Division of Dermatopathology, Department of Pathology, Loyola University Medical Center, Maywood, Illinois, USA, USA.
479th Flying Training Group, Aviation Medicine Department, Naval Hospital Pensacola, Pensacola, Florida, USA, USA.
J Cutan Pathol. 2020 Aug;47(8):675-680. doi: 10.1111/cup.13681. Epub 2020 Mar 30.
Objective methods for distinguishing melanoma in situ (MIS) from photodamaged skin (PS) are needed to guide treatment in patients with melanocytic proliferations. Melanocyte density (MD) could serve as an objective histopathological criterion in difficult cases. Calculating MD via manual cell counts (MCC) with immunohistochemical (IHC)-stained slides has been previously published. However, the clinical application of this method is questionable, as quantification of MD via MCC on difficult cases is time consuming, especially in high volume practices.
ImageJ is an image processing software that uses scanned slide images to determine cell count. In this study, we compared MCC to ImageJ calculated MD in microphthalmia transcription factor-IHC stained MIS biopsies and control PS acquired from the same patients.
We found a statistically significant difference in MD between PS and MIS as measured by both MCC and ImageJ software (P < 0.01). Additionally, no statistically significant difference was found when comparing MD measurements recorded by ImageJ vs those determined by the MCC method.
MD as determined by ImageJ strongly correlates with the MD calculated by MCC. We propose the use of ImageJ as a time-efficient, objective, and reproducible tool to assess MD.
需要客观的方法来区分原位黑色素瘤(MIS)和光损伤皮肤(PS),以便为有黑色素细胞增生的患者提供治疗指导。黑色素细胞密度(MD)可以作为困难情况下的客观组织病理学标准。通过免疫组化(IHC)染色切片的手动细胞计数(MCC)计算 MD 已被先前报道。然而,这种方法的临床应用存在疑问,因为在困难病例中通过 MCC 对 MD 进行定量既耗时又耗力,尤其是在工作量大的情况下。
ImageJ 是一种图像处理软件,它使用扫描的幻灯片图像来确定细胞计数。在这项研究中,我们比较了 MCC 与 ImageJ 计算的小眼畸形转录因子-IHC 染色的 MIS 活检和从同一患者获得的对照 PS 中的 MD。
我们发现通过 MCC 和 ImageJ 软件测量的 PS 和 MIS 之间的 MD 存在统计学差异(P < 0.01)。此外,当比较 ImageJ 记录的 MD 测量值与 MCC 方法确定的 MD 测量值时,没有发现统计学差异。
ImageJ 确定的 MD 与通过 MCC 计算的 MD 具有很强的相关性。我们建议使用 ImageJ 作为一种高效、客观和可重复的工具来评估 MD。