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Apparent diffusion coefficient histogram in breast cancer brain metastases may predict their biological subtype and progressionopen access

Authors
Ahn, Sung JunPark, MijinBang, SungkyuCho, EunseoAhn, Sung GweSuh, Sang HyunLee, Jong Min
Issue Date
Jul-2018
Publisher
NATURE PUBLISHING GROUP
Citation
SCIENTIFIC REPORTS, v.8
Indexed
SCIE
SCOPUS
Journal Title
SCIENTIFIC REPORTS
Volume
8
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/149739
DOI
10.1038/s41598-018-28315-y
ISSN
2045-2322
Abstract
Our aims for this study were to investigate the relationship between diffusion weighted image (DWI) parameters of brain metastases (BMs) and biological markers of breast cancer, and moreover, to assess whether DWI parameters accurately predict patient outcomes. DWI data for 34 patients with BMs from breast cancer were retrospectively reviewed. Apparent diffusion coefficient (ADC) histogram parameters were calculated from all measurable BMs. Two region of interest (ROI) methods are used for the analysis: from the largest BM or from all measurable BMs per one patient. ADC histogram parameters were compared between positive and negative groups depending on ER/PR and HER2 statuses. Overall survival analysis after BM (OSBM) and BM-specific progression-free survival (BMPFS) was analyzed with ADC parameters. Regardless of ROI methods, 25th percentile of ADC histogram was significantly lower in the ER/PR-positive group than in the ER/PR-negative group (P < 0.05). Using ROIs from all measurable BMs, Peak location, 50th percentile, 75th percentile, and mean value of ADC histogram were also significantly lower in the ER/PR-positive group than in the ER/PR-negative group (P < 0.05). However, there was no significant difference between HER2-postive and negative group. On univariate analysis, using ROIs from all measurable BMs, lower 25th percentile, 50th percentile and mean of ADC were significant predictors for poor BMPFS. ADC histogram analysis may have a prognostic value over ER/PR status as well as BMPFS.
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COLLEGE OF ENGINEERING (서울 바이오메디컬공학전공)
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