Conventional Breast MRI Research Articles

Feasibility of online non-rigid motion correction for high-resolution supine breast MRI.

Conventional breast MRI is performed in the prone position with a dedicated coil. This allows high-resolution images without breast motion, but the patient position is inconsistent with that of other breast imaging modalities or interventions. Supine breast MRI may be an interesting alternative, but respiratory motion becomes an issue. Motion correction methods have typically been performed offline, for instance, the corrected images were not directly accessible from the scanner console. In this work, we seek to show the feasibility of a fast, online, motion-corrected reconstruction integrated into the clinical workflow. Fully sampled T2 -weighted (T2 w) and accelerated T1 -weighted (T1 w) breast supine MR images were acquired during free-breathing and were reconstructed using a non-rigid motion correction technique (generalized reconstruction by inversion of coupled systems). Online reconstruction was implemented using a dedicated system combining the MR raw data and respiratory signals from an external motion sensor. Reconstruction parameters were optimized on a parallel computing platform, and image quality was assessed by objective metrics and by radiologist scoring. Online reconstruction time was 2 to 2.5 min. The metrics and the scores related to the motion artifacts significantly improved for both T2 w and T1 w sequences. The overall quality of T2 w images was approaching that of the prone images, whereas the quality of T1 w images remained significantly lower. The proposed online algorithm allows a noticeable reduction of motion artifacts and an improvement of the diagnostic quality for supine breast imaging with a clinically acceptable reconstruction time. These findings serve as a starting point for further development aimed at improving the quality of T1 w images.

Advances in Abbreviated Breast MRI and Ultrafast Imaging

Abbreviated breast MRI is an emerging technique that is being incorporated into clinical practice for breast cancer imaging and screening. Conventional breast MRI includes barriers such as high examination cost and lengthy examination times which make its use in the screening setting challenging. Abbreviated MRI aims to address these pitfalls by reducing overall examination time and increasing accessibility to MRI while preserving diagnostic accuracy. Sequences selected for abbreviated MRI protocols allow for preserved accuracy in breast cancer detection and characterization. Novel techniques such as ultrafast imaging are being used to provide kinetic information from early post-contrast imaging.

Role of conventional magnetic resonance imaging and diffusion-weighted imaging in evaluation of breast lesions

Background and Aim This study aimed to evaluate the role of diffusion-weighted imaging (DWI) and apparent diffusion coefficient in diagnosis of the breast lesions. Patients and methods This study included 100 patients referred to the Radiology Department of Al-Azhar Assiut University Hospital from February 2018 to May 2020 for DWI MRI examination with a provisional diagnosis of breast lesions. All patients were recruited after meeting the inclusion criteria. They underwent clinical examination, mammography, ultrasonography, and contrast-enhanced MRI with DWI. Results Our study included 100 cases. The combined MRI protocol of dynamic contrast-enhanced (DCE)-MRI and DWI was true positive in 60 and true negative in 30 patients. The combined MRI protocol of DCE-MRI and DWI provided a sensitivity of 92%, a specificity of 90%, a positive predictive value of 95.8%, a negative predictive value of 81.8% and accuracy of 91.43%. In this study, the addition of DWI to standard DCE-MRI provided a 10% increase in the specificity of breast MRI, with a 4% decrease in the sensitivity. Conclusion DWI is a short unenhanced scan and had the highest specificity compared with other imaging modalities, as it reduced the false-positive results. It should be added to conventional breast MRI to increase the sensitivity and specificity of MRI.

Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions.

