ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2017
Multiparametric evaluation of preoperative MRI in early stage breast cancer: prognostic impact of peri-tumoral fat.
Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- CT-based variables of perirenal fat are risk factors for assessing pathological T-stage in patients with clear cell renal cell carcinoma.Annals of medicine · 2026Article
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- How Radiomics Can Improve Breast Cancer Diagnosis and Treatment.Journal of clinical medicine · 2023Review
- Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine.Cancers · 2022Review
- MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer.European radiology · 2022Article
- Clinical Significance of Peritumoral Adipose Tissue PET/CT Imaging Features for Predicting Axillary Lymph Node Metastasis in Patients with Breast Cancer.Journal of personalized medicine · 2021Article
- Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre- and early treatment predicts pathologic complete response.Biomedical engineering online · 2021Article
- Radiogenomics in brain, breast, and lung cancer: opportunities and challenges.Journal of medical imaging (Bellingham, Wash.) · 2021Review
- Machine Learning Based on Multi-Parametric MRI to Predict Risk of Breast Cancer.Frontiers in oncology · 2021Article
- Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms.Journal of oncology · 2021Review
- The role of ectopic adipose tissue: benefit or deleterious overflow?European journal of clinical nutrition · 2021Review
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- Will traditional biopsy be substituted by radiomics and liquid biopsy for breast cancer diagnosis and characterisation?Medical oncology (Northwood, London, England) · 2020Review
- Radiomics for radiation oncologists: are we ready to go?BJR open · 2020Review
- Article
- Quantitative analysis of peri-tumor fat in different molecular subtypes of breast cancer.Magnetic resonance imaging · 2018Article
- Correlation between obesity and fat-infiltrated axillary lymph nodes visualized on mammography.The British journal of radiology · 2018Article
- The crucial role of multiomic approach in cancer research and clinically relevant outcomes.The EPMA journal · 2018Review
- A New Challenge for Radiologists: Radiomics in Breast Cancer.BioMed research international · 2018Review
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeObesity is associated with adverse outcomes in breast cancer patients. Fat-specific cytokines (adipokines) have been proposed as key drivers of breast cancer progression, invasion, and metastasis. We aimed at assessing correlations between peri-tumoral fat, quantified on magnetic resonance imaging (MRI) and pathologic factors potentially impacting therapy recommendations.
methodsWe retrospectively reviewed records of 63 patients with early stage breast cancer who underwent preoperative MRI imaging using appropriately weighted series for breast and tumor contouring. Fat volumes were generated through voxel intensity filtering. The peri-tumoral region was defined as the intersection of a 1-cm spherical extension around the tumor and the breast contour. Peri-tumoral fat was defined as the fraction of a fat content in this volume. Surgical pathology records were used to extract clinical data. Statistical analyses were conducted using Pearson and Spearman correlation coefficients.
resultsAmong reviewed patients, 45 had T1 tumors (1.22 ± 0.85 cm diameter) and 18 had T2 tumors (2.08 ± 1.06 cm). Axillary lymph nodes were dissected in 31 and positive in 17 patients analyzed. Peri-tumoral fat ratio ranged between 25 and 99 %. Peri-tumoral fat ratio significantly correlated with the nodal-positive ratio of positive axillary lymph nodes (r = 0.532). Peri-tumoral fat ratio demonstrated optimally prominent correlation among obese patients upon body mass index categorical stratification.
conclusionsIn women with early stage breast cancer, peri-tumoral fat correlates positively with the ratio of pathologically involved axillary nodes. This work highlights a novel method for quantitating peri-tumoral fat content. Preoperative breast MRI may be utilized to predict extent of axillary disease.
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