PURPOSE: The American Cancer Society estimates that in 2006, 212,920 women will be diagnosed with breast cancer and that 40,970 women will die from the disease. The development of more efficacious chemotherapies has improved outcomes, but the rapid assessment of clinical benefit from these agents remains challenging. In breast cancer patients receiving neoadjuvant chemotherapy, treatment response is traditionally assessed by physical examination and volumetric-based measurements, which are subjective and require macroscopic changes in tumor morphology. In this study, we evaluate the feasibility of using diffusion magnetic resonance imaging (MRI) as a reliable and quantitative measure for the early assessment of response in a breast cancer model. EXPERIMENTAL DESIGN: Mice implanted with human breast cancer (MX-1) were treated with cyclophosphamide and evaluated using diffusion MRI and growth kinetics. Histologic analyses using terminal nucleotidyl transferase-mediated nick end labeling and H&E were done on tumor samples for correlation with imaging results. RESULTS: Cyclophosphamide treatment resulted in a significant reduction in tumor volumes compared with controls. The mean apparent diffusion change for treated tumors at days 4 and 7 posttreatment was 44 +/- 5% and 94 +/- 7%, respectively, which was statistically greater (P < 0.05) than the control tumors at the same time intervals. The median time-to-progression for control and treated groups was 11 and 32 days, respectively (P < 0.05). CONCLUSION: Diffusion MRI was shown to detect early changes in the tumor microenvironment, which correlated with standard measures of tumor response as well as overall outcome. Moreover, these findings show the feasibility of using diffusion MRI for assessing treatment response of a breast tumor model in a neoadjuvant setting.
PURPOSE: The American Cancer Society estimates that in 2006, 212,920 women will be diagnosed with breast cancer and that 40,970 women will die from the disease. The development of more efficacious chemotherapies has improved outcomes, but the rapid assessment of clinical benefit from these agents remains challenging. In breast cancerpatients receiving neoadjuvant chemotherapy, treatment response is traditionally assessed by physical examination and volumetric-based measurements, which are subjective and require macroscopic changes in tumor morphology. In this study, we evaluate the feasibility of using diffusion magnetic resonance imaging (MRI) as a reliable and quantitative measure for the early assessment of response in a breast cancer model. EXPERIMENTAL DESIGN:Mice implanted with humanbreast cancer (MX-1) were treated with cyclophosphamide and evaluated using diffusion MRI and growth kinetics. Histologic analyses using terminal nucleotidyl transferase-mediated nick end labeling and H&E were done on tumor samples for correlation with imaging results. RESULTS:Cyclophosphamide treatment resulted in a significant reduction in tumor volumes compared with controls. The mean apparent diffusion change for treated tumors at days 4 and 7 posttreatment was 44 +/- 5% and 94 +/- 7%, respectively, which was statistically greater (P < 0.05) than the control tumors at the same time intervals. The median time-to-progression for control and treated groups was 11 and 32 days, respectively (P < 0.05). CONCLUSION: Diffusion MRI was shown to detect early changes in the tumor microenvironment, which correlated with standard measures of tumor response as well as overall outcome. Moreover, these findings show the feasibility of using diffusion MRI for assessing treatment response of a breast tumor model in a neoadjuvant setting.
Authors: Craig J Galbán; Stefanie Galbán; Marcian E Van Dort; Gary D Luker; Mahaveer S Bhojani; Alnawaz Rehemtulla; Brian D Ross Journal: Prog Mol Biol Transl Sci Date: 2010 Impact factor: 3.622
Authors: Jennifer L Boes; Benjamin A Hoff; Nola Hylton; Martin D Pickles; Lindsay W Turnbull; Anne F Schott; Alnawaz Rehemtulla; Ryan Chamberlain; Benjamin Lemasson; Thomas L Chenevert; Craig J Galbán; Charles R Meyer; Brian D Ross Journal: Transl Oncol Date: 2014-02-01 Impact factor: 4.243
Authors: Francesco De Cobelli; Francesco Giganti; Elena Orsenigo; Michaela Cellina; Antonio Esposito; Giulia Agostini; Luca Albarello; Elena Mazza; Alessandro Ambrosi; Carlo Socci; Carlo Staudacher; Alessandro Del Maschio Journal: Eur Radiol Date: 2013-04-16 Impact factor: 5.315
Authors: Thomas S C Ng; David Wert; Hargun Sohi; Daniel Procissi; David Colcher; Andrew A Raubitschek; Russell E Jacobs Journal: Clin Cancer Res Date: 2013-03-26 Impact factor: 12.531
Authors: Renu M Stephen; Abhinav K Jha; Denise J Roe; Theodore P Trouard; Jean-Philippe Galons; Matthew A Kupinski; Georgette Frey; Haiyan Cui; Scott Squire; Mark D Pagel; Jeffrey J Rodriguez; Robert J Gillies; Alison T Stopeck Journal: Magn Reson Imaging Date: 2015-08-15 Impact factor: 2.546
Authors: Sungheon Kim; Laurie Loevner; Harry Quon; Eric Sherman; Gregory Weinstein; Alex Kilger; Harish Poptani Journal: Clin Cancer Res Date: 2009-02-01 Impact factor: 12.531