1. Integrating Spatial and Morphological Characteristics into Melanoma Prognosis: A Computational Approach.
- Author
-
Bian, Chang, Ashton, Garry, Grant, Megan, Rodriguez, Valeria Pavet, Martin, Isabel Peset, Tsakiroglou, Anna Maria, Cook, Martin, and Fergie, Martin
- Subjects
- *
MELANOMA prognosis , *RESEARCH funding , *MULTIVARIATE analysis , *DESCRIPTIVE statistics , *STATISTICS , *MACHINE learning , *CONFIDENCE intervals , *CELLS , *DISEASE progression - Abstract
Simple Summary: Spatial characteristics, including cell morphology and spatial distribution patterns, hold potential prognostic value in melanoma. This study builds on existing research by exploring these spatial factors through a computational pipeline, including both univariate and multivariate Cox proportional hazards models, supplemented by rigorous cross-validation techniques. Our findings reveal that spatial and morphological features can potentially enhance the prognostication of melanoma, supporting their integration into standard prognostic models. We also discuss potential limitations and outline directions for future research. 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. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF