Tumour Nuclear Morphometrics Predict Survival in Lung Adenocarcinoma

Providing a quantitative assessment of tumour nuclei would improve decision objectivity and overcome inter and intra-observer variation. In this study, we show that the summary statistics for the whole slide image of nuclear pleomorphism can provide such quantification. We characterise the heterogeneity of lung adenocarcinoma (LUAD) using morphometric features of tumour nuclei. The Cox proportional hazard regression model is employed on a dataset of 78 patients to find the top discriminative features such that there is a strong correlation with patient survival. We find that global nuclear morphometric features, characterised by heatmap statistics, have a significant correlation with overall survival in LUAD (p < 0.0003).

Automated summary

The study demonstrates that global nuclear morphometric features show significant correlation with overall survival in lung adenocarcinoma (LUAD), providing insight into quantitative assessment of tumour nuclei. Using Cox proportional hazard regression model on a dataset of 78 patients, top discriminative features associated with patient survival were identified through heatmap statistics, highlighting the potential for improved decision objectivity in cancer diagnosis.