Baseline splenic volume as a biomarker for clinical outcome and circulating lymphocyte count in gastric cancer

Systemic immune-related spleen radiomics predict progression-free survival in patients with locally advanced cervical cancer underwent definitive chemoradiotherapy

PURPOSE

Systemic immunity is essential for driving therapeutically induced antitumor immune responses, and the spleen may reflect alterations in systemic immunity. This study aimed to evaluate the predictive value of contrast-enhanced CT-based spleen radiomics for progression-free survival (PFS) in patients with locally advanced cervical cancer (LACC) who underwent definitive chemoradiotherapy (dCRT). Additionally, we investigated the role of spleen radiomics features and changes in spleen volume in assessing systemic immunity.

METHODS

This retrospective study included 257 patients with LACC who underwent dCRT. The patients were randomly divided into training and validation groups in a 7:3 ratio. Radiomic features were extracted from CT images obtained before and after dCRT. Radiomic scores (Radscore) were calculated using features selected through least absolute shrinkage and selection operator (LASSO) Cox regression. The percentage change in spleen volume was determined from measurements taken before and after treatment. Independent prognostic factors for PFS were identified through multivariate Cox regression analyses. Model performance was evaluated with the receiver operating characteristic (ROC) curve and the C-index. The Radscore cut-off value, determined from the ROC curve, was used to stratify patients into high- and low-risk survival groups. The Wilcoxon test was used to analyze differences in hematological parameters between different survival risk groups and between different spleen volume change groups. Spearman correlation analysis was used to explore the relationship between spleen volume change and hematological parameters.

RESULTS

Independent prognostic factors included FIGO stage, pre-treatment neutrophil-to-lymphocyte ratio (pre-NLR), spleen volume change, and Radscore. The radiomics-combined model demonstrated the best predictive performance for PFS in both the training group (AUC: 0.923, C-index: 0.884) and the validation group (AUC: 0.895, C-index: 0.834). Compared to the low-risk group, the high-risk group had higher pre-NLR (p = 0.0054) and post-NLR (p = 0.038). Additionally, compared to the decreased spleen volume group, the increased spleen volume group had lower post-NLR (p = 0.0059) and post-treatment platelet-to-lymphocyte ratio (p < 0.001).

CONCLUSION

Spleen radiomics combined with clinical features can effectively predict PFS in patients with LACC after dCRT. Furthermore, spleen radiomics features and changes in spleen volume can reflect alterations in systemic immunity.

The role of spleen radiomics model for predicting prognosis in esophageal squamous cell carcinoma patients receiving definitive radiotherapy

BACKGROUND

The spleen plays an important role in systemic antitumor immune response, but whether spleen imaging features have predictive effect for prognosis and immune status was unknown. The aim of this study was to investigate computed tomography (CT)-based spleen radiomics to predict the prognosis of patients with esophageal squamous cell carcinoma (ESCC) underwent definitive radiotherapy (dRT) and to try to find its association with systemic immunity.

METHODS

This retrospective study included 201 ESCC patients who received dRT. Patients were randomly divided into training (n = 142) and validation (n = 59) groups. The pre- and delta-radiomic features were extracted from enhanced CT images. LASSO-Cox regression was used to select the radiomics signatures most associated with progression-free survival (PFS) and overall survival (OS). Independent prognostic factors were identified by univariate and multivariate Cox analyses. The ROC curve and C-index were used to evaluate the predictive performance. Finally, the correlation between spleen radiomics and immune-related hematological parameters was analyzed by spearman correlation analysis.

RESULTS

Independent prognostic factors involved TNM stage, treatment regimen, tumor location, pre- or delta-Rad-score. The AUC of the delta-radiomics combined model was better than other models in the training and validation groups in predicting PFS (0.829 and 0.875, respectively) and OS (0.857 and 0.835, respectively). Furthermore, some spleen delta-radiomic features are significantly correlated with delta-ALC (absolute lymphocyte count) and delta-NLR (neutrophil-to-lymphocyte ratio).

CONCLUSIONS

Spleen radiomics is expected to be a useful noninvasive tool for predicting the prognosis and evaluating systemic immune status for ESCC patients underwent dRT.