To assess the diagnostic performance of radiomic analysis using high temporal resolution (HTR)-dynamic contrast enhancement (DCE) MR sequences compared to BI-RADS analysis to distinguish benign from malignant breast lesions. We retrospectively analyzed data from consecutive women who underwent breast MRI including HTR-DCE MR sequencing for abnormal enhancing lesions and who had subsequent pathological analysis at our tertiary center. Semi-quantitative enhancement parameters and textural features were extracted. Temporal change across each phase of textural features in HTR-DCE MR sequences was calculated and called "kinetic textural parameters." Statistical analysis by LASSO logistic regression and cross validation was performed to build a model. The diagnostic performance of the radiomic model was compared to the results of BI-RADS MR score analysis. We included 117 women with a mean age of 54years (28-88). Of the 174 lesions analyzed, 75 were benign and 99 malignant. Seven semi-quantitative enhancement parameters and 57 textural features were extracted. Regression analysis selected 15 significant variables in a radiomic model (called "malignant probability score") which displayed an AUC = 0.876 (sensitivity = 0.98, specificity = 0.52, accuracy = 0.78). The performance of the malignant probability score to distinguish benign from malignant breast lesions (AUC = 0.876, 95%CI 0.825-0.925) was significantly better than that of BI-RADS analysis (AUC = 0.831, 95%CI 0.769-0.892). The radiomic model significantly reduced false positives (42%) with the same number of missed cancers (n = 2). A radiomic model including kinetic textural features extracted from an HTR-DCE MR sequence improves diagnostic performance over BI-RADS analysis. • Radiomic analysis using HTR-DCE is of better diagnostic performance (AUC = 0.876) than conventional breast MRI reading with BI-RADS (AUC = 0.831) (p < 0.001). • A radiomic malignant probability score under 19.5% gives a negative predictive value of 100% while a malignant probability score over 81% gives a positive predictive value of 100%. • Kinetic textural features extracted from HTR-DCE-MRI have a major role to play in distinguishing benign from malignant breast lesions.

Diffusion weighted (DW) MRI role in characterization of breast lesions using absolute and normalized ADC values

IntroductionDiffusion-weighted imaging (DWI) is a modality that depicts the diffusivity of water molecules. This technique has the potential to play an adjunct role to conventional and dynamic MRI in the assessment of breast tissue. Aim of workTo evaluate the role of DWI with absolute and normalized ADC value measurements in characterization of breast lesions. Patients and methodsSeventy patients with mass or non mass lesions on mammography or breast ultrasound were included in this study. DWI were added to routine MR study with calculation of ADC absolute value and normalized ratio for lesions before biopsy of their breast lesions and results were correlated with histopathology. ResultsThirty out of 70 detected lesions were malignant. Malignant lesions showed lower ADC values and lower ratio of normalized ADC than benign lesions. The ROC study revealed that a cutoff ADC value of 1.1 × 10−3 mm2/s and normalized ADC ratio of 0.9 had high sensitivity of 89.75%, and 92.2% with specificity of 94.4% and 94.4% respectively in the differentiation between benign and malignant breast lesions. ConclusionDWI is a short unenhanced scan that can be potential adjunct to conventional breast MRI and can be used to accurately characterize breast lesions with high sensitivity and specificity Suggested.

Using quantitative features extracted from T2-weighted MRI to improve breast MRI computer-aided diagnosis (CAD).

Computer-aided diagnosis (CAD) has been proposed for breast MRI as a tool to standardize evaluation, to automate time-consuming analysis, and to aid the diagnostic decision process by radiologists. T2w MRI findings are diagnostically complementary to T1w DCE-MRI findings in the breast and prior research showed that measuring the T2w intensity of a lesion relative to a tissue of reference improves diagnostic accuracy. The diagnostic value of this information in CAD has not been yet quantified. This study proposes an automatic method of assessing relative T2w lesion intensity without the need to select a reference region. We also evaluate the effect of adding this feature to other T2w and T1w image features in the predictive performance of a breast lesion classifier for differential diagnosis of benign and malignant lesions. An automated feature of relative T2w lesion intensity was developed using a quantitative regression model. The diagnostic performance of the proposed feature in addition to T2w texture was compared to the performance of a conventional breast MRI CAD system based on T1w DCE-MRI features alone. The added contribution of T2w features to more conventional T1w-based features was investigated using classification rules extracted from the lesion classifier. After institutional review board approval that waived informed consent, we identified 627 breast lesions (245 malignant, 382 benign) diagnosed after undergoing breast MRI at our institution between 2007 and 2014. An increase in diagnostic performance in terms of area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was observed with the additional T2w features and the proposed quantitative feature of relative T2w lesion intensity. AUC increased from 0.80 to 0.83 and this difference was statistically significant (adjusted p-value = 0.020).

