Literature DB >> 30925542

Comparison of the volumetric and radiomics findings of 18F-FDG PET/CT images with immunohistochemical prognostic factors in local/locally advanced breast cancer.

Emine Acar1,2, Bülent Turgut1, Seyran Yiğit3, GamzeÇapa Kaya4.   

Abstract

OBJECTIVE: The aim of this study was to determine the change in volumetric and radiomics parameters of fluorine-18 fluorodeoxyglucose (F-FDG) PET/computed tomography (CT) imaging in local/locally advanced cancer patients according to immunohistochemical findings. PATIENTS AND METHODS: A total of 72 patients who were diagnosed with local/locally advanced breast cancer and then examined by F-FDG PET/CT for staging were included in this study. Immunohistochemical prognostic factors [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her-2), p53 mutation, Ki-67 proliferation index] and histological grades were determined. Standardized uptake value (SUV)-based, volume-based, and radiomics findings were obtained from F-FDG PET/CT images.
RESULTS: In cases of ER and PR negativity, Her-2 positivity, presence of the p53 mutation, and Ki-67 index of at least 20% patients, total volumetric parameters were significantly higher in paired comparisons. The results of the ER-negative group were significantly higher than those of ER-positive patients in GLRLM_GLNU, GLRLM_RLNU, GLZLM_GLNU, and GLZLM_ZLNU comparisons. In grade 3 patients, mean SUV, maximum SUV, and GLRLM_LRHGE values were higher than those of grade 2 patients. SUV and volumetric parameters were significantly higher in patients with Ki-67 index of at least 20% than those with less than 20%. Maximum SUV, breast tumor lesion glycolysis values, and entropy in nuclear polymorphism in the 3+ patient group were found to be higher compared with the 2+ patient group. Moreover, patients with mitosis 3+ had significantly higher breast metabolic tumor volume, breast tumor lesion glycolysis, and kurtosis values than the 1+ group.
CONCLUSION: ER negativity, triple negativity, high tumor grade, and high nuclear polymorphism were associated with tumor heterogeneity. With respect to ER negativity, PR negativity, high tumor grade, high mitosis number, high Ki-67 index, Her-2 positivity, and the presence of p53 mutation, an increased tumor load were observed. In addition to immunohistochemical parameters, the use of radiomics data is believed to contribute to breast cancer management.

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Year:  2019        PMID: 30925542     DOI: 10.1097/MNM.0000000000001019

Source DB:  PubMed          Journal:  Nucl Med Commun        ISSN: 0143-3636            Impact factor:   1.690


  7 in total

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2.  Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study.

Authors:  Emine Acar; Asım Leblebici; Berat Ender Ellidokuz; Yasemin Başbınar; Gamze Çapa Kaya
Journal:  Br J Radiol       Date:  2019-07-10       Impact factor: 3.039

3.  Hormonal Receptor Immunochemistry Heterogeneity and 18F-FDG Metabolic Heterogeneity: Preliminary Results of Their Relationship and Prognostic Value in Luminal Non-Metastatic Breast Cancers.

Authors:  Nicolas Aide; Nicolas Elie; Cécile Blanc-Fournier; Christelle Levy; Thibault Salomon; Charline Lasnon
Journal:  Front Oncol       Date:  2021-01-12       Impact factor: 6.244

4.  Habitat radiomics analysis of pet/ct imaging in high-grade serous ovarian cancer: Application to Ki-67 status and progression-free survival.

Authors:  Xinghao Wang; Chen Xu; Marcin Grzegorzek; Hongzan Sun
Journal:  Front Physiol       Date:  2022-08-25       Impact factor: 4.755

5.  Frontiers and hotspots of 18F-FDG PET/CT radiomics: A bibliometric analysis of the published literature.

Authors:  Xinghai Liu; Xianwen Hu; Xiao Yu; Pujiao Li; Cheng Gu; Guosheng Liu; Yan Wu; Dandan Li; Pan Wang; Jiong Cai
Journal:  Front Oncol       Date:  2022-09-13       Impact factor: 5.738

6.  Use of radiomic features and support vector machine to distinguish Parkinson's disease cases from normal controls.

Authors:  Yue Wu; Jie-Hui Jiang; Li Chen; Jia-Ying Lu; Jing-Jie Ge; Feng-Tao Liu; Jin-Tai Yu; Wei Lin; Chuan-Tao Zuo; Jian Wang
Journal:  Ann Transl Med       Date:  2019-12

7.  Can Radiomics Analyses in 18F-FDG PET/CT Images of Primary Breast Carcinoma Predict Hormone Receptor Status?

Authors:  Mine Araz; Çiğdem Soydal; Pınar Gündüz; Ayça Kırmızı; Batuhan Bakırarar; Serpil Dizbay Sak; Elgin Özkan
Journal:  Mol Imaging Radionucl Ther       Date:  2022-02-02
  7 in total

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