OBJECTIVE: Cancerous neovascular changes in histologically normal-appearing breast tissue have been shown to increase risk for local recurrence after breast-conserving therapy. However, the imaging characteristics of this tissue have not been well studied. We hypothesized that signal enhancement ratios from dynamic contrast-enhanced breast MRI could be used to analyze the contrast kinetics of microvasculature in breast stroma beyond the tumor margin and that this information can be developed to improve local treatment options. MATERIALS AND METHODS: Signal enhancement ratio analysis of nontumor breast stroma was performed on dynamic contrast-enhanced MRI scans of 42 patients who received neoadjuvant chemotherapy for invasive breast cancer performed before chemotherapy (scan 1) and after one cycle of chemotherapy (scan 2). Stromal signal enhancement ratio values were then correlated to several clinical parameters and to clinical outcome using univariate and multivariate analyses. Median follow-up for the group was 52.1 months. RESULTS: On univariate analysis, factors that were significantly associated (p < 0.05) with disease-free survival included the mean stromal signal enhancement ratio at scan 2 (hazard ratio [HR] = 0.11, 95% CI = 0.013-0.88, p = 0.03), pretreatment tumor size (HR = 1.33, 95% CI = 1.07-1.66, p = 0.012), pretreatment tumor volume (HR = 1.04, 95% CI = 1.01-1.07, p = 0.006), and number of involved axillary lymph nodes (HR = 1.18, 95% CI = 1.05-1.32, p = 0.005). These factors were then analyzed in a multivariate Cox proportional hazards model. The only factor that was associated with disease-free survival was mean stromal signal enhancement ratio at scan 2 (HR = 0.11, 95% CI = 0.012-0.95, p < 0.045). CONCLUSION: These findings indicate that breast stroma tissue outside the incident tumor can be quantified using signal enhancement ratio analysis on dynamic contrast-enhanced MRI. Stromal signal enhancement ratio is a potential indicator for response to treatment and for overall outcome in patients with breast cancer; however, these results should be validated in a prospective study.
OBJECTIVE:Cancerous neovascular changes in histologically normal-appearing breast tissue have been shown to increase risk for local recurrence after breast-conserving therapy. However, the imaging characteristics of this tissue have not been well studied. We hypothesized that signal enhancement ratios from dynamic contrast-enhanced breast MRI could be used to analyze the contrast kinetics of microvasculature in breast stroma beyond the tumor margin and that this information can be developed to improve local treatment options. MATERIALS AND METHODS: Signal enhancement ratio analysis of nontumor breast stroma was performed on dynamic contrast-enhanced MRI scans of 42 patients who received neoadjuvant chemotherapy for invasive breast cancer performed before chemotherapy (scan 1) and after one cycle of chemotherapy (scan 2). Stromal signal enhancement ratio values were then correlated to several clinical parameters and to clinical outcome using univariate and multivariate analyses. Median follow-up for the group was 52.1 months. RESULTS: On univariate analysis, factors that were significantly associated (p < 0.05) with disease-free survival included the mean stromal signal enhancement ratio at scan 2 (hazard ratio [HR] = 0.11, 95% CI = 0.013-0.88, p = 0.03), pretreatment tumor size (HR = 1.33, 95% CI = 1.07-1.66, p = 0.012), pretreatment tumor volume (HR = 1.04, 95% CI = 1.01-1.07, p = 0.006), and number of involved axillary lymph nodes (HR = 1.18, 95% CI = 1.05-1.32, p = 0.005). These factors were then analyzed in a multivariate Cox proportional hazards model. The only factor that was associated with disease-free survival was mean stromal signal enhancement ratio at scan 2 (HR = 0.11, 95% CI = 0.012-0.95, p < 0.045). CONCLUSION: These findings indicate that breast stroma tissue outside the incident tumor can be quantified using signal enhancement ratio analysis on dynamic contrast-enhanced MRI. Stromal signal enhancement ratio is a potential indicator for response to treatment and for overall outcome in patients with breast cancer; however, these results should be validated in a prospective study.
Authors: Valencia King; Yajia Gu; Jennifer B Kaplan; Jennifer D Brooks; Malcolm C Pike; Elizabeth A Morris Journal: Eur Radiol Date: 2012-07-04 Impact factor: 5.315
Authors: Jim Zhong; Narasimhan Rajaram; David M Brizel; Amy E Frees; Nirmala Ramanujam; Ines Batinic-Haberle; Mark W Dewhirst Journal: Radiother Oncol Date: 2013-03-28 Impact factor: 6.280
Authors: Nima Nabavizadeh; Catherine Klifa; David Newitt; Ying Lu; Yunn-Yi Chen; Howard Hsu; Clark Fisher; Taku Tokayasu; Adam B Olshen; Paul Spellman; Joe W Gray; Nola Hylton; Catherine C Park Journal: Integr Biol (Camb) Date: 2011-03-18 Impact factor: 2.192
Authors: H Preibsch; L Wanner; S D Bahrs; B M Wietek; K C Siegmann-Luz; E Oberlecher; M Hahn; A Staebler; K Nikolaou; B Wiesinger Journal: Eur Radiol Date: 2015-09-17 Impact factor: 5.315