1. Prediction of low-risk breast cancer using perfusion parameters and apparent diffusion coefficient
- Author
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Byung Ho Son, Jong Won Lee, Hak Hee Kim, Sei Hyun Ahn, Hee Jung Shin, Ki Chang Shin, Joo Hee Cha, and Yoo Sub Sung
- Subjects
Adult ,medicine.medical_specialty ,Lymphovascular invasion ,Biomedical Engineering ,Biophysics ,Sensitivity and Specificity ,030218 nuclear medicine & medical imaging ,Metastasis ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,Image Interpretation, Computer-Assisted ,Republic of Korea ,medicine ,Prevalence ,Effective diffusion coefficient ,Humans ,Radiology, Nuclear Medicine and imaging ,Computer Simulation ,Aged ,Proportional Hazards Models ,Univariate analysis ,Models, Statistical ,Receiver operating characteristic ,business.industry ,Area under the curve ,Reproducibility of Results ,Middle Aged ,medicine.disease ,Prognosis ,Exact test ,Diffusion Magnetic Resonance Imaging ,030220 oncology & carcinogenesis ,Female ,Radiology ,business ,Nuclear medicine ,Algorithms ,Magnetic Resonance Angiography - Abstract
article i nfo Article history: Received 14 August 2015 Accepted 21 October 2015 Purpose: To assess whether perfusion and diffusion parameters were different between low-risk tumors and non-low-risk tumors. Materials and Methods: We prospectively enrolled 87 patients with 91 tumors patients (mean, 49.6 years; range, 29-74 years) who underwent definitive surgery. We defined estrogen receptor (ER)-positive tumors with low histologic grade (HG), low Ki67 (b14%), and negative lymph node metastasis as a low-risk breast cancer. We obtained quantitative and semiquantitative perfusion parameters and apparent diffusion coefficient (ADC) for all tumors. We compared perfusion parameters and ADCs between low-risk tumors (n = 33; 36%) and the others (n = 58; 64%) using Fisher's exact test, Chi-square test, and student t-test. We developed empirical model to predict low-risk tumor using logistic regression analysis and receiver operating characteristics (ROC) analysis. Results: On univariate analysis, wash-in and the initial area under the curve on qualitative analysis (iAUCqualitative) were significantly different according to HG, ER, HER-2, Ki67 and lymphovascular invasion (P b .05 for all variables). ADCdiff was significantly different according to HG, HER-2, and Ki67 status (P = .010, .007, and .013). On multivariate analysis, Ktrans, iAUCqualitative, and ADCdiff were the significant variables for the prediction of low-risk tumors, and the area under the ROC curve (AUC) of combined parameters was 0.78, which was higher than those of the individual parameter. ADCdiff was positively correlated with wash-in (r = 0.263) and iAUCqualitative (r = 0.245), respectively. Conclusion: The prediction model using Ktrans, wash in, iAUCqualitative, and ADCdiff on DCE-MRI and DWI could be helpful for identifying of low-risk breast cancer and may be used as an imaging biomarker to guide the treatment plan.
- Published
- 2015