Literature DB >> 32427700

Molecular subtypes of invasive breast cancer: correlation between PET/computed tomography and MRI findings.

Meliha Akin1, Sebnem Orguc1, Feray Aras2, Ali Riza Kandiloglu3.   

Abstract

OBJECTIVE: The aim of the study was to investigate the diagnostic value of fluorodeoxyglucose-18 (FDG)-PET/computed tomography (CT) and MRI parameters in determining the molecular subtypes of invasive breast cancer.
METHODS: Data from 55 primary invasive breast cancer masses in 51 female patients who underwent pre-treatment PET/CT and MRI scans, and histopathological diagnosis at the authors' center were retrospectively reviewed. The relationship between FDG-PET/CT and MRI parameters, including maximum and mean standard uptake values (SUVmax and SUVmean, respectively), mean metabolic index (MImean) and metabolic tumor volume (MTV) values obtained from FDG-PET, and shape, margin, internal contrast-enhancement characteristics, kinetic curve types, functional tumor volume (FTV), apparent diffusion coefficient (ADC) values obtained from MRI was evaluated. Subsequently, differences among molecular subtypes (i.e. luminal A, luminal B, c-erbB-2 positive, and triple-negative) in terms of PET/CT and MRI parameters were evaluated.
RESULTS: The luminal B subtype of invasive breast cancer had higher SUVmax and SUVmean (P = 0.002 and P = 0.017, respectively) values than the luminal A subtype. In addition, the triple-negative subtype had a higher SUVmax (P = 0.028) than the luminal A subtype. There was a statistically significant positive correlation between pathological tumor volume (PTV) and SUVmean (P = 0.019, r = 0.720). SUVmax and ADC were negatively correlated (P = 0.001; r = -0.384). A very strong positive correlation was detected between MTV and FTV (P = 0.000; r = 0.857), and between MTV and PTV (P = 0.006, r = 0.796), and between FTV and PTV (P = 0.006, r = 0.921).
CONCLUSION: Results of the present study suggest that SUVmax was superior to MRI findings in predicting molecular subtypes and that MRI was superior to PET/CT in predicting PTV.

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Year:  2020        PMID: 32427700     DOI: 10.1097/MNM.0000000000001220

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


  3 in total

Review 1.  Micropapillary Breast Carcinoma: From Molecular Pathogenesis to Prognosis.

Authors:  Georgios-Ioannis Verras; Levan Tchabashvili; Francesk Mulita; Ioanna Maria Grypari; Sofia Sourouni; Evangelia Panagodimou; Maria-Ioanna Argentou
Journal:  Breast Cancer (Dove Med Press)       Date:  2022-03-12

2.  The Effect of PACS in Breast Tumor Diagnosis Based on Numerical Analysis.

Authors:  Guijun Guo; Yi Chen
Journal:  Comput Math Methods Med       Date:  2022-07-13       Impact factor: 2.809

3.  A Simultaneous Multiparametric 18F-FDG PET/MRI Radiomics Model for the Diagnosis of Triple Negative Breast Cancer.

Authors:  Valeria Romeo; Panagiotis Kapetas; Paola Clauser; Pascal A T Baltzer; Sazan Rasul; Peter Gibbs; Marcus Hacker; Ramona Woitek; Katja Pinker; Thomas H Helbich
Journal:  Cancers (Basel)       Date:  2022-08-16       Impact factor: 6.575

  3 in total

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