Comparison of mammography, digital breast tomosynthesis, automated breast ultrasound, magnetic resonance imaging in evaluation of residual tumor after neoadjuvant chemotherapy

2018 ◽  
Vol 108 ◽  
pp. 261-268 ◽  
Author(s):  
Jiyoon Park ◽  
Eun Young Chae ◽  
Joo Hee Cha ◽  
Hee Jung Shin ◽  
Woo Jung Choi ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Neoadjuvant Chemotherapy ◽  
Digital Breast Tomosynthesis ◽  
Residual Tumor ◽  
Breast Ultrasound ◽  
Resonance Imaging ◽  
Breast Tomosynthesis ◽  
Automated Breast Ultrasound

scholarly journals Comparative Study of Digital Breast Tomosynthesis (DBT) with and without Ultrasound versus Breast Magnetic Resonance Imaging (MRI) in Detecting Breast Lesion

2022 ◽  
Vol 19 (2) ◽  
pp. 759
Author(s):  
Janice Hui Ling Goh ◽  
Toh Leong Tan ◽  
Suraya Aziz ◽  
Iqbal Hussain Rizuana
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Diagnostic Performance ◽  
Breast Lesion ◽  
Breast Magnetic Resonance Imaging ◽  
Digital Breast Tomosynthesis ◽  
Resonance Imaging ◽  
Breast Tomosynthesis ◽  
Breast Magnetic Resonance ◽  
Magnetic Resonance Imaging Mri

Digital breast tomosynthesis (DBT) is a fairly recent breast imaging technique invented to overcome the challenges of overlapping breast tissue. Ultrasonography (USG) was used as a complementary tool to DBT for the purpose of this study. Nonetheless, breast magnetic resonance imaging (MRI) remains the most sensitive tool to detect breast lesion. The purpose of this study was to evaluate diagnostic performance of DBT, with and without USG, versus breast MRI in correlation to histopathological examination (HPE). This was a retrospective study in a university hospital over a duration of 24 months. Findings were acquired from a formal report and were correlated with HPE. The sensitivity of DBT with or without USG was lower than MRI. However, the accuracy, specificity and PPV were raised with the aid of USG to equivalent or better than MRI. These three modalities showed statistically significant in correlation with HPE (p < 0.005, chi-squared). Generally, DBT alone has lower sensitivity as compared to MRI. However, it is reassuring that DBT + USG could significantly improve diagnostic performance to that comparable to MRI. In conclusion, results of this study are vital to centers which do not have MRI, as complementary ultrasound can accentuate diagnostic performance of DBT.

scholarly journals Diagnostic Value of Digital Breast Tomosynthesis Combined with Magnetic Resonance Imaging for Breast Cancer in Dense Breast Tissues

2021 ◽  
Vol 18 (4) ◽  
Author(s):  
Hongfang Xu ◽  
Wei Zeng ◽  
Zehong Fu ◽  
Qing Cui
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Early Diagnosis ◽  
Digital Breast Tomosynthesis ◽  
Diagnostic Value ◽  
Diagnostic Efficiency ◽  
Breast Cancer Patients ◽  
Resonance Imaging ◽  
Breast Tomosynthesis

Background: Early diagnosis and timely treatment are crucial for breast cancer patients. Objectives: This study aimed to investigate the diagnostic value of full-field digital mammography (FFDM), digital breast tomosynthesis (DBT), and magnetic resonance imaging (MRI) for breast cancer. Patients and Methods: This study was performed on 210 patients diagnosed with breast cancer and benign breast lesions (n = 105) by FFDM, DBT, MRI, and pathological examination from January 2019 to December 2020. The patients’ imaging and clinical data were retrospectively analyzed. The lesions were evaluated according to the breast imaging-reporting and data system, with pathological diagnosis as the gold standard. The diagnostic efficiency of the examination methods was analyzed by plotting the receiver operating characteristic (ROC) curves. The DBT and MRI results were finally compared. Results: In 210 patients, 105 benign and 105 malignant lesions were detected. The area under the ROC curve (AUC) of FFDM, DBT, MRI, FFDM + DBT, and FFDM + MRI was 0.734, 0.857, 0.883, 0.865, and 0.924, respectively. Based on the results, the AUC values were significantly higher for DBT, MRI, FFDM + DBT, and FFDM + MRI compared to FFDM (P < 0.05), while similar values were reported for the former methods (P > 0.05). The diagnostic sensitivity of MRI was higher than that of DBT and FFDM; the sensitivity of DBT was higher than that of FFDM; and the specificity and positive predictive value were higher for DBT compared to MRI and FFDM. Conclusion: Compared to FFDM, DBT and FFDM + DBT could significantly improve the diagnostic efficiency of breast cancer; the diagnostic efficiency of these modalities was comparable to that of MRI and FFDM + MRI. The sensitivity of DBT was lower than that of MRI and higher than that of FFDM, while its specificity and positive predictive value were higher than those of MRI. Overall, FFDM + DBT and FFDM + MRI are conducive to early diagnosis.

scholarly journals Direct comparison of magnetic resonance imaging and pathological shrinkage patterns of triple-negative breast cancer after neoadjuvant chemotherapy

2020 ◽  
Author(s):  
Katsuhiro Yoshikawa ◽  
Mitsuaki Ishida ◽  
Naoki Kan ◽  
Hirotsugu Yanai ◽  
Koji Tsuta ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Tumor Size ◽  
Triple Negative ◽  
Residual Tumor ◽  
Predictive Equation ◽  
Resonance Imaging

Abstract Background We aimed to investigate the usefulness of magnetic resonance imaging (MRI) and histopathological shrinkage patterns to formulate a predictive equation for estimating residual tumor size after neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients.Methods We enrolled 34 TNBC patients who underwent MRI before and after NAC. The MRI and histopathological shrinkage patterns were analyzed and classified into five categories—types I and II (concentric shrinkage without or with surrounding lesions, respectively), type III (shrinkage with residual multinodular lesions), type IV (diffuse contrast enhancement in the entire quadrant), and non-visualization. The residual tumor sizes following MRI and histopathological examination were also compared.Results The most common MRI and histopathological shrinkage pattern was type I (41.2% and 38.2%, respectively), followed by non-visualization (26.5% and 32.4%, respectively); the concordance rate between MRI and histopathological shrinkage patterns was 41.2%. There was a strong correlation between MRI tumor size and pathological tumor size (r = 0.89). Based on these findings, a predictive equation for pathological tumor size was formulated as follows: pathological tumor size \left(mm\right) = 1.1502 \times \left(MRI tumor size \right[mm\left]\right) + 8.4277.Conclusions Our equation may aid accurate preoperative assessment. Further studies are needed to determine its predictive value and applicability.

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