文章：

整合空间与形态特征于黑色素瘤预后评估：一种计算方法

Integrating Spatial and Morphological Characteristics into Melanoma Prognosis: A Computational Approach

原文发布日期：27 May 2024

DOI: 10.3390/cancers16112026

类型: Article

开放获取: 是

英文摘要：

In this study, the prognostic value of cellular morphology and spatial configurations in melanoma has been examined, aiming to complement traditional prognostic indicators like mitotic activity and tumor thickness. Through a computational pipeline using machine learning and deep learning methods, we quantified nuclei sizes within different spatial regions and analyzed their prognostic significance using univariate and multivariate Cox models. Nuclei sizes in the invasive band demonstrated a significant hazard ratio (HR) of 1.1 (95% CI: 1.03, 1.18). Similarly, the nuclei sizes of tumor cells and Ki67 S100 co-positive cells in the invasive band achieved HRs of 1.07 (95% CI: 1.02, 1.13) and 1.09 (95% CI: 1.04, 1.16), respectively. Our findings reveal that nuclei sizes, particularly in the invasive band, are potentially prognostic factors. Correlation analyses further demonstrated a meaningful relationship between cellular morphology and tumor progression, notably showing that nuclei size within the invasive band correlates substantially with tumor thickness. These results suggest the potential of integrating spatial and morphological analyses into melanoma prognostication.

摘要翻译： 

本研究探讨了黑色素瘤中细胞形态与空间构型的预后价值，旨在补充传统预后指标（如有丝分裂活性和肿瘤厚度）的不足。通过采用机器学习和深度学习方法构建的计算流程，我们量化了不同空间区域内细胞核的大小，并利用单变量及多变量Cox模型分析了其预后意义。结果显示，浸润带内细胞核大小具有显著的风险比（HR=1.1，95%置信区间：1.03-1.18）。同样，浸润带内肿瘤细胞及Ki67/S100双阳性细胞的细胞核大小分别达到风险比1.07（95%置信区间：1.02-1.13）和1.09（95%置信区间：1.04-1.16）。我们的研究结果表明，细胞核大小（尤其在浸润带内）可能成为潜在的预后因素。相关性分析进一步揭示了细胞形态与肿瘤进展之间存在显著关联，特别指出浸润带内细胞核大小与肿瘤厚度具有实质性相关。这些发现提示，将空间与形态学分析整合到黑色素瘤预后评估中具有重要潜力。

原文链接：

Integrating Spatial and Morphological Characteristics into Melanoma Prognosis: A Computational Approach