PURPOSE: To compare the capability of diffusion-weighted (DW) and contrast material-enhanced magnetic resonance (MR) imaging to provide diagnostic information on residual breast cancers following neoadjuvant chemotherapy and to assess apparent diffusion coefficients (ADCs) of the carcinoma prior to neoadjuvant chemotherapy to determine if the method could help predict response to chemotherapy. MATERIALS AND METHODS: Institutional review board approval and informed consent were obtained. Three hundred ninety-eight patients underwent MR imaging of the breast, including DW MR (b values, 0 and 1500 sec/mm(2)) and contrast-enhanced MR imaging. Of these, the contralateral breast in 73 women was used as a control. Seventy-two patients with 73 lesions with malignant disease were treated by using neoadjuvant chemotherapy and were examined for residual disease following therapy. Three were excluded because of prolonged intervals between final MR imaging and surgery. Thus, 69 patients (70 lesions) with DW and contrast-enhanced MR imaging results were compared with postoperative histopathologic findings. The ADCs of the carcinoma prior to neoadjuvant chemotherapy were calculated for each patient, and those with complete response and residual disease were compared. RESULTS: The accuracy for depicting residual tumor was 96% for DW MR imaging, compared with an accuracy of 89% for contrast-enhanced MR imaging (P = .06). There was no significant difference in prechemotherapy ADCs between pathologic complete response cases and those with residual disease. CONCLUSION: DW MR imaging had at least as good of accuracy as did contrast-enhanced MR imaging for monitoring neoadjuvant chemotherapy. The ADCs prior to chemotherapy did not predict response to chemotherapy. The use of DW imaging to visualize residual breast cancer without the need for contrast medium could be advantageous in women with impaired renal function. (c) RSNA, 2010
PURPOSE: To compare the capability of diffusion-weighted (DW) and contrast material-enhanced magnetic resonance (MR) imaging to provide diagnostic information on residual breast cancers following neoadjuvant chemotherapy and to assess apparent diffusion coefficients (ADCs) of the carcinoma prior to neoadjuvant chemotherapy to determine if the method could help predict response to chemotherapy. MATERIALS AND METHODS: Institutional review board approval and informed consent were obtained. Three hundred ninety-eight patients underwent MR imaging of the breast, including DW MR (b values, 0 and 1500 sec/mm(2)) and contrast-enhanced MR imaging. Of these, the contralateral breast in 73 women was used as a control. Seventy-two patients with 73 lesions with malignant disease were treated by using neoadjuvant chemotherapy and were examined for residual disease following therapy. Three were excluded because of prolonged intervals between final MR imaging and surgery. Thus, 69 patients (70 lesions) with DW and contrast-enhanced MR imaging results were compared with postoperative histopathologic findings. The ADCs of the carcinoma prior to neoadjuvant chemotherapy were calculated for each patient, and those with complete response and residual disease were compared. RESULTS: The accuracy for depicting residual tumor was 96% for DW MR imaging, compared with an accuracy of 89% for contrast-enhanced MR imaging (P = .06). There was no significant difference in prechemotherapy ADCs between pathologic complete response cases and those with residual disease. CONCLUSION: DW MR imaging had at least as good of accuracy as did contrast-enhanced MR imaging for monitoring neoadjuvant chemotherapy. The ADCs prior to chemotherapy did not predict response to chemotherapy. The use of DW imaging to visualize residual breast cancer without the need for contrast medium could be advantageous in women with impaired renal function. (c) RSNA, 2010
Authors: Xia Li; Richard G Abramson; Lori R Arlinghaus; Hakmook Kang; Anuradha Bapsi Chakravarthy; Vandana G Abramson; Jaime Farley; Ingrid A Mayer; Mark C Kelley; Ingrid M Meszoely; Julie Means-Powell; Ana M Grau; Melinda Sanders; Thomas E Yankeelov Journal: Invest Radiol Date: 2015-04 Impact factor: 6.016
Authors: E E Sigmund; G Y Cho; S Kim; M Finn; M Moccaldi; J H Jensen; D K Sodickson; J D Goldberg; S Formenti; L Moy Journal: Magn Reson Med Date: 2011-02-01 Impact factor: 4.668
Authors: Hakmook Kang; Allison Hainline; Lori R Arlinghaus; Stephanie Elderidge; Xia Li; Vandana G Abramson; Anuradha Bapsi Chakravarthy; Richard G Abramson; Brian Bingham; Kareem Fakhoury; Thomas E Yankeelov Journal: J Med Imaging (Bellingham) Date: 2017-12-29
Authors: Xia Li; Hakmook Kang; Lori R Arlinghaus; Richard G Abramson; A Bapsi Chakravarthy; Vandana G Abramson; Jaime Farley; Melinda Sanders; Thomas E Yankeelov Journal: Transl Oncol Date: 2014-02-01 Impact factor: 4.243