Literature DB >> 34991831

Association of 18F-FDG PET/CT textural features with immunohistochemical characteristics in invasive ductal breast cancer.

Hasan Önner1, Nazim Coskun2, Mustafa Erol3, Meryem İlkay Eren Karanis3.   

Abstract

OBJECTıVES: This study investigates whether textural features (TFs) extracted from 18F-FDG positron emission tomography/computed tomography (PET/CT) are associated with immunohistochemical characteristics (IHCs) of invasive ductal breast carcinoma (IDBC).
MATERIALS AND METHODS: The relationship of TFs with IHCs [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2), Ki-67 proliferation index, and histological grades] from solely excised primary tumors were evaluated for a more accurate assessment. Therefore patients with early-stage IDBC who underwent pre-operative 18F-FDG PET/CT scan for staging were included in this retrospective study. The clinical staging was performed according to the 8th edition of the American Joint Committee on Cancer. Maximum standardized uptake value (SUVmax) and 37TFs of the primary tumor were extracted from 18F-FDG PET/CT. Spearman's rank correlation test was used to evaluate the correlation between TFs and SUVmax. Receiver operating characteristic curves were generated to define the diagnostic performance of each parameter. Among these parameters, those with the highest diagnostic performance were included in the multivariate logistic regression model to identify the independent predictors of histopathological characteristics.
RESULTS: A total of 124 patients were included. Histogram-uniformity, grey-level co-occurrence matrix (GLCM), GLCM-energy, and GLCM-homogeneity showed a strong negative correlation with SUVmax, while grey-level run-length matrix (GLRLM), GLRLM-SRHGE, grey-level zone length matrix (GLZLM), GLZLM-HGZE, GLRLM-HGRE, GLCM-entropy, GLCM-contrast, histogram-entropy, and GLCM-dissimilarity showed a strong positive correlation. Some of the TFs were independently associated with ER-negativity, PR-negativity, HER-2-positivity, and increased Ki-67 proliferation index (GLCM-contrast, GLZLM-GLNU, histogram-uniformity, and shape-sphericity respectively). While SUVmax had an independent association with high-grade and triple-negativity, GLZLM-SZLGE, a high-order TF that shows the distribution of the short homogeneous zones with low grey-levels, had an independent association with axillary lymph node metastasis.
CONCLUSIONS: ER-negative, PR-negative, HER-2-positive, triple-negative, high-grade, highly proliferative, and high-stage tumors were found to be more glycolytic and metabolically heterogeneous. These findings suggest that the use of TFs in addition to SUVmax may improve the prognostic value of 18F-FDG PET/CT in IDBC, as certain TFs were independently associated with many IHCs and predicted axillary lymph node involvement.
Copyright © 2020 Sociedad Española de Medicina Nuclear e Imagen Molecular. Published by Elsevier España, S.L.U. All rights reserved.

Entities:  

Keywords:  Breast cancer; Características de textura; Cáncer de mama; Fluoride-18 fluorodeoxyglucose; Fluoruro-18 Fluorodesoxiglucosa; Heterogeneidad tumoral; Positron emission tomography/Computed tomography; Textural features; Tomografía por emisión de positrones/tomografía computarizada; Tumor heterogeneity

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Year:  2021        PMID: 34991831     DOI: 10.1016/j.remnie.2020.12.009

Source DB:  PubMed          Journal:  Rev Esp Med Nucl Imagen Mol (Engl Ed)        ISSN: 2253-8089


  1 in total

1.  Development of High-Resolution Dedicated PET-Based Radiomics Machine Learning Model to Predict Axillary Lymph Node Status in Early-Stage Breast Cancer.

Authors:  Jingyi Cheng; Caiyue Ren; Guangyu Liu; Ruohong Shui; Yingjian Zhang; Junjie Li; Zhimin Shao
Journal:  Cancers (Basel)       Date:  2022-02-14       Impact factor: 6.639

  1 in total

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