Detailed microarchitecture analysis of breast tumors using diffusion tensor imaging

Introduction Conventional breast MRI has shown high diagnostic sensitivities for the detection of breast cancer, whereas relatively low specificities have been reported, resulting in many unnecessary biopsies of benign lesions. Purpose The main purpose of this study was to investigate whether diffusion measures of anisotropy (DWI & DTI) can improve the discrimination between benign and malignant lesions. Moreover, using detailed DTI microstructure analysis, we sought to investigate the contribution of the architecture of breast fibroglandular tissue in the differential diagnosis of malignancy. Methods and materials The study included 58 women with a total of 86 breast lesions. DTI and DWI were performed complementary to dynamic contrast MRI. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and fractional anisotropy (FA) were measured for lesions and contralateral breast parenchyma of each patient. All values were compared between malignant, benign lesions and the normal parenchyma by univariate and multivariate analyses. Results The FA values showed high variation and hence moderate statistical significance. Nevertheless the analysis of DTI vector maps and parametric maps, revealed significantly lower values of the tumor’s orthogonal diffusion coefficients λ1, λ2, λ3 comparing to normal breast and benign tissue. Despite the significant overlap the FA values of malignant tissue were significantly higher than normal and benign tissue (p = 0.002). ROC curve analysis was also performed for every discrimination factor studied. Conclusion ADC measures have accurate discrimination ability in all cases. Careful microstructural analysis revealed significantly lower values of the tumor’s prime diffusion coefficient λ1, and may be used as a potential indicator.

Role of diffusion weighted images combined with breast MRI in improving the detection and differentiation of breast lesions

PurposeTo assess the impact of diffusion-weighted images as a complementary tool to conventional breast MRI in the evaluation of various breast lesions. Materials and methodsFrom November 2013 to June 2014 thirty patients referred from breast clinic by breast symptoms and abnormal sono-mammography lesions have been included in this study. All patients underwent breast DCE-MRI combined with DWI and the results were compared with the histopathological examination which was used as the standard diagnostic method. ResultsThe study included thirty patients complaining of breast lesions, 35 lesions were detected, according to the histopathological analysis, there were 20 malignant lesions (57.14%) and 15 benign lesions (42.86%). DCE-MRI had a sensitivity of 80%, a specificity of 73.33%, PPV of 80%, NPV of 73.3% and accuracy of 77.14%. The malignant lesions showed a mean ADC value of 1.03±0.35. Alternatively, the benign lesions showed a mean ADC value of 1.38±0.26. Among the 20 malignant lesions, 17 lesions showed an ADC value ⩽1.20mm2/s and 3 lesions showed an ADC value >1.20mm2/s. While among the 15 benign lesions, 14 lesions showed ADC value >1.20mm2/s and 1 lesion showed an ADC value ⩽1.20. The ROC curve showed that the best ADC cut-off value to differentiate between benign and malignant lesions was 1.2mm2/s (P<0.001) with sensitivity, specificity, PPV, NPV and accuracy of 85%, 93.33%, 94.4%, 82.4% and 90.3% respectively. ConclusionDWI had a higher sensitivity and specificity than DCE-MRI with ADC cut off value 1.20. This value was a sensitive and specific parameter in differentiating benign and malignant breast lesions.

Diffusion-weighted MR imaging: role in the differential diagnosis of breast lesions.

To evaluate the diagnostic value of magnetic resonance diffusion-weighted imaging (DWI) using apparent diffusion coefficient (ADC) values to the characterization of breast lesions and differentiation of benign and malignant lesions. Thirty-seven women (mean age, 38 years) with 37 enrolled in the study. DWI and ADC maps in the axial plane were obtained using a 1.5 Tesla MRI device. Mean ADC measurements were calculated among cysts, normal fibroglandular tissue, benign lesions and malignant lesions were evaluated. Out of 37 women, 4 had normally breast MRI findings. The diagnosis of remaining 33 patients with 37 breast lesions were as follows; malign lesions (n = 23), benign lesions (n = 10) and simple breast cyst (n = 4). The ADC values were as follows (in units of 10(-3) mm2/s): Normal fibroglandular tissue (range: 1.39-2.06; mean: 1.61 ± 0.23), benign breast lesions (range: 1.09-1.76; mean: 1.47 ± 0.25), cyts (range: 2.27-2.46, mean: 2.37 ± 0.07) and malignant breast lesions (range: 0.78-1.26, mean: 0.96 ± 0.25). The mean ADC obtained from malignant breast lesions was statistically different from that observed in benign solid lesions (p < < 0.01) and normal fibroglandular breast tissue (p < 0.01). Furthermore, the mean ADC values of benign breast lesions was not statistically different from cyst (p ≥ 0.01) and normal fibroglandular breast tissue (p ≥ 0.01). A ADC value of 1.1 x 10(-3) mm'/s as a treshold value provided differantiation for malign and benign lesions, with a sensitivity of 91.3% and a specificity of 85.7% compared with conventional breast MRI values. DWI with quantitative ADC measurements is a reliable tool for differentiation of benign and malignant breast lesions.

