CT-derived spatial intratumoural heterogeneity and KRAS mutation status in a predominantly lung adenocarcinoma cohort: an exploratory study of association and incremental discrimination

Abstract Background To assess whether CT-derived spatial intratumoural heterogeneity (ITH) is associated with KRAS mutation status after accounting for tumour burden and clinical covariates, and whether it adds predictive information beyond clinical and volume-based reference models. Methods In this retrospective single-centre study, 271 candidate records from an intentionally KRAS-enriched cohort underwent final eligibility review; after excluding 71 patients, 200 were included (101 KRAS-positive, 99 KRAS-negative), and the original 140/60 train–test split was preserved without re-partitioning. Separate 2D and 3D ITHscore associations were assessed with adjustment for log2 tumour volume, T category, age, sex and smoking history, with restricted and overlap-weighted sensitivity analyses. Six logistic-regression reference models were fitted in the training cohort and compared using paired bootstrap confidence intervals in the previously examined internal-test partition. Results Tumour volume correlated strongly with both ITH scores (Spearman ρ = 0.658 for 2D and 0.679 for 3D). Fully adjusted odds ratios per SD increase were 3.84 (95% CI, 2.23–6.59) for the 2D score and 3.45 (95% CI, 1.98–6.00) for the 3D score. Within the overlapping tumour-volume range ( n = 102) the estimates attenuated to 2.39 (95% CI, 1.14–5.00) for 2D and 2.28 (95% CI, 0.999–5.22) for 3D, whereas under overlap weighting, which balanced the modelled covariates to absolute standardised mean differences below 0.001, they were 3.94 (95% CI, 2.53–10.91) and 3.07 (95% CI, 1.96–6.57). Attenuation occurred but the association did not disappear; the restricted cohorts were not matched, however, and residual imbalance in sex and smoking history persisted. The clinical-plus-volume model achieved an internal-test AUC of 0.844 (95% CI, 0.726–0.941), versus 0.833 (95% CI, 0.725–0.925) after adding both ITH scores; the paired ΔAUC was −0.011 (95% CI, −0.099 to 0.077). Conclusions Spatial ITH was associated with KRAS mutation status after adjustment for measured covariates. Estimates attenuated within the overlapping tumour-volume range (2D, 2.39; 3D, 2.28) but persisted under overlap weighting (2D, 3.94; 3D, 3.07), so independence from measured tumour burden was neither confirmed nor excluded. Incremental discrimination beyond clinical and volume-based references was not established. These exploratory findings do not establish molecular specificity or clinical utility and require validation in representative external cohorts.

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Journal
BMC Medical Imaging
Published
2026-10-17
DOI
https://doi.org/10.1186/s12880-026-02962-4
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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article
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article

CT-derived spatial intratumoural heterogeneity and KRAS mutation status in a predominantly lung adenocarcinoma cohort: an exploratory study of association and incremental discrimination

Lihao Wu, Rou Su, Peng Changyu, Liping Zhang et al.
BMC Medical Imaging
Radiomics and Machine Learning in Medical Imaging
article

CT-derived spatial intratumoural heterogeneity and KRAS mutation status in a predominantly lung adenocarcinoma cohort: an exploratory study of association and incremental discrimination

Lihao Wu, Rou Su, Peng Changyu, Liping Zhang, Yongjie Zhou, Lifeng Li, Fan Xu, Zheng Rao, Haijun Li, Dechang Peng, Xiang Liu
article en

Abstract

Abstract Background To assess whether CT-derived spatial intratumoural heterogeneity (ITH) is associated with KRAS mutation status after accounting for tumour burden and clinical covariates, and whether it adds predictive information beyond clinical and volume-based reference models. Methods In this retrospective single-centre study, 271 candidate records from an intentionally KRAS-enriched cohort underwent final eligibility review; after excluding 71 patients, 200 were included (101 KRAS-positive, 99 KRAS-negative), and the original 140/60 train–test split was preserved without re-partitioning. Separate 2D and 3D ITHscore associations were assessed with adjustment for log2 tumour volume, T category, age, sex and smoking history, with restricted and overlap-weighted sensitivity analyses. Six logistic-regression reference models were fitted in the training cohort and compared using paired bootstrap confidence intervals in the previously examined internal-test partition. Results Tumour volume correlated strongly with both ITH scores (Spearman ρ = 0.658 for 2D and 0.679 for 3D). Fully adjusted odds ratios per SD increase were 3.84 (95% CI, 2.23–6.59) for the 2D score and 3.45 (95% CI, 1.98–6.00) for the 3D score. Within the overlapping tumour-volume range ( n = 102) the estimates attenuated to 2.39 (95% CI, 1.14–5.00) for 2D and 2.28 (95% CI, 0.999–5.22) for 3D, whereas under overlap weighting, which balanced the modelled covariates to absolute standardised mean differences below 0.001, they were 3.94 (95% CI, 2.53–10.91) and 3.07 (95% CI, 1.96–6.57). Attenuation occurred but the association did not disappear; the restricted cohorts were not matched, however, and residual imbalance in sex and smoking history persisted. The clinical-plus-volume model achieved an internal-test AUC of 0.844 (95% CI, 0.726–0.941), versus 0.833 (95% CI, 0.725–0.925) after adding both ITH scores; the paired ΔAUC was −0.011 (95% CI, −0.099 to 0.077). Conclusions Spatial ITH was associated with KRAS mutation status after adjustment for measured covariates. Estimates attenuated within the overlapping tumour-volume range (2D, 2.39; 3D, 2.28) but persisted under overlap weighting (2D, 3.94; 3D, 3.07), so independence from measured tumour burden was neither confirmed nor excluded. Incremental discrimination beyond clinical and volume-based references was not established. These exploratory findings do not establish molecular specificity or clinical utility and require validation in representative external cohorts.

BMC Medical Imaging
Nanchang University (CN), Changsha Medical University (CN), Durham University (GB), First Affiliated Hospital of Jiangxi Medical College (CN), Jiangxi Provincial Cancer Hospital (CN), First Affiliated Hospital of Nanchang University (CN)
Good health and well-being
Openalex Percentile: Top 13%
Radiomics and Machine Learning in Medical Imaging
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