BACKGROUND: Under-estimation of invasion components occur occasionally at core needle diagnosed ductal carcinoma in situ (DCIS) that may change the prognosis or treatment planning. PURPOSE: To determine whether enhanced magnetic resonance imaging (MRI) features of biopsy-proven ductal cancers in situ help predict the under-estimation of invasive breast cancers. MATERIAL AND METHODS: After a retrospective review of the enhanced MRI features on preoperative proven breast ductal cancers in situ by biopsy, tumor morphology (mass and non-mass), enhancing curve patterns, and non-mass enhanced appearances were compared between pure ductal cancers in situ and invasive ductal cancers (IDCs) after surgery. A statistical analysis was performed, and P values <0.05 were deemed significant. RESULTS: Twenty-five breast cancers from 24 women were analyzed. Eleven DCIS remained as DCISs, and 14 were upgraded to IDC after surgery. Eight of 14 IDCs (57%) and one of 11 DCISs (9%) presented as mass lesions; otherwise six (43%) IDCs and 10 (91%) DCISs were non-mass lesions (P = 0.013). Among the non-mass cancers, six of 10 DCISs (60%) were focally enhanced and six of 6 IDCs (100%) were segmentally enhanced. The overall cancer sizes measured on enhanced MRI were moderately correlated with histopathology, with a Spearman's rank correlation coefficient of 0.656 (P = 0.001). The mean diameter of the IDCs was larger than that of the pure DCISs on enhanced MRI (2.69 ± 1.42 cm for IDC and 1.62 ± 1.03 cm for DCIS; P = 0.048). The cut-off size was optimally selected at 1.95 cm with a 64% sensitivity and a 77% specificity, using a receiver-operating characteristic curve. The enhancement curves, with washout or persistent rising, were statistically insignificant (P = 0.085 and 0.93, respectively). CONCLUSION: Enhanced MRI provided informative morphology and size features that might help to predict the underestimation of invasiveness in preoperative biopsy-proven DCIS.
BACKGROUND: Under-estimation of invasion components occur occasionally at core needle diagnosed ductal carcinoma in situ (DCIS) that may change the prognosis or treatment planning. PURPOSE: To determine whether enhanced magnetic resonance imaging (MRI) features of biopsy-proven ductal cancers in situ help predict the under-estimation of invasive breast cancers. MATERIAL AND METHODS: After a retrospective review of the enhanced MRI features on preoperative proven breast ductal cancers in situ by biopsy, tumor morphology (mass and non-mass), enhancing curve patterns, and non-mass enhanced appearances were compared between pure ductal cancers in situ and invasive ductal cancers (IDCs) after surgery. A statistical analysis was performed, and P values <0.05 were deemed significant. RESULTS: Twenty-five breast cancers from 24 women were analyzed. Eleven DCIS remained as DCISs, and 14 were upgraded to IDC after surgery. Eight of 14 IDCs (57%) and one of 11 DCISs (9%) presented as mass lesions; otherwise six (43%) IDCs and 10 (91%) DCISs were non-mass lesions (P = 0.013). Among the non-mass cancers, six of 10 DCISs (60%) were focally enhanced and six of 6 IDCs (100%) were segmentally enhanced. The overall cancer sizes measured on enhanced MRI were moderately correlated with histopathology, with a Spearman's rank correlation coefficient of 0.656 (P = 0.001). The mean diameter of the IDCs was larger than that of the pure DCISs on enhanced MRI (2.69 ± 1.42 cm for IDC and 1.62 ± 1.03 cm for DCIS; P = 0.048). The cut-off size was optimally selected at 1.95 cm with a 64% sensitivity and a 77% specificity, using a receiver-operating characteristic curve. The enhancement curves, with washout or persistent rising, were statistically insignificant (P = 0.085 and 0.93, respectively). CONCLUSION: Enhanced MRI provided informative morphology and size features that might help to predict the underestimation of invasiveness in preoperative biopsy-proven DCIS.
Authors: Michael R Harowicz; Ashirbani Saha; Lars J Grimm; P Kelly Marcom; Jeffrey R Marks; E Shelley Hwang; Maciej A Mazurowski Journal: J Magn Reson Imaging Date: 2017-02-09 Impact factor: 4.813
Authors: Dorota Jakubowski Wisner; E Shelley Hwang; C Belinda Chang; Hilda H Tso; Bonnie N Joe; Juan N Lessing; Ying Lu; Nola M Hylton Journal: Breast J Date: 2013 Nov-Dec Impact factor: 2.431
Authors: Kwan Ho Lee; Jeong Woo Han; Eun Young Kim; Ji Sup Yun; Yong Lai Park; Chan Heun Park Journal: BMC Cancer Date: 2019-12-10 Impact factor: 4.430