Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms.
Purpose: The purpose of this study is to investigate the association between breast cancer recurrence-free survival and breast magnetic resonance imaging (MRI) tumor enhancement dynamics which are quantified semi-automatically using computer algorithms.Methods: In this retrospective IRB-approved stu...
| Publicado en: | European Journal of Radiology Vol. 84; no. 11; pp. 2117 - 2123 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Nov2015
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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=110303906&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110303906 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0720048X 3S7 jtl: European Journal of Radiology issn: 0720048X maglogo: N pubinfo: dt: Nov2015 vid: 84 iid: 11 pid: 1004 pub: Elsevier B.V. artinfo: ui: 110303906 110303906 NLM26210095 110303906 10.1016/j.ejrad.2015.07.012 NLM26210095 110303906 ppf: 2117 ppct: 6 formats: tig: atl: Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms. aug: au: Mazurowski, Maciej A. Grimm, Lars J. Zhang, Jing Marcom, P. Kelly Yoon, Sora C. Kim, Connie Ghate, Sujata V. Johnson, Karen S. affil: Department of Radiology, Duke University Medical Center, Durham, NC, USA sug: subj: Magnetic Resonance Imaging Methods Neoplasm Recurrence, Local Pathology Breast Pathology Breast Neoplasms Pathology Image Interpretation, Computer Assisted Breast Neoplasms Mortality Prognosis Aged Middle Age Predictive Value of Tests Adult Information Science Female Algorithms Retrospective Design Cox Proportional Hazards Model Human Aged: 65+ years Middle Aged: 45-64 years Adult: 19-44 years Female ab: Purpose: The purpose of this study is to investigate the association between breast cancer recurrence-free survival and breast magnetic resonance imaging (MRI) tumor enhancement dynamics which are quantified semi-automatically using computer algorithms.Methods: In this retrospective IRB-approved study, we analyzed data from 275 breast cancer patients at a single institution. Recurrence-free survival data were obtained from the medical record. Routine clinical pre-operative breast MRIs were performed in all patients. The tumors were marked on the MRIs by fellowship-trained breast radiologists. A previously developed computer algorithm was applied to the marked tumors to quantify the enhancement dynamics relative to the automatically assessed background parenchymal enhancement. To establish whether the contrast enhancement feature quantified by the algorithm was associated with recurrence-free survival, we constructed a Cox proportional hazards regression model with the computer-extracted feature as a covariate. We controlled for tumor grade and size (major axis length), patient age, patient race/ethnicity, and menopausal status.Results: The analysis showed that the semi-automatically obtained feature quantifying MRI tumor enhancement dynamics was independently predictive of recurrence-free survival (p=0.024).Conclusion: Semi-automatically quantified tumor enhancement dynamics on MRI are predictive of recurrence-free survival in breast cancer patients. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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