Relationship between functional imaging and immunohistochemical markers and prediction of breast cancer subtype: a PET/MRI study.
Purpose: The aim of this study was to determine if functional parameters extracted from the hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) correlate with the immunohistochemical markers of breast cancer (BC) lesions, to assess their ability to predict BC subtype.Methods: Th...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 45; no. 10; pp. 1680 - 1694 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=131034483&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 131034483 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Sep2018 vid: 45 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 131034483 10.1007/s00259-018-4010-7 131034483 ppf: 1680 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Relationship between functional imaging and immunohistochemical markers and prediction of breast cancer subtype: a PET/MRI study. aug: au: Incoronato, Mariarosaria Grimaldi, Anna Maria Cavaliere, Carlo Inglese, Marianna Mirabelli, Peppino Monti, Serena Ferbo, Umberto Nicolai, Emanuele Soricelli, Andrea Catalano, Onofrio Antonio Aiello, Marco Salvatore, Marco affil: IRCCS SDN, Via Gianturco n 113, Naples, Italy sug: ab: Purpose: The aim of this study was to determine if functional parameters extracted from the hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) correlate with the immunohistochemical markers of breast cancer (BC) lesions, to assess their ability to predict BC subtype.Methods: This prospective study was approved by the institution’s Ethics Committee, and all patients provided written informed consent. A total of 50 BC patients at diagnosis underwent PET/MRI before pharmacological and surgical treatment. For each primary lesion, the following data were extracted: morphological data including tumour-node-metastasis stage and lesion size; apparent diffusion coefficient (ADC); perfusion data including forward volume transfer constant (Ktrans), reverse efflux volume transfer constant (Kep) and extravascular extracellular space volume (Ve); and metabolic data including standardized uptake value (SUV), lean body mass (SUL), metabolic tumour volume and total lesion glycolysis. Immunohistochemical reports were used to determine receptor status (oestrogen, progesterone, and human epidermal growth factor receptor 2), cellular differentiation status (grade), and proliferation index (Ki67) of the tumour lesions. Correlation studies (Mann-Whitney U test and Spearman’s test), receiver operating characteristic (ROC) curve analysis, and multivariate analysis were performed.Results: Association studies were performed to assess the correlations between imaging and histological prognostic markers of BC. Imaging biomarkers, which significantly correlated with biological markers, were selected to perform ROC curve analysis to determine their ability to discriminate among BC subtypes. SUVmax, SUVmean and SUL were able to discriminate between luminal A and luminal B subtypes (AUCSUVmean = 0.799; AUCSUVmax = 0.833; AUCSUL = 0.813) and between luminal A and nonluminal subtypes (AUCSUVmean = 0.926; AUCSUVmax = 0.917; AUCSUL = 0.945), and the lowest SUV and SUL values were associated with the luminal A subtype. Kepmax was able to discriminate between luminal A and luminal B subtypes (AUC = 0.779), and its highest values were associated with the luminal B subtype. Ktransmax (AUC = 0.881) was able to discriminate between luminal A and nonluminal subtypes, and the highest perfusion values were associated with the nonluminal subtype. In addition, ADC (AUC = 0.877) was able to discriminate between luminal B and nonluminal subtypes, and the lowest ADCmean values were associated with the luminal B subtype. Multivariate analysis was performed to develop a prognostic model, and the best predictive model included Ktransmax and SUVmax parameters.Conclusion: Using multivariate analysis of both PET and MRI parameters, a prognostic model including Ktransmax and SUVmax was able to predict the tumour subtype in 38 of 49 patients (77.6%, p < 0.001), with higher accuracy for the luminal B subtype (86.2%). pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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