Screening Breast MRI Primer: Indications, Current Protocols, and Emerging Techniques

2021 ◽  
Author(s):  
Naziya Samreen ◽  
Cecilia Mercado ◽  
Laura Heacock ◽  
Celin Chacko ◽  
Savannah C Partridge ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Imaging Modality ◽  
Image Interpretation ◽  
Breast Mri ◽  
Gadolinium Contrast ◽  
Dce Mri ◽  
Diffusion Weighted ◽  
Scan Time ◽  
Contrast Enhanced ◽  
Abbreviated Breast Mri

Abstract Breast dynamic contrast-enhanced MRI (DCE-MRI) is the most sensitive imaging modality for the detection of breast cancer. Screening MRI is currently performed predominantly in patients at high risk for breast cancer, but it could be of benefit in patients at intermediate risk for breast cancer and patients with dense breasts. Decreasing scan time and image interpretation time could increase cost-effectiveness, making screening MRI accessible to a larger group of patients. Abbreviated breast MRI (Ab-MRI) reduces scan time by decreasing the number of sequences obtained, but as multiple delayed contrast enhanced sequences are not obtained, no kinetic information is available. Ultrafast techniques rapidly acquire multiple sequences during the first minute of gadolinium contrast injection and provide information about both lesion morphology and vascular kinetics. Diffusion-weighted imaging is a noncontrast MRI technique with the potential to detect mammographically occult cancers. This review article aims to discuss the current indications of breast MRI as a screening tool, examine the standard breast DCE-MRI technique, and explore alternate screening MRI protocols, including Ab-MRI, ultrafast MRI, and noncontrast diffusion-weighted MRI, which can decrease scan time and interpretation time.

scholarly journals Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Dalia Abdelhady ◽  
Amany Abdelbary ◽  
Ahmed H. Afifi ◽  
Alaa-eldin Abdelhamid ◽  
Hebatallah H. M. Hassan
Keyword(s):  
Breast Cancer ◽  
Diffusion Tensor Imaging ◽  
Sensitivity And Specificity ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Breast Mri ◽  
Breast Lesions ◽  
Dce Mri ◽  
Additional Tool ◽  
Diffusion Weighted

Abstract Background Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible. Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity. Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI. Results By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05). Conclusion While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

scholarly journals Differentiation of breast tuberculosis and breast cancer using diffusion-weighted, T2-weighted and dynamic contrast-enhanced magnetic resonance imaging

2018 ◽  
Vol 22 (2) ◽  
Author(s):  
Dibuseng P. Ramaema ◽  
Richard J. Hift
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Resonance Imaging ◽  
Adc Value ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Diffusion Weighted ◽  
Breast Tuberculosis ◽  
Contrast Enhanced

Background: The use of multi-parametric magnetic resonance imaging (MRI) in the evaluation of breast tuberculosis (BTB).Objectives: To evaluate the value of diffusion-weighted imaging (DWI), T2-weighted (T2W) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating breast cancer (BCA) from BTB.Method: We retrospectively studied images of 17 patients with BCA who had undergone preoperative MRI and 6 patients with pathologically proven BTB who underwent DCE-MRI during January 2014 to January 2015.Results: All patients were female, with the age range of BTB patients being 23–43 years and the BCA patients being 31–74 years. Breast cancer patients had a statistically significant lower mean apparent diffusion coefficient (ADC) value (1072.10 +/- 365.14), compared to the BTB group (1690.77 +/- 624.05, p = 0.006). The mean T2-weighted signal intensity (T2SI) was lower for the BCA group (521.56 +/- 233.73) than the BTB group (787.74 +/- 196.04, p = 0.020). An ADC mean cut-off value of 1558.79 yielded 66% sensitivity and 94% specificity, whilst the T2SI cut-off value of 790.20 yielded 83% sensitivity and 83% specificity for differentiating between BTB and BCA. The homogeneous internal enhancement for focal mass was seen in BCA patients only.Conclusion: Multi-parametric MRI incorporating the DWI, T2W and DCE-MRI may be a useful tool to differentiate BCA from BTB.

scholarly journals Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jennifer Xiao ◽  
Habib Rahbar ◽  
Daniel S. Hippe ◽  
Mara H. Rendi ◽  
Elizabeth U. Parker ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Characteristic Curve ◽  
Breast Mri ◽  
Texture Features ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Mri Features ◽  
Contrast Enhanced ◽  
Initial Peak

