Loading
Life sciences · Journal article
Scientific Reports · October 9, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Journal article.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
Gastric-type adenocarcinoma (GAS) of the cervix is usually diagnosed at advanced stages and has a poor prognosis due to resistance to standard therapies. Tumor-infiltrating lymphocytes (TILs) are an important component of the tumor immune microenvironment (TME) and have been associated with prognosis across multiple cancer types. Histopathological assessment of GAS is challenging because it often arises in the upper cervix. This study aimed to explore the association between MRI-based radiomics features and the TME in GAS. We enrolled 16 patients with GAS treated at our institution. TILs were evaluated by immunohistochemistry, quantifying them with the modified Immunoscore (mIS). Fourteen patients with usual endocervical adenocarcinoma (UEA) served as controls. A total of 1,302 radiomic features were extracted from each primary tumor and peritumoral region on each pre-treatment MRI image. After feature selection within leave-one-out cross-validation (LOOCV), regression models were developed to predict the TME in GAS, followed by exploratory clustering of the mIS groups. GAS exhibited significantly lower T-cell infiltration than UEA, particularly in early-stage tumors. The regression model showed a correlation with observed TIL densities in the full cohort ( r = 0.87, P < 0.001); however, LOOCV showed limited out-of-sample performance ( r = 0.36). Exploratory full-cohort clustering showed 81.3% concordance with the mIS groups (low vs. intermediate-to-high). These findings may provide a basis for the future development of MRI-based radiomic models for assessing the TME in GAS.