Melanin Index analysis and ImageJ‐based histopathologic quantification of nevus cell area fraction and melanin distribution. At the 3‐month follow‐up, 30.8% of patients achieved an IGA score of 5 (≥ 75% improvement), and 84.6% achieved an IGA score of 4 (50%–74% improvement) or higher. The Melanin Index decreased significantly ( p < 0.001); at 1 year, the group‐level mean remained significantly below baseline, although 3 of 13 patients had values above baseline. Histopathologic analysis showed a strong negative correlation between IGA score and nevus cell area fraction ( ρ = −0.849, p = 0.0002). In an exploratory multivariable analysis, nevus cell area fraction remained significantly associated with clinical outcome, whereas peak cumulative mean melanin area fraction was not. All participants experienced transient local treatment‐related adverse events; however, these resolved by the 3‐month follow‐up without treatment discontinuation or irreversible sequelae. These findings suggest that picosecond laser therapy may be a safe and effective minimally invasive treatment option for CMN and that clinical responsiveness may be more closely associated with nevus cell burden than with the depth‐related melanin distribution parameter. Pretreatment histopathologic evaluation of nevus cell area fraction may therefore be useful for predicting clinical response.