Role of MR Spectroscopy in Characterization of Breast Masses

Introduction: Dynamic contrast enhanced magnetic resonance imaging “MRI” is not 100 percent accurate in distinguishing benign from malignant lesions, resulting in a large number of breast biopsy procedures recommended on the basis of imaging findings. Proton magnetic resonance spectroscopy “¹H MRS” can provide chemical information about a lesion by measuring the levels of choline compounds, which are markers of an active tumor. In most cases, the results indicate whether the lesion is cancerous without need for biopsy. In addition to being used in breast cancer diagnosis, in vivo ¹H MRS has also been used to monitor breast cancer response to chemotherapy as well as in differentiating between scar tissue and recurrent cancer after breast-conserving therapy. Aim of the work: To evaluate the diagnostic performance of magnetic resonance spectroscopy “MRS” in characterization of breast masses with histopathologic findings or follow up used as the reference standard. Methods: The studied group included 50 female patients referred for MRI breast for workup of a suspicious clinical, mammographic, or sonographic abnormality. ¹H MRS was added to the routine study. Results of the contrast enhanced bilateral breast MRI and ¹H MRS of the 50 patients were all reported and compared with the histo-pathological results of surgery or biopsy and with the results of follow up of lesions that were not surgically removed or biopsied. Results: there was a highly significant relation between ¹H MRS and histopathological. Follow Up results with p value = 0.005. The sensitivity, specificity, positive and negative predictive values of ¹H MRS for characterization of suspicious breast lesions in patients included in the study, were 90%, 93.3%, 90%, and 93.3% respectively. Conclusion: ¹H MRS is a short non-invasive scan that can be inserted easily into standard clinical breast MRI protocols as a potential adjunct that can be added routinely to conventional breast MRI. Detection of choline peak with estimation of the choline signal to noise ratio “SNR” can accurately differentiate benign from malignant breast lesions with high sensitivity and specificity especially when its results are combined with the results of the standard dynamic MRI scan.

Role of Diffusion Weighted Magnetic Resonance Imaging in Evaluation of Suspicious Breast Lesions

Introduction: Diffusion weighted Imaging“DWI”is a specific modality to produce images of tissues weighted with the local microstructural characteristics of water diffusion. DWI can give information as regards cellularity of breast lesions and it can be used for distinguishing between benign and malignant breast lesions, differentiating surgical scar from recurrence and monitoring therapies in locally advanced breast cancer Aim of the work: To assess the diagnostic value of diffusion weighted imaging as an adjuvant to breast magnetic resonance imaging for detection and differentiation of suspicious breast lesions and correlation with histopathologic findings, available clinical data or follow up. Methods: The studied group included 50 female patients referred for MRI breast for workup of a suspicious clinical, mammographic, or sonographic abnormality. Diffusion weighted imaging (DWI) was added to the routine study. Results of the contrast enhanced bilateral breast MRI and DWI of the 50 patients were all reported and compared with the histo-pathological results of surgery or biopsy and with the results of follow up of lesions that were not surgically removed or biopsied. Results: there was a highly significant relation between DWI and histopathological/ Follow Up results with p value = 0.000. The sensitivity, specificity, positive and negative predictive values of DWI for characterization of suspicious breast lesions in patients included in the study, were 89.5%, 100%, 100%, and 93.94% respectively. Conclusion: DWI is a short unenhanced scan that can be inserted easily into standard clinical breast MRI protocols as a potential adjunct that can be added routinely to conventional breast MRI, and can accurately differentiate benign from malignant breast lesions with high sensitivity and specificity.

