用于评估肝细胞癌中 TIL（肿瘤浸润淋巴细胞）的 MRI 组织匹配分析

Tumor-infiltrating lymphocytes (TILs) play critical roles in the tumor microenvironment and immunotherapy response.

This study aims to explore the feasibility of multi-parametric magnetic resonance imaging (MRI) in evaluating TILs and to develop an evaluation model that considers spatial heterogeneity. Multi-parametric MRI was performed on hepatocellular carcinoma (HCC) mice (N = 28). Three-dimensional (3D) printing was employed for tissue sampling, to match the multi-parametric MRI data with tumor tissues, followed by flow cytometry analysis and next-generation RNA-sequencing. Pearson's correlation, multivariate logistic regression, and receiver operating characteristic (ROC) curve analyses were utilized to model TIL-related MRI parameters.

MRI quantitative parameters, including T1 relaxation times and perfusion, were correlated with the infiltration of leukocytes, T-cells, CD4+ T-cells, CD8+ T-cells, PD1 + CD8+ T-cells, B-cells, macrophages, and regulatory T-cells (correlation coefficients ranged from -0. 656 to 0. 482, p <. 05) in tumor tissues. TILs were clustered into inflamed and non-inflamed subclasses, with the proportion of T-cells, CD8+ T-cells, and PD1 + CD8+ T-cells significantly higher in the inflamed group compared to the non-inflamed group (43.

37% vs. 25. 45%, 50. 83% vs. 34. 90%, 40. 45% vs. 29. 47%, respectively; p <. 001). The TIL evaluation model, based on the Z-score combining Kep and T1post, was able to distinguish between these subgroups, yielding an area under the curve of 0. 816 (95% confidence interval 0. 721-0. 910) and a cut-off value of -0. 03 (sensitivity 68. 4%, specificity 91. 3%).

Additionally, the Z-score was related to the gene expression of T-cell activation, chemokine production, and cell adhesion. The tissue-matched analysis of multi-parametric MRI offers a feasible method of regional evaluation and can distinguish between TIL subclasses.