Exploratory associations between regional immune-stromal features and 18F-FDG PET-derived metabolic heterogeneity in breast cancer
Makaleler > Tam Makale · 2026
Yazarlar: Berkay Çağdaş, Elif Kardelen Çağdaş
BMC Medical Imaging, Uluslararası, Wos, 2026
DOI: 10.1186/s12880-026-02789-z
Özet
Abstract Background The breast tumor microenvironment harbors spatially heterogeneous immune and stromal populations that may influence functional imaging. This exploratory study examined whether regional immune-stromal differences relate to 18 F-FDG PET-derived metabolic heterogeneity and radiomics phenotypes, and which metrics show the largest nominal correlations. Methods Retrospective study of 61 women with invasive breast carcinoma undergoing baseline 18F-FDG PET/CT. A pathologist blinded to PET annotated ten intratumoral regions (≥ 1 mm²) per case on whole-slide images; QuPath machine-learning classification quantified stromal tumor-infiltrating lymphocytes (sTILs) and fibroblast-like stromal cells (FLSC). The regions with numerically highest and lowest sTIL density were retained for paired analysis; values therefore represent the observed range, not a comprehensive spatial map. The H&E-based FLSC measurement was cross-checked against α-smooth muscle actin (α-SMA) immunohistochemistry in the same regions as a supporting measurement check. PET features comprised SUVmax, MTV, TLG, texture (GLCM, GLRLM, GLSZM) and heterogeneity indices (HI2, HI3; MTV30–MTV50 slope). Spearman correlation with Benjamini–Hochberg FDR correction was used. Results Of 270 correlations (nine immune-stromal endpoints × 30 PET features), 38 reached nominal significance ( p < 0.05), but none survived FDR correction within an endpoint (smallest q = 0.077) or study-wide (smallest q = 0.33). The largest coefficient was weak: |ρ|=0.379 (TIL-high region sTIL density vs. HI2; 95% CI 0.126–0.586; p = 0.0026). sTIL density correlated inversely with MTV (ρ=−0.29 to − 0.35) and positively with HI2; the TIL/FLSC ratio correlated with SUV parameters (largest ρ = 0.299, SUVmean). FLSC density and regional difference metrics were weaker. Across 122 paired regions, α-SMA-based stromal density agreed closely with the H&E-based measurement (ρ = 0.992; Lin CCC = 0.996), and reanalysis reproduced the same correlation profile ( r = 0.94–0.996). Excluding extreme densities or smallest regions, 9–24 of 38 associations persisted; after adjustment for T stage, Nottingham score, Ki-67 and subtype, 13 persisted. Conclusions This hypothesis-generating study presents a paired, region-level integration of machine-learning digital pathology with PET radiomics in breast cancer. Only weak nominal associations between regional immune-stromal composition and PET-derived metabolic heterogeneity were observed, and none remained significant after FDR correction. These findings require independent validation in larger, multi-institutional cohorts before any biological or clinical interpretation can be drawn.