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Volume-based metabolic parameter of breast cancer on preoperative 18F-FDG PET/CT could predict axillary lymph node metastasis

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dc.contributor.authorAn, YS-
dc.contributor.authorKang, DK-
dc.contributor.authorJung, Y-
dc.contributor.authorKim, TH-
dc.date.accessioned2018-08-24T01:49:20Z-
dc.date.available2018-08-24T01:49:20Z-
dc.date.issued2017-
dc.identifier.issn0025-7974-
dc.identifier.urihttp://repository.ajou.ac.kr/handle/201003/15981-
dc.description.abstractThe purpose of our study was to evaluate the association between metabolic parameters on FDG PET/CT and axillary lymph node metastasis (ALNM) in patients with invasive breast cancer.From January 2012 to December 2012, we analyzed 173 patients with invasive ductal carcinoma (IDC) who underwent both initial breast magnetic resonance imaging (MRI) and F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) examinations. All metabolic parameters were measured from the tumor volume segmented by a gradient-based method. Once the primary target lesion was segmented, maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated automatically by the MIMvista software.Mean age of 173 patients was 49 years. Of 173 patients, 45 (26%) showed ALNM. On univariate analysis, larger tumor size (>2.2 cm: P = .002), presence of lymphovascular invasion (P < .001), higher SUVmax (>2.82: P = .038), higher SUVmean (>1.2: P = .027), higher MTV (>2.38: P < .001), and higher TLG (>3.98: P = .007) were associated with a higher probability of ALNM. On multivariate analysis, presence of lymphovascular invasion (adjusted odds ratio [OR], 11.053: 95% CI, 4.403-27.751: P < .001) and higher MTV (>2.38) (adjusted OR, 2.696: 95% CI, 1.079-6.739: P = .034) maintained independent significance in predicting ALNM. In subgroup analysis of T2/T3 breast cancer, lymphovascular invasion (adjusted OR, 20.976: 95% CI, 5.431-81.010: P < .001) and higher MTV (>2.38) (adjusted OR, 4.906: 95% CI, 1.616-14.896: P = .005) were independent predictors of ALNM. However in T1 breast cancer, lymphovascular invasion (adjusted OR, 16.096: 95% CI, 2.517-102.939: P = .003) and larger SUV mean (>1.2) (adjusted OR, 13.275: 95% CI, 1.233-142.908: P = .033) were independent predictors while MTV was not.MTV may be associated with ALNM in patients with invasive breast cancer, particularly T2 and T3 stages. In T1 breast cancer, SUVmean was associated with ALNM.-
dc.language.isoen-
dc.subject.MESHAdult-
dc.subject.MESHAxilla-
dc.subject.MESHBreast Neoplasms-
dc.subject.MESHCarcinoma, Ductal, Breast-
dc.subject.MESHFemale-
dc.subject.MESHFluorodeoxyglucose F18-
dc.subject.MESHHumans-
dc.subject.MESHLymph Nodes-
dc.subject.MESHLymphatic Metastasis-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPositron Emission Tomography Computed Tomography-
dc.subject.MESHPredictive Value of Tests-
dc.subject.MESHRadiopharmaceuticals-
dc.subject.MESHRetrospective Studies-
dc.subject.MESHTumor Burden-
dc.titleVolume-based metabolic parameter of breast cancer on preoperative 18F-FDG PET/CT could predict axillary lymph node metastasis-
dc.typeArticle-
dc.identifier.pmid29137072-
dc.identifier.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690765/-
dc.contributor.affiliatedAuthor안, 영실-
dc.contributor.affiliatedAuthor강, 두경-
dc.contributor.affiliatedAuthor정, 용식-
dc.contributor.affiliatedAuthor김, 태희-
dc.type.localJournal Papers-
dc.identifier.doi10.1097/MD.0000000000008557-
dc.citation.titleMedicine-
dc.citation.volume96-
dc.citation.number45-
dc.citation.date2017-
dc.citation.startPagee8557-
dc.citation.endPagee8557-
dc.identifier.bibliographicCitationMedicine, 96(45). : e8557-e8557, 2017-
dc.identifier.eissn1536-5964-
dc.relation.journalidJ000257974-
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Nuclear Medicine & Molecular Imaging
Journal Papers > School of Medicine / Graduate School of Medicine > Radiology
Journal Papers > School of Medicine / Graduate School of Medicine > Surgery
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