AbstractAngiogenesis is a critical component of breast cancer development, and identification of imaging-based angiogenesis assays has prognostic and treatment implications. We evaluated the association of semi-quantitative kinetic and radiomic breast cancer features on dynamic contrast-enhanced (DCE)-MRI with microvessel density (MVD), a marker for angiogenesis. Invasive breast cancer kinetic features (initial peak percent enhancement [PE], signal enhancement ratio [SER], functional tumor volume [FTV], and washout fraction [WF]), radiomics features (108 total features reflecting tumor morphology, signal intensity, and texture), and MVD (by histologic CD31 immunostaining) were measured in 27 patients (1/2016–7/2017). Lesions with high MVD levels demonstrated higher peak SER than lesions with low MVD (mean: 1.94 vs. 1.61, area under the receiver operating characteristic curve [AUC] = 0.79, p = 0.009) and higher WF (mean: 50.6% vs. 22.5%, AUC = 0.87, p = 0.001). Several radiomics texture features were also promising for predicting increased MVD (maximum AUC = 0.84, p = 0.002). Our study suggests DCE-MRI can non-invasively assess breast cancer angiogenesis, which could stratify biology and optimize treatments.

scholarly journals Assessing PD-L1 Expression Status Using Radiomic Features from Contrast-Enhanced Breast MRI in Breast Cancer Patients: Initial Results

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6273
Author(s):  
Roberto Lo Gullo ◽  
Hannah Wen ◽  
Jeffrey S. Reiner ◽  
Raza Hoda ◽  
Varadan Sevilimedu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Mri ◽  
Standard Of Care ◽  
Tumor Segmentation ◽  
Imaging Features ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Expression Status

The purpose of this retrospective study was to assess whether radiomics analysis coupled with machine learning (ML) based on standard-of-care dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict PD-L1 expression status in patients with triple negative breast cancer, and to compare the performance of this approach with radiologist review. Patients with biopsy-proven triple negative breast cancer who underwent pre-treatment breast MRI and whose PD-L1 status was available were included. Following 3D tumor segmentation and extraction of radiomic features, radiomic features with significant differences between PD-L1+ and PD-L1− patients were determined, and a final predictive model to predict PD-L1 status was developed using a coarse decision tree and five-fold cross-validation. Separately, all lesions were qualitatively assessed by two radiologists independently according to the BI-RADS lexicon. Of 62 women (mean age 47, range 31–81), 27 had PD-L1− tumors and 35 had PD-L1+ tumors. The final radiomics model to predict PD-L1 status utilized three MRI parameters, i.e., variance (FO), run length variance (RLM), and large zone low grey level emphasis (LZLGLE), for a sensitivity of 90.7%, specificity of 85.1%, and diagnostic accuracy of 88.2%. There were no significant associations between qualitative assessed DCE-MRI imaging features and PD-L1 status. Thus, radiomics analysis coupled with ML based on standard-of-care DCE-MRI is a promising approach to derive prognostic and predictive information and to select patients who could benefit from anti-PD-1/PD-L1 treatment.

scholarly journals Breast cancer in dense breasts: comparative diagnostic merits of contrast-enhanced mammography and diffusion-weighted breast MRI

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Reham Anwar ◽  
Mohamed Amr Farouk ◽  
Wafaa Raafat Abdel Hamid ◽  
Amal Amin Abu El Maati ◽  
Hanan Eissa
Keyword(s):  
Breast Cancer ◽  
Diagnostic Accuracy ◽  
Breast Mri ◽  
Breast Lesions ◽  
Dense Breasts ◽  
Diffusion Weighted ◽  
Contrast Enhanced ◽  
Mass Lesions ◽  
And Diffusion ◽  
Total Accuracy

Abstract Background The study was done to compare the value of contrast-enhanced mammography and diffusion-weighted breast MRI in dense breast screening and accurate detection of the breast cancer with correlation of the findings to the histopathological results. The study included 32 female patients having suspicious breast lesions and underwent digital mammography then scheduled for CESM and MRI DW imaging technique. The imaging findings were correlated to the histopathological findings. Results The study was conducted on 40 breast lesions in 32 female patients having dense breasts; they were classified by the digital mammography into ACR C (59.4%) and ACR D (40.6%). By CESM, there were twenty three lesions (57.5%) as mass lesions and thirteen lesions (32.5%) as non-mass lesions. Four lesions (10%) showed no contrast enhancement. According to the lesion characteristics in diffusion-weighted imaging, the breast lesions were classified into thirty three lesions (82.5%) with restricted diffusion and seven lesions (17.5%) with non-restricted diffusion. The study showed a cutoff ADC value to detect the malignant lesions in the dense breasts ≤ 1.1 × 10-3 s/mm2 at b value of 1000 s/mm2 with a sensitivity of 96.77%, specificity of 66.67%, PPV of 96.77%, NPV of 55.55%, and an overall total accuracy of 92.5%. On comparing the diagnostic accuracy of the CESM to that of the DW MRI, the sensitivity of DW MRI (96.77%) was higher than that of CESM (90.32%). The specificity of DW MRI (66.67%) was higher than that of CESM (33.33%). Total accuracy of DW MRI was higher than that of CESM; they were 90% and 77.5%, respectively. Also, PPV and NPV of DW MRI were 90.91 and 85.71% as compared with 82.35 and 50.00% in CESM, respectively. When comparing the sensitivity of CESM to DW MRI in the detection of multiple breast lesions, they were 88.8 and 100%, respectively. Conclusion CESM is a useful technique in identification of hidden lesions in mammographically dense breasts. DW MRI is a fast, unenhanced modality that can be used as a breast cancer screening modality. CESM and DWI demonstrated good overall diagnostic accuracy in dense breast patients; however, DW MRI has a higher diagnostic accuracy than CESM for the detection of malignant breast lesions and their multiplicity.

