Reproducibility of the radiosensitivity index and failure of CT radiomics as its surrogate: a public-data study in non-small cell lung cancer.

Purpose. The radiosensitivity index (RSI) and genomic-adjusted radiation dose (GARD) are increasingly treated as quantitative inputs to radiotherapy dose calculation. Two reproducibility issues bear on this use: whether CT radiomics can non-invasively recover RSI, and whether one coefficient of the equation is uniquely specified (printed CDK1 but implemented as PAK2). We examine both on public data. Methods. In GEO GSE103584 RNA-seq (n = 130 non-small cell lung cancer [NSCLC]), we recomputed RSI with the Eschrich 2009 coefficients using CDK1 or PAK2 in the disputed slot and derived GARD under four fixed dose/fractionation schemas. In the paired TCIA NSCLC-Radiogenomics cohort (n = 117), we trained cross-validated Elastic Net and Random Forest models to predict continuous RSI and a median-split RSI label from IBSI-conformant, scanner-corrected CT radiomic features, under a pre-set viability rule. Results. CT radiomics did not recover RSI (Spearman rho = 0.05 and 0.03; binary AUC = 0.43), below the pre-set viability threshold. Separately, the two probesets listed for the disputed coefficient in the founding paper's Table 3 both map to PAK2; using the printed CDK1 left rank correlation high (rho = 0.980) but reclassified 6.2% and 9.2% of patients (median and tertile) and shifted GARD by 4.1 to 6.3 Gy. Conclusions. CT radiomics is not a viable RSI surrogate in this public cohort, so imaging-GARD should not assume radiomic recovery of RSI. The disputed coefficient resolves to PAK2; implementing the printed CDK1 shifts GARD and reclassifies patients despite high rank correlation. Outcome-directed, dose-adjusted imaging is the more defensible next step.