OBJECTIVE: The objective of our study was to determine the relative accuracy of mammography, sonography, and MRI in predicting residual tumor after neoadjuvant chemotherapy for breast cancer as compared with the gold standards of physical examination and pathology. SUBJECTS AND METHODS: Forty-one women with stage IIB-III palpable breast cancer were prospectively enrolled in a study investigating the effects of sequential single-agent chemotherapy (doxorubicin followed by paclitaxel or vice versa) on tumor imaging. The study cohort consisted of the first 31 patients (age range, 31-65 years; mean, 45 years) who completed the protocol. All underwent physical examination, mammography, sonography, and MRI before and after receiving each neoadjuvant chemotherapeutic drug. Imaging studies were reviewed by two radiologists using conventional lexicons for lesion analysis, and the findings were compared with clinical response and pathology results. RESULTS: Complete, partial, and stable clinical response as defined by clinical examination was seen in 15, 14, and two of the 31 patients, respectively. Agreement rates about the degree of response were 32%, 48%, and 55%, respectively, for mammography, sonography, and MRI compared with clinical evaluation and did not differ statistically. Agreement about the rate of response as measured by clinical examination, mammography, sonography, and MRI compared with the gold standard (pathology) was 19%, 26%, 35%, and 71%, respectively. Of the four, MRI agreed with the gold standard significantly more often (p < 0.002 for all three paired comparisons with MRI). When there was disagreement with the gold standard, none of the four exhibited a significant tendency to either under- or overestimate. CONCLUSION: MRI appears to provide the best correlation with pathology-better than physical examination, mammography, and sonography-in patients undergoing neoadjuvant chemotherapy. However, MRI may overestimate (6%) or underestimate (23%) residual disease in approximately 29% of the patients (95% confidence interval, 14-48%).
OBJECTIVE: The objective of our study was to determine the relative accuracy of mammography, sonography, and MRI in predicting residual tumor after neoadjuvant chemotherapy for breast cancer as compared with the gold standards of physical examination and pathology. SUBJECTS AND METHODS: Forty-one women with stage IIB-III palpable breast cancer were prospectively enrolled in a study investigating the effects of sequential single-agent chemotherapy (doxorubicin followed by paclitaxel or vice versa) on tumor imaging. The study cohort consisted of the first 31 patients (age range, 31-65 years; mean, 45 years) who completed the protocol. All underwent physical examination, mammography, sonography, and MRI before and after receiving each neoadjuvant chemotherapeutic drug. Imaging studies were reviewed by two radiologists using conventional lexicons for lesion analysis, and the findings were compared with clinical response and pathology results. RESULTS: Complete, partial, and stable clinical response as defined by clinical examination was seen in 15, 14, and two of the 31 patients, respectively. Agreement rates about the degree of response were 32%, 48%, and 55%, respectively, for mammography, sonography, and MRI compared with clinical evaluation and did not differ statistically. Agreement about the rate of response as measured by clinical examination, mammography, sonography, and MRI compared with the gold standard (pathology) was 19%, 26%, 35%, and 71%, respectively. Of the four, MRI agreed with the gold standard significantly more often (p < 0.002 for all three paired comparisons with MRI). When there was disagreement with the gold standard, none of the four exhibited a significant tendency to either under- or overestimate. CONCLUSION: MRI appears to provide the best correlation with pathology-better than physical examination, mammography, and sonography-in patients undergoing neoadjuvant chemotherapy. However, MRI may overestimate (6%) or underestimate (23%) residual disease in approximately 29% of the patients (95% confidence interval, 14-48%).
Authors: Stephanie M W Y van de Ven; Niculae Mincu; Jean Brunette; Guobin Ma; Mario Khayat; Debra M Ikeda; Sanjiv S Gambhir Journal: Mol Imaging Biol Date: 2011-04 Impact factor: 3.488
Authors: Albert E Cerussi; Vaya W Tanamai; David Hsiang; John Butler; Rita S Mehta; Bruce J Tromberg Journal: Philos Trans A Math Phys Eng Sci Date: 2011-11-28 Impact factor: 4.226
Authors: Gabriel Ramirez; Ashley R Proctor; Ki Won Jung; Tong Tong Wu; Songfeng Han; Russell R Adams; Jingxuan Ren; Daniel K Byun; Kelley S Madden; Edward B Brown; Thomas H Foster; Parisa Farzam; Turgut Durduran; Regine Choe Journal: Biomed Opt Express Date: 2016-08-24 Impact factor: 3.732
Authors: Bruce J Tromberg; Zheng Zhang; Anaïs Leproux; Thomas D O'Sullivan; Albert E Cerussi; Philip M Carpenter; Rita S Mehta; Darren Roblyer; Wei Yang; Keith D Paulsen; Brian W Pogue; Shudong Jiang; Peter A Kaufman; Arjun G Yodh; So Hyun Chung; Mitchell Schnall; Bradley S Snyder; Nola Hylton; David A Boas; Stefan A Carp; Steven J Isakoff; David Mankoff Journal: Cancer Res Date: 2016-08-15 Impact factor: 12.701