Breast MRI Overview: Imaging Techniques and Equipment, Clinical Uses, Image Interpretation

2018 ◽  
Author(s):  
Pragya Dang ◽  
Constance D. Lehman
Keyword(s):  
Breast Cancer ◽  
Imaging Techniques ◽  
Image Interpretation ◽  
Breast Mri ◽  
Mri Imaging ◽  
Applied Physics ◽  
Contrast Enhanced ◽  
Patient Preparation ◽  
High Risk Populations ◽  
Detection And Diagnosis

Contrast-enhanced breast MRI is a highly sensitive modality for early detection and diagnosis of breast cancer, particularly in high-risk populations. It has also been shown to be superior to mammography in establishing the extent of disease in patients with newly diagnosed breast cancer. This chapter, appearing in the section on breast cancer overview, reviews breast MRI imaging technique, clinical uses, gives an overview of image interpretation, and applied physics. Topics discussed include equipment such as hardware, imaging protocols, patient preparation and positioning, and relevant physics. Additionally, clinical situations where the use of breast MRI is appropriate, systematic review of images, and formulation of final assessment and recommendations in accordance with the ACR BI-RADS imaging lexicon are discussed in this chapter.

scholarly journals Discrimination of breast cancer from healthy breast tissues using a three-component diffusion-weighted MRI model

2020 ◽  
Author(s):  
Maren M. Sjaastad Andreassen ◽  
Ana E. Rodriguez-Soto ◽  
Christopher C. Conlin ◽  
Igor Vidic ◽  
Tyler M. Seibert ◽  
...  
Keyword(s):  
Breast Cancer ◽  
False Positive Rate ◽  
B Value ◽  
Cancer Tissue ◽  
Breast Cancer Patients ◽  
Gadolinium Contrast ◽  
Diffusion Weighted ◽  
Scan Time ◽  
Apparent Diffusion ◽  
Breast Tissues

Purpose: Diffusion-weighted magnetic resonance imaging (DW-MRI) is a contrast-free modality that has demonstrated ability to discriminate between pre-defined benign and malignant breast lesions. However, the ability of DW-MRI to discriminate cancer tissue from all other breast tissues in a clinical setting is unknown. Here we explore the ability to distinguish breast cancer from healthy breast tissues using signal contributions from the newly developed three-component multi-b-value DW-MRI model. Experimental design: Pathology-proven breast cancer patients from two datasets (n=81 and n=25) underwent multi-b-value DW-MRI. The three-component signal contributions C1 and C2 and their product, C1C2, were compared to the image defined on maximum b-value (DWImax), conventional apparent diffusion coefficient (ADC), and apparent diffusion kurtosis (Kapp). Ability to discriminate between cancer and healthy breast tissues was assessed by the false positive rate given sensitivity of 80% (FPR80) and receiver operating characteristic (ROC) area under the curve (AUC). Results: Mean FPR80 for both datasets was 0.016 (95%CI=0.008-0.024) for C1C2, 0.136 (95%CI=0.092-0.180) for C1, 0.068 (95%CI=0.049-0.087) for C2, 0.159 (95%CI=0.114-0.204) for DWImax, 0.731 (95%CI=0.692-0.770) for ADC and 0.684 (95%CI=0.660-0.709) for Kapp. Mean ROC AUC for C1C2 was 0.984 (95%CI=0.977-0.991). Conclusions: The three-component model yields a clinically useful discrimination between cancer and healthy breast tissues, superior to other DW-MRI methods and obliviating pre-defining lesions by radiologists. This novel DW-MRI method may serve as non-contrast alternative to standard-of-care dynamic contrast-enhanced MRI (DCE-MRI); removing the need to administer Gadolinium contrast decreases scan time and any accumulation of Gadolinium in the brain.

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