Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data

2018 ◽  
Author(s):  
Zhe Zhu ◽  
Michael R. Harowicz ◽  
Jun Zhang ◽  
Ashirbani Saha ◽  
Lars J. Grimm ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ductal Carcinoma In Situ ◽  
Preliminary Data ◽  
Carcinoma In Situ ◽  
Ductal Carcinoma ◽  
Breast Mri ◽  
Invasive Disease

scholarly journals Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ Using Deep Learning Features

2018 ◽  
Vol 15 (3) ◽  
pp. 527-534 ◽  
Author(s):  
Bibo Shi ◽  
Lars J. Grimm ◽  
Maciej A. Mazurowski ◽  
Jay A. Baker ◽  
Jeffrey R. Marks ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ductal Carcinoma In Situ ◽  
Carcinoma In Situ ◽  
Ductal Carcinoma ◽  
Invasive Disease ◽  
Deep Learning Features

scholarly journals Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ

2019 ◽  
Vol 115 ◽  
pp. 103498 ◽  
Author(s):  
Zhe Zhu ◽  
Michael Harowicz ◽  
Jun Zhang ◽  
Ashirbani Saha ◽  
Lars J. Grimm ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ductal Carcinoma In Situ ◽  
Carcinoma In Situ ◽  
Ductal Carcinoma ◽  
Invasive Disease ◽  
Learning Analysis

scholarly journals Advances in Breast MRI in the Setting of Ductal Carcinoma In Situ

2018 ◽  
Vol 53 (4) ◽  
pp. 261-269
Author(s):  
Nita Amornsiripanitch ◽  
Diana L. Lam ◽  
Habib Rahbar
Keyword(s):  
Ductal Carcinoma In Situ ◽  
Carcinoma In Situ ◽  
Ductal Carcinoma ◽  
Breast Mri

Solitary, Well-Circumscribed, T2 Hyperintense Masses on MRI Have Very Low Malignancy Rates

2019 ◽  
Vol 1 (1) ◽  
pp. 37-42 ◽  
Author(s):  
Lars J Grimm ◽  
Michael Enslow ◽  
Sujata V Ghate
Keyword(s):  
Ductal Carcinoma In Situ ◽  
Carcinoma In Situ ◽  
Ductal Carcinoma ◽  
Breast Mri ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Malignancy Rate ◽  
The Masses

Abstract Objective The purpose of this study was to determine the malignancy rate of solitary MRI masses with benign BI-RADS descriptors. Methods A retrospective review was conducted of all breast MRI reports that described a mass with a final BI-RADS assessment of 3, 4, or 5, from February 1, 2005, through February 28, 2014 (n = 1510). Studies were excluded if the mass was not solitary, did not meet formal criteria for a mass, or had classically suspicious BI-RADS features (e.g., washout kinetics, and spiculated margin). The masses were reviewed by 2 fellowship-trained breast radiologists who reported consensus BI-RADS mass margin, shape, internal-enhancement, and kinetics descriptors. The T2 signal was reported as hyperintense if equal to or greater than the signal intensity of the axillary lymph nodes. Pathology results or 2 years of imaging follow-up were recorded. Comparisons were made between mass descriptors and clinical outcomes. Results There were 127 women with 127 masses available for analysis. There were 76 (60%) masses that underwent biopsy for an overall malignancy rate of 4% (5/127): 2 ductal carcinoma in situ (DCIS) and 3 invasive ductal carcinoma. The malignancy rate was 2% (1/59) for T2 hyperintense solitary masses. The malignancy rate was greater than 2% for all of the following BI-RADS descriptors: oval (3%, 3/88), round (5%, 2/39), circumscribed (4%, 5/127), homogeneous (4%, 3/74), and dark internal septations (4%, 2/44). Conclusion T2 hyperintense solitary masses without associated suspicious features have a low malignancy rate, and they could be considered for a BI-RADS 3 final assessment.

scholarly journals Predictive factors for the presence of invasive components in patients diagnosed with ductal carcinoma in situ based on preoperative biopsy

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Kwan Ho Lee ◽  
Jeong Woo Han ◽  
Eun Young Kim ◽  
Ji Sup Yun ◽  
Yong Lai Park ◽  
...  
Keyword(s):  
Ductal Carcinoma In Situ ◽  
Carcinoma In Situ ◽  
Preoperative Diagnosis ◽  
Ductal Carcinoma ◽  
Univariate Analysis ◽  
Breast Mri ◽  
Nuclear Grade ◽  
Preoperative Biopsy ◽  
Areolar Complex

Abstract Background In patients diagnosed with ductal carcinoma in situ (DCIS) with needle biopsy before surgery, invasive component (IC) is often found in the postoperative tissue, which results in altered post-surgical care. However, there are no clinically available factors to predict IC, and few MRI studies are available for the detection of IC in DCIS patients. The purpose of this study was to evaluate which risk factors can predict IC preoperatively. Methods Patients with a DCIS diagnosis based on preoperative biopsy, who underwent breast surgery Kangbuk Samsung Hospital between Jan 2005 and June 2018, were retrospectively evaluated. Clinico-pathological and breast MRI factors were compared between DCIS and DCIS with IC in postsurgical specimens. Results Of the 431 patients with a preoperative diagnosis of DCIS, 34 (7.9%) showed IC during the postoperative pathological investigations, and 217 (50.3%) underwent breast MRI. Among MRI-related factors, Mass-like enhancement on MRI was the sole but significant predictor of IC (HR = 0.26, C.I. = 0.07–0.93, p = 0.038), while nipple-areolar complex invasion, enhancement peak and pattern were not statistically significant. Nuclear grade was the only significant predictor of IC in the analysis of other clinico-pathological factors (HR = 2.39, C.I. = 1.05–5.42, p = 0.038 in univariate analysis, HR = 2.86, C.I. = 1.14–7.14, p = 0.025 in multivariate analysis). Conclusions Mass-like enhancement on MRI and high nuclear grade were associated with IC in patients with preoperative diagnosis of DCIS. Considering the high sensitivity of breast MRI for IC, further evaluation of the predictive value of MRI in preoperative DCIS patients is desirable.

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