SU‐E‐I‐24: Determining the Optimal B‐Values to Use in Diffusion Weighted Imaging for Differentiating Benign and Malignant Breast Lesions

To investigate and determine the optimal b-values for Diffusion Weighted Imaging(DWI) for Apparent Diffusion Coefficient(ADC) maps in differentiating normal, benign and malignant breast tissue. Twenty-five patients underwent diffusion-weighted magnetic resonance imaging (DWI-MRI) and conventional breast MRI with suspicious breast fmdings(BIRADS >4). Breast lesions were defined by pathology. The DWI was acquired with different b-values ranging from 0,500, 600,750 and 1000s/mm2 . Apparent Diffusion Coefficient(ADC) maps of breast tissue were constructed using different b-values, e.g., using either 2 b-values(0- 1000) or combinations of 3 or more (0,500,1000 or 0,600,750,1000). Quantitative analyses of the ADC maps of glandular, fatty and lesion tissue were obtained. Ratios of lesion to glandular tissue(L/GT) and signal to noise(SNR) were assessed. Paired t-tests were performed for statistical significance. Eighteen patients had invasive ductal carcinoma and 7 had benign breast lesions. The mean ADC value for malignant lesions using all b values was 1.17±0.16×10-3mm2 /s with a lesion to glandular(L/GT) ratio=0.65. The benign lesions, ADC map value was 1.86±0.03×10-3mm2 /s with L/GT=0.98. There was a significant difference(P<0.05) between benign and malignant lesions ADC map value.The lowest SNR(12±6) was with single b-values. There was a significant difference(P<0.05) in SNR with multiple b-values(34±6) compared to single b-values. The highest SNR was given by using two b values greater than 500. Finally, the background noise for all combinations was surprising stable and ranged between 60±20%. This is the first study to investigate the effect of changing different b values in DWI breast imaging. There were significant differences in the SNR between single and multiple b values. Our data show suggest that the recommended b-values for DWI in breast are 0, and two that are 500 or greater. Therefore use of at least 3 b-values in DWI/ADC mapping of breast lesions are needed for better characterization of benign and malignant breast tissue. P50CA88843, Avon Foundation for Women:01-2008-012, U01CA070095, andU01CA140204.

Value of diffusion-weighted MRI in the differentiation of benign and malign breast lesions

Our purpose was to determine whether diffusion-weighted MR imaging (DWI) could be used in differentiation of benign and malign breast lesions. 41 women patients were included in the study. 45 lesions were diagnosed by biopsy; 25 (55.5%) of these lesions were malignant and 20 (44.5%) were benign. The apparent diffusion coefficient (ADC) values of these lesions were prospectively compared with their histopathological results. Differentiation of the malignant and benign masses revealed that the threshold value of the ADC was 1.0 x 10(-3) mm(2)/s, its sensitivity was demonstrated as 95%, specificity as 100%, positive predictive as 100%, negative predictive as 94% and accuracy rate as 97%. DWI improves diagnostic accuracy of the conventional breast MRI. ADC measurements may be useful for differentiation of the malign and benign masses.

Quantitative Diffusion-Weighted Imaging as an Adjunct to Conventional Breast MRI for Improved Positive Predictive Value

The purpose of our study was to investigate whether adding diffusion-weighted imaging (DWI) to dynamic contrast-enhanced MRI (DCE-MRI) could improve the positive predictive value (PPV) of breast MRI. The retrospective study included 70 women with 83 suspicious breast lesions on DCE-MRI (BI-RADS 4 or 5) who underwent subsequent biopsy. DWI was acquired during clinical breast MRI using b = 0 and 600 s/mm(2). Apparent diffusion coefficient (ADC) values were compared for benign and malignant lesions. PPV was calculated for DCE-MRI alone (based on biopsy recommendations) and DCE-MRI plus DWI (adding an ADC threshold) for the same set of lesions. Results were further compared by lesion type (mass, nonmasslike enhancement) and size. Of the 83 suspicious lesions, 52 were benign and 31 were malignant (11 ductal carcinoma in situ [DCIS], 20 invasive carcinoma). Both DCIS (mean ADC, 1.31 +/- 0.24 x 10(-3) mm(2)/s) and invasive carcinoma (mean ADC, 1.29 +/- 0.29 x 10(-3) mm(2)/s) exhibited lower mean ADC than benign lesions (1.70 +/- 0.44 x 10(-3) mm(2)/s, p < 0.001). Applying an ADC threshold of 1.81 x 10(-3) mm(2)/s for 100% sensitivity produced a PPV of 47% versus 37% for DCE-MRI alone, which would have avoided biopsy for 33% (17/52) of benign lesions without missing any cancers. DWI increased PPV similarly for masses and nonmasslike enhancement and preferentially improved PPV for smaller (< or = 1 cm) versus larger lesions. DWI shows potential for improving the PPV of breast MRI for lesions of varied types and sizes. However, considerable overlap in ADC of benign and malignant lesions necessitates validation of these findings in larger studies.