Utility of Targeted Sonography in Management of Probably Benign Breast Lesions Identified on Magnetic Resonance Imaging

2012 ◽  
Vol 31 (7) ◽  
pp. 1033-1040 ◽  
Author(s):  
Ana P. Lourenco ◽  
Michelle Tsang Mui Chung ◽  
Martha B. Mainiero
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Benign Breast Lesions

Washout of Mass-Like Benign Breast Lesions at Dynamic Magnetic Resonance Imaging

2012 ◽  
Vol 36 (3) ◽  
pp. 301-305 ◽  
Author(s):  
Penampai Tannaphai ◽  
Rubina Manuela Trimboli ◽  
Luca Alessandro Carbonaro ◽  
Sara Viganò ◽  
Giovanni Di Leo ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Dynamic Magnetic Resonance Imaging ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Dynamic Magnetic Resonance ◽  
Benign Breast Lesions

scholarly journals Evaluation of diagnostic value of ultrasound and magnetic resonance imaging for malignant and benign breast lesions

2018 ◽  
Vol 2 (5) ◽  
Author(s):  
Yanni Zeng ◽  
Hongwei Zhang ◽  
Jiuxia Zhang ◽  
Yan Yu ◽  
Liangjin Liu
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Statistical Significance ◽  
Diagnostic Value ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Benign Lesions ◽  
Specificity And Sensitivity ◽  
Treatment Data ◽  
Benign Breast Lesions

[Abstract] Objectives: To investigate diagnostic value of ultrasound and magnetic resonance imaging (MRI) for malignant and benign breast lesions. Methods: Retrospective analysis of treatment data of 48 patients diagnosed with malignant and benign breast lesions in our hospital, collected from December 2017 to November 2018. A total number of 56 breast masses were examined by both ultrasound and MRI, and were compared with postoperative pathological biopsy results. Results: Postoperative pathological biopsy results showed that there were 26 and 30 malignant and benign lesions respectively. Comparison of MRI curve type of malignant and benign lesions showed statistical significance (P<0.05). By comparison with pathological biopsy results, specificity and sensitivity of ultrasound diagnosis were 83.33% (25/30) and 84.61% (22/26) respectively; specificity and sensitivity of MRI diagnosis were 96.66% (29/30) and 92.30% (24/26) respectively. Conclusions: Ultrasonographic examination of malignant and benign breast lesions is straight-forward, simple and inexpensive. Accuracy, specificity and sensitivity of MRI are significantly higher than ultrasound in examining malignant and benign breast lesions, this can reduce misdiagnosis.

scholarly journals Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yu Ji ◽  
Hui Li ◽  
Alexandra V. Edwards ◽  
John Papaioannou ◽  
Wenjuan Ma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Machine Learning ◽  
Magnetic Resonance ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Single Institution ◽  
Dce Mri ◽  
Benign Breast Lesions ◽  
Mass Lesions

Abstract Background As artificial intelligence methods for the diagnosis of disease advance, we aimed to evaluate machine learning in the predictive task of distinguishing between malignant and benign breast lesions on an independent clinical magnetic resonance imaging (MRI) dataset within a single institution for subsequent use as a computer aid for radiologists. Methods Computer analysis was conducted on consecutive dynamic contrast-enhanced MRI (DCE-MRI) studies from 1483 breast cancer and 496 benign patients who underwent MRI examinations between February 2015 and October 2017; with the age ranges of the cancer and benign patients being 19 to 77 and 16 to 76 years old, respectively. Cases were separated into a training dataset (years 2015 & 2016; 1444 cases) and an independent testing dataset (year 2017; 535 cases) based solely on MRI examination date. After radiologist indication of the lesion, the computer automatically segmented and extracted radiomic features, which were subsequently merged with a support-vector machine (SVM) to yield a lesion signature. Area under the receiving operating characteristic (ROC) curve (AUC) with 95% confidence intervals (CI) served as the primary figure of merit in the statistical evaluation for this clinical classification task. Results In the task of distinguishing malignant and benign breast lesions DCE-MRI, the trained predictive model yielded an AUC value of 0.89 (95% CI: 0.858, 0.922) on the independent image set. AUC values of 0.88 (95% CI: 0.845, 0.926) and 0.90 (95% CI: 0.837, 0.940) were obtained for mass lesions only and non-mass lesions only, respectively. Compared with actual clinical management decisions, the predictive model achieved 99.5% sensitivity with 9.6% fewer recommended biopsies. Conclusion On an independent, consecutive clinical dataset within a single institution, a trained machine learning system yielded promising performance in distinguishing between malignant and benign breast lesions.

