ArticlePloS one2014
Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 3 of them syntheses that pooled it.
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93 citing papers in PubMed, 3 syntheses or guidelines pooled it, 151 citations in OpenAlex.
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- Joint EANM-SNMMI guideline on the role of 2-[European journal of nuclear medicine and molecular imaging · 2024Guideline
- PET-Derived Radiomics and Artificial Intelligence in Breast Cancer: A Systematic Review.International journal of molecular sciences · 2022Pooled it
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- The Future of Quantitative Breast Imaging: Integrated to Integral Imaging Biomarkers for Precision Cancer Care, From theAJR. American journal of roentgenology · 2026Review
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- Progress in monitoring molecular, cellular and metabolic dynamics using mass spectrometry imaging.Bioanalysis · 2025Review
- Elucidation of FDG-PET Imaging Characteristics that Reflect the Heterogeneity within Tumors Due to Variability in Metabolic Activity: A Phantom Study.World journal of nuclear medicine · 2025Article
- Clinicopathologic and metabolic variables fromAnnals of nuclear medicine · 2025Article
- Validation of Clinical Dynamic Contrast-Enhanced Magnetic Resonance Imaging Perfusion Modeling and Neoadjuvant Chemotherapy Response Prediction in Breast Cancer UsingJCO clinical cancer informatics · 2025Article
- Baseline [European journal of nuclear medicine and molecular imaging · 2024Article
- PET Molecular Imaging in Breast Cancer: Current Applications and Future Perspectives.Journal of clinical medicine · 2024Review
- The current role of nuclear medicine in breast cancer.The British journal of radiology · 2023Review
- Prediction of pathological response after neoadjuvant chemotherapy using baseline FDG PET heterogeneity features in breast cancer.The British journal of radiology · 2023Review
- Evaluation of functional and metabolic tumor volume using voxel-wise analysis in childhood rhabdomyosarcoma.Pediatric radiology · 2023Article
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7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is currently little support to understand which pathological factors led to differences in tumor texture as measured from FDG PET/CT images. We studied whether tumor heterogeneity measured using texture analysis in FDG-PET/CT images is correlated with pathological prognostic factors in invasive breast cancer.
methodsFifty-four patients with locally advanced breast cancer who had an initial FDG-PET/CT were retrospectively included. In addition to SUVmax, three robust textural indices extracted from 3D matrices: High-Gray-level Run Emphasis (HGRE), Entropy and Homogeneity were studied. Univariate and multivariate logistic regression was used to identify PET parameters associated with poor prognosis pathological factors: hormone receptor negativity, presence of HER-2 and triple negative phenotype. Receiver operating characteristic (ROC) curves and the (AUC) analysis, and reclassification measures, were performed in order to evaluate the performance of combining texture analysis and SUVmax for characterizing breast tumors.
resultsTumor heterogeneity, measured with HGRE, was higher in negative estrogen receptor (p = 0.039) and negative progesterone receptor tumors (p = 0.036), and in Scarff-Bloom-Richardson grade 3 tumors (p = 0.047). None of the PET indices could identify HER-2 positive tumors. Only SUVmax was positively correlated with Ki-67 (p<0.0004). Triple negative breast cancer (TNBC) exhibited higher SUVmax (Odd Ratio = 1.22, 95%CI [1.06-1.39],p = 0.004), lower Homogeneity (OR = 3.57[0.98-12.5],p = 0.05) and higher HGRE (OR = 8.06[1.88-34.51],p = 0.005) than non-TNBC. Multivariate analysis showed that HGRE remained associated with TNBC (OR = 5.27[1.12-1.38],p = 0.03) after adjustment for SUVmax. Combining SUVmax and HGRE yielded in higher area under the ROC curves (AUC) than SUVmax for identifying TNBC: AUC = 0.83 and 0.77, respectively. Probability of correct classification also increased in 77% (10/13) of TNBC and 71% (29/41) of non-TNBC (p = 0.003), when combining SUVmax and HGRE.
conclusionsTumor heterogeneity measured on FDG-PET/CT was higher in invasive breast cancer with poor prognosis pathological factors. Texture analysis might be used, in addition to SUVmax, as a new tool to assess invasive breast cancer aggressiveness.
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