OBJECTIVE: The clinical breast tumour size can be assessed preoperatively by physical examination, mammography and ultrasound. At present it is not clear which modality correlates best with the histological invasive breast tumour size. This prospective study aims to determine the most accurate clinical method (physical examination, mammography or ultrasound) to predict the histological invasive tumour size preoperatively. METHODS AND PATIENTS: Between October 1999 and August 2000, 96 women with 105 invasive malignant breast tumours were included in this study. All patients underwent excision and the tumour size was measured on histology. Tumour size was measured by all three modalities in 73 cases. Results were evaluated by calculating correlation coefficients. The examination modalities presenting the best estimation of the pathological tumour size were used in a stepwise linear regression analysis to construct a formula predicting the pathological tumour size from the result of the various diagnostic modalities. RESULTS: The correlation coefficient between ultrasound and pathological size (r=0.68) was significantly better than the correlations between physical examination and pathological size (r=0.42) and mammographic and pathological size (r=0.44). Physical examination overestimates and ultrasound underestimates breast tumour classification. The most accurate prediction formula was: Pathological tumour size (mm) equals sonographic tumour size (mm)+3 mm. CONCLUSION: When comparing physical examination, mammography and ultrasound for the prediction of the pathological size of a malignant breast tumour, ultrasound is the best predictor. The ensuing regression formula determines pathological size as tumour size by ultrasound+3 mm. However, with the wide 95% confidence interval of +/-11 mm, it remains difficult to predict the exact pathological size for an individual invasive breast tumour. A small deviation in millimetres of the tumour size could lead to a change in treatment and to another prognostic estimate.
OBJECTIVE: The clinical breast tumour size can be assessed preoperatively by physical examination, mammography and ultrasound. At present it is not clear which modality correlates best with the histological invasive breast tumour size. This prospective study aims to determine the most accurate clinical method (physical examination, mammography or ultrasound) to predict the histological invasive tumour size preoperatively. METHODS AND PATIENTS: Between October 1999 and August 2000, 96 women with 105 invasive malignant breast tumours were included in this study. All patients underwent excision and the tumour size was measured on histology. Tumour size was measured by all three modalities in 73 cases. Results were evaluated by calculating correlation coefficients. The examination modalities presenting the best estimation of the pathological tumour size were used in a stepwise linear regression analysis to construct a formula predicting the pathological tumour size from the result of the various diagnostic modalities. RESULTS: The correlation coefficient between ultrasound and pathological size (r=0.68) was significantly better than the correlations between physical examination and pathological size (r=0.42) and mammographic and pathological size (r=0.44). Physical examination overestimates and ultrasound underestimates breast tumour classification. The most accurate prediction formula was: Pathological tumour size (mm) equals sonographic tumour size (mm)+3 mm. CONCLUSION: When comparing physical examination, mammography and ultrasound for the prediction of the pathological size of a malignant breast tumour, ultrasound is the best predictor. The ensuing regression formula determines pathological size as tumour size by ultrasound+3 mm. However, with the wide 95% confidence interval of +/-11 mm, it remains difficult to predict the exact pathological size for an individual invasive breast tumour. A small deviation in millimetres of the tumour size could lead to a change in treatment and to another prognostic estimate.
Authors: Anees B Chagpar; Lavinia P Middleton; Aysegul A Sahin; Peter Dempsey; Aman U Buzdar; Attiqa N Mirza; Fredrick C Ames; Gildy V Babiera; Barry W Feig; Kelly K Hunt; Henry M Kuerer; Funda Meric-Bernstam; Merrick I Ross; S Eva Singletary Journal: Ann Surg Date: 2006-02 Impact factor: 12.969
Authors: Jason D Keune; Donna B Jeffe; Mario Schootman; Abigail Hoffman; William E Gillanders; Rebecca L Aft Journal: Am J Surg Date: 2010-04 Impact factor: 2.565