Magnetic Resonance Imaging of Benign Breast Lesions

2017 ◽  
pp. 153-164
Author(s):  
LW Lo ◽  
◽  
T Wong ◽  
EPY Fung ◽  
MH Lai ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Benign Breast Lesions

Benign Breast Lesions that Simulate Malignancy: Magnetic Resonance Imaging with Radiologic–Pathologic Correlation

2007 ◽  
Vol 36 (2) ◽  
pp. 66-82 ◽  
Author(s):  
Alfonso Iglesias ◽  
Mercedes Arias ◽  
Paz Santiago ◽  
Marta Rodríguez ◽  
Jorge Mañas ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Pathologic Correlation ◽  
Benign Breast Lesions

scholarly journals Effects of Neoadjuvant Chemotherapy on Benign Breast Lesions Compared to Cancers: Should an Additional Lesion on Magnetic Resonance Imaging Responding Similar to Cancer after Neoadjuvant Chemotherapy be Viewed with Suspicion?

2016 ◽  
Vol 6 ◽  
pp. 39
Author(s):  
Rebecca Leddy ◽  
Abid Irshad ◽  
Lara Hewett ◽  
Heather Collins ◽  
Frank Vento ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Neoadjuvant Chemotherapy ◽  
Breast Lesions ◽  
Resonance Imaging ◽  
Benign Lesions ◽  
Mean Size ◽  
Malignant Lesions ◽  
The Mean ◽  
Benign Breast Lesions

Purpose: Determining the effects of neoadjuvant chemotherapy (NAC) on benign breast lesions and to evaluate their response in comparison to breast cancers. Methods: A retrospective analysis performed on breast cancer patients between 2008 and 2014 to identify patients who had a pre- and post-NAC magnetic resonance imaging (MRI) and biopsy-proven benign lesions. Pre- and post-NAC size and intensity of enhancement of benign lesions and cancers were measured. Breast glandularity and background enhancement were graded. A 2 × 2 repeated measures ANOVAs and Sidak post hoc tests were conducted for multiple comparisons. Paired t-tests were conducted to examine changes over time, and two-tailed P values were reported. Results: The effects of NAC in 38 cancers were compared to the effects of NAC in 47 benign lesions in these patients. From pre- to post-NAC, the mean size (cm) of malignant lesions on MRI decreased from 4.09 (±standard deviation [SD] 2.51) to 1.54 (±SD 2.32), (P < 0.001); the mean size (cm) of benign lesions decreased from 0.83 (±SD 0.54 cm) to 0.28 (±SD 0.51), (P < 0.001). Both benign and malignant lesions decreased in size after NAC, the size reduction in malignant lesions was significantly greater than benign lesions. From pre- to post-NAC, the mean lesion enhancement of the malignant lesions (scale 1–4) decreased from 3.43 (±SD 0.80) to 1.02 (±SD 1.34); the mean lesion enhancement of benign lesions decreased from 2.96 (±SD 1.04) to 0.98 (±SD 1.51). For both benign and malignant lesions, there was a significant overall reduction in enhancement after NAC from moderate at pre-NAC to minimal at post-NAC, P < 0.001. There was no overall difference in the enhancement of cancers (mean = 2.22, SD = 0.79) versus benign lesions (mean = 1.97, SD = 1.08), (P = 0.23). There was no significant change in glandularity from pretherapy (mean = 3.11, SD = 0.84) to posttherapy (mean = 3.13, SD = 0.82), P < 0.001. Conclusion: Similar to cancers, benign breast lesions also show a significant decrease in size and enhancement after NAC; however, the decrease in size is less compared to cancers.

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